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Glu in vitro. Meanwhile, western blot assay was conducted to unearth the underlying mechanism and the possible signal pathways involved in the protective effects. Furthermore, we assessed THVF's possible protective effects for Caenorhabditis elegans (C. elegans) against Glu-induced injury and its potential function in nematode physiological activity. Materials and Methods 2.1. Extraction and Purification of THVF. T. hemsleyanum vines were first washed, dried, smashed into powder, and extracted with 80% ethanol at 45°C for 90 min by ultrasonication (with the ratio of material and solution in 1 : 5). The above extraction produce was repeated three times. Then, the filtered fluid was collected and settled at 4°C overnight. On the second day, the filtrate was centrifuged at 4000 r/min for 10 min to gain the supernatants. Then, the supernatants were evaporated to concentrate under reduced pressure at 45°C, the concentrations were later centrifuged at 10000 r/min, and then the supernatants were loaded onto an equilibrated AB-8macroporous resin column (Ø 3:2 × 60 cm) for further purification. Finally, the eluted fluid was evaporated and lyophilized and later stored at -80°C for further research. 2.3. Cell Culture and Treatments. PC12 cell line was obtained from Shanghai Institute of Cell Biology (Shanghai, China) and cultured in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin solution in an incubator with 5% CO 2 at 37°C. THVF powder was always freshly dissolved in DMEM with 10% FBS before use. After being cultured for 24 h, the cells were washed with phosphate-buffered saline (PBS) twice and then pretreated with different concentrations of THVF for another 24 hours. Later, Glu (20 mM) was added for 24 h in the absence/presence of different concentrations of THVF. Cell Viability Assays. The assays of cell viability were carried out according to our previous protocol [21]. PC12 cells were seeded onto a 96-well plate, and 3-(4,5dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) diluted with serum-free DMEM at a final concentration of 0.5 mg/mL was added to each well after different treatments. After 4 h of incubation at 37°C, the formazan precipitate was dissolved in 150 μL of dimethyl sulfoxide (DMSO) and shook for 15 minutes and the absorbance was measured at 570 nm with a spectrophotometer. The viability of the untreated group was regarded as 100%, and each experiment was repeated at least three times. Fluorescent Probes Staining for PC12 Cells. After cell treatment, serum-free DMEM, respectively, containing 6 kinds of fluorescent probes were applied, including 2,7dichlorofluorescein diacetate (DCFH-DA), DHE, aphthalene-2,3-dicarboxaldehyde (NDA), Rhodamine 123, 10-N nonyl acridine orange (NAO), and Hoechst 33258. Cells were washed twice in PBS buffer after treatments and incubated in free-serum DMEM containing the probe at 37°C for 30 min. Then, cells were washed three times with PBS buffer and detected on a fluorescence microscope (Nikon) with different 2 Oxidative Medicine and Cellular Longevity filters at identical acquisition settings. Image-Pro Plus 6.0 software was adopted to analyze the densitometry. 2.6. Determination of the Level of SOD, MDA, and GSH. Cells were treated with different treatments, after washing with PBS buffer twice, 500 μL WB/IP cell lysis buffer was added, and cells were scratched and collected. An ultrasonic shredder and centrifuge (Sigma, USA) were used, and the supernatants were collected for further assay. SOD, MDA, and GSH contents were determined with assay kits purchased from Beyotime Biotechnology (Jiangsu, China). Western Blot. Total protein of cells was prepared using the WB/IP lysis buffer (Beyotime Biotechnology, Jiangsu, China). Equal amounts of protein were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene fluoride (PVDF) membranes. Membranes were probed with primary antibodies, and primary antibodies against p-p38 mitogen-activated protein kinase (MAPK), p38 MAPK, p-JNK, c-Jun Nterminal kinase JNK, and β-actin were purchased from Abcam (Shanghai, China). They were detected with horseradish-peroxidase-conjugated secondary antibodies using the enhanced chemiluminescence (ECL) detection system. β-Actin was used as a loading control, and ImageJ software was used to analyze densitometry. C. Elegans Strains and Treatment. C. elegans bristol N2 (wild-type) was provided by Dr. Du (Zhejiang University, China). The mutants were maintained at 20°C on a standard nematode growth medium (NGM) with E. coli OP50 as food resources. To collect eggs, adult animals on NGM were dissolved in bleaching solution. Then, the eggs were transferred into a new plate for hatching and synchronized at the same period. Synchronized L3 stage C. elegans were collected and transferred to NGM containing THVF of different concentrations (2.5, 5, and 10 μg/mL). After 24-hour treatments, 20 mM of glutamate was added while the concentration of TVE kept the same as before. Determination of Survival Rate, Body Length, and Body Width. The survival rate assays were performed in the 24well plates. A total of 40 young nematodes were raised in each well with culture medium (NaCl 3.1 g/L, KCl 2.4 g/L, cholesterol 1 mg/L), and E. coli OP50 was added for food supply. 0, 2.5, 5, and 10 μg/mL THVF were added into medium, respectively. After treating for 24 h, 20 mM Glu was later added for another 24 h. Survival rate was defined as survival rate ð%Þ = the living worm numbers after treatment/total worm numbers before treatment * 100%: The survival rate in the control group was regarded as 100% when calculated. Meanwhile, the photos of C. elegans were captured by a microscope and animals' body length and body width were measured by Auto CAD. 2.10. Locomotion Behavior Assay. Head thrash and body bend assays were used to evaluate locomotion behavior ability of nematodes. Once, head thrash was defined as a change in the direction of bending in the mid body which was counted for 1 min. A body bend was defined as a change in the direction of the part of nematodes corresponding to the posterior bulb of the pharynx along the y-axis, assuming that the long axis of the body was the x-axis (n = 30 per replicate; three replicates per group). 2.11. Visualization of ROS, Superoxide, and GSH. To measure the level of ROS, superoxide, and GSH, three fluorescence probes (DCFE-DA, DHE, and NDA) were added, respectively. Images of animals were obtained through a fluorescence microscope. 2.12. Statistical Analysis. Data were expressed as mean ± standard deviations ðSDsÞ from at least three independent experiments. Significant differences were determined by one-way analysis of variance (ANOVA) followed by the multiple comparison at p < 0:05. Significant differences were all analyzed using SPSS. Densitometry analyses were performed using Image-Pro Plus 6.0 software. THVF Alleviated Oxidative Stress Caused by Glu. According to the results of MTT assay (Figure 1(f)), we found that the concentration range of 0.78-25 μg/mL showed no toxicity to PC12 cells. Thus, we choose 2.5, 5, 10, and 20 μg/mL of THVF for further study. DNA damage is a key feature of cytotoxicity [26]. Therefore, Hoechst 33258, a specific DNA fluorescence probe, was adopted to assess nuclear fragmentation. As shown in Figure 2(a), the number of high light blue dots was markedly elevated after Glu stimulation while THVF treatments decreased such light dots at a doserelated manner. Besides genotoxicity, Glu further caused intracellular redox disturbance, resulting in overproduction of ROS [27]. Since plant flavones were regarded as a potent free radical scavenger both in vitro and in vivo [28], we tested the intracellular ROS level in the presence or absence of THVF by DCFH-DA, a specific ROS fluorescence probe. An enhanced DCF fluorescence intensity was observed in Glu-treated cells Oxidative Medicine and Cellular Longevity compared with the control group (Figures 2(a) and 2(b)). Intriguingly, 10 and 20 μg/mL THVF significantly declined the ROS level, with the DCF fluorescence intensity decreased to 0.18 and 0.15, respectively. Meanwhile, DHE, a unique probe of intracellular superoxide anion radicals, was further used to analyze O 2 contents. Similar findings were got, Glu significantly raised the mean DHE fluorescence intensity of PC12 cells (Figures 2(a) and 2(b)). In contrast, the intervention of THVF helped scavenging the overproduced O 2 with the DHE fluorescence intensity 5 Oxidative Medicine and Cellular Longevity declined. Superoxide dismutase (SOD) is an antioxidant metalloenzyme that specifically acts as a disproportionation catalyst to suppress superoxide anion radical generation [29]. As Figure 2(c) demonstrated, Glu severely inhibited activity of SOD in PC12 cells. Fortunately, THVF reversed this situation and 20 μg/mL THVF could even recover the SOD activity similar to control. These dates jointly revealed the protective effect of THVF under Glu-induced toxicity. THVF Relieved Mitochondrial Dysfunction Induced by Glu. ROS is often regarded as a by-product of mitochondrial dysfunction [30], and mitochondrial dysfunction could and then, 20 mM Glu was added for a total of 24 hours. Cells without Glu and THVF were used as negative control group. Cells treated with Glu alone were used as a glu group. Images were captured with a fluorescence microscope in the same settings. All the fluorescence images were quantified in the whole field with the background removed and represented by normalized fluorescence (y-axes) via Image-Pro Plus 6.0 (n = 3). Significance analysis was carried out according to the one-way ANOVA test, and different letters in figures mean statistically significant differences among the groups (a, b, c, etc., were labeled from large to small and once columns containing a same word means statistically insignificant, otherwise means statistically significant, p < 0:05). 6 Oxidative Medicine and Cellular Longevity further accelerate the progression of various diseases, such as atherosclerosis, diabetes, Alzheimer's disease, and Parkinson's disease [31]. Based on these findings, we suspected that THVF might provide a defense effect to the toxicity via recovering mitochondrial function. RH123 fluorescence probe is specific for mitochondrial membrane potential (MMP) detection and NAO is for mitochondrial membrane lipid peroxidation (MMLP), respectively. As Figure 3(a) illustrated, a Rh123 fluorescence intensity decline could be observed with the stimulation of Glu, suggesting the decreased MMP, which is usually regarded as prerequisite and a landmark event in early apoptosis. Similarly, the NAO fluorescence intensity was markedly suppressed by Glu, indicating the disturbed MMLP. However, after THVF treatments, NAO intensity increased compared with Glutreated cells. Malondialdehyde (MDA) is a crucial product of MMLP, and its production can aggravate damage and leading to aging and resistance physiology [32]. Consistent with previous results, Glu stimulation triggered MDA production and accumulation in PC12 cells while 2.5 μg/mL was sufficient to decrease intracellular MDA content. Mitochondrial dysfunction could further facilitate consumption of glutathione (GSH), and NDA fluorescence intensity reduction was found after Glu stimulation. Conversely, THVF treatments increased intensity significantly, suggest-ing the alleviation of mitochondrial damage and enhancement of antioxidative ability. Based on these results, we believe THVF exerted a beneficial effect against Glu-induced mitochondrial dysfunction. THVF Promoted Cell Proliferation Inhibited by Glu. Besides genotoxicity, ROS generation, and mitochondrial dysfunction, Glu also directly induce PC12 cells apoptosis. B-cell lymphoma-2 (Bcl-2) protein family is closely related to apoptosis [33]. As Figure 4(a) showed, Glu upregulated the Bax expression and suppressed the protein level of Bcl-2, which manifested the apoptotic state of PC12 cells. Besides, the production level of caspase-9 was also increased to 3-fold of control. However, we found THVF obviously down-regulated expressions of Bax, caspase-9, and upregulated Bcl-2 levels at a dose-dependent manner. PCNA plays a crucial role in cell proliferation and regulating cell cycle [34]. Consists with previous results, Glu significantly inhibited the expression of PCNA, indicating the damage of PC12 cell proliferation caused by Glu. On the contrary, THVF reversed such inhibition and up-regulated PCNA level to 2 times of control. These results suggested that THVF reversed apoptosis induced by Glu and facilitated cell proliferation. The quantitative data of panel (a). Images were captured with a fluorescence microscope in the same settings. All the fluorescence images were quantified in the whole field with the background removed and represented by normalized fluorescence (y-axes) via Image-Pro Plus 6.0 (n = 3). Significance analysis was carried out according to one-way ANOVA test and different letters in figures mean statistically significant differences among the groups (a, b, c, etc., were labeled from large to small and once columns containing a same word means statistically insignificant, otherwise means statistically significant, p < 0:05). 7 Oxidative Medicine and Cellular Longevity 3.5. The Protective Effect of THVF Involved in MAPK Pathways. As an important transmitter of signals from the cell surface to the interior of the nucleus, MAPKs can be activated by different extracellular stimuli such as cytokines, hormones, and cellular stress [35]. Figure 4(b)

showed that with the stimulation of Glu, the phosphorylation of JNK, ERK, and p38 was upregulated. However, after THVF treatments, downregulation of phospho-p38 and phosphor-ERK was observed. Meanwhile, though THVF had both inhibited the expression level of total JNK and p-JNK, the ratio of p-JNK/JNK had not changed compared to Glu-induced cells. Based on these results, we deduced that THVF protect PC12 cells from toxicity via ERK/p38 pathways. THVF Recovered the Locomotory Ability of C. elegans. With short lifespan and low cost, C. elegans is regarded as an ideal in vivo model to study toxicity [36]. As shown , and vertical lines in the histogram represent SDs of three replicates. Significance analysis was carried out according to the one-way ANOVA test, and different letters mean statistically significant differences among the groups (a, b, c, etc., were labeled from large to small and once columns containing a same word means statistically insignificant, otherwise means statistically significant, p < 0:05). Discussion The Chinese have used certain seaweeds to enhance the flavor of food for some 2,000 years. In 1908, the flavorenhancing agent was identified as glutamic acid [37]. Nowadays, Glu has been applied to a large amount of industrial production with its various applications such as flavor enhancer, wrinkles reducer, energy supplier, and neurotherapeutic agent. However, the toxicity especially neurotoxicity of Glu has been continuously uncovered recently. Many studies have revealed that natural products are able to help alleviate toxicity and protect from outer stimulation. TH is a traditional Chinese herb and food with various confirmed bioactive functions, while TH vine is usually regarded useless and often discarded as a by-product, resulting in a waste of source. We extracted and purified the flavones of TH and use UPLC-TOF/MS to characterized the main compounds of THVF. Results showed that THVF was composed of 3-caffeoylquinic acid, 5-caffeoylquinic acid, quercetin-3-O-rutinoside, and kaempferol-3-O-rutinoside. With extreme versatility for pharmacological manipulation, ease of culture, and the large amount of background knowledge on their proliferation and neuro characterization, rat phaeochromocytoma (PC12) cells have been widely used as a model for neural research [38]. Glu caused severe genotoxicity to PC12, hereby triggered enhanced ROS generation and overproduction of O 2 -, which were by-products of mito-chondrial dysfunction induced by Glu. Additionally, Glu inhibited the SOD enzyme activity and then increased the MDA accumulation as results. Conversely, THVF attenuated the Glu-induced toxicity by alleviating the genotoxicity, relieving oxidative stress, and recovering mitochondrial functions. It is implying that cell death in central nervous system irregulating may play a part in an etiology of cancer, AIDS, autoimmune diseases, and degenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and Huntington's disease. Similarly, PC12 cell proliferation was inhibited by Glu with down-regulation of PCNA and Bcl-2, as well as up-regulation of Bax and caspase-9, suggesting the apoptosis of cells. As expected, THVF recovered the cell proliferate ability and enhanced the expression levels of PCNA, Bcl-2. Mitogen-activated protein kinase (MAPK), as an important transmitter of signal transmission from the cell surface to the interior of the nucleus, plays a key role in stress response [35]. Glu markedly activated the phosphorylation of p38, JNK, and ERK. Nevertheless, down-regulation of p38 phosphorylation was found in THVF treated cells. Considering p38 MAPK is vital in immune response to stress and cell survival [39], THVF can inactivate, at least partly, the p38 MAPK pathway. Besides, THVF suppressed the expression of Glu-induced ERK over-phosphorylation. Previous studies have reported that ERKs, as a downstream protein of various growth factors (EGF, NGF, PDGF), regulate cell proliferation, differentiation, and survival. It acts like a receptor of signals from growth factors, mitogens, and environmental stimuli and then regulates nuclear transcription factors through the ERK signal cascade [40]. Thus, THVF might help protect PC12 cells from Glu-induced toxicity by suppressing over-phosphorylation of ERK and p38. It has been proved that neurotransmitters and their metabolism, vesicle circulation, and synaptic transmission are highly conserved, and all 302 neurons of the nematode have been well studied, which makes C. elegans an ideal alteration. (c) NDA staining for GSH contents. Images were captured with a fluorescence microscope in the same settings (n = 6). 10 Oxidative Medicine and Cellular Longevity model to learn neurotoxicity and behavior in vivo [41]. Locomotor behaviors require the control of neural circuits [42]. Our results implied that Glu toxicity might be involved in the disruption of motor control function or appropriate synaptic contacts between neurons and muscle cells. As C. elegans lacks afunctional blood-brain barrier, Glu could quickly diffuse into the nervous system and directly produce neurotoxic actions, resulting in damaged head thrashes and body bends. Fortunately, here THVF turned to be a neuroprotective agent and recovered the locomotory ability of nematodes. Consistent with in vitro results, Glu elevated the intracellular ROS, O 2 − generation, and GSH depletion in nematodes and THVF prevented larvae from Glutoxicity. However, it is unclear whether MAPK pathways are also involved in the THVF-treated nematodes, and further research is needed to confirm the inner mechanism in C. elegans level. Conclusion In this study, we focus on Glu neurotoxicity rather than its wide applications and well-known protective effects. As results illustrated, Glu caused damage to PC12 cells and C. elegans while THVF, flavones extracted, and purified from TH vine was able to protect Glu-induced toxicity via MAPK pathways. These data provide a novel insight and raise worthwhile questions about the Glu-accompanied side-toxicity and THVF potential neuroprotective effects both in vitro and in vivo, as well as MAPK pathways' role in neurotoxicity. Data Availability The data used to support the findings of this study are available from the corresponding author upon request. The importance of the olfactory system in human well-being, through nutrition and social behavior The human sense of smell is still much underappreciated, despite its importance for vital functions such as warning and protection from environmental hazards, eating behavior and nutrition, and social communication. We here approach olfaction as a sense of well-being and review the available literature on how the sense of smell contributes to building and maintaining well-being through supporting nutrition and social relationships. Humans seem to be able to extract nutritional information from olfactory food cues, which can trigger specific appetite and direct food choice, but may not always impact actual intake behavior. Beyond food enjoyment, as part of quality of life, smell has the ability to transfer and regulate emotional conditions, and thus impacts social relationships, at various stages across life (e.g., prenatal and postnatal, during puberty, for partner selection and in sickness). A better understanding of how olfactory information is processed and employed for these functions so vital for well-being may be used to reduce potential negative consequences. Introduction Among the different human sensory modalities, the sense of smell is one of the least explored, and much of its functions have yet to be clarified. This gap in our knowledge has been supported by decades of repeated attitude of laymen and scientists alike, who considered-and sometimes still consider-the sense of smell as an intuitive, yet not particularly telling source of information for humans. But, we have now collected sufficient information to disprove this prejudice (McGann 2017), and the COVID-19 pandemic has shown us full force the limits of fueling these outdated theories Pellegrino et al. 2020;Cooper et al. 2020;Gerkin et al. 2020;Pierron et al. 2020). Yet, olfaction is still a sense that is not strongly associated with the idea of well-being in the general population. Whereas impairments of sight or hearing are screened for routinely since an early age to detect issues that may impact quality of life, this is not the case for olfactory disorders that still go massively unnoticed. As a result, olfaction becomes important to wellbeing when smell loss and/or smell alterations appear, and they are very much treated not only as an invisible disability but one that is hard to even conceive of. Up to 49% percent of people report over their lifetime an olfactory disorder, with anosmia accounting for 5% of the population (Landis et al. 2004;Murphy 2002;Mullol et al. 2012). All in all, millions of people during their lifetimes suffer from olfactory disorders, and as a consequence, report a negative impact on mental and emotional health, increased social isolation, and associated financial difficulties related to receiving the support they need, which often consists of non-curative solutions (Neuland et al. 2011;Erskine and Philpott 2020). These patients often report to have issues in their ability to protect themselves from environmental hazards, in their food enjoyment and eating behavior, and in their social relationships, all scenarios linked to the main functions of the sense of smell (Stevenson 2010). A wealth of research both in the domain of common and of social odors has focused on danger detection and the role of the sense of smell in fostering the preservation of the human species (Parma et al. 2017a;Parma et al. 2017b). In the present chapter, we focus our attention on the more understudied perspective of olfaction as a sense for well-being. Based on our experience with patients with smell loss, and their significantly reduced quality of life as a result of their disorder (Neuland et al. 2011;Erskine and Philpott 2020;), we will review how the sense of smell critically contributes to building and maintaining well-being (Fig. 1). Although the third major function of olfaction-related to avoidance and protection from environmental hazards -clearly contributes to human well-being, this function has been reviewed in previous work (Parma et al. 2017a). Here we choose to focus on functions with more positive connotation and emphasize how olfaction supports nutrition and social relationships. Nutrition Odors are part of the flavor percept during food consumption (retronasal) (McCrickerd and Forde 2016; Small 2012), but more importantly, even before ingestion, odors can alert us to food in our environment and orient our appetite (McCrickerd and Forde 2016;Boesveldt and Graaf 2017). Just imagine walking past a bakery in the morning, and sensing the smell of freshly-baked bread. A sudden sensation of appetite is triggered, and that may result in the irresistible urge to treat yourself. On the other hand, when you have a cold, and your nose is blocked, food does not taste so good anymore and lacks enjoyment, because the olfactory component is missing. In addition, early exposure to flavors in breast milk or formula, or even exposure in utero, can shape food preferences later in life (Beauchamp and Mennella 2011). These olfactory signals are crucial behavioral drivers in our food-abundant environment, and it is imperative to better understand the underlying mechanisms, and under what conditions they act, in order to steer people towards better eating patterns. Olfaction, similarly to vision, can be considered a so-called distant sense. In the presence of food, olfactory signals can be perceived before consumption, and may stimulate appetite in anticipation of food intake. Several studies have now clearly demonstrated that odors trigger appetite specifically for the cued product (Fedoroff et al. 2003;Ramaekers et al. 2014;Zoon et al. 2016), a phenomenon coined sensoryspecific appetite. In addition, this effect may generalize to other foods with similar characteristics. For instance, after exposure to a meat odor, the specific appetite for meat increases most, but also stimulates appetite for other savory products, such as curry. Moreover, this sensory-specific appetite is not only present for odors and foods that share similar sensory characteristics (i.e., taste category, such as sweet, savory) (Ramaekers et al. 2014), but also odors representing high-or low-energydense foods specifically induce appetite for (same and other) food products high or low in energy density (Zoon et al 2016). Interestingly, we have recently shown that humans, like other species, can use their olfactory sense (2010) with a focus on how olfaction promotes well-being through nutrition and social behavior, with an outline of the topics reviewed in the chapter in their foraging or eating behavior strategies, i.e., to navigate for (high-calorie) food in different environments (de Vries et al. 2020). It is thus likely that, similar to taste being a nutrient sensing system, food odors can signal information about the nutrient composition of their associated foods already before ingestion. This would be based on learned associations, due to repeated combined exposure to an odor and the post-ingestive consequences of the food throughout life (Brunstrom and Mitchell 2007;Small et al. 2008;Yeomans and Boakes 2016;). This information may trigger cephalic phase responses-a myriad of physiological responses

(e.g., saliva, hormones, digestive enzymes), to help the body start preparing for the ingestion and digestion of that specific food/macronutrient (Smeets et al. 2010;. For a detailed review of the relation between olfaction and appetite hormones, see Palouzier-Paulignan et al. (2012). Even though subjective ratings of appetite have predictive value for food intake (de Graaf et al. 2004), they cannot be directly extrapolated; i.e., people do not always eat what they want or when they are hungry, and they also do not always refrain from eating when satiated (Drapeau et al. 2007;Mattes et al. 1990;Stubbs et al. 2000;Parker et al. 2004). Hitherto, beyond appetite, reports on the effect of olfactory cues on more tangible measures of eating behavior, such as food choices, and intake, are conflicting. These inconsistent results may be grounded in methodological differences between study designs. For instance, in a series of studies, Gaillet and colleagues have shown that starters and desserts containing fruit and vegetables were selected more frequently from a menu upon unconscious exposure to melon and pear odor, respectively (Gaillet et al. 2013;Gaillet-Torrent et al. 2014). Others have similarly shown a positive influence of unaware odor exposure on subsequent congruent food choices (de Wijk and Zijlstra 2012; Chambaron et al. 2015), while awareness of the odor did not result in similar food choices (Zoon et al. 2014). As much decision making occurs at a non-conscious level (Köster 2009), this suggests that olfactory effects on food choice may operate through priming, and the odor needs to be unattended or presented subthreshold in order to exert its influences (Smeets and Dijksterhuis 2014). The relationship between odor exposure and subsequent intake is also not straightforward. Fedoroff et al. observed an increase in intake after odor exposure only for restrained eaters (Fedoroff et al. 2003), whereas Coelho et al. found that restrained eaters decreased their food intake upon odor exposure (Coelho et al. 2009). On the other hand, Larsen and colleagues and Proserpio et al. observed an increase in intake for low impulse eaters only (Larsen et al 2012), or upon unconscious odor exposure (Proserpio et al. 2017;Porserpio et al. 2019). Finally, several studies did not find any differences in intake after (conscious) exposure to odors signaling foods differing in macronutrient content or energy-density Zoon et al. 2014). Impact of smell loss on eating behavior Most of the studies above have focused on short-term effects of experimental interventions to study the influence of olfaction on eating behavior. If our sense of smell indeed plays an important role in the dietary choices we make in our daily lives, this may exert longer-term effects, such as changes in body weight or body mass index (BMI). Additionally, patients that experience olfactory dysfunction (e.g., elderly, anosmics; although olfactory loss can occur for a plethora of reasons (Temmel et al. 2002) may show differences in their food preferences and intake, and such findings will provide further insight into the importance of smell for nutritional behavior. Though most studies have indicated that a decreased sense of smell is related to poor appetite, lower interest in food-related activities, or decreased food enjoyment (Aschenbrenner et al. 2008;Jong et al. 1999;Duffy et al. 1995;Philpott and Boak 2014;Postma et al. 2020), the impact on dietary patterns or overall diet quality appears to be less consistent (Mattes et al. 1990;Aschenbrenner et al. 2008;Duffy et al. 1995;Postma et al. 2020;Gopinath et al. 2016), and may depend on the duration of olfactory loss (i.e., being it acquired throughout life or congenital and thus present from birth). Moreover, patients with smell loss typically do not have lower energy intake or present with low BMI (Mattes et al. 1990;de Jong et al. 1999;Duffy et al. 1995). In addition, research has shown no relation between (loss of) olfactory function and liking of (flavor-enhanced) foods (Kremer et al. 2007(Kremer et al. , 2014Koskinen et al. 2003;Boesveldt et al. 2018). Thus, although there may not be a direct relation between olfactory function and nutritional status (Toussaint et al. 2015), smell loss mostly affects the pleasure in food behavior. Moreover, eating can be considered as social behavior (e.g., enjoying family dinners, going out to a restaurant with friends, or cooking for your loved-ones), and it is indeed known that olfactory loss is associated with depressive symptoms , as the absence of smell can have more general impact on quality of life and well-being (Philpott and Boak 2014;). Social behavior The sense of smell represents a significant medium to transfer information that is critical to foster relationships among co-specifics (Lübke and Pause 2015; Semin and de Groot 2013), as well as inter-species (Semin et al. 2019). Possibly due to its evolutionary role in creating and maintaining sociality, sweat-based olfactory communication is effortless-we spontaneously sweat and breathe-and we are among the most odoriferous hominidis species (Stoddart 1990). Indeed, despite most research on human sweat being confined to the axillary area (Mitro et al. 2012;Pause et al. 1998;Mutic et al. 2016;Chen and Havilandjones 1999;Ferdenzi et al. 2009;Cecchetto et al. 2019;Doty et al. 1978;Dalton et al. 2013;Sorokowska et al. 2016;de Groot et al. 2018;Rocha et al. 2018), many areas of the body are able to produce and transfer chemosignals (e.g., eyes through tears (Gelstein et al. 2011), hands (Frumin et al. 2015), increasing the potential for chemosensory communication. Furthermore, sweat-based olfactory communication is resistant to perturbation from the restrictions imposed by physical and time barriers, since chemical molecules can freely disperse in air and water (Zelano and Sobel 2005). It therefore remains efficient when senses that humans typically rely on are unavailable (e.g., in the dark, in loud environments), even when chemosensory noise is present (Roberts 2012). Indeed, chemosensory communication is not blocked by the use of fragrances, a widespread custom across societies (Saxton et al. 2008). The processing of information decoded from sweat represents a form of honest communication (Martín and López 2008), which does not require conscious awareness (Lundström and Olsson 2010) and is applied to a variety of human relational contexts. These features make communication based on chemicals possible across developmental stages, from intrauterine life (Beauchamp and Mennella 2011) to the elderly (Prokop-Prigge et al. 2016), and available to the fraction of the population affected by cognitive and social impairments (Parma et al. 2013). By simply reviewing the type of information that sweat-based olfactory communication successfully conveys, it is clear that one of its main functions is the fostering of stable relationships: sweat chemically encodes personal identity (Schleidt et al. 1981;Platek et al. 2001), kin and relatives Porter et al. 1986), partner choice (Schleidt et al. 1981;, and more broadly, friendship ). Additionally, sweat can also chemically encode health status (Moshkin et al. 2012;Olsson et al. 2014), sexual availability (Gildersleeve et al. 2012), and emotional states (fear, de Groot and Smeets 2017;disgust, Zheng et al. 2018;aggression/competition, Mutic et al. 2016;sadness, Oh et al. 2012;happiness, de Groot et al. 2015), factors that regulate the more transient aspects of relationships. The role of smell in relationships follows mankind across developmental stages Odors start to become a form of social communication as early as in utero, and it further strengthens postnatally when the odorous secretions of the areola attract the newborn and facilitate latching and breastfeeding (Doucet et al. 2012), while mothers' attachment to their baby is also reinforced through a chemosensory channel (Lundström et al. 2013). In infancy, the maternal odor is used to regulate the infant's emotional processing (Jessen 2020) and disambiguates the visual environment e.g., faces (Leleu et al. 2020). During childhood, children tend to like and be comforted by their mother's odors (Ferdenzi et al. 2010), whereas same-sex parental odors become aversive during pubertal age, contributing to the discouragement of incestuous relationships Westermarck effect . Despite a renaissance of the investigation of body odor processing in childhood in the most recent years , this area of research is rather understudied. Instead, a wealth of evidence has been collected on the role of body odors in attraction and mate choice. Many studies reveal that preferences for the body odors that signal the quality of a partner in terms of compatibility, with a preference for the odors of people having a dissimilar HLA (Havlicek and Roberts 2009), and for the odor of people having a compatible sexual orientation (Martins et al. 2005). Additionally, men prefer the smell of women while they are in the fertile phase of their menstrual cycle (Singh and Bronstad 2001;Havlíček et al. 2006), an effect that fades away when women use contraceptives (Kuukasjarvi 2004). All in all, body odors, along with other sensory cues, shape physical attractiveness and promote (or not) mating (Miller and Todd 1998). Smell-triggered emotion regulation More broadly, sweat-based information is used to transfer information about well-being via transferring happiness (de Groot et al. 2015) or a lack thereof (Mutic et al. 2016;de Groot and Smeets 2017;Zheng et al. 2018;Oh et al. 2012). Human sweat produces behavioral, psychophysiological, and neurophysiological consequences in recipients in line with the emotional condition at encoding. In a communication perspective , human sweat collected in emotional 1 3 situations stimulates partial synchronization between donors and recipients, in line with the concept of emotional contagion (Hatfield et al. 1993). In other words, affective, behavioral, and perceptual processes observed in a receiver following exposure to human sweat constitute in many cases a partial reproduction of the state of the donor at the time of body odor production. Specific experiences, such as pregnancy, reduce the effectiveness of sweat-based emotional communication, such as in the case of reduced responses to anxiety sweat signals to protect the mother and the fetus from the adverse consequences of stress reactions (Lübke et al. 2017). Though emotional contagion is a widespread mechanism regulating sweat communication, it is not the only one. Individuals can respond not only by mimicking the sweat donor's experience but also by providing complementary responses to it, such as when "smelling aggression" is met with heightened anxiety (Mutic et al. 2016). These mechanisms are particularly interesting when at play to promote personal well-being, and social attuning. In the specific case of autism spectrum disorder, a pathology that is keenly characterized by lack or reduction in social competence, smelling the odor of a familiar person, with whom interaction is positive, has the great advantage of letting emerge functional behaviors such as automatic imitation (Parma et al. 2013(Parma et al. , 2014. By leveraging the power of odors to modulate breathing patterns (Arshamian et al. 2018), individuals with autism can be offered a low-effort opportunity of emotional regulation. It is well known by now that regulating breathing patterns, whether voluntarily or not, has a calming effect (Zaccaro et al. 2018). Impact of smell loss on relationships The impact that smell loss has on relationships is strong, simply imaging failing to detect one's own bad body odor and how this will immediately affect the people in the vicinity. Taking this negative outcome a step forward, smell loss can affect sexual relationships and mate choice in people, especially for those with congenital anosmia (Philpott and Boak 2014;Croy et al. 2013;Schäfer et al. 2019). Having no or reduced ability in reading the social world through the lens of olfaction can severely affect attachment, limit the ability to "read a room," and the strategies used to initiate emotional regulation, associated with the experience of having an invisible illness. These phenomena are not only limited to early development and adulthood, but span continuously over the lifespan, including the elderly population. Indeed, it is believed that the association between olfactory performance and the richness of social connectedness could reflect social modulation processes occurring in aging , which are known variables influencing health outcomes in this segment of the population. General conclusions Overall, the evidence presented in this chapter suggests that the olfactory modality is a reliable medium through which social communication can occur among humans. By playing a critical role in nutrition and social relationships, smell is a sense that is instrumental to the achievement and maintenance of well-being. As the COVID-19 pandemic revealed, the widespread olfactory loss and dysfunction often left in the wake of a COVID-19 diagnosis, significantly trumps one's sense of wellbeing, shedding light on the silent importance of the sense of smell. From a nutrition perspective, changes in or loss of olfactory capability mostly impacts food enjoyment and can, but do not automatically, lead to

changes in dietary patterns. It is clear that the relation between olfactory signals and eating behavior is complex and entails more than plain liking or wanting of food induced by odor cues. Moreover, few studies have looked at real-life situations, e.g., shopping malls and nursing homes, to investigate the effect odors may have on our daily food choices and eating patterns, or over longer periods of time. The study of the effect of odors on social relationships has so far highlighted the pervasive role of olfaction in fostering sociality. Importantly, the majority of this evidence is collected in the absence of a real-time communicative exchange (often donors and recipients do not jointly interact). The decontextualization of the information encoded in sweat may possibly be removing part of the beneficial effects of this social behavior. What are the social dimensions in human chemosensory emotional contagion? How does sweat-based communication affect relationships and well-being outside of the laboratory? These remain at present open questions. If we understand how and under which circumstances olfactory signals lead up to food intake, this may be used to steer (overweight) people towards healthier foods, or to enhance appetite in malnourished elderly or patients. Similarly, if we understand how social chemosensory information can be used to foster accurate social information processing and emotional regulation, this may be used to reduce the negative consequences of these inabilities. Research for the years to come, that we plan on doing and that we look forward to seeing in bulk in the literature, will aid to fully exploit the potential that olfaction offers to improve human well-being. Quantitative assessment of SARS‐CoV‐2 RNAemia and outcome in patients with coronavirus disease 2019 Abstract The disease spectrum of coronavirus disease 2019 (COVID‐19) varies from asymptomatic infection to critical illness and death. Identification of prognostic markers is vital for predicting progression and clinical practice. Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) RNA, known as RNAemia, has been detected in the blood. However, the potential clinical value of SARS‐CoV‐2 RNAemia remains unknown. We, therefore, conducted a meta‐analysis using a random‐effects model to estimate the pooled prevalence of SARS‐CoV‐2 RNAemia as well as summary strength of RNAemia in association with disease severity and unfavorable clinical outcomes. A total of 21 studies involving 2181 patients were included. SARS‐CoV‐2 RNAemia in COVID‐19 patients varied from 9.4% to 74.1%, with a pooled estimate of 34% (95% confidene interval [CI]: 26%–43%). Overall, SARS‐CoV‐2 RNAemia was associated with COVID‐19 severity with odds ratio (OR) of 5.43 (95% CI: 3.46–8.53). In addition, SARS‐CoV‐2 RNAemia was a significant risk factor for unfavorable clinical outcomes (OR = 6.54, 95% CI: 3.82–11.21). The summary OR was 4.28 (95% CI: 2.20–8.33) for intensive care unit (ICU) admission, 11.07 (95% CI: 5.60–21.88) for mortality. Furthermore, RNAemia was also a significant risk factor for invasive mechanical ventilation and multiple organ failure. SARS‐CoV‐2 RNAemia is associated with disease severity, ICU admission, death in COVID‐19, and may serve as a clinical predictor. More prospective trials in evaluating the potential of SARS‐CoV‐2 RNAemia as a prognostic indicator are necessary. | INTRODUCTION Coronavirus disease 2019 (COVID- 19), originally reported from Wuhan, China, has spread globally in a very short period. 1 As of December 17, 2020, there were over 75 million confirmed cases and 1.6 million deaths. 2 Deep sequencing revealed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was responsible for the development of the COVID-19 pandemic. 3 Although most patients present mild-to-moderate symptoms, including fever, dry cough, and fatigue, 5%-10% progress to a severe or critical disease characterized by pneumonia and respiratory failure, and death occurred in 2%-5% of the cases. 4 SARS-CoV-2 RNA can be detected in nasopharyngeal (NP)/ throat swab, sputum, respiratory tract, peripheral blood, serum, feces, urine, and tear by polymerase chain reaction (PCR)-based methods. [5][6][7][8][9] Viral load by sample type is indicative of virus replication and clearance and is routinely used to monitor disease progression, response to antiviral agents, and relapse. 10 Since the lungs are most often affected and viral RNA is commonly detected in NP swabs, several studies have investigated viral loads in samples from the upper respiratory tract as a biomarker for severity assessment. Zou et al.reported that the viral load was similar among asymptomatic patients and symptomatic patients. 11 Metagenomic sequencing of NP swabs from COVID-19 patients with different severity indexes suggested that increased SARS-CoV-2 RNA detection is associated with the early stages rather than disease severity. 12 These results suggest that viral load in respiratory samples cannot be considered as a prognostic indicator for severe or critically ill cases. Currently, the relationship between viral load dynamics in samples from extrapulmonary sites (fecal, tear, and urinary samples) and disease severity remains unknown. Recently, coagulopathy has been reported in severe COVID-19 cases, 13,14 implying the spread of SARS-CoV-2 within extrapulmonary sites via blood flow. In addition to the difficulty of SARS-CoV-2 virus culture from the blood, 15 serum SARS-CoV-2 nucleic acid (RNAemia) represents a practical and powerful approach to evaluate the impact of viral load dynamics on disease severity in extrapulmonary sites. Increasing evidence addressing SARS-CoV-2 RNAemia and disease progression are available; a definite conclusion has not yet been reached. Therefore, we aimed to establish a comprehensive picture of the association between RNAemia and disease severity as well as unfavorable outcomes, including intensive care unit (ICU) admission, invasive mechanical ventilation (IMV), and death. | Identification and eligibility of relevant studies RNAemia was defined as the presence of viral RNA, above the technical limits of detection of PCR-based assays, in the blood, serum, or plasma. Eligible studies were required to meet the following criteria: (1) clinical study evaluated the association between SARS-CoV-2 F I G U R E 1 Flowchart of study selection RNAemia and COVID-19 severity or outcomes; (2) original articles reported independent data; (3) reported relative risks with 95% confidence intervals (CIs) or sufficient information for effect size calculation. Studies with fewer than 10 patients; studies only examined samples other than the blood (e.g., digestive tract, feces, and respiratory samples) were excluded. | Data extraction Information with regard to authorship, publication year, country, study design, numbers of patients, age, gender distribution, SARS-CoV-2 RNAemia rate, unfavorable outcomes (ICU admission and/or death), severity (mild, moderate, severe, and critical illness), IMV, multiple organ failure (organ ≥ 2), viral RNAemia, SARS-CoV-2 detection method, variables adjusted for in the multivariable analysis, and risk estimates with corresponding 95% CIs was summarized independently by two reviewers according to a fixed protocol. Inconsistency from data reports was resolved by further discussion among all authors through consensus. | Statistical analysis The strength of the association between the presence of SARS-CoV-2 RNAemia and clinical severity or outcomes was estimated using odds ratios (ORs), with the corresponding 95% CIs. Hazard ratio (HR), relative risk (RR), and rate ratio were treated as equivalent estimates of OR since the unfavorable outcome of patients with COVID-19 is relatively rare. 16 The association of SARS-CoV-2 RNAemia was first compared between different clinical severity (mild/moderate vs. severe/critical). Then we examined the association between SARS-CoV-2 RNAemia and adverse clinical outcomes (ICU admission and/or death). Stratified meta-analyses based on country (East Asian vs. Western country) and study design (prospective vs. retrospective) Characteristics of the included studies are shown in Table 1. When analyzed according to country and study design, significant associations were detected almost in all comparisons ( | Assessment of heterogeneity There was statistical heterogeneity in comparison (Table 2) and the study by Lei et al. was identified as the main source of betweenstudies heterogeneity in sensitivity analyses. As for limited data, meta-regression could not be performed to assess the correlation between SARS-CoV-2 RNAemia and disease severity or clinical outcomes. | Sensitivity analyses and publication bias A single study involved in the meta-analysis was deleted each time to reflect the influence of the individual data set to the pooled ORs, and the corresponding pooled ORs were not qualitatively altered. No publication bias (p > .05 for all) was observed for this overall metaanalysis ( Figures S2 and S3). | DISCUSSION To our knowledge, this is the first meta-analysis to explore the as- There is inconsistency in the positive rate of SARS-CoV-2 RNAemia among published data, whereas some authors reported 0%-1% of RNAemia. 1,11 Here are several explanations to interpret the abovementioned phenomenon. First, clinical characteristics (e.g., the number of patients with severe/critically illness, and age) may attribute to these different results since SARS-CoV-2 RNAemia occurred more frequently in older age and severe cases. Second, differences in sample collection protocols (e.g., at hospital admission, after confirmed COVID-19 cases, several days before or after the NP collection or symptom) may also have affected the results, as an optimal period for blood sampling remain unknown. RNAemia as a prognostic marker for predicting progression and outcomes of COVID-19. Second, our results were mainly based on unadjusted estimates. Ideally, we would like to pool individual-level data and conduct a more precise analysis, which could be adjusted for other covariants, such as age, obesity, and other common comorbidities, including cancer, hypertension, diabetes, and cardiovascular diseases. Third, subgroup meta-analyses were performed on the basis of a fraction of all the possible data, so selection bias may have occurred. | CONCLUSIONS In summary, the findings of this study revealed that SARS-CoV-2 RNAemia is a significant risk factor for disease severity and adverse outcomes in COVID-19, particularly for ICU admission and death. These results suggest that RNAemia may serve as a clinical scoring component for risk stratification, and SARS-CoV-2 RNAemia evaluation would be crucial for COVID-19 patients. To confirm these findings, future studies should involve a prospective design, strict selection of cases, testing protocols, and larger studies of diverse populations. Design, Synthesis, Evaluation and Structure of Allenic 1α,25‐Dihydroxyvitamin D3 Analogs with Locked Mobility at C‐17 Abstract Vitamin D receptor ligands have potential for the treatment of hyperproliferative diseases and disorders related to the immune system. However, hypercalcemic effects limit their therapeutical uses and call for the development of tissue‐selective new analogs. We have designed and synthesized the first examples of 1α,25‐dihydroxyvitamin D3 analogs bearing an allenic unit attached to the D ring to restrict the side‐chain conformational mobility. The triene system was constructed by a Pd0‐mediated cyclization/Suzuki‐Miyaura cross‐coupling process in the presence of an allenic side chain. The allenic moiety was built through an orthoester‐Claisen rearrangement of a propargylic alcohol. The biological activity and structure of (22S)‐1α,25‐dihydroxy‐17,20‐dien‐24‐homo‐21‐nor‐vitamin D3 bound to binding domain of the vitamin D receptor, provide information concerning side‐chain conformational requirements for biological activity. Introduction The active form of the secosteroid hormone vitamin D 3 , 1α,25dihydroxyvitamin D 3 [1, calcitriol, 1,25-(OH) 2 D 3 , 1,25D, Figure 1], exerts its biological functions by binding to the vitamin D receptor (VDR), a transcription factor of the nuclear receptor superfamily (NRs). [1] 1,25D was known for many years as a primary regulator of calcium homeostasis, but it also controls a wide range of other biological functions including cell differentiation, cell proliferation, and immune responses. [2,3] 1,25D induces the expression of more than 200 genes associated with several diseases such as arthritis, diabetes and cancer, suggesting that this secosteroid hormone might induce a wide range of biological functions. [4] Unfortunately, 1,25D induces hypercalce- [ mia at the doses required for the treatment of hyperproliferative diseases such as cancer. [3] This limitation has led to intense synthetic efforts towards VDR ligands with selective activities as potential therapeutic agents for the treatment of cancer, immunodeficiency syndromes, autoimmune diseases and skin disorders. [5] Calcipotriol and maxacalcitol, examples of 1,25D analogs with a modified side-chain, exhibit similar or higher antiproliferative potency with reduced calcemic effects in comparison with natural hormone 1,25D ( Figure 1). [6] Other potent 1,25D analogs structurally modified at the CD-rings or triene system that induce low potency for calcium metabolism have also been synthesized. Representative examples of these compounds include inecalcitol (19-nor-14-epi-23-yne-1,25D, TX522) [7] and PG-136, [8] which exhibit anticancer properties, and paricalcitol (19-nor-1,25D), which induces immunomodulatory effects and was recently proposed as a therapeutic option for patients with severe COVID-19. [9] Unfortunately, the mechanism underlying the dissociation of the antiproliferative effects from the calcemic effects, as well as the conformational requirements for selective biological functions, have not yet been established. [10] The crystallographic structures of 1,25D and various of its analogs in complex with the VDR ligand binding domain indicate that the corresponding side-chain-C25OH groups adopt similar

positions. [11] However, the side-chain flexibility makes difficult to predict the conformation associated with a particular biological function. Okamura and coworkers, in efforts to understand structure-activity relationships, pioneered the synthesis of 1,25D analogs with rigid structural units at the side chain to restrict its conformational mobility. [12] In the search for vitamin D analogs with an even higher degree of restricted mobility of the side chain, we have started a research program on the synthesis and biological evaluation of 1,25D analogs with locked units at the side chains attached to the D-ring, in the form of double bond, [13] cyclopropane ring, [14] aromatic ring, [15] and triple bond. [16] In connection with this program, we describe here the development of the first side-chain analogs of 1,25D that incorporate an allenic unit at C17 as the structural element to impart restricted mobility to the side chain. Results and Discussion Design Based on the crystal structure of the active hVDR ligand-binding domain (LBD) bound to 1,25D, [11a] we studied the docking of the analogs 2 a-2 e bearing an allenic unit at the side chain attached to C17 of the D-ring ( Figure 1). We showed that analog 2 d binds well (97 %) to the VDR LBD in comparison with the native hormone 1,25D (100 %) ( Figure 2). This analog adopts the canonical active conformation as the natural hormone in the binding pocked, where the A, C and D rings, and the triene system occupy similar positions. The A-ring and side-chain hydroxyl groups form effective hydrogen bonds with the same amino acid residues (His-305, His-397, Ser-278, Arg-274, Tyr-143, Ser-237) as the natural hormone. The other allenic analogs 2 a (87 %), 2 b (92 %), 2 c (86 %), and 2 e (84 %) bind to the hVDR LBD less efficiently than 2 d. On the basis of the in silico binding results, we chose compounds 2 a, 2 b and 2 d as the synthetic targets. Retrosynthetic analysis of target compounds The synthetic plan for the synthesis of target compounds 2 a, 2 b, and 2 d is outlined in Scheme 1. The formation of the vitamin D triene system involves a stereoselective Pd 0 -catalyzed ring closure of enoltriflate 4 and subsequent Suzuki-Miyaura coupling with unprotected alkenyl-boronic ester 3 in protic medium following procedures developed in this laboratory. [17] At this point, the stability of the allenic unit under the Pdcatalyzed reaction conditions was uncertain. The boronates 3 are envisaged to arise from the allene 5 by conventional Chemistry-A European Journal Full Paper doi.org/10.1002/chem.202101578 chemistry. The key allene 5 would arise from propargylic alcohol 6 through an orthoester-Claisen rearrangement. [18] Compound 6 would be prepared in several steps by degradation of vitamin D 2 . [19] The synthesis of boronate 3 d began with ester 5, which was converted to iodide 13 by a three steps sequence (81 % yield) involving reduction with diisobutylaluminum hydride in THF, treatment of the resulting alcohol 12 with p-toluenesulfonyl chloride in pyridine, and subsequent reaction of the resulting boronates 3 a, 3 b, and 3 d. Chemistry-A European Journal Full Paper doi.org/10.1002/chem.202101578 tosylate with sodium iodide in acetone. Chain extension by reaction of iodide 13 with the lithium anion derived from tertbutyl acetate in THF provided ester 14 in 95 % yield, which was converted to diol 16 (90 %) by methylation (MeLi, THF) and subsequent deprotection (nBu 4 NF, THF). Pyridinium dichromate oxidation of 16 in CH 2 Cl 2 and subsequent Wittig-olefination of the resulting ketone 17 with ylide Ph 3 P=CHBr afforded the (E)alkenyl bromide 18 in 82 % yield (two steps), which was transformed into the desired upper boronate 3 d (57 % yield) by reaction with bis(pinacolato)diboron and KOAc in the presence of catalytic [1,1'bis(diphenylphosphino) ferrocene] dichloropalladium(II) in DMSO as above (23.3 % overall yield from ketone 7, 12 steps). The allene moiety survived the Pd-catalyzed process during the formation of the vitamin D triene system though in moderate yield. [23] Functional activity As the in silico data indicate that the allene 2 d binds to VDR with the highest efficiency, we determined its biological properties. Transactivation assay in HeLa cells transfected with human full length VDR showed that 1,25D (1) and 2 d induce the expression of a luciferase reporter gene under the control of the promoter of human CYP24A1, the main vitamin D target gene (Figure 3, A). Note that at lower doses, 2 d was less potent than 1. In addition, we monitor the expression of CYP24A1 transcripts in cells derived from prostate cancer metastasis (DU-145) treated for 24 h. Ligands 2 d and 1 induced transcript levels at 100 nM and 10 nM, but the levels were lower in cells treated with 2 (Figure 3, B). To determine the effects of 2 d in vivo, wild type mice were daily treated with various doses of 2 d and 1 for 5 days. In agreement with previous results, [24] 1 μg/kg of 1 induced hypercalcemia and the transcript levels of the vitamin D target genes Cyp24a1 and S100g in the kidney (Figure 3, D-E). However, the renal transcript levels were similar in mice treated with 2 d and with vehicle ( Figure 3, D-E). The calcemic activity of 2 d was evaluated by monitoring the serum calcium levels in the treated mice (Figure 3, C). Serum calcium levels were unaffected at 1 and 3 μg/kg. Thus, these results indicate that 2 d is less potent than 1,25D, but behaves as a low-calcemic 1,25D analog. Crystal structure To determine the binding pose of the analog 2 d, we cocrystallized the zebrafish wild-type VDR LBD [11c] in complex with Chemistry-A European Journal Full Paper doi.org/10.1002/chem.202101578 the ligand and a coactivator peptide and solved the structure with a resolution up to 2.1 Å (Supporting Table 1). The overall structure is highly homologous to the VDR-1,25D structure with a root mean square deviation of 0.3 Å over 235 residues when comparing the Cα atoms of the two complexes. Superposition of the VDR ligand binding pocket in the presence of 2 d and 1,25D shows similar positioning of the ligands (Figure 4, A), in agreement with the in silico docking data. The C1-OH, C3-OH and C25-OH groups of 2 d form similar H-bonds as 1,25D ( Figure 4A), however the C25-OH forms weaker H-bonds with His-333 and His-423 (3.2 Å and 3.0 Å for analog 2 d compared to 2.8 Å and 2.8 Å for 1,25D). The secosteroidal part of the ligand forms similar interactions with the zVDR ligand binding pocket compared to 1,25D. The side chain of 2 forms extensive interactions with Leu-255, Leu-258, Val-262, Ala-331, His-333, His-423, Tyr-427, Leu-430 at a 4.0 Å distance cutoff (Figure 4, B). The difference in side chain position as a consequence of the rigid allenic unit attached to C17, results in a loss of interaction to residue Leu-337 in complex with 2 d. Overall, the contacts formed by 2 d in the zVDR complex stabilize the agonist conformation of VDR in agreement with the agonist potency of this novel compound. The weaker hydrogen bonds with His-333 and His-423 and loss of interaction with Leu-337 explain the observed difference in activity between the 1,25D and compound 2 d. Conclusion In summary, we have designed and synthesized three analogs of the hormone 1α,25-dihydroxyvitamin D 3 bearing an allenic unit attached to C17 as the structural element to impart conformational rigidity near the D-ring. Highlights of the synthetic route (about 14 % overall yield from bicyclic ketone 7, 14 steps), include the access to the allenic moiety by an orthoester-Claisen rearrangement and the formation of the triene system by a Pd 0 -catalyzed cyclization/cross coupling process involving an enoltriflate, precursor of the A-ring, and a vinyl boronate containing an allenic side-chain unit corresponding to the CD-Side chain framework. Biological evaluation of 2 d with the highest affinity for VDR, reveals that the geometry imposed by the C17-allene moiety reduces the transcriptional potency and calcemic activity. The crystallographic structure of 2 d in complex with the VDR LBD provides information concerning side-chain conformational requirements for the design of new noncalcemic vitamin D analogs of potential therapeutic interest. Experimental Section General: For details on the general materials and methods, see Supporting Information. Identification and Analysis of microRNA-Disease Associations with Kernelized Bayesian Matrix Factorization MicroRNA (miRNA) molecules, which are effective on the initiation and progression of many different diseases, are a type of noncoding RNA with a length of about 22 nucleotides. Scientists have reported the importance of miRNAs in the prevention, diagnosis, and treatment of complex human diseases. Therefore, in the last decade, researchers have been working hard to find potential miRNAdisease associations. Many computational techniques have been developed because of the experimental techniques are time-consuming and expensive used to find new relationships between miRNAs and diseases. In this study, we suggested Kernelized Bayesian matrix factorization (KBMF) technique to predict new miRNA-disease relationships. We applied 5-fold cross validation technique and obtained an average value AUC of 0.9450. Also, we applied case studies based on breast, lung, and colon neoplasms to prove the performance of KBMF technique. The results showed that KBMF can be used as a reliable computational model to reveal possible miRNA-disease relationships. Introduction MicroRNAs are a type of non-coding RNAs with a length of about 22 nucleotides. Several research studies have concluded that miRNAs have important functions in various basic biological processes such as cell development, signal transduction, proliferation, apoptosis, differentiation, viral infection, metabolism, and aging (Bartel, 2009;Chen, Zhou, & Zhao, 2018;Lan et al., 2018;Tang, Zhou, Zheng, Zhang, & Sha, 2019). With the development of molecular biology and biotechnology, researchers have revealed that miRNAs have an important links with many diseases (X. Chen et al., 2016;Kim, 2015). For example, miRNA de-regulation triggers the development of various cancers such as breast, skin, lung, colon, prostate etc. Furthermore, down-regulations of miRNA-143 and miRNA-145 have been observed in colorectal tumors and especially breast cancer (Espinosa & Slack, 2006). In this study, first of all we calculated the functional similarity (FS) for each miRNA and the semantic similarity (SS) for each disease. Secondly, we calculated the Gaussian Interaction Profile (GIP) kernel similarities for both miRNA and disease. Thirdly, we integrated the miRNA GIP kernel similarity with FS and the disease GIP kernel similarity with SS. Lastly, we estimated the potential relationships between miRNAs and diseases by analyzing these data with the Kernelized Bayesian Matrix Factorization (KBMF) method. We evaluated the success of our model with the most widely used 5-fold cross-validation technique and several case studies. Material and Method We obtained 495 miRNAs and 383 diseases data set from the HMDD v2.0. This data set includes 5430 miRNA-disease relationships that were experimentally verified (Y. Li et al., 2014). The relationships between miRNAs and diseases are represented by constructing an adjacency matrix (A495x383) matrix. To calculate disease semantic similarity, we first downloaded the Medical Subject Headings (MeSH) definitions from the web page of National Library of Medicine (http://www.nlm.nih.gov). The connections between various diseases can be explained by using Directed Acyclic Graph (DAG). In DAGA, when calculating the semantic value of disease A, the contribution of other diseases can be expressed as given below: where Δ represents the contribution coefficient between disease t with its child disease t'. Moreover, the semantic value (DV) of disease A can be described with Eq. 2. The SS between disease A and disease B can be computed as shown below: where all ancestor of disease A and disease B, including disease A and disease B themselves, are represented by TA and TB. DA(t) and DB(t) represent the semantic value of disease t associated with disease A and disease B, respectively. Semantic similarity of each disease is calculated according to the Eq. 3 (D. Wang et al., 2010). Gaussian Interaction Profile (GIP) Kernel Similarity for miRNAs and Diseases Assuming that similar diseases tend to be associated with miRNAs with similar functions, we have created miRNA GIP kernel similarity and disease GIP kernel similarity (Lan et al., 2018;van Laarhoven, Nabuurs, & Marchiori, 2011). The GIP kernel similarity value (GM) between miRNA m(i) and miRNA m(j) can be computed with Eq. 4. Similarly, the GIP kernel similarity value (GD) between disease d(i) and disease d(j) can be computed with Eq. 5. Here, and parameters control

kernel bandwidth and can be obtained from the Eq. 6 and Eq. 7. The parameters δm and δd and represent the new bandwidth parameters and were adjusted to 1 according to ( Integrated Similarity for miRNAs and Diseases We have integrated the functional similarity and the GIP kernel similarity of miRNAs using Eq. 8. Similarly, we have combined the semantic similarity and the GIP kernel similarity of diseases with Eq. 9. where, β was assumed to be 0.5. Kernelized Bayesian Matrix Factorization (KBFM) The KBMF described in detail in the study reported by Gönen et al. (Gönen, Khan, & Kaski, 2013) is an effective way to obtain a bipartite graph by multiple data source integration. We assume that miRNAs and diseases come from two domains: 5-fold Cross Validation (CV) Technique We tested the predictive ability of the KBMF method we used in this study with a 5-fold cross validation technique. In this validation technique, we divided all known miRNA-disease relationships into five subgroups. For testing of the model four of the 5 subgroups were used as training data and one as test data. Additionally, we have computed false positive rate (FPR) and true positive rate (TPR) and have plotted the receiver operator characteristics (ROC) curve according to the results, then have computed the area under the ROC curve (AUC) for performance evaluations. As a result, we plotted the ROC curve shown in Fig. 1, and computed AUC value of 0.9450 for 5-fold cross-validation. We (Chen & Huang, 2017), and NDAMDA (X. Chen, L. Y. to prove the performance of KBMF method we used. The other eight methods, using 5-fold cross-validation technique, had AUC values of 0. 8185, 0.8767, 0.6723, 0.8878, 0.8980, 0.9048, 0.9181, and 0.8935, respectively. Figure 2 shows the comparative AUC values. Here, it is clearly seen that KBMF method gives a better result than the other eight compered methods. Case Studies In order to predictive accuracy demonstration of the KBMF method, three case studies have been conducted based on breast, lung, and colon neoplasms from databases of miR2Disease, dbDEMC, and HMDD v2.0. In our model, we used 5430 known miRNA-disease relationships from HMDD v2.0 as a training set. In this training set, we made the known relationships for each disease to zero. Based on the results obtained, all miRNAs for three diseases were ranked according to their scores. Then, the first 20 miRNAs predicted for each disease were confirmed from three different databases mentioned above. Breast neoplasms, which cause many deaths each year, are the most common type of female cancer among female cancers and comprise approximately 22% of female cancers (Al-Hajj, Wicha, Benito-Hernandez, Morrison, & Clarke, 2003;Qinghua Jiang et al., 2010). The list of the top 20 candidate miRNAs predicted by our method for breast neoplasm is shown in Table 1. We have confirmed all 20 miRNAs are 100% associated with breast cancer from the mentioned databases. Lung neoplasms are one of the main factors in cancer-related deaths in the world. We have listed the top 20 candidate miRNAs for lung neoplasm using the same method (shown in Table 2). Examining the table, it can be seen that 19 out of 20 candidate miRNAs were confirmed to be associated with lung cancer. In other words, we can say that 95% of candidate miRNAs are associated with lung cancer. Conclusions and Recommendations Related research studies have shown that miRNAs play a major role in various biological processes (Bartel, 2009;Xing Chen et al., 2018;Lan et al., 2018;Tang et al., 2019). Therefore, it is important to determine miRNA-disease relationships by computational techniques before applying costly and timeconsuming experimental techniques. In this study, we used the Kernelized Bayesian matrix factorization method to predict possible relationships between miRNAs and diseases. In our previous study (Toprak & Eryilmaz, 2020), high quality results were obtained by using similar approaches with a different method. We evaluated the predictive performance of our model with 5-fold cross validation technique and several case studies. The calculated AUC value of the 5-fold cross validation technique is 0.9450. Also, we conducted three case studies like breast, lung, and colon neoplasms to further verify the performance of KBMF and validated the results with dbDEMC, miR2Disease and HMDD databases. The results indicates that the KBMF method can be used as an efficient method to predict possible relationships between miRNAs and diseases. GRP 78 antibodies are associated with clinical phenotype in neuromyelitis optica Abstract Background We previously reported the association between blood–brain barrier (BBB) dysfunction and glucose‐regulated protein 78 (GRP 78) autoantibodies in neuromyelitis optica (NMO). Objective We clarify whether the BBB‐endothelial cell activation induced by immunoglobulin G (IgG) is associated with the clinical phenotype, disease activity, and markers of BBB disruption. Methods We purified serum IgG from 24 serum samples from patients with NMO spectrum disorder (NMOSD), who were positive for anti‐AQP4 antibodies (longitudinally extensive transverse myelitis [LETM], n = 14; optic neuritis [ON], n = 6; other phenotype, n = 4) and nine healthy controls. IgG was exposed to human brain microvascular endothelial cells (TY10) and the number of nuclear NF‐κB p65‐positive cells, as a marker of endothelial cell activation, was analyzed using a high‐content imaging system. Change in BBB permeability was also measured. The presence of GRP78 autoantibodies was detected by Western blotting. Results In the LETM group, IgG significantly induced the nuclear translocation of NF‐κB p65 in comparison to the ON and healthy control groups. A significant correlation was observed between the number of NF‐κB nuclear‐positive cells and clinical markers of BBB disruption, including Gd enhancement in spinal MRI and the cerebrospinal fluid/serum albumin ratio. This effect was significantly reduced at the remission phase in the individual NMOSD patients. Furthermore, GRP78 antibody positivity was associated with the LETM phenotype and disease severity in NMOSD patients. Conclusion Endothelial cell activation was associated with the LETM phenotype, clinical markers of BBB disruption and disease activity. These observations may explain the phenotypic differences between the NMOSD subtypes, LETM, and isolated ON. Introduction Neuromyelitis optica (NMO) is an inflammatory disease associated with recurrent episodes of optic neuritis (ON) and longitudinally extensive transverse myelitis (LETM), leading to severe loss of visual and motor function. 1 A specific feature of NMO is the presence of an autoantibody against aquaporin 4 (AQP4), which is densely expressed in the astrocytic foot processes; recent studies have demonstrated that anti-AQP4 antibodies have a pathogenic role. 2 Isolated ON is one of the major clinical signs in NMO as well as in multiple sclerosis (MS). 3 The ON attacks in NMO are more severe than those in multiple sclerosis (MS), and can lead to unilateral or bilateral blindness. 3 In addition, the lesions and involvement in optic chiasm and tracts in NMO are more extensive in comparison to those in MS in the MRI. 4 Serum anti-AQP4 antibodypositive patients with isolated ON are recently classified as having NMO spectrum disorder (NMOSD), because they have a high risk of eventual conversion into definite NMO. 5,6 The disruption of the blood-brain barrier (BBB) plays key roles in the pathogenesis of NMOSD. [7][8][9] We recently identified that glucose-regulated protein (GRP) 78 autoantibodies are a potential biomarker associated with BBB-endothelial cell activation in NMO. 10 However, it remains unclear whether endothelial activation is associated with the disease activity or clinical phenotype of NMO. In the present study, we evaluated the contribution of IgG in serum samples obtained from individual patients with each clinical phenotype of NMO (ON and LETM) to BBB breakdown using human BBB-derived immortalized endothelial cells. We next clarified the association between BBB disruption and the patients' clinical profiles and investigated the GRP78 antibody status of patients with these two phenotypes of NMO. Patient sample This study was approved by the ethics committees of the Medical Faculties of Yamaguchi Universities. Written informed consent was obtained from each participant. Serum samples were collected from 24 NMOSD patients who were diagnosed at Yamaguchi University Hospital based on the revised criteria for NMOSD (Table 1). All patients were found to be positive for anti-AQP4 antibodies using either an immunofluorescence method or ELISA methods. 11 We included the 14 samples from patients with LETM attacks (isolated LETM, n = 13; definite NMO, n = 1), six samples from patients with ON attacks (isolated ON, n = 5; definite NMO, n = 1) and four samples from patients with other attacks (short myelitis, n = 3; brainstem symptom, n = 1) during the acute phase within 1 month after the initiation of the attack (Table 1). All LETM patients showed paresis in the legs (Patients 1-14). One LETM patient (Patient 4) initially showed area postrema syndrome before developing severe quadriplegia with respiratory failure. Another patient with other NMOSD phenotype (Patient 24) presented with brainstem syndromes (double vision and dizziness), and a lesion of brainstem including area postrema was observed in the magnetic resonance imaging (MRI) (Fig. S1). We also included five samples from LETM patients in the remission phase, who were being treated with corticosteroids after relapse and who had been in clinical remission for at least 6 months (Patient 1, 2, 3, 7, and 9 in Table 1). Five isolated ON patients had first or second attack of unilateral or bilateral visual loss and showed optic nerve changes in MRI, including enlargement, T2 hyperintensity, and gadolinium enhancement; however, no abnormal brain or spinal cord lesions were observed in MRI (Patient 16,17,18,19,20). Cerebrospinal fluid (CSF) samples were concurrently obtained from all NMOSD patients during the acute phase. We investigated the disease duration, number of relapses, change in the score in the Expanded Disability Status Scale (EDSS) from before to after relapse (DEDSS), IgG index (as a marker of intrathecal IgG synthesis), CSF/ serum albumin ratio (Q Alb) (as a marker of BBB dysfunction), length of the spinal cord lesion in MRI, and the presence of Gd-enhanced lesions in MRI in the 24 NMOSD patients (Table 1). In addition, nine individuals served as healthy controls (HCs) (male, n = 4; female, n = 5; mean ages, 32.6 years). All samples were immediately stored at À 80°C until the analysis and were inactivated at 56°C for 30 min immediately before the analysis. The IgG preparations were purified from sera using a Melon Gel IgG Spin Purification Kit (Thermo Fisher Scientific, MA). Immunohistochemistry and the highcontent imaging assay TY10 cells are adult human brain microvascular endothelial cells (BMECs) immortalized with temperature-sensitive SV40 large T antigen (tsA58), as previously described. 12 All of the analyses were performed 2 days after a temperature shift from 33 to 37°C. The cells were cultured in medium containing IgG (final concentration, 500 µg/mL) obtained from patients with NMOSD or healthy controls after substitution for serum-free MCDB 131 medium for 1 h for the NF-jB p65 analyses; the primary Abs (NF-jB p65 rabbit monoclonal antibody [mAb]) and secondary Abs (Alexa Fluor 488 goat antirabbit IgG) were previously described. TY10 cells were fixed with 4% paraformaldehyde (PFA), washed and then permeabilized with 0.3% Triton X-100. After blocking overnight in 5% FBS/0.3% Triton X-100 in PBS, the cells were incubated with primary Abs, followed by the secondary Abs at room temperature. Five thousand cells per well were plated in Greiner CELLSTARâ 96-well plates (Greiner), then immunostaining for NF-jB p65 was performed. The plates were scanned, and images were captured by an In Cell Analyzer 2000 (GE healthcare) at 9 20 magnification with six fields of view per well (equivalent to 800-1000 cell events). The images were then analyzed with the In Cell Analyzer software program (GE healthcare). The data represent the mean value of triplicate experiments. The paracellular permeability of 10-kDa dextran TY10 cells were cultured on 24-well collagen-coated Transwell tissue culture inserts (0.4-mm pore size) for 3 days at 33°C and then 2 days at 37°C. TY10 cell monolayers were exposed, on the luminal side, to NMOSD IgG or control-IgG (500 lg/mL) for 24 h at 37°C. After the replacement of the media, FITC-dextran fluorescence (10 kDa; Sigma-Aldrich) was added to the luminal insert (final concentration, 1 mg/mL), and 200 lL of medium was collected from the abluminal chamber over 40 min. After transfer into 96-well black plates, fluorescence signals were measured at 490/520 nm (absorption/emission) wavelengths using a FlexStation 3 Multi-Mode microplate reader (Molecular Devices). Western blotting using human recombinant GRP78 protein Western blotting was performed as previously described. 7,8 We used the human

full length GRP78 recombinant protein (Abcam, MA, U.S.A) as antigen. Individual IgG (5 µg/mL) from 14 LETM patients, six ON patients, four other NMOSD phenotype patients and 10 healthy controls, and anti-GRP78 antibodies (dilution 1:200) was used as the primary antibody. The protein samples (2 lg) were fractionated in a 10% gel and electrophoretically transferred onto polyvinylidene difluoride membranes (Amersham, Chalfont, UK), as previously described. 7,8 The membranes were treated with the primary antibody in PBS-T and 5% milk for an hour, followed by incubation with the anti-human secondary fluorescent antibodies (dilution 1:5000) for an hour. The bands were visualized with an enhanced chemiluminescence kit (ImmunoStar LD, Japan). The relative density of each band was measured using the Quantity One software program (Bio-Rad, Hercules, CA). Depletion of GRP78 antibodies from LETM-IgG or ON-IgG For immunoprecipitation, 500 lg/mL of LETM-IgG (Patient 3) or ON-IgG (Patient 17) was incubated with 5 lg of HEK 293T cell lysates with or without the overexpression of FLAG-tagged GRP78 (Origene) for 4 h at 4°C, and then incubated with 40 lL of anti-FLAG-IgG coupling resin (EZview Red Anti-FLAG M2 Affinity Gel beads; Sigma-Aldrich), for 2 h at 4°C. After the GRP78 antigen-antibody complexes were precipitated, the supernatants (LETM-IgG or ON-IgG with/without GRP78 antibodies) were used for the analysis. 10 Images were captured and evaluated by an In Cell Analyzer 2000 (GE Healthcare) at 9 20 magnification. Statistical analysis All statistical analyses were performed using the Prism 7 software program (Graph Pad Software). For analyses with a single comparison, either the unpaired Mann-Whitney U or a paired Student's t-test was used to determine statistical significance (two-sided). For analyses with multiple comparisons, a one-way ANOVA between individual groups was performed using Tukey multiple comparisons test. All values are expressed as the mean AE SEM. Pearson's correlation coefficients were used to test associations. The Fisher exact probability test was used to assess differences in the GRP78 antibody positivity between groups. *P < 0.05 was considered to indicate statistical significance. IgGs from the acute LETM patients induced BBB-endothelial cell activation Three IgGs (Patients 3, 4 and 12) from the LETM patients significantly induced the nuclear translocation of NF-jB p65 in BMECs in comparison those from ON patients and healthy controls ( Fig. 1A and B). We next compared the percentage of nuclear NF-jB p65-positive BMECs in the LETM, ON, other NMOSD phenotypes (others), and healthy control groups. The number of nuclear NF-jB p65-positive cells in the LETM group was significantly increased in comparison to the ON, others, and healthy control groups (Fig. 1C). Furthermore, we confirmed that the permeability was increased after exposure to IgG from LETM patients but not after exposure to IgG from ON or other NMOSD patients or healthy controls (Fig. 1D). In addition, we determined the correlations between the spinal MRI and laboratory findings and the percentage of NF-jB p65-positive BMECs after exposure to NMO-IgG. LETM patients with Gd-enhanced lesions in spinal MRI showed greater amount of NF-jB nuclear-positive BMECs in comparison to those without Gd-enhanced lesions ( Fig. 2A). Higher percentage of NF-jB p65-positive BMECs and higher permeability of BMECs incubated with NMO-IgG was correlated with a higher Q Alb level and DEDSS (Fig. 2B-E). In addition, in the analysis using IgG obtained from the LETM patients between the acute and remission phases (in the same individual), the number of nuclear NF-jB p65-positive cells was significantly decreased after exposure to IgG from patients during the remission phase (Fig. 2F). A specific positive band against human GRP78 was detected in the IgG from NMOSD patients by western blotting using the recombinant protein prepared from Escherichia coli. The number of patients with GRP78 antibodies in the LETM group (10 of 14, 71%) was significantly higher in comparison to that in the ON group (1 of 6, 17%), the other NMDSD phenotype group (0 of 4, 0%) Figure 1. NF-jB p65 activation of brain endothelial cells after exposure to IgG from LETM or ON patients. (A) Immunostaining of human brain microvascular endothelial cells (TY10 cells) for NF-jB p65 (green) after exposure to IgG (500 lg/mL) from patients with longitudinally extensive transverse myelitis (LETM) or optic neuritis (ON), or healthy controls (HC). Images were captured by an In cell analyzer 2000 (B) Quantification of nuclear NF-jB p65-positive TY10 cells by high-content imaging after exposure to LETM-IgG, ON-IgG, other NMOSD phenotype (others)-IgG, or control-IgG (500 lg/mL). Data were normalized to cultures unexposed to human IgG and are shown as the mean AE SEM of four independent experiments performed in triplicate (*P < 0.05 vs. control followed by Tukey's multiple comparison test). (C) Scatter plots of the number of nuclear NF-jB p65-positive TY10 cells, as determined by high-content imaging after exposure to LETM-IgG (LETM group), ON-IgG (ON group), other NMOSD phenotype-IgG (others group), or control-IgG (Healthy control group). The number of nuclear NF-jB p65-positive cells in the LETM group was significantly increased in comparison to the ON, others and control groups. The P values were determined by a one-way ANOVA followed by Tukey's multiple comparison test (*P < 0.05 vs. control, ON or other group followed by Tukey's multiple comparison test). (D) Scatter plots of the 10-kDa dextran permeability of TY10 cells after exposure to LETM-IgG, ON-IgG, other-IgG, or control-IgG (***P < 0.001 vs. control, ON or other group followed by Tukey's multiple comparison test) Table 1). In contract, no bands were found in any of the serum samples from 10 healthy controls (Fig. 3A). The presence of CSF GRP78 antibodies was detected in only one LETM patient (patient 4) among six NMOSD patients (5 LETM and 1 ON patients; 1 of 6, 16%) (Fig. 3B). Positivity for GRP78 antibodies was significantly associated with an increased BBB permeability using our in vitro model (Fig. 3C) as well as with a higher DEDSS, a clinical marker of disease severity (Fig. 3D). The removal of GRP78 antibodies from LETM-IgG, not ON-IgG, resulted in less NF-jB nuclear translocation of BMECs (Fig. 3E). Discussion It remains unclear why NMO predominantly affects the spinal cord and optic nerves. Some reports have shown that the optic nerve susceptibility of NMO patients may be associated with higher expression levels of AQP4 proteins and the relative abundance of large orthogonal arrays of particles that bind the anti-AQP4 antibodies in astrocytic endfeet of the optic nerve in comparison to the brain. 3,13,14 Another possible explanation is that dysfunction of the blood-optic nerve barrier (BONB) or bloodspinal cord barrier (BSCB) may determine the development of the clinical phenotype (ON or LETM), because this barrier restricts the entry of anti-AQP4 antibodies into the optic nerve or spinal space. We recently reported that the GRP78 autoantibodies in NMO-IgG were associated with the breakdown of the BBB in NMO. 10 The aim of this study was to address the next question; whether BBB-endothelial cell activation and GRP78 antibodies are correlated with the clinical phenotype and disease activity, and whether it is a clinical marker of the breakdown of the BBB in NMOSD. The cell surface expression of GRP78 is involved in NF-jB signal transduction 15 and the nuclear translocation of NF-jB p65 in BMECs, as a marker of BBB activation, is associated with BBB dysfunction. 10 In the present study, we demonstrated that three IgGs from individual LETM patients significantly induced NF-jB p65 nuclear translocation in the BMECs in comparison to the IgGs from controls. As a group, we also observed the significant induction of cell activation and increase in BBB permeability in the LETM group than the ON, other NMOSD phenotype and healthy control groups. This effect was significantly decreased in the individual NMOSD patients during the remission phase. Furthermore, we found a significant correlation between endothelial cell activation in the BBB and two clinical markers of BBB dysfunction (Q Alb and Gd-enhanced lesions)/clinical marker of disease severity (DEDSS) in NMOSD. A significant association with an increased BBB permeability and a higher Q Alb/DEDSS in NMOSD patients was also observed. Taken together, the activation of endothelial cells in the BBB, which was induced by NMO-IgG, was associated with the LETM phenotype, the presence of clinical markers of BBB disruption, disease severity, and disease activity in NMOSD patients. Furthermore, the rate of GRP78 autoantibody positivity in the LETM group was significantly higher than that in ON group (LETM 71% vs ON 17%, others 0%). The presence of GRP78 antibodies was correlated with an increased DEDSS (disease severity) and BBB leakage in our in vitro BBB model. These results suggest that the phenotypical discrepancy between LETM and ON may be derived from the difference in the disruption of the BBB/BSCB that is caused by GRP78 autoantibodies. Namely, the large amount of GRP78 antibodies in IgG from definite NMO or LETM patients can cause the diffuse destruction of the BBB/BSCB and the massive entry of AQP4 antibodies, thus leading to the development of severe clinical symptoms and central nerve system (CNS) disability. In contrast, the lower amount of GRP78 autoantibodies in IgG from isolated ON patients is not enough to disrupt the BBB/BSCB; thus, these patients develop optic nerve symptoms without CNS symptoms. Four LETM patients (patients 1, 2, 3, and 7) were positive for GRP78 antibodies in their serum samples but, not their CSF samples. The positivity of GRP78 antibodies in the CSF was less marked than that in the serum of NMOSD, suggesting that GRP78 antibodies may be produced by peripheral B cells. One LETM patient (patient 4) was positive for GRP78 antibodies in both the sera and CSF, possibly reflecting the entry of GRP78 antibodies into the CNS space due to BBB disruption. Interestingly, serum GRP78 antibodies were negative in one patient (patient 24), who developed only brainstem symptoms Figure 2. Correlations between the clinical findings and the percentage of NF-jB p65-positive BMECs/BBB permeability after exposure to NMO-IgG. (A) The number of nuclear NF-jB p65-positive BMECs in the LETM patients with Gd-enhanced lesions on spinal MRI was significantly increased in comparison to those without Gd-enhanced lesions (*P < 0.05). (B and C) Correlation between the number of nuclear NF-jB p65positive cells after exposure to IgG from acute NMOSD patients and the albumin ratio (Q Alb) (B) and DEDSS (C). (D and E) The correlation between the 10-kDa dextran permeability of TY10 cells after exposure to IgG from acute NMOSD patients and the albumin ratio (Q Alb) (D) and DEDSS (E). (F) The number of nuclear NF-jB p65-positive cells was significantly decreased in the remission phase. Statistical significance was assessed by a paired two-tailed t-test (*P < 0.05) including area postrema, suggesting that anti-AQP4 antibodies had entered the area postrema, where endothelial cells lack tight junctions and the AQP4 expression is enriched, leading to brainstem symptoms in this case. The reason why LETM-IgG but not ON-IgG causes the breakdown of the BBB is not still clear. There are two possible explanations: LETM patients have a higher titer of GRP78 antibodies than ON patients. In the present study, the association between the GRP78 antibody titer and the NMO phenotype was not examined because we have not established an ELISA to determine the GRP78 antibody titer. The other possible explanation is the difference in the cell surface expression of GRP78 between BBB/BSCB-endothelial cells and BONB-endothelial cells. We found that the cell surface expression of GRP78 was abundant in BMECs. 10 In contrast, the expression of GRP78 on BONB-endothelial cells may be lower than that on BBB-endothelial cells. Further studies using human BONB-endothelial cells are needed to understand the role of GRP78 autoantibodies in the breakdown of the BONB. assistance in establishment of high-content imaging system. Facebook group affiliation ties, group topics, and HIV behavioral characteristics among young Black men who have sex with men: Potential for public health intervention Highlights • YBMSM were more likely to belong to personal/professional development groups.• YBMSM clustered around pairs of LGBTQ identity, sex, and nightlife groups.• Regular testers tended to belong to LGBTQ identity and nightlife groups.• Those who engaged in condomless sex tended to affiliate with LGBTQ identity groups.• Those who were aware of PrEP aware tended to affiliate with chat groups. Introduction In the United States, HIV incidence is disproportionately concentrated at the intersection of sexual and racial minority communities. Here, young Black men who have sex with men (YBMSM) experience greater burden of HIV incidence than any other subgroup by race/ ethnicity, age, and gender

(Centers for Disease Control and Prevention, 2017). YBMSM, however, are not monolithic, nor are their social environments. The social contexts in which YBMSM communicate and form relationships are critical in determining the HIV protection and risk they experience. For example, YBMSM members of the Ballroom House and Gay Family communities, clandestine systems of queer kinship in LGBTQ communities of color (Arnold & Bailey, 2009;Bailey, 2009), are more likely than non-members to be accepted in their gender and sexual identities, have greater access to emotional and instrumental social support, and participate in routine testing (Arnold & Bailey, 2009;Kubicek et al., 2013;Young et al., 2017a). Similarly, HIV positive YBMSM with strong connections to the Black community are known to have greater antiretroviral adherence than those on the margins of this community (Behler, Cornwell, & Schneider, 2018). Increasingly, social interactions among YBMSM occur online. Social networking sites (SNS) -i.e., the web-based platforms that enable connection and communication between usersare prominent and mainstream features of young adults' lives, and YBMSM are no exception to this rule. About 90 percent of young adults use social media of some kind, with Facebook being the most popular irrespective of race (Pew Research Center, 2018). Further, early trends in social media consumption indicated that young LGBTQ adults engaged one another on SNS more frequently than their heterosexual counterparts (Harris, 2008;Taylor, 2013). Together, these trends suggest that SNS are not only relevant social settings for YBMSM but that they also present opportunities for public health engagement (Allison et al., 2012;Holloway et al., 2014aHolloway et al., , 2014bYoung et al., 2013). Much has been written about the potential of SNS and other mobile applications as tools for HIV prevention engagement in this community, however little is known about if or how these interactive environments yield HIV risks and protections for users. Numerous studies document HIV risk and prevention behaviors among MSM users of partner-seeking SNS, such as Grindr (Goedel & Duncan, 2015;Landovitz et al., 2013;Rice et al., 2012;Winetrobe et al., 2014), but a truly relational account of HIV risk and protection in online networks remains undeveloped. A relational account brings explicit attention to patterns of social interaction that expose individuals to exogenous sources of HIV risk and protection, namely in the characteristics and behaviors of their online peers and in the topics they discuss. To this end, we underscore the intermediary role of Facebook groups in online network structure. Facebook groups are virtual organized communication platforms where users go to communicate in groups, share common interests, and express opinions, all typically around a common cause, interest, activity or identity. As such, the designated topic of a group is a barometer for the subject matter to which a user is exposed. With this in mind, we explore whether and how group topics bring structure to an HIV risk or preventive network among YBMSM. From a network perspective, we typically imagine HIV risks and protections emerging from the organization of individual behaviors in personal networks. On the other hand, Facebook group memberships represent much broader social networks formed through crowds with shared identity and interest, reflecting YBMSM's preference for associating with others like themselves (McPherson, Smith-Lovin, & Cook, 2001) in a virtual setting. Thus, Facebook membership may serve as an additional source of influence by virtue of the issues discussed in these settings, which can reflect or affect individuals' attitudes about HIV-related behaviors through diffusion of group-specific information. In prior work we examined the privacy level of a Facebook group as a mechanism of group affiliation among YBMSM (Young et al., 2018). We now expand on this approach with our attention to Facebook group topics that are explicitly related to HIV vulnerability and resilience, like sexual identity, sex, and nightlife as well as topics indirectly related like professional development (blinded for review), To this end, we use exponential random graph models (ERGMs) to model the structure of a Facebook group affiliation network among YBMSM by accounting for the dependencies between group affiliation ties and attribute-based covariates like group topics and individual sex behaviors. We anticipate our analysis will reveal local configurations within the Facebook group affiliation network, characterized by particular HIV-related topics and behavioral characteristics, that can be interpreted as constituting online contexts of prevention and risk for network members. Further, identifying group topics that appeal to YBMSM allows us to establish which types of content they naturally seek out and are exposed to on SNS and, consequently, the topics that concerted HIV prevention messaging will have to compete with or leverage to gain traction in these virtual spaces. Of great public health importance is the direct attention to the types of groups that offer the greatest potential for HIV prevention engagement and intervention in this community. Methods Data were collected April 2014 to May 2015 as part of a longitudinal cohort study of YBMSM living in Chicago[]. Here we draw on data from Wave 2 of the study when Facebook group affiliations were collected. As described in previous work (blinded for review), participants were recruited using a variant of classic link-tracing called Respondent Driven Sampling (RDS). Widely used in public health studies (Goel & Salganik, 2010), RDS enables valid statistical inference of "hard to reach" populations (e.g., intravenous drug-users, sex workers, men who have sex with men) by providing a design for sampling as well as a method for obtaining parameter estimates of the target population. Referral chains were generated from 62 RDS "seeds", drawn from a variety of social spaces that YBMSM occupy, including LGBTQ social venues, online networking sites, community-based organizations, and HIV treatment and prevention programs. Candidate participants were eligible to be interviewed if they: 1) self-identified as African American or Black, 2) were assigned male at birth, 3) were between 16 and 29 years of age, and 4) reported oral or anal sex with a male within the past 24 months. Sampling procedures resulted in a baseline sample of 618 YBMSM, 525 of which were retained at Wave 2. At each study wave, respondents were asked about demographics, sexual health, health behaviors, and sexual and social networks. Additionally, Facebook data, including Facebook group memberships, were obtained from consenting respondents, using a software application that accessed Facebook's application programming interface (API). Using the application interface, respondents logged into their primary Facebook account, which enabled the application to retrieve the respondent's Facebook groups. This method of Facebook data acquisition is now obsolete, as Facebook made changes to its API permissions. Generating the Facebook group affiliation network At wave 2, 423 (of 525) respondents self-reported having an active Facebook profile, 301 (71%) of whom consented to the Facebook data collection and belonged to at least one Facebook group. Filtered cases (n ¼ 224) included 99 (44%) individuals who did not have a Facebook profile, 76 (34%) who had a profile but did not consent to Facebook data collection, and 46 (21%) consenters who did not belong to any Facebook groups. Filtered cases did not differ significantly from the analytic sample (n ¼ 301) by HIV testing, PrEP awareness, condomless sex, and group sex. Individuals in the analytic sample were, however, more likely to be HIV positive (OR ¼ 1.75, p < 0.05). To construct a corresponding Facebook group sample, we began with 4743 unique Facebook groups that were associated with the 301 YBMSM with available group data. Of these groups, approximately 80% (n ¼ 3813) had only one YBMSM study respondent member. Excluding these groups and groups that lacked a description for identifying a primary group topic yielded 657 Facebook groups with 2 or more study respondent members for further consideration. Because the distribution of YBMSM study respondent members across these 657 groups was characterized by tail extremity relative to a normal distribution, we selected the 90th percentile as a cutoff for inclusion of Facebook groups. This corresponded to groups with 8 or more YBMSM members and yielded a final group sample of 82 groups. Filtering out respondents who had no affiliations with these 82 groups resulted in a final network comprised of 221 YBMSM and 82 Facebook groups. Characterizing Facebook groups The topic orientation of a Facebook group is suggestive of the interests of its members and what they discuss and, therefore, has implications for HIV care and sex behavior engagement. As described in greater detail elsewhere (Young, Fujimoto, Alon, Zhang, & Schneider, 2019), we drew on the name of a group and its brief description to identify a primary topic. Topics were derived from a survey of the literature and from an environmental scan of a random sample of Facebook groups in our analytic sample. In total, eight topics were identified and are described in Table 1. Seven of the eight topics are present in our analytic group sample (n ¼ 82), including: LGBTQ Identity, Sexual Attraction, Chat, Nightlife, Personal/Professional Development, Recreational Interests, and Health & Well-being. Table 1 Facebook group topic classifications. Topic Category Definition Sexual Attraction a Groups that underscore physical/sexual attractiveness and that enable partner "cruising", flirtatious exchange, sexual networking, and sexual expression Chat a Groups that provide a casual forum for posting and conversational exchange among members; posts tend not to be subject specific and content tends to be random (e.g., gossip groups) LGBTQ Identity a Groups that are about gay pride or gay identity; the focus is on celebrating gay identity and "being" in the LGBTQ community (e.g., LGBTQ advocacy groups); also includes groups dedicated to the Ballroom House community, which are queer surrogate kinship groups that take on the role structure of traditional heteronormative families (e.g., mothers, fathers, children, siblings) and participate in gender expression competitions/performances. Nightlife a Groups that promote eventse. HIV-related characteristics of YBMSM HIV status. The HIV status of each respondent was determined on the basis of blood testing conducted at time of data collection. In the model we estimate the effects of being HIV positive. Sex behaviors. Sex behaviors included condomless sex and group sex. Condomless sex was measured on the basis of whether or not a respondent indicated not always using condoms with any named sex partner in the past 9 months, which corresponds to the respondent's last study visit. Group sex is a self-reported measure of whether or not a respondent engaged in sex with two or more partners at the same time at least once in the past 9 months. Prevention traits. Prevention characteristics included regular HIV testing and awareness of pre-exposure prophylaxis (PrEP) for HIV prevention. HIV testing frequency was based on how frequently a respondent had been tested since their last study visit. Given CDC testing recommendations for MSM (testing every 3-4 months), regular testers were defined as those who had been tested at least twice since their last visit. PrEP awareness was ascertained by asking respondents, "Before today, have you heard of PrEP?" No other PrEP-related information was presented to respondents at the time of data collection. Data analysis Toward understanding how Facebook group topics and HIV-related characteristics bring structure to the Facebook group affiliations among YBMSM, our analysis is driven by the following research questions: RQ1: Which Facebook group topics are YBMSM more likely to affiliate with? RQ2: Do individuals cluster around Facebook groups that focus on the same topic? RQ3: Are YBMSM with particular HIV-related characteristics more likely to belong to Facebook groups? RQ4: To what extent are affiliations with particular group topics associated with group members' HIV-related characteristics? To begin, we conceptualize Facebook group affiliations among YBMSM as a bipartite (or 2-mode) network, comprised of YBMSM (n ¼ 221) and Facebook groups (n ¼ 82) with ties between node sets representing group membership . We then apply a class of statistical models for social networks called exponential random graph models (ERGMs) to model network structure (Robins et al., , 2007Wasserman & Pattison, 1996;Wasserman & Robins, 2005). Traditional statistical methods like regression analysis assume independence in observations; meaning that what one observes about an individual, like their sexual orientation, is assumed to occur independently from what one observes about another's sexual orientation. That said, network (or relational) data structures, such as a Facebook group affiliation network, violate this assumption because the presence of some ties in the network affects the probability that other ties may be observed . For example, an individual's decision to join a particular Facebook group may depend on the other types of groups they

belong to or the other types of people that belong to a group (Young et al., 2017a,b). ERGMs, on the other hand, permit inferences about how network ties emerge by estimating the likelihood of a tie being present (or absent) in the network as a function of local tie-based configurations. Each configuration represents a distinct social process, such as reciprocity or balance, and corresponds to a specific parameter in the model (depictions of 2-mode configurations are shown in Table 2S in the supplement to the online version of this paper). Configurations can emerge from connections actors make in response to other ties in the network (e. g., when popular groups continue to attract more YBMSM members) or in response to properties that exist outside the network like YBMSM or group attributes. An estimate of a parameterized configuration that is positive and significant indicates ties are more likely to occur within the configuration than by chance alone. Further details about the specification, estimation, and simulation of ERGMs can be found in (Lusher, Koskinen, & Robins, 2013). As our objective is to ascertain the relationship between Facebook group affiliation network structure and the attributes of groups and YBMSM, we estimated the effects of four attribute-based parameters to determine whether they were more likely to occur than expected by chance alone. Fig. 1 illustrates and describes the corresponding configurations of these effects. The ERGM also includes four parameters that represent purely structural (or non-attribute) effects. The endogenous Edge parameter represents the overall propensity for YBMSM to belong to Facebook groups, which corresponds to network density. The Alternating Group Kstar parameter represents the tendency for YBMSM to belong to groups that are popular among other YBMSM and, therefore, corresponds to the variance in the distribution of YBMSM affiliates among the Facebook groups. Similarly, the Alternating YBMSM K-Star represents the variability between individuals in terms of the number of groups they belong to. Finally, the Alternating YBMSM two-path represents a form of closure in the network, whereby pairs of Facebook groups tend to share multiple YBMSM members in common. Modeling results were implemented using MPNet, a network estimation program designed for multilevel network data (Wang et al., 2006(Wang et al., , 2014. Results Characteristics of the 221 YBMSM and 82 Facebook groups are shown in Table 2 relative to characteristics of the larger samples from which each was drawn. Of the 221 YBMSM, 41 percent were HIV positive and majorities were regular testers (61%), were aware of PrEP (78%), and had engaged in condomless sex (62%). About 15 percent reported engaging in group sex. Descriptive results for the analytic sample are consistent with those for the full sample of YBMSM. Among the 82 Facebook groups, 21 focused on LGBTQ identity (26%), 17 focused on personal/professional development (21%), 14 were chat groups (17%), 12 promoted nightlife (15%), and 10 focused on sexual attraction (12%). The remaining 8 groups (10%) were categorized as "Recreational Interests" (n ¼ 6) or "Health" (n ¼ 2) but were later combined and recategorized as "Other." Relative to the larger sample of Facebook groups, that had a description and more than one respondent member, LGBTQ identity and nightlife groups are overrepresented in the analytic sample, while sexual attraction and "other" groups are underrepresented. Although results should be interpreted with these differences in mind, the analysis was purposively constructed to represent groups that are salient to enough of the YBMSM in our sample and, therefore, are considered viable points of potential intervention. Fig. 2 illustrates the 2-mode Facebook group affiliation network with YBMSM study respondents shown as circles and Facebook groups collapsed into 6 group topic meta-nodes shown as squares. Group topic meta-nodes are colored by topic and sized by average degree (i.e., the average number of YBMSM study respondent members among the groups within a topic category). Among the 221 YBMSM and 82 Facebook groups (now collapsed into group topic meta-nodes) there a total of 1268 group affiliation ties, corresponding to a network density of 0.07. YBMSM belong to on average 5.7 Facebook groups and Facebook groups have on average 15.4 YBMSM members. On average, groups that promote personal image/professional development and nightlife events are most popular with 16.7 and 16.0 YBMSM members on average, respectively. Groups that focus on LGBTQ Identity, Chat, and Sexual Attraction have on average 12.5, 12.0, and 11.1 YBMSM members, respectively. The exponential random graph model (ERGM) Results of the two-mode ERGM are shown in Table 3. Reported in this table are parameter estimates and standard errors. Significance is achieved when the absolute value of the maximum likelihood (ML) estimate is greater than twice the magnitude of the standard error. 2-Mode structural effects To begin, the ERGM controls for the endogenous effects of three structural (or non-attribute) parameters. The Edge parameter is negative and significant, indicating that YBMSM are less likely than expected by chance to belong to Facebook groups (Estimate ¼ À 8.69, SE ¼ 2.64), which reinforces what we previously stated about the low density of this group affiliation network. The positive and significant estimate of the Alternating YBMSM K-Star parameter suggests that the network is centralized around a small number of YBMSM who belong to a lot of Facebook groups (Estimate ¼ 1.11, SE ¼ 0.08). The positive and significant effect of the Alternating two-path term indicates that there is a tendency for some pairs of Facebook groups to share YBMSM members in common (Estimate ¼ 0.09, SE ¼ 0.01), although the magnitude of this effect is small. Group attribute-based edge effects (RQ1) The first set of attribute-based parameters in Table 3 reflect tendencies for individuals, irrespective of their characteristics, to belong to groups with particular topic orientations. Results reveal that YBMSM are less likely than expected to belong to LGBTQ identity (Estimate ¼ -0.56, SE ¼ 0.18), sexual attraction (Estimate ¼ À 0.45, SE ¼ 0.16), and chat groups (Estimate ¼ À 1.07, SE ¼ 0.30). Conversely, they are more likely to belong to personal/professional development groups (Estimate ¼ 0.33, SE ¼ 0.15). Individuals were no more or less likely to belong to groups that promote nightlife. Group attribute-based 4-cycle effects (RQ2) To capture clustering tendencies around groups that focus on the same topic, we estimate effects of five different group attribute-based 4cycle terms. Results show that there are positive and significant tendencies for clustering to occur among YBMSM around pairs of Facebook groups that focus on LGBTQ identity (Estimate ¼ 0.37, SE ¼ 0.11), sexual attraction (Estimate ¼ 0.45, SE ¼ 0.22), and nightlife (Estimate ¼ 0.58, SE ¼ 0.23). So, although LGBTQ identity and sexual attraction groups have a smaller than expected chance of being joined by YBMSM, when they are joined, they tend to share multiple YBMSM members in common. YBMSM attribute-based edge effects (RQ3) Toward modeling the main effects of HIV behavioral traits on group affiliation, we estimate a set of YBMSM attribute-based edge terms. Results show that YBMSM who engage in regular testing are less likely than expected to belong to Facebook groups irrespective of group topic (Estimate ¼ À 0.16; SE ¼ 0.07). Meanwhile, individuals who are HIV positive, who engage in condomless sex and/or group sex, and who are aware of PrEP were no more or less likely to belong to Facebook groups. Fig. 1. Attribute-based parameters among YBMSM i, j, k and Facebook groups m and n included the twomode ERGM that estimate: (a) the likelihood of YBMSM belonging to a Facebook group with a particular topical orientation, (b) the likelihood of YBMSM with a particular HIV-related attribute belonging to a Facebook group, (c) the likelihood of YBMSM with a particular HIV-related attribute belonging to a Facebook group with a particular topical orientation, and (d) the likelihood that a pair of Facebook groups with the same topical orientation will share multiple YBMSM members in common. Group x YBMSM attribute-based interactions (RQ4) Finally, we estimate a series of interaction terms to determine whether particular group topics appeal to YBMSM with particular behavioral characteristics. With five group topics and five behavioral characteristics, 25 possible interactions could have been included in the model. Toward analytic parsimony, we estimated a separate ERGM (see Table 1S in the supplement to the online version of this paper) that included all 25 interaction terms and the main effect terms for each group and YBMSM attribute. Interaction terms that were significant in this precursory model were included in the featured ERGM. Results show that each interaction term we added to the featured model remain significant when adjusting for all other structural and attribute-based parameters. Individuals who engage in condomless sex are more likely than expected to belong to LGBTQ identity groups (Estimate ¼ 0.31, SE ¼ 0.14), individuals who are aware of PrEP are more likely to belong to chat groups (Estimate ¼ 1.03, SE ¼ 0.29), and regular testers are more likely to belong to LGBTQ identity groups (Estimate ¼ 0.54, SE ¼ 0.16) and nightlife groups (Estimate ¼ 0.47, SE ¼ 0.18). Results of the two-mode structural effects and the goodnessof-fit tests are available in the supplement to the online version of this article. Discussion Relationships between peer groups and HIV risk and prevention are the subject of much research. However, few studies examine how risk and prevention manifest in online peer group settings. In this paper, we adopted a network analytic approach to this question and applied a class of stochastic network models to help us determine how Facebook group topics and HIV prevention and risk behaviors jointly characterize patterns of Facebook group affiliation among YBMSM. Doing so enabled us The 2-mode Facebook group affiliation network is comprised of 221 young Black men who have sex with men (shown as circles) and 82 Facebook groups collapsed into 6 group topic meta-nodes (shown as squares). Affiliation ties between YBMSM and group meta-nodes represent membership in at least one group within a topic category. Group topic meta-nodes are colored by topic, including LGBTQ Identity (yellow), Personal/ Professional Promotion (red), General Chat (blue), Nightlife (green), Sexual Attraction (pink), and Other (aqua). Group topic meta-nodes are also sized by average degree (i.e., the average number of YBMSM study respondent members among the groups within a topic category). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) to model the observed structure of the Facebook group affiliation network by accounting for both the dependencies among affiliation ties as well as the dependencies between affiliation ties and exogenous covariates like the attributes of Facebook groups and YBMSM . We found that YBMSM were less likely to belong to Facebook groups generally assumed to be attractive to young MSM, namely groups that underscore LGBTQ identity and sexual expression, and were more likely to belong to groups that promote personal and professional development. Although it is intuitive to consider groups like LGBTQ identity groups as sources of resilience and affirmation for members, groups that help YBMSM more practically to enhance their professional networks are also an important yet understudied aspect of HIV resilience, especially for marginalized groups like YBMSM (Woodward et al., 2017;O'Leary et al., 2014). Our findings also reveal significant clustering around pairs of groups sharing the same topic orientation, namely for LGBTQ identity groups, sexual attraction groups, and groups that promote nightlife. And finally, we learned about the associations between certain types of people and certain group topics. Individuals who engaged in condomless sex and who were regular testers were more likely to belong to LGBTQ identity groups, regular testers were also more likely to belong to groups that promote nightlife events, and those who were PrEP aware were more likely to belong to chat forums. Taken together, there are several features of our study and its findings that have noteworthy implications. First, we feature an examination of online group topics, which are an underexplored mechanism of online social interaction with implications for prevention engagement. Identifying topics that appeal to YBMSM provides a glimpse into their interests and, consequently, what HIV prevention messaging will have to compete against or leverage to capture their attention. Given that talking about HIV is counter-normative for most young adults, interventions should create messaging gateways that leverage the interests of the targeted audience as a means to ease into more sensitive issues. With respect to these

group topics, our analysis identified topic clusters, where network members are brought together via their shared interest in particular group topics. Social clusters signal where social and behavioral norms may emerge due to reinforced communication that occurs when a group of people participate in a common set of groups and conversations. As such, online topic clusters represent key subcommunities that could be targeted for intervention using shared topic interests as messaging gateways. Further, individuals who bridge groups with similar topic orientations could be recruited as peer influencers to spread information from one group to another. In either case, knowledge of group-mediated communities among YBMSM could provide interventionists more tractable and specific populations on which to focus outreach. Second, knowledge of the specific topics that appeal to prevention oriented YBMSM could be used to identify group environments where it may be more socially acceptable to engage co-members who are less prevention oriented around HIV prevention modalities. For example, our findings show that regular testers and those who engage in condomless sex are both more likely to belong to LGBTQ identity groups. This provides an opportunity to employ these regular testers as peer leaders and to use the shared interest in LGBTQ-related issues as a message catalyst to engage their co-members who engage in condomless sex and other sexual risk behaviors in discussions about the importance of routine testing. This assets-based approach to behavioral change (Morgan & Ziglio, 2007) could also be leveraged to engage YBMSM outside the online group environment. For example, regular testers are also more likely to belong to groups that promote LGBTQ nightlife. As such, these individuals could be recruited and trained to promote prevention opportunities in the club scene. Finally, although interest in online networks has grown among HIV researchers, research to date has relied primarily on self-reported information about SNS use and online sex partners to draw inferences about the relationship between HIV risk and prevention and online social networking behaviors. This leaves unaddressed the role of network structure in facilitating risk and prevention for network members. Further, we turn our attention to an underexplored online networka 2mode network based on Facebook group affiliations. In offline contexts, group-mediated peer interactions have been shown to influence substance use among adolescents (Fujimoto & Valente, 2013) and HIV risk engagement among high-risk populations (Fujimoto et al., , 2015Young, Fujimoto, & Schneider, 2018). As such it is important that we extend that focus to include their online counterparts. Limitations Despite these strengths, there are limitations worth noting. First, the affiliation network includes only groups that had eight or more respondent members. As such, the fact that YBMSM were less likely to belong to sexual attraction and LGBTQ identity groups may reveal more about their hesitation or disinterest in joining groups that attract a certain threshold of other YBMSM in their community than it does about their general interest in either topic. Future work should be directed toward understanding how our results change when the affiliation threshold is relaxed. Second, the goal of this study was to directly model Facebook group affiliations to identify local configurations in relation to characteristics of YBMSM and Facebook groups. However, we acknowledge that these online relationships may co-evolve with "offline" friendships among YBMSM. Future studies could be extended to verify whether shared interests in particular group topics among YBMSM is a network mechanism in its own right or whether it is a confounder for some other type of ongoing relationship by employing multiplex modeling techniques . Third, the fact that an individual belongs to a particular Facebook group is only indicative of their general interest in its subject matter. With no information about an individual's actual engagement within a group, we are challenged in our ability to determine how important the group setting is to the individual as well as the degree of influence that group members and content could exert on the individual. Having a more accurate sense of which Facebook groups garner the greatest user engagement (e.g., visitations, posts, comments, and reactions) would help identity which groups have the greatest reach and influence potential, both of which are critical attributes of a setting that could be leveraged for HIV prevention engagement. Finally, we acknowledge that Facebook is not the only relevant SNS platform used by YBMSM. Other platforms like Instagram and Snapchat are rapidly increasing in popularity. However, Facebook remains the most popular social media platform across a wide variety of demographic groups (Greenwood, Perrin, & Duggan, 2016) and is used most frequently by the YBMSM in this cohort. As such, we use Facebook as a case study to inform future explorations of other social networking platforms. Conclusion Despite these limitations, our findings provide a structural account of HIV risk and protection as observed in an underexplored, yet culturally salient social context. Given that SNS are now mainstreamed into our daily routines, it behooves the research community to understand their role in forging both sexual risk and prevention norms in high-risk populations like YBMSM. Developing interventions that leverage the groupbased affiliation network structure of YBMSM and, by extension, the topics they discuss in these environments may prove more effective than off-the-shelf interventions that remain agnostic to the needs and interests of this population. Symptom Relief is the Most Signicant Prognostic Factor for Unresectable Locally Advanced/Recurrent Pancreatic Cancer Receiving Chemoradiotherapy: Analysis of 65 Cases for LAPC/LRPC patients after comprehensive CRT. Introduction As one of the malignant digestive tract tumors, pancreatic cancer has an increasing trend at home and abroad. Chemoradiotherapy (CRT) is a main choice for local advanced and recurrent pancreatic cancer, which may prolong their survival and ease patients' symptoms. [1] This study retrospectively enrolled all the local advanced or recurrent pancreatic cancer (LAPC/LRPC) patients received de nitive CRT in XXX hospital, to evaluate the effect of the treatment and analyze the prognostic factors for those patients. Patient characteristics Patients diagnosed with primary unresectable LAPC or LRPC after radical resection in our hospital from June, 2004 to February, 2018 were retrospectively reviewed. All of them received de nitive CRT with or without neoadjuvant chemotherapy. Unresectable cancer was de ned as superior mesenteric artery or celiac axis encasement> 180 degrees, unreconstructible superior mesenteric vein (SMV) / portal occlusion, or aortic invasion. Exclusion criteria included: (1) distant metastasis before radiotherapy, (2) patients received tumor resection after CRT, (3) LRPC patients with adjuvant RT after tumor resection before local recurrence, (4) missing data of clinical treatment. Detail of patients enrollment is shown in Fig. 1. Totally, 65 patients are included into our study, with 47 unresectable LAPC patients and 18 unresectable LRPC patients. Among the 47 patients, primary tumor lay in pancreatic head, neck or uncinate process, and body or tail in 22, 7 and 18 patients, respectively. Among the 18 unresectable LRPC patients, tumor recurred in situ, at regional lymph nodes, and at both sites in 8, 6 and 4 patients, respectively. The median age for all patients were 58 years (range 33-82 years). Male and female patients accounted for 60% and 40%, respectively. Other clinical characteristics are shown in Table 1. All the radiologic image data were re-evaluated by a senior radiologist to assess the possibility of radical resection according to the guidelines from National Comprehensive Cancer Network [2] and tumor response according to the RECIST criteria V1.1. [3] Radiation treatment To fully appreciate the location of the gross tumor volume (GTV), the tumor is evaluated on all triphasic diagnostic scans (CT/MR) as well as on CT simulation images, to create an GTV. In recent years, an internal GTV (GTVin) is also de ned by omitting the tumor part invading or locating approximate to the gastrointestinal tract, as shown in Fig. 2, for dose escalation, to treat GTVin volume to a higher dose level respecting the gastrointestinal tract tolerance. The clinical target volume (CTV) comprises a 5-10mm expansion from the GTVin all directions and may need to be further expanded to include areas at risk of microscopic extension, as well as nodal elective irradiation around the celiac axis, superior mesenteric artery (SMA), and SMV (generally starting at the origin of the arteries and including the vessels at the same axial slice levels as the GTV). The CTV can extend into bowel structures, ensuring coverage of microscopic risk of disease in the adjacent duodenum and nodal basins. Planning treatment volume (PTV) was generated by adding a 5-mm margin in all directions to the CTV in consideration of respiratory management. Follow-up The follow-up was performed regularly after treatments. Physical examination, serum CA199 detection and imaging examination (abdomen CT or magnetic resonance imaging) were implemented at follow-up. Afterwards the patients were followed by an outpatient interview or household registration system. The last follow-up was completed on 1 April, 2020. Statistical analysis Overall survival (OS) was de ned as the time from the start of CRT to death or the last follow-up. All statistical analyses were conducted using the R statistical package (R software version 4-0.0; R foundation for statistical computing. Vienna, Austria). The Kaplan-Meier method was used to analyze OS. Differences between two groups were tested using Log-rank. Variables with P< 0.22 in the univariate analysis were subjected to the multivariate model. Cox proportion hazards model was performed to analyze variables. A two-sided P-value < 0.05 was considered statistically signi cant. Short-term outcome According to the RECIST criteria, 10, 28 and 5 patients had partial response (PR), stable disease (SD) and progressive disease (PD), respectively. The length of 18 patients' lesions contracted less than 30% and 3 patients' tumor increased less than 20% among SD patients. For all evaluated patients, the total rate of disease control was 88.4%. Since the year of 2012, most patients accepted radiation therapy with higher BED 10 (Fig. 4a). As shown in Table 1 and Fig. 4b, 11 and 54 patients received radiation with BED 10 When treatment response was included in the multivariate analysis, it was the most signi cant prognostic factor for OS as shown in Table 2 (Multivariate analysis 1). When only the pretreatment clinical factors and treatment related factors were included in the multivariate analysis, age and tumor status were the signi cant prognostic factors for OS as shown in Table 2 (Multivariate analysis 2), favoring younger patients and LRPC. Comparison of toxicities In the whole cohort, 15 and 4 patients had grade 1-2 and grade 3 digestive adverse events, respectively. Discussion As a gordian knot, pancreatic cancer is the fourth leading cause of cancer-related death throughout the world. [4] More than 80% of pancreatic cancer patients lost surgical resection probability, at initial diagnosis due to di culty in early diagnosis. The 5-year OS rate was less than 5%. [5] CRT is an optional scheme for locally advanced and recurrent pancreatic cancer patients. [6] Here we analyzed 65 patients with locally advanced or recurrent pancreatic cancer after CRT. In our study, we purposefully delineate a GTVin for dose escalation, other than using dose constraints to give higher dose to area away from normal tissues as suggested by ASTRO 2019 guideline. Our method also achieved satisfactory results. Purposefully delineating a GTVin may help radiation oncologists to avoid the temptation to "under-contour" the GTV which lends itself to poor plan evaluation and coverage. Our results suggested dose escalation for tumor on the premise of normal tissue dose tolerance may bring more survival bene t for patients with large tumor volumes, especially when tumor is quite near to small intestine. Nicholas G. Zaorsky et al. meta analysis show that BED 10 = 70 Gy was not signi cantly associated with one-year local control rate, but the criteria of studies in this meta analysis were not consistent. [7] Data regarding the bene ts of dose-escalation in pancreatic ductal adenocarcinoma are emerging. [ 8] Soumon Rudra et al. analyzed 44 unresectable local advanced pancreatic cancer patients with comprehensive treatment combined radiation and chemotherapy. [9] In their research, hypofractionated IMRT and SBRT were used to elevate radiation dose. They contrasted patients' clinical outcomes in terms of BED 10 ≥ 70 Gy and< 70 Gy. It appeared higher dose group had a better 2-year OS (49% vs 30%, P= 0.03) and a better trend of 2-year free from local failure rate (77% vs 57%, P= 0.15). Grade 3 and over toxicities did not appeared in higher dose group. Although evidence level is low,

ASTRO guideline suggest dose escalation for LAPC with high consensus in panel (85%). [10] Technical innovations and the relatively low toxicity observed thus far with SMART, has led to new initiatives to attempt local dose-escalation for LAPC. Advanced techniques and higher radiation doses are currently being evaluated in a prospective clinical trials (Clinical Trials.gov: NCT03621644, CT003340974). [11] Our analysis showed LRPC without distant metastasis after radical resection had longer mOS than those with primary unresectable LAPC, which may be due to the smaller tumor volume in the LRPC group and CRT could yield better tumor control. Local recurrence without distant metastasis may be a manifestation of good tumor biological behavior. At present, there is a lack of research on the difference between LRPC and LAPC, which warrant further exploration to explain this phenomenon. Univariate and multivariate analysis showed that the short-term symptom relief was a signi cant prognostic factor for OS, including relief of jaundice, pain, diarrhea and/or other symptoms. Pancreatic cancer is generally considered to be radiation resistant and those patients without response to CRT had poor survival results. Prediction of tumor response to standard treatment strategy is of vital importance. Vipin Dalal et al reviewed studies using radiomics to predict the short-term e cacy, local control, DFS and OS of pancreatic cancer patients with different stages to antitumor therapy. [12] Allen Li's team used daily CT image extraction parameters to predict tumor withdrawal after CRT, [13] which we can consider to apply in further study, to stratify patients before treatment and try to optimize treatment in clinical studies. CA199 as that signi cant biomarker to diagnosis of pancreatic cancer, has a high speci city and sensitivity even up to 80%. [14]The level of serum CA199 is negatively correlated with patients' better prognosis. Our study indicated patients with CA199 > 115 U/mL before radiation therapy had a relative shorter survival time, which had a consensus of previous studies. However, we failed to prove CA199 as a negative prognostic factor probably due to the long span of these patients. And it was one of our study's limitation. Also, radiation techniques were various, resulting the discrepancy in tumor dose when it comes to tumor with the same size. Limited patients may cause biases when analyzing. We do hope larger and more powerful prospective study and randomized controlled trials will be developed in the future to strengthen what we found in this study. Conclusion In conclusion, LAPC/LRPC patients with larger tumor volume may get survival bene t from CRT with simultaneous integrated boost of radiation dose, with acceptable toxicities. Short term treatment response, especially symptom relief is the most signi cant prognostic factor for LAPC/LRPC patients after comprehensive CRT, thus prediction of treatment response before start of treatment is in urgent need. This study was approved by the Institutional Review Board of Sun Yat-sen University Cancer Center. All procedures performed in the present study involving human participants were in accordance with the ethical standards of institutional and/or national research committees and the 1964 Helsinki Declaration and its later amendments or similar ethical standards. Written informed consent was obtained from all individual participants included in the study. Consent for publication Not applicable Availability of supporting data The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that there are no competing interests. Not applicable Authors' contributions JT , SJX and LS contributed to this work equally. WWX and ZYJ are responsible for conceptualization, design and quality control of this study. JT, LS and WWX performed the study selection, data curation, statistical analyses, and writing the manuscript. SJX and WWX re-evaluated all images. LQ supervised statistical analyzing of this study. WWX and ZYJ reviewed and edited the manuscript respectively. All authors reviewed the manuscript and approved the nal version. Successful Treatment of Genital Warts with Ingenol Mebutate Monitored with Optical Coherence Tomography and Reflectance Confocal Microscopy Ingenol mebutate (IM) is approved for the treatment of actinic keratosis and induces cell death in precancerous lesions. The efficacy of IM in the treatment of genital warts was investigated in a therapy-refractory patient. The 74-year-old male was treated with IM gel for three consecutive days. Treatment course and efficacy were evaluated by clinical inspection and non-invasive diagnostics namely optical coherence tomography (OCT) and reflectance confocal microscopy (RCM). Within 24 to 48 hours IM induced a strong local inflammatory reaction. One week later a complete response was observed. OCT and RCM showed a strong reaction after treatment with erosions, swelling of cells, and a subepidermal dark band in representative lesions. IM has the advantage of a short treatment period in contrast to other topical treatments and shows a promising clinical outcome. Larger studies are needed to validate the data. INTRODUCTION Infections with human papillomavirus (HPV) are a modern pandemic with millions of people being infected each year. The 170 different types of this double-stranded DNA virus are divided into low-and high-risk virus classes according to their oncogenic potential 1 . The high-risk subtypes are commonly found in cervical, penile, or anal dysplasias 2 with the potential to progress to carcinomas after a long-standing infection. Low-risk virus subtypes can lead to the development of genital warts, which are biologically benign but very bothersome and stigmatizing for the patient 3 . Moreover HPV is highly contagious; therefore genital warts are a very common manifestation of HPV infection in sexually active adults. Sexual contact with an HPV-infected individual results in a 75 percent chance of contracting the virus, with additional risk factors being immunosuppression, unprotected intercourse, smoking, or a history of sexually transmitted diseases 4 . For the treatment of genital warts various topical medications including 5-fluorouracil, sinecatechins, trichloroacetic acid, and imiquimod are available. Other treatment options include cryosurgery, laser, electrocautery, or surgical excision, but with higher risk of scarring. Recently, ingenol mebutate (IM) has been approved as a new agent for topical treatment of actinic keratosis 5 . IM is one of the active compounds of the plant Euphorbia peplus L. The hydrophobic diterpene ester called ingenol-3-angelate was identified as an active ingredient. Usage of wild E. peplus for treatment of various medical conditions is known from ancient times. The objective of our investigation was the initiation of an immune response to the genital warts through topical application of IM. We hypothesized that IM would trigger apoptosis and necrosis of the affected cells and additionally induce an antigenic immune response. Modern imaging techniques such as optical coherence tomography (OCT) and reflectance confocal microscopy (RCM) have proven useful in practice for the noninvasive diagnosis of non-melanoma skin cancer and treatment monitoring [6][7][8] . Reaction and response to treatment were mainly evaluated by clinical examination, while OCT and RCM were used to monitor the response, similar to monitoring the therapeutic success of IM gel in actinic keratosis 9 . CASE REPORT In this case report, we evaluated a 74-year-old male patient who had several unsuccessful standard treatments previously. The patient presented with 15 genital warts in the area of the radix penis and scrotum (Fig. 1). The patient was treated at the Department of Dermatology, University Hospital of Munich (Ludwig Maximilian University, LMU), after obtaining written informed consent for the individual off-label use of topical ingenol mebutate in geni-tal warts. A single dose of 0.47 g IM gel (150 μg/g, daily dose: 70.5 μg IM; Picato Ⓡ ; LEO Pharma A/S, Ballerup, Danmark) was applied topically for three consecutive days in a predefined treatment area of 25 cm 2 . The site of infection was evaluated and monitored clinically as well as documented via OCT and RCM on baseline and day 4, 7, and 21 after initial treatment. The initial clinical evaluation revealed 15 condylomata acuminata with typical features of papillomatous or verrucous tumors or plaques with brownish-red coloration. Non-invasive imaging For non-invasive imaging the following commercially available devices were used: a Fourier-domain OCT system (Vivosight Ⓡ ; Michelson Diagnostics, Kent, UK) with a 1,310 nm multi-beam laser providing a penetration depth of 1.5 to 2 mm and a resolution of 5 to 7.5 μm and an in-vivo RCM device (Vivascope Ⓡ 1500; Lucid-Tech Inc., Henrietta, NY, USA; Mavig GmbH, Munich, Germany) with a penetration depth of about 250 μm and a resolution of 1.25 to 2.5 μm 10,11 . OCT and RCM imaging was performed in one defined target lesion before and after seven and 21 days after treatment with IM gel. Clinical evaluation IM induced an inflammatory reaction after 24 hours in the treated area. This reaction lasted up to seven days with decreasing intensity (Fig. 1). The observed local reactions were temporary and similar to previously described reactions seen after application in actinic keratosis 12 . Erythema, flaking/scaling, swelling and erosion were observed between day two and four. Additionally crusting, vesiculation and pustulation were seen. In the patient the warts disappeared completely and were not detectable even after three weeks, neither by clinical inspection (Fig. 1) nor by non-invasive imaging (OCT or RCM) (Fig. 2). Three weeks after application of IM gel, the skin normalized without any sign of HPV infection (Fig. 1). A residual erythema was found in the patient after 21 days (Fig. 1D). No systemic side effects were observed. Post-treatment erythema was reported by the patient, but no other adverse event. Six months after the treatment the patient was still in remission, so it can be assumed the treatment was successful. OCT and RCM Prior to treatment, the genital warts presented as papillomatous tumors with a broadening of the epidermis and sometimes keratotic changes including signal-intense dots intratumorally in OCT (Fig. 2). In RCM the genital warts showed aggregated hyperplastic nodules in the Vivablock Ⓡ (Mavig GmbH) mosaic overview (5×5 mm) of superficial layers and in the single RCM image (0.5×0.5 mm) a broadened epidermis with signal-intense bright epidermal cells and hypervascularization (Fig. 2). Four days after treatment start, OCT showed flattening of the epidermis and disappearance of layering. A signalpoor dark band sublesionally was characteristic and consistent with inflammatory reactions and edema (Fig. 2). On day four multiple bright cells spreading throughout the epidermis were present in RCM imaging compatible with inflammatory cells, which showed disruption of cells and prominent vessels within the papillae (Fig. 2). Three weeks after treatment, OCT imaging showed a still prevailing subepidermal signal-poor dark band. For the publishing of the photographic materials a patient's consent form has been received. DISCUSSION In the conventional topical therapies of genital warts the treatment success depends mainly on the adherence of the patients. Due to the often long-term treatment course the patients commonly fail to maintain proper procedure or develop uncomfortable side effects like pain or burning sensations. The common treatment options for genital warts include the following therapies: Podophyllotoxin shows high recurrence rates after clearance 13 while imiquimod has lower recurrence rates 14 . The application of sinecatechins ointment and trichloroacetic acid has led to moderate clearance rates 15 . Cryosurgery, electrosurgery, and scissors excision are additional invasive treatment options 16,17 . Particularly the topical drug treatments are associated with inconveniences for the patients as long-lasting, high-frequent application with partially severe side effects. Therefore the treatment with IM could serve as an alternative for the therapy of genital warts. In contrast to the recently published case report of Braun et al. 18 , which described the single spot-like use of the 500 μg/g formulation on multiple condylomata acuminata, the repetitive application of the 150 μg/g formulation leads to less severe local reactions including burning sensation and pain. The mechanism of action of IM is not yet fully understood, but latest studies suggest a dual mode of action via both cellular necrosis and neutrophil-mediated antibody-dependent cellular cytotoxicity 19 . It was shown that within one to two hours of application, the exposure of cancerous cells to IM induces cellular necrosis 20 . IM gel destroys epidermal cells within hours and induces the production of antibodies that result in neutrophils targeted to kill any residual dysplastic epidermal cells, which is important for preventing relapses following treatment 19 . Therefore, in contrast to more invasive approaches the herein mentioned therapy has potentially less side effects like scarring. In comparison to hitherto available topical remedies the treatment with IM has the advantage of a reduced treatment time. In summary, IM may represent

a novel treatment option for refractory genital warts. Even in a pretreated patient it showed a good clinical response and lasting results. Larger prospective randomized controlled trials are needed to objectify and evaluate this clinical concept. CONFLICTS OF INTEREST MR has received speaker's and advisor's fees by Galderma and MEDA Pharma GmbH & Co. Kommanditgesellschaft, BMCE none, MVH none, YH none, TR has received speaker's and advisor's fees by Galderma; CB has received speaker's and advisor's fees by Almirall-Hermal, Biofrontera, Galderma, and LEO Pharma A/S. TvB and CB have received a research grant by LEO Pharma A/S. TvB has received speaker's fees by Almirall-Hermal. The OCT Vivosight Ⓡ device used in this study has been provided by Michelson Diagnostics, UK, and the RCM Vivascope 1500 Ⓡ device used in this study has been provided Mavig GmbH, Munich, Germany. Integrated transcriptome and proteome analysis in human brain organoids reveals posttranscriptional regulation of ribosomal genes During development of the human cerebral cortex, multipotent neural progenitors generate excitatory neurons and glial cells. Investigations of the transcriptome and epigenome have revealed important gene regulatory networks underlying this crucial developmental event. However, the post-transcriptional control of gene expression and protein abundance during human corticogenesis remains poorly understood. We addressed this issue by using human telencephalic brain organoids grown using a dual reporter cell line to isolate neural progenitors and neurons and performed cell class and developmental stage-specific transcriptome and proteome analysis. Integrating the two datasets revealed modules of gene expression during human corticogenesis. Investigation of one such module uncovered mTOR-mediated regulation of translation of the 5’TOP element-enriched translation machinery in early progenitor cells. We show that in early progenitors partial inhibition of the translation of ribosomal genes prevents precocious translation of differentiation markers. Overall, our multiomics approach reveals novel posttranscriptional regulatory mechanisms crucial for the fidelity of cortical development. Introduction The development of the human cerebral cortex is a highly elaborate process occurring over several months. During this process multipotent neural progenitors give rise initially to excitatory neurons of the different layers of the cerebral cortex and later to glial cells. Studies using mouse model systems, human fetal samples as well as brain organoids have revealed elaborate spatiotemporal gene regulatory networks that orchestrate mammalian corticogenesis (Cadwell et al., 2019;Greig et al., 2013;Shibata et al., 2015;Vaid and Huttner, 2020). However, an emerging theme from mouse corticogenesis studies highlights the additional role of post-transcriptional gene regulatory mechanisms, such as alternative splicing and translational repression, in determining progenitor cell fate and neuronal migration (Hoye and Silver, 2020; Lennox et al., 2017;Zahr et al., 2019). Whether similar mechanisms play a role in human neurodevelopment remains elusive. Hence, investigating the post-transcriptional control of gene expression and protein abundance is crucial to comprehensively understand gene regulation during human neurodevelopment. Transcriptome analyses have placed a lot of importance on transcript abundance, however, the relationship between transcript and protein abundance remains elusive. While previous studies have investigated post-transcriptional regulation of specific genes or the impact of loss of key RNAbinding proteins (Hoye and Silver, 2020), proteome-scale analyses of gene regulation during human corticogenesis have been lacking. Currently available proteome data from hiPSC-derived neural progenitors and neurons (Djuric et al., 2017;Varderidou-Minasian et al., 2020), cerebral organoids (McClure-Begley et al., 2018;Melliou et al., 2022;Nascimento et al., 2019), and the fetal brain (Djuric et al., 2017;Kim et al., 2014;Melliou et al., 2022) are an important step towards establishing a human neurodevelopmental proteomic repertoire. However, these studies suffer from some of the following limitations: a) due to the inherent diversity of cell types present during corticogenesis, bulk tissue data do not provide cell type-specific information, b) cell sorting strategies result in datasets that suffer from low number of successfully detected proteins, and c) importantly, a direct comparison of the transcript and protein expression to understand posttranscriptional gene regulation has been missing. We addressed these issues by using a dual reporter cell line to separate progenitors and neurons from the human brain organoid tissue and performed cell class-and developmental stage-specific transcriptome and proteome analysis. We integrated the two datasets to identify gene expression modules active during neural progenitor proliferation and subsequent neurogenesis in the developing cortical tissue. This dataset is available as a resource for the community in the form of a Shiny app (https://organoid.multiomics.vbc.ac.at). We followed up on one gene expression module in detail and found that the genes of the core translational machinery, containing the '5' Terminal Oligo Pyrimidine' (5'TOP) motif in their 5'UTR, are coregulated post-transcriptionally during neurodevelopment. We show that in contrast to neurons, translation of 5'TOP transcripts is partially inhibited in early progenitors, resulting in discordant RNA-protein relationship between the two cell classes. This regulation of the 5'TOP element-enriched translational machinery is due to lower mTOR activity in early progenitors and is crucial for the fidelity of cortical development. RNA-protein multiomics of neural progenitors and neurons isolated from telencephalic organoids. To investigate progenitor and neuron-specific gene regulatory programs, we generated a dual reporter H9 human embryonic stem cell (hESC) line that enables sorting of neural progenitors and neurons ( Figure 1A). To label neural progenitors, we replaced the stop codon of one allele of the pan-neural progenitor marker gene SOX2 with P2A-EGFP ( Figure 1-figure supplement 1A). On the other hand, to label neurons, we inserted dTomato driven by human Synapsin1 (hSYN1) promoter in the AAVS1 safe harbor locus (Figure 1 -figure supplement 1B). Using this reporter line, we generated brain organoids enriched in dorsal telencephalic tissue using a previously published organoid culture protocol (Esk et al., 2020) (Figure 1 -figure supplement 1C) to recapitulate the key stages of corticogenesis, when multipotent progenitors give rise to diverse excitatory neurons of distinct layer identities. Immunostaining for EGFP and dTomato confirmed expression of the fluorophores in the progenitor and neuronal zones, respectively ( Figure 1B). Furthermore, analysis of sparsely labeled organoids set up using 5% dual report hESCs and 95% non-reporter, wildtype hESCs confirmed expression of EGFP and dTomato in the progenitor-rich ventricular zone (VZ) (SOX2), and the surrounding neuron-rich region (NeuN), respectively (Figure 1-figure supplement 1D-F). To study progenitor and neuron-specific gene regulatory programs, we aimed to perform whole transcriptome and proteome analysis of the respective cell classes. Dissociation of the organoids followed by fluorescence activated cell sorting (FACS) confirmed the occurrence of EGFP positive (EGFP+) and dTomato positive (dTomato+) cell populations across different stages of organoid development (Days 40, 60, 90 and 120) ( and neurons (hSYN1::dTomato+) and did not include the double positive cells for further analysis. PCA showed that SOX2::EGFP+ cells and hSYN1::dTomato+ cells clustered separately and showed transcriptomic signatures of progenitors and neurons, respectively (PC1, Figure 1-figure supplement 3A,B). These samples further separated according to the organoid developmental stages with little batch effect (PC2, Figure 1-figure supplement 3A,B). For proteome analysis, proteins from the cells sorted from the same organoid culture batches and time points as used for RNA-seq were tandem mass tag (TMT) labeled and combined for each batch separately. In total, 6,740 proteins were detected by mass spectrometry of the sorted cell populations. Initial analysis confirmed that similar to the transcriptome, the proteome of sorted neurons (hSYN1::dTomato+) and progenitor cells (SOX2::EGFP+) segregated according to the cell class and age (Figure 1-figure supplement 3C,D). Transcriptome and proteome analysis ( Figure 1C-E) confirmed that EGFP and dTomato expression matched the expression of endogenous SOX2 and SYN1 ( Figure 1C, D). Furthermore, this analysis revealed that the SOX2::EGFP+ population encompassed all different classes of cortical progenitors including ventricular radial glia (expression of SOX1, PAX6), intermediate progenitors (EOMES) as well as outer radial glia (HOPX, MOXD1, TNC). The expression patterns of these markers followed the expected temporal trajectories of cortical development. While the markers of ventricular radial glia were expressed at all stages, markers of intermediate progenitors and outer radial glia showed enrichment at day 60 and day 90, respectively ( Figure 1C). Similarly, the hSYN1::dTomato+ population included excitatory neurons of all different cortical layers and followed the expected temporal expression patterns ( Figure 1D), with deep-layer markers (TBR1, BCL11B) being expressed before upper-layer markers (SATB2, CUX2). The enrichment of dorsal telencephalic fate was confirmed by the expression of above stated markers of cortical progenitors and neurons along with high expression of FOXG1 and EMX2 ( Figure 1E) and undetectable levels of ventral markers (NKX2.1, LHX6) (TPM values below 1). Thus, we generated a time-resolved transcriptome and proteome dataset of neural progenitors (SOX2::EGFP+) and neurons (hSYN1::dTomato+) sorted from telencephalic organoids (Figure 1-source data 1, 2). Integrated transcriptome and proteome analysis reveals gene expression modules active during neurodevelopment. Next, we examined the general degree of correlation between mRNA and protein levels. We detected mean TPM values greater than 0 and at least one peptide for 6,714 genes. Similar to a previous report (Schwanhäusser et al., 2011), we observed only a limited correlation between absolute mRNA and protein levels, which seemed comparable between cell classes and developmental timepoints (Figure 1-figure Fig. 1. RNA-protein multi-omics of progenitors and neurons in human brain organoids. A) Schematic representation of the experimental design. A dual reporter line was generated in H9 hESC background. Cells from brain organoids grown using this reporter line were sorted and collected by FACS in EGFP and dTomato positive fractions. Gene expression of the sorted cell populations were analyzed by RNA-seq and Massspec. B) Confocal scan of a dual reporter organoid cryosection (day 60) stained with anti-EGFP, anti-dTomato antibodies and DAPI. Scale bar = 500 µm. C,D,E) Plots showing RNA (top) and protein (bottom) abundance of key progenitor-specific markers (C), neuronal markers (D) and dorsal telencephalic fate markers (E) in SOX2::EGFP+ (green) and hSYN1::dTomato+ positive (red) cells at different stages of organoid development. RNA abundance is measured as transcript per million (TPM). F,G) Principal component analysis of z-score normalized integrated transcriptome and proteome of progenitors (EGFP+, green) and neurons (dTomato+, red) at different stages of organoid development with (G) loading scores for PC1 and PC2 top contributing genes. supplement 4A). Given the very different measurement units of RNA-seq and Mass-spec, a PCA on the combined datasets revealed that almost 80% of the variation was explained by the omics method (PC1, Figure 1-figure supplement 4B) and not by cell class or developmental time point highlighting the importance of data normalization. Furthermore, to identify groups of genes that follow similar relative gene expression profiles at RNA and protein level in progenitors and neurons over time, we combined the two data sets upon rescaling using gene-by-gene z-score normalization (Figure 1-source data 3). PCA of the combined datasets confirmed that the scaled data grouped by cell classes and developmental age and not by the omics method ( Figure 1F,G). Using the z-score scaled dataset we first fit a global regression model to identify genes differentially expressed between the two cell classes on RNA and/or protein level. In a second regression step, genes showing significant temporal profile differences for RNA and protein expression in progenitors and neurons were identified (Nueda et al., 2014). Out of the 6,714 genes, we could successfully fit 5,978 genes, 3,668 of which showed significant temporal expression changes between cell classes on RNA and/or protein levels. Finally, we performed hierarchical clustering to identify genes with underlying common trends of RNA-protein expression. To estimate an optimal number of biologically meaningful clusters, we used the "within cluster sums of squares", "average silhouette" and "gap statistics" methods ( Figure 1-figure supplement 4C). In the end, a total of 3,368 genes were classified into 9 modules (Figure 2A,B). The remaining 2,310 genes were considered as "not clustered" and 736 genes for which the first regression fit failed as "not fit" ( showed very strong cell class-specific expression patterns matching the sorting strategy for progenitors and neurons (defined here as "C" modules) ( Figure 2B). Modules 1 and 2 showed higher relative expression in the progenitors than neurons across all time points and were enriched in DNA replication and cell activation-related genes, respectively ( Figure 2C and Figure 2-figure supplement 1A,B). For module 2, progenitor-enriched expression increased with time, in line with the observation that many outer radial glia markers were members of this cluster. Genes in modules 7, 8 and 9 showed higher expression in neurons than progenitors across all timepoints. Module 7 was enriched in genes related to mitochondrial respiration ( Figure 2C, Figure 2-figure supplement 1A,B), which is in agreement with the metabolic shift from

glycolysis to oxidative phosphorylation observed during neurogenesis (Iwata and Vanderhaeghen, 2021). Modules 8 and 9 were enriched in axonal and preand postsynaptic genes ( Figure 2C and Figure 2-figure supplement 1A,B). Importantly, in "C" modules, global relative expression of RNA and protein followed largely similar trends, indicating that the regulation of these genes might occur via cell class-specific transcription or transcript retention and decay. Interestingly, the global profiles of relative RNA and protein expression did not follow similar trends for other modules, which instead showed a temporal or cell class-specific discrepancy. Modules 4 and 6 showed relative gene expression changing with time ("T" modules) (Figures 2B). In Module 4, expression decreased with time and the average RNA trends for these genes were similar for progenitors and neurons. However, progenitors expressed relatively higher amounts of protein. Such a trend might be explained by less effective translation or reduced protein stability of these genes in neurons. This module includes known early fate specification genes such as FEZF2, as well as genes related to glycolysis, a process more prominent in progenitors (Iwata and Vanderhaeghen, 2021). In contrast, module 6 genes were expressed more at later stages. The average RNA trends of these genes were similar for progenitors and neurons, but protein levels were higher in neurons ( Figure 2B), suggesting less effective translation or reduced protein stability in progenitors over neurons. This cluster includes upper-layer fate regulators such as SATB2 and CUX2. The remaining modules 3 and 5 showed more ambiguous patterns of expression ("A" modules) (Figures 2B). Genes from module 3 showed considerably higher transcript levels in progenitors than neurons, although protein levels between the two cell classes were more similar. This observation suggested that translation of these genes is either less effective in progenitors or enhanced in neurons, or that protein stability is different between the two cell classes. Gene enrichment analysis suggested enrichment of translational machinery proteins including those of ribosomes ( Figure 2C, Figure 2-figure supplement 1A,B). Lastly, module 5 genes showed opposite patterns for RNA and protein relation in progenitors and neurons. The relative RNA levels showed a temporal increase in the two cell classes, with late stage neurons expressing even higher amounts than corresponding progenitors. Despite this trend, the relative protein levels were higher in progenitors than neurons and with the difference being highest at early stages. This pattern suggested higher yield of translation or higher protein stability of these genes in progenitors over neurons ( Figure 2B). This module is enriched in RNA-binding proteins like DEAD box Clustering of genes based on RNA-protein expression patterns in progenitors and neurons in human brain organoids. A) Heatmap showing clustering results for the nine gene expression modules. Z-score normalized abundance of RNA (R) and protein (P) in progenitors (EGFP+, green) and neurons (dTomato+, red) at different stages of organoid development. B) Z-score normalized RNA and protein abundance in progenitors (EGFP+, green) and neurons (dTomato+, red) at different stages of organoid development for the nine modules. For each dataset, each dot displays the relative abundance of one gene and a trendline was fit through all data points. C) Enrichment analysis for gene ontology (GO) cellular component (CC) for genes in the nine modules. Shown are the top five enriched terms per module and the number of genes (x-axis) belonging to the respective GO term. Bar fill colors show binned adjusted p-values and not significant (ns) terms are indicated. Modules are categorized according to their global expression pattern: cell class-specific expression ("C" modules), temporal expression ("T" modules) and ambiguous expression ("A" modules). proteins and proteins important for rRNA processing and ribosome biogenesis ( Figure 2C, Figure 2-figure supplement 1A,B). Finally, we analyzed the correlation of the relative abundance of RNA to protein for each gene expression module ( Figure 2-figure supplement 2B). Modules that show a high cell class-specific expression ("C" modules) showed a higher correlation than modules with broader expression patterns ("T" and "A" modules) reflected in the coherency between RNA and protein trends. Thus, by combining RNA and protein expression data, we identified gene modules with cell class-specific and temporal gene expression patterns, as well as modules with seemingly ambiguous expression patterns that show divergent coherency between relative RNA and protein abundance. Analysis of module-specific RNA regulatory features highlights the 5'TOP gene module. The emergence of highly distinct expression modules raises the possibility that the genes within each module are regulated transcriptionally and post-transcriptionally by common cell class-or stage-specific mechanisms. The post-transcriptional mechanisms can include regulation of translation as well as stability of the mRNAs and proteins, either uniformly or partially through compartmentalisation. As transcript features of the 5' and 3' UTR elements are postulated to be a major factor that directly influences RNA stability and translation (Blair et al., 2017;Floor and Doudna, 2016), we performed a comprehensive transcript feature analysis of the members of the 9 modules ( Figure 3A, Figure 3-source data 1,2). Firstly, we analyzed trans-regulatory features that can potentiate binding of RNA binding proteins (RBPs) and miRNAs ( Figure 3A). To this end, we performed module-wise over-and under-representation analysis for RBP-binding motifs in the 5' and 3' UTR elements of the member genes ( Figure 3B-C, Figure 3-figure supplement 1A-B, Figure 3-source data 1). Modules 1 and 9, whose member genes showed most cell class-specific expression, showcased high numbers of RBP motifs that were significantly enriched or depleted in the 3'UTR ( Figure 3B). Upon comparing overand underrepresented motifs among different modules, we observed that there was a reciprocal relationship between motifs enriched in the progenitor modules 1 and 2 and the neuronal module 9 ( Figure 3C). These data suggest that the RBP motifs we identified and their associated proteins might play a prominent role in cell class-specific expression to promote progenitor or neuron-specific gene regulation. For instance, we observed that motifs for the RNA-binding protein RBFOX1, which was shown to promote neuronal expression of synaptic genes (Lee et al., 2016), were enriched in the 3'UTRs of module 9 ( Figure 3C) in line with the enrichment for GO terms for synaptic genes ( Figure 2C). Next, we searched for miRNA binding sites in the 3'UTR, which are known to repress the expression of transcripts they bind to. Module-wise analysis showed a significantly higher density of miRNA binding sites for genes of modules 6 and 8, indicating that the expression of some fate regulators and neuronal genes might be regulated by miRNAs ( Figure 3-figure supplement 1C). For example, the upper-layer neuronal fate regulator gene SATB2, a member of module 6 is regulated through the binding of miR-541 and miR-92a/b to its 3'UTR thereby preventing its translation (Martins et al., 2021). Altogether, these data indicated that trans-regulatory factors play a major role in the regulation of transcripts with cell class-specific expression ("C" modules). Next, we analyzed cis-regulatory features inherent in the mRNA sequence ( Figure 3A, Figure 3-source data 2). We compared the lengths of coding sequences (CDS) and the 5' and 3'UTRs ( Figure 3-figure supplement 1D-F). Compared to all other modules, module 3 transcripts were overall shorter in all these features, whereas modules 8 and 9 seemed to have longer 5' and 3'UTRs ( Figure 3-figure supplement 1D-F). Secondary structures in a transcript can be estimated by prediction of minimum free energy (MFE) (Lorenz et al., 2011;Mathews and Turner, 2006), which is positively correlated with translation rate and a measure of RNA stability (Nomura et al., 1984). Our analysis revealed that the MFE for the CDS as well as the 5' and 3'UTRs were overall higher for module 3, indicative of less stable secondary structures ( Translation initiation efficiency is directly influenced by the Kozak sequence, which refers to the six nucleotides preceding the AUG start codon and the nucleotide immediately downstream. We computationally calculated a Kozak context score (Floor and Doudna, 2016) that describes the overall similarity to the consensus sequence GCCRCCAUGG (R = A or G) for all transcripts. Interestingly, genes in "C" modules have weaker Kozak context scores, suggesting reduced translational initiation rates that potentially allow precise translational regulation of these transcripts via additional mechanisms ( Figure 3D). In contrast, genes in "A" modules have the overall highest Kozak scores ( Figure 3D). Similar differences between "C" and "A" modules were also observed for the occurrence of upstream open reading frames (uORFs) in the 5' UTR. It has been suggested that uORFs do not affect mRNA levels but can significantly reduce translation (Barbosa et al., 2013). We predicted uORFs by occurrence of [ACT]TG sequence upstream of the main ORF (Floor and Doudna, 2016). We observed a reduced number of uORFs predicted in modules 3, 4 and 5 ( Figure 3E) suggesting a limited role of uORFs in their expression pattern in contrast to gene expression in the "C" The heatmap on the right shows the -log10 p-value of the pairwise wilcox test of gene modules. Significant comparisons are marked by an asterisk (p < 0.01). F) 5' terminal sequences of five selected 5'TOP transcripts. Pyrimidine-rich 5'TOP sequences are highlighted in blue. G) Dot plot showing overrepresentation analysis of 5'TOP genes across the 9 modules. Significance threshold: Adjusted p-value <0.05. Gene lists refer to Classical 5'TOP genes (Philippe et al., 2020) and predicted 5'TOP mRNAs (Yamashita et al., 2008) (Figure 3-source data 3). H) Z-score normalized relative abundance of transcripts and proteins in progenitors and neurons of all 5'TOP genes and of module 3 excluding 5'TOP genes. modules. Lastly, we observed that the 3'UTRs of genes in module 6 are enriched in adenylate/uridylate (AU)-rich sequences that promote cellular context-dependent mRNA decay or stability (Figure 3-figure supplement 1J) (Otsuka et al., 2019). This mode of regulation probably supports the expression pattern of this module, where transcripts are translationally silenced in late progenitors and active in neurons ( Figure 2B). On the other hand, module 9 has significantly less AU-rich elements in the 3'UTR ( Figure 3-figure supplement 1J) that corroborates the observed depletion of binding motifs for the ELAV-like family ( Figure 3C), which is a major binding partner of AU-rich sequences (Ma et al., 1997). Overall, this analysis revealed that cell class-specific gene expression seems to be regulated by diverse posttranscriptional mechanisms: trans-regulatory factors, secondary structures in UTRs, imperfect Kozak and uORFs ( (Cockman et al., 2020;Philippe et al., 2020;Yamashita et al., 2008). This observation raised the possibility that 5'TOP genes exhibit a unique RNA-protein expression pattern during corticogenesis. Relative protein yield of 5'TOP mRNAs is lower in early progenitors compared to early born neurons. Analyzing the expression pattern of all 5'TOP genes showed that although expressed highly in both progenitors and neurons, 5'TOP transcripts were relatively more abundant in progenitors compared to neurons, with this effect being the most striking at early stage of organoid development at day 40 ( Figure 3H). Analyzing the transcript distribution by RNA-FISH for two example 5'TOP genes RPL5 and RPL11 in 40 day old organoids confirmed this observation ( Figure 4A), with high intensity of fluorescence being present in the progenitor-rich VZ, and low in the surrounding neuron-rich region. This pattern was not observed by RNA-FISH for the immature neuron marker DCX and in the no-probe control ( Figure 4-figure supplement 1A,B). At protein level, however, a relative difference in progenitor-and neuron-rich regions was not detectable ( Figure 4B). This discrepancy was also replicated in the absolute levels of RNA and protein for RPL5 and RPL11 (data available in the R shiny app). To verify this RNA-protein discrepancy at cellular resolution, we grew sparsely labeled organoids using 95% of unlabeled control H9 cells and 5% of the dual reporter cell line ( Figure 1-figure supplement 1D). Next, we stained cryosections from these organoids for transcripts and protein of the 5'TOP genes RPL5 and RPL11 by RNA-FISH and by immunostainings, respectively. We quantified the average RNA and protein intensity per cell of individual progenitors labeled by EGFP and neurons labeled by dTomato ( Figure 4-figure supplement 1C). Indeed, we could validate that RPL5 and RPL11 show higher transcript levels in progenitors than neurons, but protein levels were not different between the two cell classes (Figure 4-figure supplement 1D,E). To confirm that this observation is also found in vivo, we analyzed a published human fetal brain scRNA-seq dataset (Eze et al., 2021). Similar to our results, 5'TOP transcripts show higher expression in neuroepithelial,

radial glia and intermediate progenitor cells compared to neurons at gestational weeks 6 to 10 (Figure 4-figure supplement 1F). To investigate possible molecular mechanisms that contribute to the observed discrepancy between RNA and protein levels of the 5'TOP genes, we analyzed a published ribosome profiling dataset from in vitro 2D cultures of hPSC-derived human neural progenitors and neurons (Blair et al., 2017) (Figure 4-figure supplement 1G). This dataset corroborated our observation that progenitors have higher levels of cytosolic 5'TOP mRNAs compared to neurons. Interestingly, while for 5'TOP mRNAs the actively translated (polysome-bound) mRNA pool was similar between the cell classes, progenitors contained significantly higher amounts of monosome-bound mRNA that is considered translationally less active ( Figure S8H). In contrast, transcripts of cell class-specific modules 1 and 9 showed not only a cell class-specific expression in the cytosol but also coherently their specific occurrence in the translated polysome fraction (Figure 4-figure supplement 1H). Hence, we hypothesized that some of the excess 5'TOP transcripts present in the progenitors might reside in a translationally-inhibited stage. To test if similar mechanisms operates in the 3-D organoid tissue and if the translation of 5'TOP genes is indeed different between early progenitors and neurons, we generated hPSC lines carrying a reporter that contained a 5'TOP motif in the 5'UTR of a doxycycline-inducible tagBFP fluorescent protein. As a negative control we generated non-5'TOP control reporter lines, in which the 5'TOP nucleotides were mutated ( Figure 4C). Initially, the fidelity of these reporter lines was evaluated at hPSC stage ( . As the translation of 5'TOP mRNAs is known to be inhibited upon mTOR inhibition (Cockman et al., 2020), we treated cells with the mTOR inhibitor Everolimus. As expected, we observed reduced tagBFP expression in the 5'TOP compared to the non-5'TOP reporter lines (Figure 4-figure supplement 2C). This observa- Fig. 4. Translation of 5'TOP mRNAs is partially inhibited in early progenitors compared to early born neurons. A) RNA-FISH for the 5'TOP transcripts RPL5 and RPL11 in 40-day old organoids. Images show a typical ventricular zone (VZ)-like structure in the brain organoid with a zoomed-in image of the boxed area on the right. Dotted line marks the apical side of VZ. Scale bar = 50 µm. B) Immunostaining for the 5'TOP proteins RPL5 and RPL11 in 40-day old organoids. Images show a typical VZ-like structure in the brain organoid with a zoomed-in image of the boxed area on the right. Dotted line marks the apical side of VZ. Scale bar = 50 µm. C) Schematic representation of the dox-inducible 5'TOP (blue) and non-5'TOP (orange) tagBFP reporter constructs. D, E) Representative cumulative distribution of reporter tagBFP levels in neural progenitors (D) and in neurons at day 40 (E) from 5'TOP reporter (blue) and non-5'TOP reporter (orange). F) Confocal scan of a typical VZ-like structure in a 40-day old organoid expressing G3BP1-mScarlet stained for RPL5 and RPL11 transcripts by RNA-FISH. Zoomed in image of the inlay shows G3BP1 granules pointed by yellow arrows. Dotted line marks the apical side of VZ. Scale bar = 20 µm. G) Quantification of RPL5 and RPL11 RNA-FISH signal intensities in the nucleus, G3BP1 positive granules and cytosol of progenitors in the VZ. P-value of Mann-Whitney test. Each dot represents a cell. (Number of cells analyzed: RPL5: n=45; RPL11: n=34). tion confirmed that tagBFP expression in the reporter lines is indeed mTOR pathway-regulated and thus suitable to study 5'TOP translation during organoid development. Hence, we used these reporter lines to grow organoids that we treated at day 40 with doxycycline to induce the expression of tagBFP. Three days after doxycycline induction, the organoids were dissociated to make a single cell suspension and immunostained for progenitor (SOX2) and neuron (TUJ1) markers ( We observed that only 30% of the cells in the organoids expressed tagBFP, indicating that it is difficult to achieve uniform doxycycline-mediated activation of the construct in 3D organoid tissue (Figure 4-figure supplement 3B). We therefore only analyzed cells that expressed tagBFP and were SOX2-PE or TUJ1-488 positive (Figure 4-figure supplement 3C). In progenitors (SOX2+), the 5'TOP reporter showed more cells with lower tagBFP fluorescence compared to the non-5'TOP reporter ( Figure 4D). On the other hand, in neurons (TUJ1+), the 5'TOP reporter showed the tendency towards higher tagBFP expressing cells compared to the non-5'TOP reporter ( Figure 4E). This was observed consistently between different cell lines and experiments ( Figure 4-figure supplement 3D,E) indicating that in general, the presence of 5'TOP motif lowers the effective tagBFP protein abundance in progenitors. Together, we provide multiple pieces of evidence indicating that despite higher mRNA levels, early progenitors exhibit less effective translation of 5'TOP element-containing mRNAs than neurons. Early progenitors exhibit a stress-associated 5'TOP translational control mechanism in a developmental context. 5'TOP translation is known to be regulated during cellular stress (Cockman et al., 2020). During stress conditions, 5'TOP RNAs localize to stress granules (SGs), which are dense RNA-protein condensates (Damgaard and Lykke-Andersen, 2011;Wilbertz et al., 2019). Hence, we asked if we also observe stress granule-like (SGL) structures during corticogenesis in organoids. We immunostained for the stress granule marker G3BP1 in untreated organoids and organoids treated with sodium arsenite (NaAs), a strong inducer of cellular stress ( ). Furthermore, we performed RNA-FISH and observed localization of RPL5 and RPL11 transcripts to these mScarlet-positive SGL structures ( Figure 4F). The intensity of the FISH signal was similar in the SGL structures and the cytoplasm ( Figure 4G), which would suggest that only a small fraction of the mRNA is sequestered in the granules, in agreement with reduced effective translation and not a translational block. In line with previous studies (Damgaard and Lykke-Andersen, 2011;Wilbertz et al., 2019) RPL5 and RPL11 transcripts were strongly enriched in G3BP1 positive granules in NaAs-treated organoids (Figure 4-figure supplement 4G). To reinforce our observation that 5'TOP transcripts are partially translationally silenced, we estimated the relative RNA stability from the fold change of exonic to intronic reads using our RNA-seq data (Alkallas et al. In contrast, the cell class-specific modules 1 and 9 showed higher transcript stabilities in progenitors and neurons, respectively, in line with our transcript and protein expression data (Figure 4-figure supplement 5B). Thus, early progenitors seem to have excess mature 5'TOP mRNAs with higher RNA stability and a fraction of these is not actively translated and sequestered into G3BP1-positive SGL structures. It is known that 5'TOP translation is regulated by the mTOR pathway and is inhibited upon mTOR pathway inhibition (Cockman et al., 2020). Therefore we assessed the status of mTOR pathway by immunostaining for phosphorylated forms of two of its substrates: 4E-BP1 and RPS6 (S6). The uniform distribution of phospho-4E-BP1 (p4E-BP1) across the tissue indicated generally active mTOR signaling (Figure 5-figure supplement 1A). However, as reported previously for organoid and fetal samples (Andrews et al., 2020;Eze et al., 2021) phospho-S6 (pS6) staining showed enrichment outside the VZ in neuronal regions ( Figure 5-figure supplement 1B). These observations suggest that differential mTOR activity in early progenitors, especially ventricular radial glia, and neurons might regulate differential 5'TOP translation. Based on these results we propose that the mTOR-5'TOP translational regulation axis is active in early neural progenitors and might play a crucial role in neuronal differentiation. mTOR-mediated regulation of 5'TOP mRNA translation is crucial for the fidelity of cortical development. We hypothesized that mTOR pathway overactivation should result in increased translation of ribosomal and other 5'TOPcontaining genes in neural progenitors. To upregulate the mTOR pathway during organoid development, we generated hPSCs with loss of function mutations in TSC2 (TSC2-/-), a A) Immunostaining of 40 days old TSC2+/+ and TSC2-/-organoid sections with anti-TSC2 antibody. Scale bar = 100 µm. B) Immunostaining of 40 days old TSC2+/+ and TSC2-/-organoid sections stained with anti-pS6 and anti-SOX2 antibodies. Zoomed in image of the inlay on the bottom. Scale bar = 100 µm. C) Schematic representation of polysome profiling of 37 days old TSC2+/+ and TSC2-/-organoids followed by RNA-seq and differential polysome association analysis of 80s monosome, low-polysome and high-polysome fractions. Data was generated from 3 batches of organoid differentiation for Rozh5 WT and Rozh5 TSC2 -/-4G11 clones. D) Heat map of hierarchical clustering of genes differentially associated with high-polysome fractions of TSC2+/+ and TSC2-/-organoids (left). Top 10 most significant cellular component GO terms for TSC2-/-enriched DAGs and TSC2+/+ enriched DAGs (right). E) MA plot of 5'TOP genes for high-polysome, low-polysome and monosome fractions shows log2 fold change of TSC2-/-over TSC2+/+ versus log2 mean TPM (expression levels). Significant genes (threshold: log2 fold change = 1, FDR = 0.1) are color coded. F) Log2 fold change of classical 5'TOP genes associated with high-polysome fractions over monosome fractions of TSC2+/+ and TSC2-/-organoids. P-value of paired t test. G) Quantification of mean z-score normalized fluorescent intensity of RPL5 and RPL11 proteins in the ventricular zones (VZs) of TSC2+/+ and TSC2-/-organoids. Error bars mark standard deviation. P-values of unpaired t-test are shown. Each dot represents a VZ. Data from 3 batches of organoid differentiation for each clone. Schematic on the left shows a typical ROI analyzed for a VZ. Figure 5C). Due to the large amount of material needed for polysome profiling, we used 37 day old intact organoids that contain a vast majority of cells in progenitor state. Initially, we performed differential gene association analysis between TSC2-/-and control samples for each fraction ( Figure 5D and Figure 5-figure supplement 2B,C, Figure 5-source data 1). We indeed found an enrichment for ribosomal genes specifically in the high-polysome fraction of TSC2-/-over control organoids ( Figure 5D). When specifically analyzing 5'TOP transcripts we found overall increased levels in the high-polysome fractions in TSC2-/-organoids compared to control organoids, whereas similar levels were detected in the low-polysome and monosome fractions ( Figure 5E). Accordingly, the relative fraction of 5'TOP transcripts actively translated in high-polysomes over the translationally less active monosomes was increased in TSC2-/-over control organoids ( Figure 5F, Figure 5-source data 1). To confirm that the upregulation of 5'TOP transcripts in the polysome fraction results in increased protein levels, we performed RNA-FISH and immunostainings in TSC2-/-and control organoids for RPL5 and RPL11. While we could not detect differences in their RNA levels ( . Taken together, these results verify an increase in 5'TOP mRNA translation upon mTOR activation and indicate that physiological mTOR activity is crucial to regulate protein levels of 5'TOP genes in early progenitors. Thus, our results suggest that the translational machinery itself is uniquely regulated post-transcriptionally during neurodevelopment. Next, we asked if mTOR overactivation and the concomitantly increased translation of ribosomes impacts gene regulation of other genes and potentially the tissue development. We checked if the genes differentially associated with ribosome fractions in polysome profiling were enriched in any of the 9 gene expression modules ( Figure 2B) by over-and under-representation analysis (Figure 5-figure supplement 4A, B). For genes, which were significantly higher in the high-polysome fraction of TSC2-/-over those of control, we observed a significant enrichment for modules 4, 7 and 9 ( Figure 5-figure supplement 4A). Module 7 is enriched in mitochondrial genes known to be differentially expressed in TSC2-/-at transcript level (He et al., 2020;Koyanagi et al., 2011). Importantly, the enrichment of neuronal module 9 to be highly translated in TSC2-/-is striking. In contrast, the genes which were less translated in the TSC2-/-organoids over control were significantly enriched in progenitor-specific modules 1 and 2 ( Figure 5-figure supplement 4A). This data suggests that mTOR overactivation and the subsequent impact on the translation machinery shifts the state of the tissue towards precocious differentiation. These observations were also corroborated in the underrepresentation analysis. Genes with higher translation in TSC2-/-were significantly depleted in modules 1 and 2 (progenitor-specific expression), whereas genes with lower translation in TSC2-/-were significantly depleted in module 9 (neuron-specific expression) as well as module 3, which is enriched in 5'TOP genes ( Figure 5-figure supplement 4B). We next tested if the increased translation of differentiationrelated genes is reflected by an increased neuronal differentiation using the dual reporter line. For this, we performed flow cytometry using dual reporter TSC2-/-and TSC2+/+ organoids ( Figure 5-figure supplement 4C,D). In agreement with the polysome profiling data, we observed a significant reduction in the fraction of EGFP+ cells (progenitors) and a significant increase in the fraction of dTomato+ cells (neurons) ( Figure 5-figure supplement 4D). Overall, the ratio of dTomato+ cells to EGFP+ was increased in the TSC2-/-, indicative of an increased differentiation

( Figure 5-figure supplement 4D). Apart from an increase in neuronal markers, we also observed precocious occurrence of the glial marker S100B in the TSC2-/-tissue at day 40 ( Figure 5-figure supplement 4E), reinforcing our observation that the progenitors are shifted towards a precocious differentiation state. This was already observed at day 40 and possibly explains the premature gliogenesis observed at later stages of TSC2-/cortical spheroids (Blair et al., 2018). While it is difficult to separate the primary and secondary effects of mTOR overactivation, we propose that the partial translational inhibition of 5'TOP mRNAs in early neural progenitors is crucial for cortical development. Discussion In this study, we show that multiple transcripts encoding components of the translational machinery that contain 5'TOP motifs are regulated on a post-transcriptional level during neurodevelopment. 5'TOP transcripts are abundantly expressed in all cells and yet show a unique regulation compared to other cellular transcripts (Cockman et al., 2020;Fonseca et al., 2014;Meyuhas and Kahan, 2015). During mitosis, 5'TOP transcripts skip the global translational inhibition (Park et al., 2016) whereas in stress context these transcripts are the first ones to be translationally inhibited to conserve the resources and energy of the cell by downregulating translation (Cockman et al., 2020;Fonseca et al., 2014;Meyuhas and Kahan, 2015). While translational regulation of 5'TOP transcripts is intensely studied in the context of stress, we show that it plays a major role during corticogenesis. Our observation of SG-like RNA-granules in early ventricular radial glia further supports the occurrence of stress-associated processes during corticogenesis. A recent report suggests that the energetic stage of a cell can impact the formation of SGLs under physiological conditions (Wang et al., 2022). Thus, the well documented difference in the metabolic states of glycolysis-dependent early progenitors and oxidative phosphorylation-heavy neurons (Iwata and Vanderhaeghen, 2021) might contribute to the regulation of 5'TOP mRNAs through the formation of SGLs. Another stress-related pathway, the unfolded protein response (UPR) is physiologically active at early stages of mouse corticogenesis to promote neurogenesis (Laguesse et al., 2015). Overactivation of the UPR beyond its physiological levels affects the generation of intermediate progenitors in the mouse and human cortical tissue, resulting in a microcephalic phenotype (Esk et al., 2020;Laguesse et al., 2015;Pas , ca et al., 2019). Perhaps, similar mechanisms regulating 5'TOP mRNA translation are utilized during development and during stress conditions. Recently, a role of the translational regulation of 5'TOP transcripts has been suggested in germline stem cell differentiation in Drosophila (Martin et al., 2022) and in mouse adult neurogenesis (Baser et al., 2019). It will be exciting to investigate if stress-associated pathways play a physiological role during the development of not only the cerebral cortex but also other tissues. Regulation of the 5'TOP mRNA translation ultimately determines the availability of ribosomes in the cells. Ribosome availability is proposed to be a critical factor determining the translation of mRNAs with complex 5'UTRs with secondary structures (Hetman and Slomnicki, 2019). Supporting this hypothesis, we found that Module 9 neuronal genes that feature more complex 5'UTRs (Figure 3-figure supplement 1H) are particularly deregulated upon 5'TOP translation deregulation accompanying mTOR overactivation ( Figure 5-figure supplement 4A). Our data suggests that regulating the number of ribosomes is particularly important in the early progenitors. An imbalance of ribosomal components caused by deregulation of 5'TOP transcripts likely causes aberrant translation of differentiation markers and affects the fidelity of cortical development. Reduced ribosome biogenesis and availability is also indicated at an early stage of mouse corticogenesis (Chau et al., 2018;Harnett et al., 2021). While many gene-specific examples of neural priming in radial glia are known (Yang et al., 2014;Zahr et al., 2018), our data suggest that radial glia regulate the translation of the translational machinery itself. We speculate that this regulation is crucial to maintain the multipotency of early progenitors to prevent aberrant translation of pre-existing transcripts of differentiation genes. A global regulation of the translational machinery has been recently reported for mid-gestation stages of mouse corticogenesis, with gradual reduction in the translational efficiency of 5'TOP genes and the availability of ribosomes (Harnett et al., 2021). It would be interesting to test if similar changes occur during late corticogenesis in humans, which includes a complex repertoire of neural progenitors, especially the outer radial glia. The mTOR pathway is a major regulator of 5'TOP mRNA translation (Cockman et al., 2020;Fonseca et al., 2014;Meyuhas and Kahan, 2015) and is a key feature of any healthy cell. The role of the mTOR pathway in progenitor proliferation and neuronal morphology and function is well documented (Switon et al., 2017). However, the cell typeand developmental stage-specific roles of the mTOR pathway are becoming clear only recently. Our results in human brain organoid tissue show that early radial glia show lower mTOR activity in interphase. Studies using mouse, 2D neuronal cultures and cortical spheroid cultures have also reported a drop in mTOR activity during early stages of corticogenesis (Blair et al., 2018(Blair et al., , 2017Chau et al., 2018). Analysis of human fetal transcriptome of early stages has also suggested a similar trend (Eze et al., 2021). On the other hand, human outer radial glia that arise at later stages of corticogenesis exhibit higher mTOR activity, both in primary fetal tissue and brain organoids (Andrews et al., 2020). Thus, despite its general role, mTOR pathway activity undergoes modulation during distinct neurodevelopmental stages. Additionally, downstream effects of mTOR signaling are linked to diverse cellular processes such as translation, cell cycle and actin biology. Therefore, linking the defects in the pathway to a final cellular phenotype remains challenging. We provide an alternative molecular role of this pathway to directly regulate ribosome availability and thus indirectly control many other downstream cellular pathways. Mutations in mTOR pathway-related genes are associated with many genetic disorders such as tuberous sclerosis, focal cortical dysplasia and megalencephaly (Crino, 2016). Thus, to understand the disease mechanisms, it will be crucial to consider cell typeand stage-specific activity of the mTOR pathway. Beyond 5'TOP genes of the translational machinery, our dataset highlights distinct gene expression modules based on transcript and protein abundance traits. This includes cell class-specific "C" modules with coherent RNA-protein expression as well as "T" and "A" modules where transcript and protein do not follow the same trajectories. Additionally, analysis of cis and trans regulatory factors alludes to distinct RNA regulation mechanisms that are potentially predominant for these genes and contribute to their expression patterns. For instance, the reciprocal relation in the RBP motif enrichment in 3'UTRs of "C" modules 1 and 9 highlights interesting roles of RBPs to regulate cell class-specific gene expression. Thus, our approach opens new avenues to study RNA regulation during corticogenesis. Finally, our integrated dataset describes cell class-and developmental stage-specific gene expression, both at RNA and protein level and is available to browse for the wider community in the form of a R-based Shiny app (https://organoid.multiomics.vbc.ac.at). To our knowledge, this is the first time RNA and protein datasets for human corticogenesis have been integrated. Only looking at transcript or protein data wouldn't have revealed the post-transcriptional regulation of the ribosomal genes, which are usually considered housekeeping genes and ignored for example in sc-RNA-seq analysis and often used as normalizers for gene expression. This rich resource can be used to browse RNA-protein expression patterns of various other genes across the human organoid developmental timeline. For instance, our data indicates that the gene regulation of the upper layer marker SATB2 observed during mouse corticogenesis (Harnett et al., 2021) also holds true in humans. As characterized by the general trend of module 6, where the RNA expression of SATB2 is high in progenitors and neurons of later stages, the trends at protein level suggest translational inhibition of the SATB2 transcripts in progenitors. Integration with information on protein abundance is crucial for the comprehensive understanding of gene expression. This approach opens a new avenue to study the regulation and expression pattern of individual genes and gene modules. Thus, integrative omics approaches can reveal new biological mechanisms underlying diverse developmental events. for sequencing analysis; the VBCF Sequencing unit for sequencing the IMBA/IMP/GMI protein chemistry core facility for mass spectrometry. We thank the group of Andrea Pauli, especially Katrin Friederike Leesch, for sharing the resources and expertise in polysome profiling. Conflict of interest J.A.K. is inventor on a patent describing cerebral organoid technology and co-founder and scientific advisory board member of a:head bio AG. Data and code availability The RNA-seq data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus (Edgar et al., 2002) and are accessible through GEO Series accession numbers GSE214654 and GSE214652. The mass spectrometry proteomics data have been deposited to the Pro-teomeXchange Consortium via the PRIDE (Perez-Riverol et al., 2021) partner repository with the dataset identifier PXD037106. Material and methods Cell lines and culture. Feeder-free hESChuman embryonic stem cell (hESCs) line WA09 (H9) and feeder-free human induced pluripotent stem cell (hiPSC) line HPSI0114i-rozh_5 (Rozh-5) were used in this study. H9 was obtained from WiCell and Rozh-5 from HipSci. Cells were verified to display a normal karyotype and regularly tested for mycoplasma. All cells were cultured on hESCs-qualified Matrigel (Corning, 354277) coated plates with a modified in-house medium based on the E8 culture system . The original E8 recipe was supplemented with 0.5% BSA (Europa Bioproducts, EQBAH62-0500), 200 ng/ml in-house produced FGF2 and 1.8 ng/ml TGFβ1 (RD Systems, RD-240-B-010). Cells were passaged every 3-4 days using 0.5 mM EDTA. For generating TSC2 KO, cells were cultured using Cellartis DEF-CS 500 culture system (Takara Bio, cat. no. Y30012). Dorsal tissue-enriched telencephalic organoid generation. Dorsal forebrain-enriched telencephalic organoids were generated as previously described with slight modifications (Esk et al., 2020). Briefly, hPSCs were grown to 60-80% confluency and dissociated with Accutase (Merck, A6964) to obtain a single cell suspension. 4000-9000 cells were resuspended in 150µl of E8 supplemented with Rock inhibitor and seeded in each well of the 96-well ultra-low-attachment U-bottom plate to form embryoid bodies (EBs). On day 3 the medium was changed to E8. From day 6 onwards the EBs were cultured in neural induction medium (NI) (Lancaster et al., 2017). On day 10, EBs were embedded in Matrigel and transferred to 10-cm cell-culture dishes coated with anti-adherence rinsing solution (Stemcell technologies, P2443) in 15ml NI. From day 13 to 25 the organoids were grown in a differentiation medium lacking vitamin A (Diff-A). During day 13 to 15 they were treated with 2 pulses of 3µM CHIR99021 (Merck, 361571) to dorsalise the tissue. On day 18 dishes were transferred to an orbital shaker at 57 rpm. From day 25 onwards the organoids were grown in differentiation medium with vitamin A (Diff+A). The medium was supplemented with 1% Matrigel from day 40 onwards and with BDNF from day 55 onwards. See the media composition in Supplementary file 2. For Tet-induction, the medium was supplemented with Doxycycline-hyclate (Merck, D9891) dissolved in water at a final concentration of 1.7 µg/ml medium of hPSCs and 3 µg/ml for organoids. For mTOR inhibition, hPSC culture medium was supplemented with Everolimus (Abcam, ab142151) dissolved in DMSO at a final concentration of 20 nM. For sodium arsenite (NaAs) treatment, the medium was supplemented with NaAs (Merck, S7400) dissolved in water to achieve a final concentration of 500 µM. To ensure diffusion in the 3D organoid tissue, treatment with NaAs was performed for 1 h. Organoid dissociation. Organoids were washed with DPBS without calcium and magnesium and added to a 9:1 mixture of Accutase (Merck, A6954) and 10x Trypsin (Thermo Fisher Scientific, 15400054) supplemented with 2 units/ml TURBO™ DNase (Thermo Fisher Scientific, AM2238). The dissociation was performed using the NTDK1 protocol on a gentleMACS™ Dissociator (Miltenyi Biotec, 130-093-235). The dissociated cells were pelleted, washed with DPBS without calcium and magensium (Thermo Fisher Scientific, 14190250) and filtered through a 70 µm cell strainer to remove residual tissue chunks. The filtered single cell suspension was then used either for live cell FACS or for immunostaining. FACS. For live cell sorting cells were resuspended in FACS buffer (DPBS without calcium and magensium with 2% BSA), filtered through a 35 µm cell strainer and then sorted on a FACS ARIAIII (BD Biosciences) controlled by FACSDiva software. For detecting GFP signal, a 488 nm laser was used with a 530/30 nm filter. For detecting dTomato signal, a 561 nm laser was used with 582/15 nm filter. The sort was done in PBS at

low pressure using a 100 µm nozzle. Immunostaining of dissociated cells. For immunostaining cells, the dissociated single cells were fixed with 4% paraformaldehyde (PFA) for 30 mins on ice. The cells were permeabilized with 0.1% Saponin (Merck, 47036) in PBS either during or after fixation. Fixed cells were then pelleted and washed with a wash solution (0.1% Saponin + 1% BSA in PBS) to remove traces of PFA. Next, the cells were split for appropriate controls and resuspended in a staining solution (Fluorophore conjugated primary antibody in 0.1% Saponin + 1% BSA in PBS) for 30 mins on ice. The stained cells were then pelleted and washed twice with wash solution and resuspended in the final resuspension buffer (0.5%BSA in PBS). Antibodies used in this study are summarized in Supplementary file 2. Flow cytometry analysis. For analyzing the expression in live cells or in immunostained single cells, flow cytometry was performed on LSR Fortessa (BD Biosciences) controlled by FACSDiva software. Data was analyzed using FlowJo. For detecting tagBPF signal, 405nm laser was used with 442/46 nm filter. For detecting Alexa-488 signal, 488nm laser was used with 530/30 nm filter. For detecting PE signal, 561nm laser was used with 582/15 nm filter. Immunohistochemistry. Organoids were fixed in 4% paraformaldehyde (PFA) for 3-4 hours at room temperature. After extensive washes with PBS, organoids were immersed overnight, first in 30% sucrose (Merck,84097) in PBS and thereafter in 1:1 mixture of 30% sucrose and OCT (Sakura, 4583). These organoids were then embedded in OCT using suitable cryomolds and frozen at -70°C. Samples were sectioned at 20 µm thickness using a Epredia Cryostar NX70 cryostat (Thermo Fisher, 957000H). The slides were dried overnight and then stored at -20°C. After washing the slides extensively with PBS to remove the OCT, cryo-sections were permeabilized and blocked with blocking solution (5% BSA containing 0.3% Triton X-100 (Merck, 93420)) for 1-2 h at room temperature. Sections were then incubated with primary antibodies diluted in antibody solution (5% BSA, 0.1% Triton X-100 in PBS) overnight at 4°C. After three washes of 10 min with PBST (0.01% Triton X-100 in PBS), sections were incubated with secondary antibodies diluted in antibody solution containing 2 µg/ml DAPI at room temperature for 2 h. After three washes of 10 min with PBST (0.01% Triton X-100 in PBS) and one wash with PBS, the samples were mounted in fluorescence mounting medium (Agilent, S302380-2) and imaged with a spinning disk confocal microscope. Antibodies used in this study are summarized in Supplementary file 2. AlexaFluor 488, 568 or 647-conjugated secondary donkey antibodies were used at a 1:500 dilution. Preparation of image panels and Image analysis was performed using Fiji (Schindelin et al., 2012). For measuring average intensity per cell, progenitors and neurons were identified in mosaic reporter organoids, and the cell outline was traced to mark a ROI. Average intensities for each ROI were measured using the multi measure tool. For measuring average intensity in the VZ, a rectangular ROI was marked in the maximum intensity projection of the VZ. Average intensities for each ROI were measured using the multi measure tool. To enable integration of data from different experiments, results were z-score normalized per experiment. Integration of transcriptomic and proteomic dataset. For the 6,740 UniProt protein identifiers from the proteomics dataset, 6,732 could be mapped to an ensembl gene identifier using the BioMart data mining tool as well as manual annotation. Accordingly, for 20,158 out of 33,849 ensembl gene identifiers from the transcriptomic dataset a UniProt protein identifier could be identified. For data integration, the theoretically observable tryptic peptide normalized protein abundances were log10 transformed followed by z-score normalization. TPM values for genes that encode for identical proteins were summed, log10 transformed and finally z-score normalized. Finally, the normalized proteomics and transcriptomics data sets were combined by UniProt identifiers resulting in gene expression data for 6,714 genes. To identify temporal gene expression modules, the R bioconductor package maSigPro version 1.68.00 for time-series was used (Nueda et al., 2014). Briefly, a first regression fit for each of the 6,714 genes was performed and significant genes selected at a false discovery rate of 0.05. For the remaining 5,978 significant genes, a second stepwise regression fit was performed to identify profile differences between experimental groups. Regression models at R-squared > 0.6 were found for 3,668 genes, which were hierarchical clustered. The optimal number of clusters were estimated using the factoextra package for R and the 'average silhouette width', 'total within sum of square' and 'gap statistics' methods. Finally, different numbers of clusters (6 to 12) were manually evaluated with regards to their biologically meaningfulnes using for example gene gene enrichment analysis tools. Finally, the 3,668 genes were clustered into nine gene expression modules and gene enrichment analysis performed using the R bioconductor package clusterProfiler (Yu et al., 2012). Transcript feature analysis. For each cluster, we considered all the transcripts of the member genes detected in our RNA-seq dataset (mean TPM >1) for the analysis. For transcript feature analysis, the Ensembl release sep2019.archive.ensembl.org in biomart R package was used to derive lengths of transcripts, coding sequence and UTRs. RNA structure features were determined using a Python program available through GitHub at https://github.com/stephenfloor/ tripseq-analysis (Blair et al., 2017). The structure was computed using RNALfold from the ViennaRNA package (Lorenz et al., 2011) in a 75-nt window. Analysis of RNA-binding protein motif enrichment. Analysis of enrichment or depletion of RBP motifs in 5'UTR and 3'UTR sequences was performed by transcript set motif analysis (TSMA) analysis with k-mer method and standard settings of Transite tool (Krismer et al., 2020) https: //transite.mit.edu/. Enrichment was calculated per module over the entire gene-set. Adjusted p-value of 0.05 was used as the significance threshold. Analysis of published tripseq data. We analyzed the previously published data for quantified expression values for TrIP-seq polysome profiling ( (Blair et al., 2017), Supplementary Table 4). The data was filtered for neural progenitors (progenitors) and 50-day old neurons (neurons) as well as for 5'TOP genes or genes in modules 1 or 9 and all TPM values were log2 transformed. Plasmid constructs and cloning. All the oligos used in the manuscript are listed in Supplementary file 1. All PCRs were performed using Thermo Scientific™ Phusion Hot Start II DNA-Polymerase (New England Biolabs, M0535S). Plasmids for CRISPR-Cas9 gene editing. For cloning guide sequences against SOX2, G3BP1 and TSC2 loci, corresponding DNA oligos containing the guide sequences were phosphorylated and hybridized to make double stranded DNA (ds-DNA) fragments. These ds-DNA fragments were cloned into pSpCas9(BB)-2A-GFP plasmid (Addgene, 48138, RRID:Addgene_48138), modified to express eCas9 instead of WT-Cas9 and dTomato instead of GFP (Esk et al., 2020), using the Bbs1 cloning strategy of Ran et al. (Ran et al., 2013). See Supplementary file 1 for the guide and oligo sequences. Reporter line generation. All reporter lines were generated by nucleofection of the plasmid DNA with the Amaxa nucleofector 2b device (Lonza, AAB-1001) and Human Stem Cell Nucleofector Kit 1 (Lonza, VPH-5012) following manufacturer's guidelines. For each nucleofection one million single cells were used. For genotyping, DNA was extracted using the QuickExtract DNA Extraction Solution (Cambio QE09050) and a PCR assay was performed to identify correctly edited clones. See Table S9 for oligo sequences used for genotyping. Genomic integrity of the final clones was confirmed by SNP arrays. Insertion into the AAVS1 safe-harbor locus was performed using TALEN technology as described before (Bagley et al., 2017;Hockemeyer et al., 2011). For this purpose, the nucleofection mix containing 0.5 µg of each of the TALEN plasmids and 1.5 µg of each of the donor plasmids was used. Nucleofected cells were grown for four to seven days and then selected with appropriate antibiotics. For puromycin resistance reporter: 1 µg/ml Puromycin dihydrochloride (Thermo Fisher Scientific, A1113803) and for neomycin resistance reporter 250 µg/ml Geneticin/G418 Sulfate (Thermo Fisher Scientific, 10131035). Surviving colonies were picked manually, transferred into 24-well plates and further expanded for genotyping and cryopreservation. For generating FF H9 SOX2::SOX2-P2A-EGFP reporter line, the nucleofection mix included 1 µg guide-Cas9 plasmid and 4 µg homology repair construct. 7 days post nucleofection, surviving cells were FACSed to obtain GFP positive cells which were sorted as single cells and further expanded for genotyping and cryopreservation. Positive clones were selected by performing PCR to verify genomic insertion of P2A-EGFP. For generating G3BP1 reporter line, FF H9 cells were electroporated with 0.8 µg guide-Cas9 plasmid and 1 µg homology repair construct. The HDR plasmid carried in addition to the APEX2-mScarlet fusion, also a floxed puromycin resistance cassette under the control of the EF1a core promoter. 48 h post electroporation, cells were selected with 0.5 µg/ml puromycin and correct gene editing was confirmed by genotyping PCRs and Sanger sequencing. Following, a pool of the correct clones was nucleofected as before with 2 µg Cre-recombinase-2A-EGFP expressing plasmid and 1 µg of pmaxGFP to remove the EF1a-puromycin cassette. Successfully electroporated cells were FACS sorted for GFP and mScarlet double positive cells. Excision of the EF1a-puromycin cassette was confirmed by genotyping PCRs and Sanger sequencing. For generating TSC2 KO hPSCs, nucleofection was performed with 3 µg guide-Cas9 plasmid. The surviving cells were FACSed the next day for dTomato fluorescence and sorted as single cells into 96-well plates. The single cell clones were expanded and genotyped to identify TSC2 homozygous mutants by Sanger sequencing. RNA extraction, library generation and RNA-seq. FACSed cells were pelleted and used for RNA isolation. Total RNA was isolated using a lysis step based on guanidine thiocyanate (adapted from (Boom et al., 1990)) with DNaseI digestion using magnetic beads (GE Healthcare, 65152105050450) applied on the KingFisher instrument (Thermo Fisher Scientific). The purified RNA was used to generate the RNA-seq library. RNA sequencing libraries were generated using 500 ng of RNA using NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina (New England BIolabs, E7760). Isolation of mRNA was done using the NEBNext® Poly(A) mRNA Magnetic Isolation Module (New England BIolabs, E7490). The size of libraries was assessed using NGS HS analysis kit and a fragment analyzer system (Agilent). Library concentrations were quantified with KAPA Kit (Roche) and 75-bp paired end-read sequencing was performed using the Illumina NextSeq550 platform. RNA-seq reads were trimmed using trim-galore v0.5.0, and reads mapping to abundant sequences included in the iGenomes UCSC hg38 reference (human rDNA, human mitochondrial chromosome, phiX174 genome, adapter) were removed using bowtie2 v2.3.4.1 alignment. Remaining reads were analyzed using genome and gene annotation for the GRCh38/hg38 assembly obtained from Homo sapiens Ensembl release 94. Reads were aligned to the genome using star v2.6.0c and reads in genes were counted with featureCounts (subread v1.6.2). Differential gene expression analysis on raw counts and variance-stabilized transformation of count data for heatmap visualization were performed using DESeq2 v1.18.1. Proteomics. A minimum of 2 million FACSed cells were pelleted, snap frozen in liquid nitrogen and stored at -80°C until processed. Each cell pellet was resuspended in 72.5 µL 10M Urea 50mM HCl and incubated 10 min at room temperature. Then 7.5 µL 1M TEAB (triethylammonium bicarbonate) buffer (pH 8) was added and total protein amount determined by Bradford assays. Following, 1 µL Benzonase and 1.25 µL 1M DTT (dithiothreitol) was added to each sample and incubated for 37°C for 1 h. Protein alkylation was performed with 2.5 µL of 1M IAA (iodoacetamide) and incubated for 30 min in the dark at room temperature and the reaction quenched with 0.6 µL 1M DTT. All samples were diluted with 100 mM TEAB Buffer to a urea concentration of 6M and proteins digested with LysC (Wako) for 3 h at 37ºC using an enzyme to protein ratio of 1:50. After the first digestion with LysC the samples were diluted with 100 mM TRIS buffer to a final Urea concentration of 2 M. The final tryptic digestion (Trypsin Gold, Promega) was performed with an enzyme to protein ratio of 1:50 overnight at 37ºC. To evaluate the digest efficiency 100 ng of all samples were analyzed on a monolithic HPLC system. Following, peptides were desalted using C18 cartridges (Sep-Pak Vac 1cc (50mg), Waters) that were equilibrated with 500 µL methanol/water 50:50, 2x 0.5mL 80% acetonitrile (ACN) 0.1% formic acid (FA) and 3x 0.5 mL 0.1% trifluoroacetic acid (TFA) applying gentle pressure with compressed air. The pH of all samples was adjusted to pH<2 with 10% TFA before they were loaded on the columns. All columns were washed

with 6x 0.5 mL 0.1% TFA applying gentle pressure using compressed air. To elute the sample 2x 200 µL of 80% ACN and 0.1% FA were used and to remove the solvent completely from the column, gentle pressure was applied with compressed air. The organic content of the eluates was removed by using a SpeedVac vacuum concentrator and samples were diluted to a volume of 200 µL with 0.1% FA, snap frozen with liquid nitrogen and lyophilized overnight. The dried samples were dissolved in 100 µL 100 mM HEPES and quantified using a monolithic HPLC system. One bridge channel was produced from all FACS sorted cells. In these channels the corresponding samples were mixed in a 1 to 1 ratio. For TMT labeling, 20 µg of peptides (in 100 µl 100 mM Hepes pH 7.6) were labeled with distinct channels of the TMTpro16 plex reagent (Thermo Fisher, TMT16plex) according to the manufacturer's description. Labeling efficiency was determined by LC-MS/MS on a small aliquot of each sample. Samples were mixed in equimolar amounts and equimolarity was evaluated again by LC-MS/MS. The mixed sample was acidified to a pH below 2 with 10% TFA and was desalted using C18 cartridges (Sep-Pak Vac 1cc (50mg), Waters). Peptides were eluted with 3 x 150 ml 80% Acetonitrile (ACN) and 0.1% Formic Acid (FA), followed by freeze-drying. The dried samples were dissolved in 70 µl of SCX Buffer A (5 mM NaH2PO4, pH 2.7, 15% ACN) and 200 µg of peptide were loaded on the column. SCX was performed using a custom-made TSK gel SP-2PW SCX column (5 µm particles, 12.5 nm pore size, 1 mm i.d. x 250 mm, TOSOH) on an Ultimate system (Thermo Fisher Scientific) at a flow rate of 35 µl/min. For the separation, a ternary gradient was used starting with 100% buffer A for 10 min, followed by a linear increase to 10% buffer B (5 mM NaH2PO4, pH 2.7, 1M NaCl, 15% ACN) and 50% buffer C (5 mM Na2HPO4, pH 6, 15% ACN) in 10 min, to 25% buffer B and 50% buffer C in 10 min, 50% buffer B and 50% buffer C in 5 min and an isocratic elution for further 15 min. The flow-through was collected as single fractions, along with the gradient fractions that were collected every minute. In total 60 fractions were collected, and low abundant fractions were pooled. ACN was removed by vacuum centrifugation and the samples were acidified with 0.1% TFA and analyzed by LC-MS/MS. The UltiMate 3000 HPLC RSLC nano system (Thermo Scientific) was coupled to a Q Exactive HF-X mass spectrometer (Thermo Scientific), equipped with a Proxeon nanospray source (Thermo Scientific). Peptides were loaded onto a trap column (Thermo Scientific, PepMap C18, 5 mm × 300 µm ID, 5 µm particles, 100 Å pore size) at a flow rate of 25 µL/min using 0.1% TFA as mobile phase. After 10 min, the trap column was switched in line with the analytical column (Thermo Scientific, PepMap C18, 500 mm × 75 µm ID, 2 µm, 100 Å). Peptides were eluted using a flow rate of 230 nl/min and a binary 120 min gradient. The two-step gradient started with the mobile phases: 98%A (water/formic acid, 99.9/0.1, v/v) and 2% B (water/acetonitrile/formic acid, 19.92/80/0.08, v/v/v) increased to 35% B over the next 120 min, followed by a gradient in 5 min to 90% B, stayed there for five min and decreased in 2 min back to the gradient 95% A and 2% B for equilibration at 30°C. The Q Exactive HF-X mass spectrometer was operated in data-dependent mode, using a full scan (m/z range 375-1650, nominal resolution of 120,000, target value 3e6) followed by MS/MS scans of the 10 most abundant ions. MS/MS spectra were acquired using normalized collision energy of 35, isolation width of 0.7 m/z, resolution of 45.000, a target value of 1e5 and maximum fill time of 250 ms. For the detection of the TMT reporter ions a fixed first mass of 110 m/z was set for the MS/MS scans. Precursor ions selected for fragmentation (exclude charge state 1, 7, 8, >8) were put on a dynamic exclusion list for 60s. Additionally, the minimum AGC target was set to 1e4 and intensity threshold was calculated to be 4e4. The peptide match feature was set to preferred and the exclude isotopes feature was enabled. Proteomics data processing. For peptide identification, the RAW-files were loaded into Proteome Discoverer (version 2.4.0.305, Thermo Scientific). All hereby created MS/MS spectra were searched using MSAmanda v2.0.0.13248 (Dorfer et al., 2014). The RAW-files were searched against the human uniprot-reference-database (20,541 sequences; 11,395,640 residues). The following search parameters were used: Iodoacetamide derivative on cysteine was set as fixed modification, deamidation on asparagine and glutamine, oxidation on methionine, TMTpro-16plex tandem mass tag on lysine, phosphorylation on serine, threonine and tyrosine as well as carbamylation on peptide N-Terminus, TMTpro-16plex tandem mass tag on peptide N-Terminus, acetylation on protein N-Terminus were set as variable modifications. Monoisotopic masses were searched within unrestricted protein masses for tryptic enzymatic specificity. The peptide mass tolerance was set to ±5 ppm and the fragment mass tolerance to ±15 ppm. The maximal number of missed cleavages was set to 2. The result was filtered to 1% FDR on peptide-spectrum-match and protein level using Percolator (Käll et al., 2007) algorithm integrated in Thermo Proteome Discoverer. The localization of the modification sites within the peptides was performed with the tool ptmRS, which is based on phosphoRS (Taus et al., 2011). Peptides were quantified based on Reporter Ion intensities extracted by the "Reporter Ions Quantifier"-node implemented in Proteome Discoverer. Proteins were quantified by summing reporter intensities of spectra with less than 50% isolation interference from unique peptides. Inspired by the iBAQ algorithm (Schwanhäusser et al., 2011), protein abundances were normalized by dividing summarized reporter intensities by the number of theoretically observable tryptic peptides with a length between 7 and 30 amino acids. TMT batches were normalized using a "bridge-channel" as reference which contains a mix of all samples. Polysome profiling by sucrose gradient fractionation. Polysome profiling was performed for 3 batches of organoid differentiation using Rozh5 WT and Rozh5 TSC2-/-4G11 hiPSC clones. For this procedure, all solutions and materials contained 100 µg/ml cycloheximide (CHX), were DPEC-treated if possible, and were pre-chilled at 4°C for at least 30 min before use. Before harvest, organoids were treated with 100 µg/ml CHX at 37°C for 10 min to arrest ribosomes and washed with ice-cold DPBS without calcium and magnesium (Thermo Fisher Scientific, 14190250). Organoids were then dissociated as described above with Accutase/Trypsin mix supplemented with 100 µg/ml CHX. All cells were pelleted at 1000 g for 10 min at 4°C. The supernatant was removed, cells were washed with 15 ml ice-cold DPBS without calcium and magnesium and pelleted at 1000 g at 4°C for 10 min. Next the pellet was resuspended in lysis buffer (20 mM TrisHCl, 30 mM MgCl2, 100 mM NaCl, 1% Triton X, 100 µg/ml CHX, 0.5 mM DTT, 1 mg/ml heparin, 100 µ/ml RNase inhibitor (Promega, NA2615) and Turbo DNase (ThermoFisher Scientific, AM2238)). Samples were triturated 10 times with a 26G needle, incubated on ice for 10 min, and spun at 21,000 g at 4°C for 20 min. 400 µl of lysate was loaded onto the sucrose gradient. Sucrose gradients of 10-50% range were prepared in 20 mM TrisHCl, 5 mM MgCl2, 140 mM NaCL with Gradient master unit (BIOCOMP, B108). Tubes were spun at 35,000 rpm for 2 h in a SW-40 rotor (Optima L-90K, Beckman Coulter). Each sample was passed through a gradient fractionator (TriaxTM Flow Cell Manual Gradient Station ip, BIOCOMP) and the A260 profile was monitored. 24 fractions with 500 µl of sample each were collected and immediately processed for RNA extraction. RNA extraction from sucrose gradient. Fractions were pooled into monosome, low-and high-polysome-associated mRNAs (Floor Doudna, 2016). RNA was extracted by adding equal volumes of acid Phenol/Chloroform (pH 4.7, Thermo Fisher Scientific, AM9720) to the sucrose fractions. The mix was vortexed briefly and spun down at 14,000 g at 4°C for 20 min. Subsequently, the aqueous phase was transferred to a new tube. RNA was precipitated with 300 mM NaAcetate, Ethanol and 20 µg Glycoblue (Thermo Fisher Scientific, AM9515). The sample was mixed by inversion and stored at -80°C overnight. The RNA was spun down at 14,000 g at 4°C for 20 min. The pellet was washed with 75% ethanol, vortexed briefly and pelleted at 14,000 g at 4°C for 5 min. Subsequently, the pellet was air-dried and resuspended in RNase-free water. The purified RNA was quality controlled and used for RNA-seq library preparation. RNA-sequencing for ribosome fractions. RNA sequencing libraries were generated using Smart-seq3 V3 protocol suitable for Illumina sequencing from low input total RNA. (Hagemann-Jensen et al., 2020) https://www.protocols.io/view/smart-seq3-protocol-bcq4ivyw. The method uses a template switch oligo which has UMIs and a binding site for Nextera read 1 side. Therefore the method creates UMI labelled, stranded 5' fragments and unstranded fragments all over the transcript body. The size of libraries was assessed using NGS HS analysis kit and a fragment analyzer system (Agilent). Library concentrations were quantified with KAPA Kit (Roche) and 50-bp paired-read sequencing was performed using the Illumina NovaSeq S1 platform. Analysis of RNA-seq of ribosome fractions. Smart-seq3 read analysis was performed using zUMI v2.9.7 (Parekh1 et al., 2018), providing the expected barcodes file, using STAR 2.7.7a with additional STAR parameters "-limitOutSJcollapsed 50000000 -limitIObufferSize 1500000000 -limitSjdbInsertNsj 2000000 -clip3pAdapterSeq CTGTCTCTTATACACATCT" and Homo sapiens Ensembl GRCh38 release 94 as a reference. zUMI generated inex UMI counts were used for downstream analyses. Differential gene association analysis between groups was performed using DESeq2 wald tests on the umi count tables after minimal pre-filtering where only protein-coding genes with at least 2 reads in multiple samples of a condition were retained. A) Results of genotyping PCR for H9 WT hESCs, dual reporter H9 hESC clones and negative control samples to test integration of the P2A-EGFP fragment in the SOX2 genomic locus. Integration of EGFP leads to the 2.5kb band. Unedited SOX2 genomic locus is marked by the 1.5kb band. B) Results of genotyping PCRs for H9 WT hESCs, dual reporter H9 hESC clones and negative control samples to test integration of the hSYN1:dTomato-WPRE-polyA transgene into the AAVS1 locus. PCRs (i) and (ii) test the presence of the transgene. For PCR (iii) a 2kb band indicates an unedited AAVS1 locus and thus reports the zygosity of AAVS1 locus after transgene insertion. C) Schematic representation of the organoid culture protocol used in this study. D) Schematic representation of sparse labeling in organoid culture using 95% unlabeled control H9 hESCs and 5% dual reporter hESCs for embryoid body formation. E,F) Confocal scan of 40 day old sparsely labeled organoid sections immunostained with anti-SOX2 (D), anti-NeuN (E), anti-EGFP and anti-dTomato antibodies. The image shows a typical ventricular zone and surrounding neuronal zone in the organoid tissue. Scale bar = 100 µm. (dTomato+, red) at different stages of organoid development before z-score normalization. C) Optimal number of clusters were estimated for z-score normalized data using the 'average silhouette width', 'total within sum of square' and 'gap statistics' methods. Six to twelve clusters were manually evaluated with regards to their biologically meaningfulness and a subjective decision made to separate the data into nine modules. D, E) Z-score normalized RNA and protein abundance in progenitors (EGFP+, green) and neurons (dTomato+, red) at different stages of organoid development for genes for which the first regression fit failed (D) and 500 randomly sampled genes that were not clustered into any module (E). For each dataset, each dot displays the relative abundance of one gene and a trendline was fit through all data points. F) Enrichment analysis for gene ontology (GO) for genes with no regression fit and unclustered genes. Shown are six selected GO terms and the number of genes (x-axis) belonging to the respective GO term. Bar fill colors show binned adjusted p-values. Image shows a typical ventricular zone (VZ)-like structure in the brain organoid with a zoomed-in image of the boxed area on the right. Dotted line marks the apical side of the VZ. Scale bar = 50 µm. C) Schematic representation of cell outlines of mosaic reporter cells marked as regions of interest (ROI) for intensity measurements. D, E) Average intensities of RPL5 and RPL11 transcripts (D) and protein

(E) measured per cell. Each dot represents a cell. Black line marks the median. P-value of Mann-Whitney test is indicated. F) Expression score of 5'TOP genes in distinct cell clusters from scRNA-seq data of fetal tissues of gestation week 6-10 (Eze et al., 2021). G) Schematic representation and analysis of polysome profiling of 2D grown progenitors and neurons performed by (Blair et al., 2017). H) Plot represents RNA abundance of genes across different polysome fractions from progenitors and neurons. All 5'TOP genes and genes from modules 1 and 9 are plotted. Each dot represents a gene. Data from (Blair et al., 2017). P values of Wilcoxon test are shown. A) Schematic representation of the dox-inducible reporter assay. hPSCs carrying 5'TOP (blue) and non-5'TOP (orange) sequences in 5'UTR of tagBFP were used to grow brain organoids. Doxycycline treated 40 days old organoids were dissociated and cells stained for SOX2 and TUJ1 to measure tag-BFP levels in progenitors and neurons, respectively. B) Representative image of flow cytometry analysis of tagBFP expression in untreated control organoids and 40 days old organoids after 72 h doxycycline treatment. Cells carrying 5'TOP (blue) and non-5'TOP (orange) sequences in 5'UTR of tagBFP are depicted. Percentage of single cells expressing tagBFP according to the gating parameters is indicated. C) Flow cytometry analysis of cells from 40 days old organoids immunostained with anti-SOX2-PE and anti-TUJ1-A488 antibodies. Panel includes isotype control antibody staining controls used to evaluate the staining and to define gating parameters. Cells stained with SOX2 (green box), TUJ1 (red box) were defined as shown in the figure. D,E) Cumulative distribution of reporter tagBFP levels in (D) progenitors (SOX2) and (E) neurons (TUJ1) dissociated from doxycyclinetreated 40 days old organoids. Each graph represents a separate experiment with a 5'TOP (blue) and non-5'TOP (orange) reporter pair. Statistical significance was calculated using the non-parametric Kolmogorov-Smirnov test. A) Confocal scan of ventricular zone (VZ) in a control and sodium arsenite-treated organoid stained with anti-G3BP1 antibody and DAPI. Zoomed-in image of the inlay shows G3BP1 granules in VZ and neuronal zones. Scale bar = 50 µm. B) Quantification of G3BP1 signal intensity in the granules observed in the control and sodium arsenite-treated organoids. P-value statistic of t test. Each dot represents a granule. (Number of organoids analyzed, control: n=3; NaAs: n=4; Number of granules analyzed: control: n=31; NaAs: n=51) C) Quantification of average number of G3BP1 granules per cell in VZ and neuronal zone of 40 days old control organoids. P-value statistic of t test. Each dot represents an area from an organoid. Quantification performed in 3 organoids with total field of views: n=8 and number of cells counted: NPCs: n=829; Neurons: n=804. D) Results of genotyping PCR to check insertion of the G3BP1-mScarlet transgene in the G3BP1 locus. Samples include G3BP1 reporter hESCs, control H9 hEScs and negative control. E) Confocal scan of VZ in a 40 day old G3BP1-mScarlet organoid stained with anti-G3BP1 antibody and DAPI. Zoomed-in images of the inlay show granules in VZ marked by mScarlet (grey) and G3BP1 (green). Scale bars = 20 µm (i), 5 µm (ii). F) Quantification of percentage of total G3BP1 granules observed in a field that are located in the VZ region. Schematic on the left shows G3BP1 granules in the tissue and quantification strategy. G) Quantification of RPL5 and RPL11 RNA-FISH signal intensities in the nucleus, G3BP1-positive granules and the cytosol of progenitors in the VZ of sodium arsenite treated organoids. The p-values of Mann-Whitney tests are shown. Each dot represents a cell (Number of granules analyzed: RPL5: SA: n-51; RPL11 SA: n=111). AA) Confocal scan of a 40 day old organoid stained with anti-phospho-4EBP1 (cyan) and anti-SOX2 (red) antibodies. Zoomed-in image of the inlay shows a ventricular zone (VZ). Scale bar = 100 µm. B) Confocal scan of a 40 day old organoid stained with anti-phospho-S6 (cyan) and anti-SOX2 (red) antibodies. Zoomed-in image of the inlay shows a VZ. Scale bar = 100 µm. C) Schematic representation of the mTOR pathway. D) Schematic representation of genome editing of TSC2 genomic locus by CRISPR-Cas9 approach. A guide targeting Exon5 was used to generate TSC2-/-hPSCs. E) Table summarizing TSC2 control and knockout hPSC clones used in this study. F) Confocal scan of 40 days old TSC2+/+ and TSC2-/-organoid sections stained with anti-TSC2 antibody and DAPI. Scale bar = 100 µm. G) Confocal scan of 40 days old TSC2+/+ and TSC2-/-organoid sections stained with anti-pS6 and antibody. Scale bar =100 µm. A) Representative traces of polysome profiling of TSC2+/+ and TSC2-/-organoids. B) Hierarchical clustered heat map of differentially associated genes (DAGs) with monosome fractions of TSC2+/+ and TSC2-/-organoids (i). Top 10 most significant cellular component GO terms for TSC2-/-enriched DAGs (ii). There was no significant GO term observed for TSC2+/+ enriched DAGs. C) Hierarchical clustered heat map of genes differentially associated with low-polysome fractions of TSC2+/+ and TSC2-/-organoids (i). Top 10 most significant cellular component GO terms for TSC2-/-enriched DAGs and TSC2+/+ enriched DAGs (ii). A) RNA-FISH for the 5'TOP transcripts RPL5 and RPL11, in 40 days old TSC2+/+ and TSC2-/-organoids. Images show a typical ventricular zone (VZ)-like structure in the brain organoid. Scale bar = 20 µm. B) Quantification of z-score normalized fluorescent intensity of RPL5 and RPL11 FISH signal in the VZs of TSC2+/+ and TSC2-/-organoids. Error bars mark standard deviation. Pvalues of unpaired t test are shown. Each dot represents a VZ. Data from 3 batches of organoid differentiation for each clone. C) Immunostaining for the 5'TOP proteins RPL5 and RPL11, in 40 days old TSC2+/+ and TSC2-/-organoids. Images show a typical VZ-like structure in the brain organoid. Scale bar = 20 µm. D) Quantification of z-score normalized fluorescent intensity of RPL5 and RPL11 proteins in the VZs of TSC2+/+ and TSC2-/-organoids. Error bars mark standard deviation. P-values of unpaired t test are shown. Each dot represents a VZ. Data from 3 batches of organoid differentiation for each clone. A) Dot plot showing overrepresentation analysis of genes differentially associated with ribosome fractions of TSC2-/-and TSC2+/+ organoids across the 9 gene modules. Significance threshold: Adjusted p-value <0.05. Gene lists refer to DAGs from clusters from Figure 5D. B) Dot plot showing underrepresentation analysis of genes differentially associated with ribosome fractions of TSC2-/-and TSC2+/+ organoids across the 9 gene modules. Significance threshold: Adjusted p-value <0.05. Gene lists refer to DAGs from clusters from Figure 5D. C) Confocal scan of cryosections of 40 days old TSC2+/+ and TSC2-/-dual reporter organoids showing EGFP and dTomato distribution. Scale bar = 100 µm. D) Schematic representation of the flow cytometry analysis of dual reporter TSC2+/+ and TSC2-/-organoids. Plots show the percentage of single cells that are EGFP+ (green), dTomato+ (magenta) and the ratio of dTomato:EGFP cells (grey). Horizontal line marks the median values. P-values of Mann Whitney tests are shown. Samples from 2 batches of organoid differentiation with 2 clones per condition. E) Confocal scan of cryosections of 40 days old TSC2+/+ and TSC2-/dual reporter organoids immunostained for dTomato and S100B. Scale bar = 100 µm. Localization of the Epileptogenic Foci in Tuberous Sclerosis Complex: A Pediatric Case Report Tuberous sclerosis complex (TSC) is a rare disorder of tissue growth and differentiation, characterized by benign hamartomas in the brain and other organs. Up to 90% of TSC patients develop epilepsy and 50% become medically intractable requiring resective surgery. The surgical outcome of TSC patients depends on the accurate identification of the epileptogenic zone consisting of tubers and the surrounding epileptogenic tissue. There is conflicting evidence whether the epileptogenic zone is in the tuber itself or in abnormally developed surrounding cortex. Here, we report the localization of the epileptiform activity among the many cortical tubers in a 4-year-old patient with TSC-related refractory epilepsy undergoing magnetoencephalography (MEG), electroencephalography (EEG), and diffusion tensor imaging (DTI). For MEG, we used a prototype system that offers higher spatial resolution and sensitivity compared to the conventional adult systems. The generators of interictal activity were localized using both EEG and MEG with equivalent current dipole (ECD) and minimum norm estimation (MNE) methods according to the current clinical standards. For DTI, we calculated four diffusion scalar parameters for the fibers passing through four ROIs defined: (i) at a large cortical tuber identified at the right quadrant, (ii) at the normal appearing tissue contralateral to the tuber, (iii) at the cluster formed by ECDs fitted at the peak of interictal spikes, and (iv) at the normal appearing tissue contralateral to the cluster. ECDs were consistently clustered at the vicinity of the large calcified cortical tuber. MNE and ECDs indicated epileptiform activity in the same areas. DTI analysis showed differences between the scalar values of the tracks passing through the tuber and the ECD cluster. In this illustrative case, we provide evidence from different neuroimaging modalities, which support the view that epileptiform activity may derive from abnormally developed tissue surrounding the tuber rather than the tuber itself. INTRODUCTION Tuberous sclerosis complex (TSC) is a multi-system, autosomal dominant disorder (Crino et al., 2006) with a prevalence of 7-12/100,000 (O'Callaghan et al., 1998). TSC children present severe neurological symptoms that are mainly related to the cortical tubers, which occur in 80% of these patients (Crino et al., 2006). Approximately 90% of TSC children develop epilepsy; nearly twothirds of patients have seizure onset within the first year of their life (Curatolo et al., 2002). In these patients, infantile spasms are the most common type of seizures (Chiron et al., 1997) with an onset of as early as 4 months of age. Partial seizures are often seen, whereas generalized seizures are relatively rare (Chiron et al., 1997;Kotagal, 2001). Approximately 50% of the TSC-related epilepsy cases are refractory to pharmacological therapy (Jansen et al., 2006). Resective epileptic surgery is thus considered for controlling the seizures. Although surgical outcome differs in these patients, many studies report a positive surgical outcome in patients who have undergone surgical resection of the tubers (Bebin et al., 1993;Avellino et al., 1997;Karenfort et al., 2002;Romanelli et al., 2004). A recent systematic review reported that with resective surgery 57% of children achieve seizure freedom and another 18% experience a reduction (>90%) in seizure frequency at 1 year follow-up (Jansen et al., 2007). The success of resective surgery in TSC patients depends on the accurate identification of the entire epileptogenic tissue (Tran et al., 1997). Multiple potentially epileptogenic tubers are usually present in TSC children and the task is to differentiate those associated with epileptiform activity from the "silent" ones. Another task is to find out whether epileptogenicity derives from Frontiers in Human Neuroscience www.frontiersin.org the tubers themselves or the abnormally developed surrounding cortex. Epileptogenic tubers may also occur in eloquent cortex, potentially rendering surgical treatment more difficult. There is conflicting evidence so far regarding these issues. Surgical studies report that the resection of large, calcified tubers is associated with a marked improvement in the seizure profiles of TSC patients (Guerreiro et al., 1998;Koh et al., 2000;Lachhwani et al., 2005). A surgical series using intraoperative electrocorticography (ECoG) indicated that the epileptiform discharges were localized within the cortical tubers (Guerreiro et al., 1998). Other ECoG studies found that the electrographic tubers were silent, and it was the surrounding neural tissue that was epileptogenic (Major et al., 2009). Currently, the epileptogenic zone is conventionally identified using a combination of invasive and non-invasive imaging modalities. Invasive intracranial recordings serve as gold standard for the localization of the epileptogenic zone; however they are costly, can be difficult due to the cooperation of the child, carry some risk for infection and bleeding (Onal et al., 2003), and neurological damage (Zaccariotti et al., 1999). Intracranial recordings explore limited areas and hence, the success of such studies depends on the hypothesis formed by the results of the non-invasive tests. Scalp ictal EEG can be non-localizing in a significant proportion of children. Magnetoencephalography is considered as one of the most promising techniques that can help in the non-invasive localization of epileptiform activity in the TSC-related epilepsy population. It provides an excellent localization accuracy of few millimeters for superficial sources (Leahy et al., 1998;Papadelis et al., 2009). Two recent studies presented evidence that MEG is superior compared to other neuroimaging techniques in the identification of the epileptogenic tissue in TSC patients. Wu et al. (2006) showed that MEG was better, in terms of sensitivity, specificity, and accuracy, compared to the ictal video-EEG in the identification of

the epileptogenic zone in TSC patients. Jansen et al. (2006) found that epileptiform activity in patients with TSC and epilepsy detected with MEG was closer to a presumed epileptogenic tuber than the epileptiform activity detected with EEG. DTI is used to detect microstructural changes in cortical development malformations (Widjaja et al., 2010) and to evaluate cortical tubers and normal appearing white matter (NAWM) in TSC patients (Peng et al., 2004;Makki et al., 2007). Previous studies reported increased apparent diffusion coefficient (ADC) and decreased fractional anisotropy (FA) values in the white matter lesions and the perilesional white matter compared to the contralateral NAWM in patients with TSC (Peng et al., 2004;Karadag et al., 2005). TSC patients with epilepsy have also been reported to have white matter abnormalities suggested to be indicative of cortical dysplasia or impaired myelin development due to seizures (Dwyser and Wasterlain, 1982;Jansen et al., 2003;Song et al., 2003;Widjaja et al., 2010), although the radial direction of the white matter abnormalities is more in keeping with dysplasia. Decreased FA (Widjaja et al., 2010) and increased ADC (Jansen et al., 2003) values were found for the cortical tubers within the epileptogenic zone compared to the cortical tubers in the non-epileptogenic zone in TSC patients with epilepsy. In this case report, we examine a 4-year-old patient with TSCrelated epilepsy by using pediatric MEG, EEG, MRI, and DTI. By using MEG and EEG, we aimed to identify whether epileptiform activity in this patient was derived from the tuber itself or its surrounding cortex and quantify the geometric configuration between source localization and tuber margin. For MEG, we used the BabySQUID system that has been especially designed for pediatric use. BabySQUID offers higher spatial resolution (3×) and sensitivity (2×) compared to conventional adult MEG (Okada et al., 2006). By using DTI, we aimed to detect white matter differences between the fibers passing through the calcified tuber, the contralateral NAWM, and the irritative zone as this was indicated by MEG and EEG. CLINICAL PRESENTATION We studied a 4-year-old female patient with refractory epilepsy as a result of TSC. The patient had an uncomplicated perinatal history. Her first seizure (infantile spasms) occurred when she was 4 months old. Cardiac rhabdomyoma, revealed by echocardiography, resulted in the diagnosis of TSC. A TSC1 mutation was found. MRI revealed multiple tubers in the bilateral frontal, parietal, and occipital lobes. A large calcified tuber was identified in the right parieto-occipital lobe. The following years the patient presented frequent gelastic seizures (smiling for~5 s) with a daily frequency at maximum. Previous routine EEG studies at the age of 3 years from this patient reported very frequent right occipital/posterior temporal sharp waves (P8 and O2). Less frequent spikes and sharp waves were identified at the left frontal (F3) as well as right frontotemporal regions. Intermittent slowing in the left frontal and right posterior quadrant was observed. Ambulatory EEG at the age of 3 years detected five electrographic seizures arising from the right occipital region. Long-term monitoring captured six gelastic seizures with apparent left frontal onset. Very frequent interictal spikes were seen in the right posterior quadrant and left anterior quadrant occurring independently. Although the ictal EEG onset was noted in the left frontal region, source analysis of the ictal onset Frontiers in Human Neuroscience www.frontiersin.org revealed a more complex pattern involving both left frontal and right occipito-parietal activity. More specifically, it was noted that there were frequent right posterior temporal interictal spikes that diminish just as frequent low amplitude left frontal spikes were observed, which precede clinical seizure onset. These spikes pause and then left frontal spikes reappear with slightly different spatial and topographic distribution. The source analysis concluded that although the seizures appear to arise from the left frontal source, the right-sided abnormality could serve to facilitate the left frontal seizure source. The alpha-methyl-tryptophan PET scan showed increased uptake over the right parieto-temporo-occipital cortex. It was decided that intracranial EEG was needed to cover both regions. However, patient became seizure free with the introduction of a different antiepileptic medication. Hence, at this time the patient is being followed up closely without a surgical evaluation. RECORDINGS Multichannel MEG and EEG signals were simultaneously recorded from the patient for 10 min during sleep when the patient was 4 years old. MEG recordings were performed using BabySQUID (Tristan Technologies Inc., San Diego, USA). The system is equipped with 74 asymmetric axial first-order gradiometers covering the brain partially. A detailed description of BabySQUID can be found in Okada et al. (2006). The system is accommodated in a single-layer magnetically shielded room (MSR) located at the Radiology Suite of Boston Children's Hospital (BCH) at Waltham, MA, USA. EEG recordings were performed using a 32channel EEG cap specially designed for pediatric use (WaveGuard cap with extended 10-20 layout; ANT b.V., Enschede, Netherlands) with common average reference. Both MEG and EEG data were sampled at 1024 samples per second. Electrocardiography (ECG) data were also recorded simultaneously at the same sampling rate. Clinical data were obtained and research MEG and EEG data were acquired and analyzed after explicit parental consent under a protocol approval by the local institutional review board. Figure 1 shows the setup of the combined MEG and EEG measurements. During the recordings, the patient's head was placed over the sensor array, which fully covered the right parieto-occipital quadrant where the large classified tuber was located. The patient was sleeping during the entire recording and no movement was observed or recorded during the whole experiment. The co-registration was performed at the beginning and at the end of the recording session, which lasted for 10 min. The observed head movement was <2 mm. The co-registration procedure followed in our lab in epilepsy patients is described in Papadelis et al. (2013). MRI ACQUISITION The MRI data were collected at a 3T Siemens Tim Trio MR scanner at BCH when the subject was 4 years old. No sedation or medication was used during the MRI scan. The imaging protocol consisted of structural and diffusion-weighted sequences. The first structural sequence was a T1-weighted highresolution magnetization-prepared rapid-acquisition gradientecho (MPRAGE) acquisition, which used volumetric EPI navigators for real time motion correction [voxel size ( IDENTIFICATION OF CORTICAL TUBERS The multifocal tubers were identified by an experienced pediatric neuroradiologist (PEG) and labeled in FreeView (http://surfer. Frontiers in Human Neuroscience www.frontiersin.org nmr.mgh.harvard.edu/). The tuber closest to the ECDs was then manually segmented in FreeView with margins confirmed by an experienced pediatric neuroradiologist (PEG). The tuber margins were used to determine the distance between the ECDs and the tuber (Section MEG and EEG Data Analysis). MEG AND EEG DATA ANALYSIS Both EEG and MEG data were band-pass filtered between 1 and 70 Hz with a notch filter applied at 60 Hz. Bad MEG and EEG channels were excluded from further analysis. Interictal spikes were marked independently in EEG and MEG data by a pediatric neurologist (SC). Marked interictal spikes were revisited in order to identify similar spatiotemporal profiles in the time traces of EEG and MEG. A prominent morphology of epileptiform activity was identified in the data of each modality (see MEG and EEG Results for details). This resulted in two groups of interictal spikes, one for EEG and one for MEG signals. The MEG and EEG signals of the interictal spikes in each group were averaged including ±100 ms around peak latency. For the averaged interictal spikes, we calculated the signal-to-noise ratio (SNR) on the sensor level as 10 times the logarithm of the ratio of the averaged signal power to the averaged noise power. The averaged signal power is the sum of the squared amplitudes of spike activity divided by the duration of the spike activity and the averaged noise power is the averaged squared amplitude of the signal before the spike started. We considered a signal interval of ±30 ms with respect to the interictal spike peak latency. The noise interval was extracted from −500 to −50 ms with respect to the peak latency. The SNR was calculated for all channels and only the maximum value was reported. A realistic three compartment boundary element method (BEM) model was constructed based on T1-weighted MRI data, for solving the forward problem. The inner skull boundary, the outer skull boundary, and the skin were automatically segmented and triangulated with 5,120 triangles per surface (Haueisen et al., 1997) using the MNE software (http://martinos.org/mne). For source analysis, we co-registered the EEG and MEG sensor configurations with the BEM model. The MNE software defined a head coordinate system based on left pre-auricular point (LPA), Nasion, and right pre-auricular point (RPA) digitization. The head digitization with Fastrack (Polhemus, Colchester, VT, USA) resulted in a digitization set of points on patient's skin in the head coordinate system including EEG electrode positions. The MRI images and the BEM model were transformed into this head coordinate system. The MEG sensor configuration was defined in the coordinate configuration of the Polaris system (Northern Digital Inc., Waterloo, ON, Canada) used for head digitization in the MSR. Predefined points marked on the patient's skin served as common points in Polhemus and Polaris digitization. Based on these common points, the MEG sensor configuration was transformed onto the BEM model in the head coordinate system. Since we do not know a priori how extended are the epileptiform generators, we analyzed the MEG and EEG data by using two source localization methods: one that assumes a focal underlying generator that explains the observed MEG/EEG signal (i.e., ECD) and one that presumes extended sources [i.e., minimum norm estimates (MNE) (Hämäläinen and Ilmoniemi, 1994)]. MNE software was used for analyzing the MEG and EEG data. The source localization findings of the two methods were finally compared to each other. Our goal was to quantify the distance between the epileptiform source activity and the margin of a distinct calcified tuber. The whole brain volume provided valid source space for the ECD localization and the MNE reconstruction based on the white-gray-matter boundary. The cortical tuber was a valid source space for the ECD analysis, but not for the MNE analysis. Within the tuber volume, it was not feasible to segment a cortical surface. Therefore, the white-gray-matter boundary passed the calcified tuber volume. ECDs were estimated for each interictal spike at the peak latency of each spike, and for the averaged interictal spike from −15 to 0 ms from the peak latency of the averaged spike in increments of 5 ms. This time-interval represented the upslope of the spike from approximately 50% of the peak amplitude to the peak amplitude. For each ECD localized to the averaged interictal spike, we computed the confidence volume using Curry 7 (Compumedics Neuroscan, Charlotte, NC, USA). For the two dipole-clusters formed by ECDs at the individual interictal EEG and MEG spikes, we performed a principal component analysis (PCA) to estimate a representative ellipsoid for the cluster (Ziolkowski et al., 2002). The eigenvalues of the covariance matrix provided the semi axis of the ellipsoid. The ellipsoid was located in the center of the dipole cluster. MNE solutions at peak time of the averaged interictal spike were also computed with restriction to the boundary between gray and white matter using the MNE software with default parameters, weighted with dynamic statistical parametric mapping (dSPM) (Dale et al., 2000) and thresholded for display. We calculated the distance from each ECD localization to its closest point on the tuber margin. In order to test whether or not the distance between the cluster of dipoles, fitted to each interictal spike, and the tuber margin differs significantly for MEG and EEG, we performed a Wilcoxon rank sum test with a level of significance of 5% for the dipole tuber distance of the two clusters. Further, we computed the distance between each ECD and the maximum point of the MNE solution. DTI DATA ANALYSIS Diffusion data were processed with Diffusion Toolkit (http:// trackvis.org/dtk/) using HARDI/Q-Ball imaging model and second order Runge Kutta propagation algorithm with an angle threshold of 45°and no FA threshold. A three-dimensional segmentation of the tuber file was transformed to create a mirror image of the tuber and then the transformed tuber was manually edited to match the gyral topography of the left hemisphere using FreeView but preserving the same ROI volume. The dipoles cluster formed by the interictal spikes ECDs was used to define the third ROI (each ECD

was considered as a cube with 3 voxels edge). ECDs cloud ROI was also transformed to create a mirror image of itself to be used as another ROI of the same volume on the left hemisphere. The original and transformed tuber volume files, the ECDs cloud, and the transformed ECDs cloud volume files, as well as the T1 and T2 FLAIR images were co-registered with the b0 image using 3D Slicer software (http://www.slicer.org). The tuber, transformed tuber, ECDs cloud, and the transformed ECDs cloud volumes were imported in TrackVis software (http://trackvis.org) Frontiers in Human Neuroscience www.frontiersin.org as ROI files. Fiber tractography was performed with TrackVis software to create fiber tracks that pass through the tuber, the transformed tuber (i.e., contralateral NAWM), the ECDs cloud (i.e., subcortical white matter adjacent to the tuber within epileptogenic zone), and the contralateral ECDs cloud ROIs. We avoid creating a fourth ROI using the MNE results, since the MNE analysis was performed on the boundary between the gray and white matters. Mean scalar measures of FA, ADC, axial diffusivity (AD), and radial diffusivity (RD) were derived for each fiber track. Figure 2 shows all the identified tubers in the patient's brain overlaid on the T1 and T2-weighted structural MRI data. The largest tuber was identified in the right parietal-occipital area with mineralization. Very frequent right posterior temporal/occipital sharp waves (mainly at electrodes P8, P4, and CP6) were observed in EEG signal. These sharp waves always presented the same spatiotemporal profile at the sensor level. Sharp waves and polyspikes were observed from left frontal regions in EEG, but their spatiotemporal map did not consistently present the same topography. For this reason and also due to the presence of predominant epileptic activity in the right posterior quadrant including the occurrence of epileptogenic seizures, we focused our MEG and EEG analysis of simultaneously recorded data on the interictal activity at the right posterior temporal/occipital region. Within our region of interest in the right parietal-occipital lobe, we identified a total of 304 interictal spikes of which 135 (44% of total spikes) were detected on EEG and MEG within a time frame of ±15 ms between the peak times. These were considered simultaneous spikes. Eighty-five spikes (28% of total spikes) were identified only on MEG, and 84 (28% of total spikes) were uniquely in EEG traces. This resulted in 220 MEG (72% of total) and 219 EEG (72% of total spikes) spikes. An overview of the number of spikes identified in our recordings is given in Table 1. Figure 3 shows 10 s of filtered data from selected MEG and EEG channels. The colored markers indicate the interictal spikes in each modality providing high signal to noise ratio (SNR) at sensor level. Two groups of interictal spikes were identified independently among the total MEG spikes and the total EEG spikes according to their localization and morphology in the time traces. MEG spikes (blue bars in Figure 3) were selected when they presented a polarity reversal between MEG channels 054 and 057. They had a mean duration of~55 ms. EEG spikes were selected if they had a polarity reversal between EEG channels P8 and O2, and were part of a spike wave complex. Spike duration was~70 ms; the spike wave complex had a mean duration of~250 ms. This selection of spikes resulted in 46 spikes in EEG and 57 spikes in MEG, with 17 of them seen in both modalities. Within the group of interictal MEG spikes, we found the SNR on a level of 11.1 ± 2.5 dB and the averaged MEG spike reached a SNR of 21.6 dB. The group of interictal EEG spikes provided a SNR of 11.7 ± 3.1 dB and the averaged EEG spike reached a SNR of 25.6 dB. Since our MEG system provides partial head coverage, our initial effort was to ensure that the sensor array covered both the minima and maxima of the epileptiform activity. At sensor level, we found lateralized minima on the edge of the sensor array for both MEG and EEG configurations (see Figure 3) with respect to the tuber localization, which is in agreement with Ochi et al. (2011). Figure 4 shows the ECD and MNE localizations for the averaged interictal spikes. Both ECDs and MNE maxima were localized in the immediate vicinity of the calcified tuber. The cluster formed by the ECDs fitted to the 57 interictal MEG spikes was localized on average in a distance of 4 ± 2 mm laterally with respect to the tuber margin (red dipoles in Figure 4A). The equivalent ellipsoid of the dipole cluster circumscribed a volume of 1.9 cm 3 ( Figure 4B). The analysis of the averaged MEG spike from −15 to 0 ms with respect to peak latency provided a stable magnetic field with respect to its orientation and increased in intensity during the considered time-interval ( Figure 3E). The dipoles localized to the averaged MEG spike generated a 4.5 mm trace in inferior direction anterior to the calcified tuber ( Figure 3F). The distance between the ECD localizations and the tuber margin decreased from~5 to~3 mm (3.8 ± 0.8 mm). The dipole localized to −15 ms provided a confidence volume of 2.9 cm 3 and the subsequent dipoles provided confidence volumes of 0.4 ± 0.15 cm 3 . The ECD fitted to the peak of the averaged interictal MEG spikes was localized~3 mm anterior lateral to the calcified tuber margin and provided a confidence volume of 0.4 cm 3 (blue dipole on Figures 4B,C). The ECDs fitted to the averaged interictal MEG spikes moved across time from −15 to 0 ms staying always at the periphery of the tuber's volume with a superior-inferior direction Frontiers in Human Neuroscience www.frontiersin.org by the lateral side of the calcified tuber ( Figure 3F). The dipole fitted to peak latency reached the maximal goodness of fit (GOF) of 90% with an amplitude of 72.9 nAm. The maximum point of the MNE distribution localized~4 mm anterior to the calcified tuber margin (Figures 4B,C). The distance between the center of the ECD cluster and the ECD localization for the averaged interictal MEG spikes was less than 0.5 mm. The distance between the ECD localization of the averaged interictal MEG spike and the maximum point of the MNE localization was~11 mm. The difference between the ECD orientation for the averaged interictal MEG spike and the surface normal for the maximum point of the MNE localization was 17.2°. The distance between the ECD cluster center and the MNE localization was~11 mm, as well. The ECDs fitted to each of the 46 interictal EEG spikes were localized on average at a distance of 5 ± 2 mm superior to the tuber margin (red dipoles in Figure 4D). The equivalent ellipsoid of the dipole cluster circumscribed a volume of 3.8 cm 3 (Figure 4E). The analysis of the averaged EEG spike provided a negative pole over the right parietal-occipital region as main feature, which increased in extend and slightly changed its morphology during upslope of the spike from −15 to 0 ms with respect to peak latency ( Figure 3H). The dipole trace localized to the averaged EEG spike started superior posterior to the calcified tuber in a distance of~12 mm to the tuber margin with a dipole orientation in posterior direction. The subsequent dipoles moved~12 mm anterior and changed orientation to a mainly anterior direction ( Figure 3I). The distance between the dipole localizations and the tuber margin remained with~14 and~12 mm relatively stable (−15 to −5 ms). The dipoles localized to the averaged EEG spikes provided confidence volumes of 11 ± 6 cm 3 . The ECD fitted to the averaged interictal EEG spikes was localized at a distance of~5 mm posterior superior to the calcified tuber margin and provided a confidence volume of 12.6 cm 3 (blue dipole in Figures 4E,F). The ECDs fitted to the averaged interictal EEG spikes moved slightly across time (from −15 to 0 ms) staying always at the periphery of the tuber's volume in an anterior-posterior direction and turned 90°( Figure 3H). The ECD trace stabilized between 0 and +10 ms. The dipole fitted to peak latency reached the maximal GOF of 70% with an amplitude of 93.6 nAm. The maximum point of the MNE distribution localized~9 mm away from the margin outside the volume of the calcified tuber (Figures 4E,F). The distance between Frontiers in Human Neuroscience www.frontiersin.org the center of the ECD cluster and the ECD localization for the averaged interictal EEG spikes was~2 mm. The distance between the ECD localization of the averaged interictal EEG spike and the maximum point of the MNE localization was~14 mm. The difference between the ECD orientation for the averaged interictal MEG spike and the surface normal for the maximum point of the MNE localization was 38.7°. The distance between the ECD cluster center and the maximum point of the MNE localization was 12 mm. The dipole cluster localized by MEG was significantly closer (p < 0.05) to the tuber's margins compared to the one localized by EEG. The distance between the centers of the two ECD clusters for interictal MEG and EEG spikes was~22 mm. Similarly, the ECDs fitted to the averaged interictal MEG and EEG spikes localized~22 mm apart. The maximum points of the MNE localizations for the averaged interictal MEG and EEG spikes localized in a distance of~24 mm to each other. Figure 5 (upper panel) presents the four ROIs and the corresponding fibers passing through them. Figure 5 (lower panel) presents the mean for the scalar values of mean FA, ADC, AD, and RD for fiber tracks passing through the four ROIs. The tracks passing through the ECD cluster had the lowest mean FA and the highest mean RD values. The tracks passing through the tuber showed the highest mean FA and highest mean AD values. The mean FA, ADC, and AD values were higher for the tuber tracks than for the ECD cluster tracks with tracks on the contralateral side showing the same pattern. However, the difference between the mean FA, ADC, and AD values for the tuber tracks and the ECD cluster tracks was more pronounced than the difference between the contralateral ROI tracks. Moreover, the increase in the mean RD value observed for the ECD cluster tracks compared with the tuber tracks on the right hemisphere was not observed between the tracks of the left hemisphere. Finally, mean ADC values were higher all together for the tuber tracks and the ECD cluster tracks than the mean ADC values of the contralateral tracks. DISCUSSION In this illustrative case, we localized predominant epileptiform brain activity in a 4-year-old child with epilepsy due to TSC by using pediatric MEG, EEG, and DTI. The predominant epileptiform activity, when analyzed by simultaneously recorded MEG and EEG, was consistently localized to the tissue surrounding the tuber rather the tuber itself. DTI results further support the notion that epileptogenicity may come from the surrounding tissue of the tuber, since, they indicate different microstructural features for the white matter tracks passing through the region of electrophysiologic abnormality localized in the vicinity of the tuber compared to the other ROIs. Additional studies are needed to determine if this is a consistent finding in large numbers of TSC patients. Previous clinical epilepsy studies indicate that epileptiform activity is sometimes visible only in MEG or in EEG (Baumgartner et al., 2000;Yoshinaga et al., 2002;Rodin et al., 2004;Iwasaki et al., 2005). The two techniques provide different sensitivity profiles depending on the orientation and depth of the underlying source (Goldenholz et al., 2009;Ahlfors et al., 2010;Haueisen et al., 2012). For the achievement of a complete picture of the underlying epileptogenic sources, it has been recommended that these two modalities are used simultaneously in epilepsy studies (Nakasato et al., 1994;Stefan et al., 2003). Here, we used both high-resolution MEG and EEG for two reasons: (i) to capture epileptiform activity visible only from a single modality, and (ii) to obtain a complete picture of the entire brain epileptiform activity, since our MEG system has a partial coverage of the head. In our study, the fraction of the commonly detected interictal spikes in both EEG and MEG was comparable to previous studies [i.e., here 44 vs. 41% in Ramantani et al. (2006) and 51.1% in Park et al. (2004)].

For source localizations to interictal epileptiform activity, it is recommended to perform the analysis during the upslope of the spike since source propagation can already occur during this interval (Alarcon et al., 1994;Lantz et al., 2003;Ray et al., 2007). The ECDs localizations were performed for the averaged interictal MEG and EEG spikes from −15 to 0 ms with respect to the peak latency in intervals of 5 ms. This time-interval represented the upslope of the spike from approximately 50% to the maximum amplitude of the interictal spike. For MEG, the field remained stable with respect to its orientation and increased in intensity during the considered time-interval. The MEG dipole trace remained relatively stable across time during the upslope of the averaged signal. For EEG, the dipole trace presented a slight propagation in anterior direction with an orientation change from posterior to anterior, but the dipoles were always localized outside the calcified tuber in millimeter distances. The dipoles at the peak of the averaged EEG and MEG spikes provided the smallest distance to the tuber margin, and therefore provided the critical configuration for testing our hypothesis. Based on these observations, we performed the localization of single-spikes at the peak time in order to achieve ECDs with relatively high GOF considering the high SNR at this time point. The ECD localizations of interictal MEG and EEG spikes formed ECD clusters similar to those reported by Iida et al. (2005), Kamimura et al. (2006), Sugiyama et al. (2009), andWidjaja et al. (2010). The generators identified by MEG located closer to the tuber's margins compared to those localized by EEG, which is in line with previous source localization findings in TSC-related epilepsy patients (Jansen et al., 2006;Xiao et al., 2006). ECDs and MNE localization results were in agreement; both were localized to the vicinity of the single calcified tuber (see Figure 4). Differences in the localization results of the two source localization methods can be due to the fact that the MNE solutions were constrained to the cortical surface, while ECDs solutions were unconstrained. This hypothesis was supported by the small deviations between the ECD orientations for the averaged interictal spikes and the surface normal for the maximum point of the MNE localizations. The different localization results for MEG and EEG with respect to the calcified tuber may indicate different epileptogenic foci associated to the tuber. These two neuroimaging modalities prefer different source orientation, which can result in the identification and localization of different source aspects. In the present case, the dipole localizations present tangential orientation for interictal MEG spikes and mainly radial orientation for interictal EEG spikes. A direct comparison between the MEG and EEG source localization results cannot be performed, since different number of sensors were used from the two neuroimaging modalities. Indeed, an explanation for the superior localization of the sources for EEG data compared to sources for MEG data could be provided by the fact that our electrode configuration contained very few electrodes below the hairline. In temporal lobe epilepsy, Sperli et al. (2006) indicated a shift of source localizations to dorsal structures when inferior temporal electrodes were not included in the recording setup. Further, the minima of the electric potential and magnetic field maps located on the edge of the sensor arrays and the maxima were incompletely circumscribed. Such an incomplete sampling of Frontiers in Human Neuroscience www.frontiersin.org the electric potential and magnetic field could potentially lead to erroneous source localizations (Michel et al., 2004). However, our findings are in agreement with previous studies indicating that epileptogenic tissue may be predominately localized in the surroundings of cortical tubers (Weiner, 2004;Xiao et al., 2006;Major et al., 2009). The high sensitivity and excellent localization accuracy of our MEG system allowed us to detect and localize accurately the epileptiform activity with respect to the location of the calcified tuber. The localization of single-spikes and averaged spikes were consistent; the two clusters for MEG and EEG were localized in a relatively small region outside tuber's margins. ECD traces across time indicated propagating epileptiform foci localized in the vicinity of a calcified tuber but never passed the tuber's margins going inside the tuber. The view that epileptiform activity is generated in the surrounding tissue of tubers is supported by both clinical as well as animal studies, which indicate that cortical tubers may not be essential for epileptogenicity. A significant improvement in the seizure profiles of TSC patients has been observed after the resection of these single epileptogenic tubers and their surrounding tissue (Guerreiro et al., 1998;Koh et al., 2000;Lachhwani et al., 2005). Kaufmann et al. (2009) reported a tuberless TSC infant with intractable epilepsy, while cortical synaptic hyperexcitability in the absence of cortical tubers was reported by Wang et al. (2007) in animals. Our DTI results support the notion that the white matter tracts associated with the region of electrophysiologic abnormality (ECD cluster) have microstructural features that may be distinct from tracts associated with the tuber and tracts generated from a similar ROI in contralateral normal appearing tissue. Decreased FA due to increased RD noted in the ECD cluster may be a sign of disorganized, demyelinated, dysmyelinated, and/or poorly myelinated axons (Beaulieu and Allen, 1994;Gulani et al., 2001;Song et al., 2002, Nair et al., 2005Song et al., 2005). Similar findings to our ECD cluster were reported in the NAWM surrounding the cortical tubers by Widjaja et al. (2010) who suggested that these abnormal diffusivity values may reflect cortical dysplasia or could be related to ictal and/or interictal activity. These results are also in accordance with animal studies where recurrent seizures are shown to cause impairment in myelin development (Dwyser and Wasterlain, 1982;Song et al., 2003). The potential etiologies of increased ADC and increased FA in the tuber primarily due to increased AD are less clear. Although prior studies have suggested that reduced axonal density or caliber could increase the extra-axonal space allowing faster water molecule movement parallel to axons (Kumar et al., 2008(Kumar et al., , 2010Sun et al., 2008), this explanation is unsatisfying in our case as RD is not increased. Increased ADC values in epileptogenic tubers have been previously reported by Jansen et al. (2003). Here, we provide additional information for tracks passing through the tuber ROI. Prior studies have suggested that increased ADC might be reflective of hypomyelination due to loss of barriers to water motion (Chandra et al., 2006), again the lack of an increase in RD makes this interpretation unsatisfactory. The present study is an illustrative case of the combined application of MEG and DTI in a single TSC pediatric patient. Our findings support the view that epileptogenicity in TSC patients may be derived from abnormally developed cortex surrounding tubers, but are not conclusive. For MEG, we used an innovative system especially designed for pediatric use that offers better localization accuracy and sensitivity compared to the adult conventional systems for a specific ROI. We provide a detailed and extensive analysis of our data making use of four different neuroimaging modalities (i.e., MEG, EEG, MRI, and DTI). Data from neurophysiological methods, such as MEG and EEG, were combined with data from DTI and MRI to examine how the epileptiform activity is coupled with anatomical changes. Although none of the observations made in this case study is strong enough to completely rule out alternative interpretations, the converging evidence of the independently used neuroimaging modalities makes our hypothesis the most parsimonious explanation and sets the stage for a larger study. Genome-Wide Meta-Analysis Identifies Variants in DSCAM and PDLIM3 That Correlate with Efficacy Outcomes in Metastatic Renal Cell Carcinoma Patients Treated with Sunitinib Simple Summary The drug sunitinib is used in metastatic renal cell carcinoma, but patients respond very differently to this drug. To better tailor sunitinib treatment to the individual patient, clinically useful markers are needed. We explored the DNA of patients with metastatic renal cell cancer to detect variations that determine how a patient would respond to sunitinib treatment. We investigated >8 million genetic variants in large patient cohorts from Europe (n = 550) and Japan (n = 204) and found novel genetic variants in PDLIM3 and DSCAM that are related to survival in sunitinib-treated patients. The mechanistic role of these variants in the action of sunitinib needs to be further explored to define its clinical potential. Our findings are a major step towards achieving personalized treatment for patients with metastatic renal cell carcinoma. Abstract Individual response to sunitinib in metastatic renal cell carcinoma (mRCC) patients is highly variable. Earlier, sunitinib outcome was related to single nucleotide polymorphisms (SNPs) in CYP3A5 and ABCB1. Our aim is to provide novel insights into biological mechanisms underlying sunitinib action. We included mRCC patients from the European EuroTARGET consortium (n = 550) and the RIKEN cohort in Japan (n = 204) which were analysed separately and in a meta-analysis of genome-wide association studies (GWAS). SNPs were tested for association with progression-free survival (PFS) and overall survival (OS) using Cox regression. Summary statistics were combined using a fixed effect meta-analysis. SNP rs28520013 in PDLIM3 and the correlated SNPs rs2205096 and rs111356738 both in DSCAM, showed genome-wide significance (p < 5 × 10−8) with PFS and OS in the meta-analysis. The variant T-allele of rs28520013 associated with an inferior PFS of 5.1 months compared to 12.5 months in non-carriers (p = 4.02 × 10−10, HR = 7.26). T-allele carriers of rs28520013 showed an inferior OS of 6.9 months versus 30.2 months in non-carriers (p = 1.62 × 10−8, HR = 5.96). In this GWAS we identified novel genetic variants in PDLIM3 and DSCAM that impact PFS and OS in mRCC patients receiving sunitinib. The underlying link between the identified genes and the molecular mechanisms of sunitinib action needs to be elucidated. Introduction Sunitinib is a multi-targeted tyrosine kinase inhibitor (TKI) and is, next to immunotherapy, an important component in the treatment of patients with metastatic renal cell carcinoma (mRCC) [1][2][3]. Treatment in mRCC patients is started based on the risk group which is determined by clinical and pathological characteristics, but does not yet provide an adequate prediction of treatment outcome. The most common histological subtype is clear cell renal cell carcinoma and occurs in about 75% of cases [4]. And although sunitinib is effective in clear cell mRCC, there is large inter-individual variability in the response to sunitinib regarding both side-effects and efficacy. One-third of patients require a dose reduction and up to 20% show no clinical response to sunitinib [1,2]. Biomarkers that enable prediction of individual response to sunitinib are imperative [5]. In previous studies, the candidate gene approach was used to test single nucleotide polymorphisms (SNPs) in genes related to the pharmacokinetics (PK) and pharmacodynamics of sunitinib. SNPs in CYP1A1, CYP3A5, CYP3A4, NR1I2, NR1I3, ABCB1, ABCG2, VEGF-A, VEGF-R1, VEGFR2, VEGF-R3, FGF-R2, FLT3, eNOS, UGT1A1 and IL8 were significantly associated with one or more of the following endpoints: toxicity, dose reduction, clearance, drug exposure, best objective response, progression-free survival (PFS) or overall survival (OS) [1,2,[5][6][7][8][9][10][11][12][13][14][15][16]. Only genetic polymorphisms in CYP3A5 (rs776746) and ABCB1 (rs1128503, rs2032582, rs1045642) were replicated for association with a twofold increase in the need for dose reductions and with PFS, respectively [17]. Germline genetic variants are, therefore, considered to be major contributors to differences in response to sunitinib. However, sample sizes in most candidate gene studies were limited (up to 350 subjects), replication is often lacking, and inconsistent endpoint definitions were used making it difficult to draw firm conclusions [1,2,[5][6][7][8][9][10][11][12][13][14][15][16]. In earlier genome-wide association studies (GWASs) in other diseases, genetic variants were associated with drug response or adverse events of commonly used drugs such as simvastatin, warfarin, and flucloxacillin, and this affected clinical practice. However, few GWAS data are available for response to anticancer agents [18]. The hypothesis-free approach of a GWAS can provide novel insights into biological mechanisms underlying sunitinib action. Yet, any GWAS in cancer remains challenging because of the need of large sample sizes, and ideally a validation in an independent cohort [18]. We established the "TArgeted therapy in Renal cell cancer: GEnetic and Tumour related biomarkers for response and toxicity" (EuroTARGET) consortium to search for sunitinib biomarkers [21]. Here, we report the results of the largest meta-GWAS for sunitinib with the aim to identify germline genetic variants that associate with sunitinib efficacy in a cohort of mRCC patients as recruited by the EuroTARGET consortium, and a cohort

available from the RIKEN Centre in Japan. Patient Cohorts Within the EuroTARGET project, a collection of blood samples and tissue material of prospectively included patients is available as well as a collection of stored samples of 'historical patients' enrolled in earlier studies [21]. Patients were recruited at participating centres in the Netherlands, the United Kingdom, Iceland, Germany, Romania and Spain. The enrolment of patients in this study occurred from 2005 until 2015 [21,22]. Inclusion criteria for the EuroTARGET GWAS were a histologically confirmed diagnosis of mRCC, the use of sunitinib as a first TKI, the availability of germline DNA, and recorded clinical data on PFS and OS. For the RIKEN cohort, a total of 219 mRCC patients treated with sunitinib were recruited from 15 Japanese medical institutes. PFS and OS data were available for 204 individuals. All patient data were collected at the Centre for Integrative Medical Sciences at the laboratory for pharmacogenomics of the research institution RIKEN, in Tokyo [23]. For this cohort, GWAS summary statistics (effect sizes, standard errors) were used in the current analyses. Patient Selection Patients from the EuroTARGET cohort were considered eligible for our genetic association analysis if genotyping data could be obtained, if the start date of sunitinib and a follow-up date after the start date were available, and if the follow-up after start of sunitinib until study end was more than 24 weeks. To enable informative future analyses, we only focus on the subset of patients for whom outcome could be assessed for at least 6 months (24 weeks). Patients were only included if no TKI or TKI-like anti-tumour treatment was given prior to sunitinib (Table S1). Patients with a clear cell histological subtype as well as those with unknown histology were included, while other histological subtypes were excluded [21]. For the 'historical patients' whole blood, serum or plasma material had been obtained. For each of the prospective patients, two 10 mL blood samples were collected. One of the two samples was stored in a central biobank in the Netherlands, and the other was used for genotyping. Genotyping of retrospective and prospective samples was performed at deCODE Genetics in Reykjavik, Iceland. The EuroTARGET study has been approved by the local research ethics committees of all participating centres and all patients gave their written informed consent. For subjects of the Dutch SUTOX consortium (the 'historical patients' in the EuroTARGET cohort), DNA samples were anonymized by a third party according to the instructions stated in the Codes for Proper Use and Proper Conduct in the Self-Regulatory Codes of Conduct (www.federa.org (accessed on 24 March 2020)) [8,21]. Clinical Data Collection For the analyses, we used the clinical EuroTARGET database version from October 2017. Clinical data from all patients of the EuroTARGET cohort were collected by medical file review and entered in web-based electronic case record forms (eCRFs) (Supplementary File S1a,b). Data included demographic information, baseline clinical characteristics, treatment lines, drug toxicities (Common Terminology Criteria for Adverse Events [CTCAE version 4.0]), tumour response (i.e., complete remission, partial remission, stable disease, or progressive disease), and death. Tumour response was defined according to RECIST version 1.1 and based on patient evaluation by local caregivers as given in the radiology report or medical record (no review of imaging) [21]. Genotyping and Quality Control (QC) EuroTARGET: Genotyping of the EuroTARGET samples was conducted at deCODE genetics (Reykjavik, Iceland). Germline DNA isolated from whole blood with the Chemagic Blood kit (PerkinElmer, Waltham, Massachusetts, United States) was used for SNP genotyping on the Illumina Human OmniExpress BeadChips 12v1-1, 24v1-0, and 24v1-1 (Illumina, San Diego, CA, USA) [24]. Quality control (QC) checks for Eurotarget were performed using software R version 3.2.3 [25] and PLINK software, version 1.07 [26]. Individuals were excluded from analyses based on an individual genotype call rate <97%, gender mismatch between reported and estimated sex based on genotypes of the X-chromosome, or excess of heterozygous genotypes (i.e., inbreeding statistic of F > 0.1). Genetic markers were excluded based on a SNP call rate <97%, minor allele frequency (MAF) <1%, and a p-value ≤ 10 −7 for the Hardy-Weinberg equilibrium (HWE) goodness-of-fit test. After exclusion of individuals and markers in these marginal QCs, the remaining set was used for integrative QC assessment. To evaluate the possibility of population stratification or outliers, multidimensional scaling (MDS) analysis was performed and pairwise identity by state (IBS) statistics was calculated to assess duplicates. Both MDS and IBS were computed using PLINK [26]. Individuals that were identified as outliers were excluded. SNP imputation was performed using shapeit and impute2 with default parameters and the reference panel 1000 genomes build version 3 with total 'cosmopolitan' set of individuals [27][28][29]. RIKEN: QC procedures for RIKEN were performed prior to association analyses and similar to those performed for the EuroTARGET cohort. Individuals were excluded based on an individual genotype call rate ≤98%. However, no exclusion was carried out based on excess of heterozygous genotypes. For population stratification, a principal components analysis (PCA) was executed in which all the 204 subjects were reported to be Japanese. Genetic markers were excluded based on a SNP call rate <97%, a MAF <1%, and a p-value ≤ 10 −7 for HWE. Genetic Association Analysis Cox-regression analyses were performed for PFS and OS correcting for covariates. For the meta-analysis, data of the EuroTARGET cohort were combined with data from the RIKEN cohort [23]. GWAS summary statistics of both cohorts were combined using a fixed effect meta-analysis (R-package metafor). When summary statistics of only one study were available, this result was used in the combined analysis. Eurotarget cohort: For each SNP, genotypes were tested for association with efficacy outcomes using Cox proportional hazard regression analysis. The primary efficacy endpoint was PFS and the secondary outcome was OS. PFS was defined as the time in months between the first day of sunitinib treatment and the date of progressive disease (PD) according to RECIST version 1.0 and 1.1. If no PD was observed, PFS was censored at the time of the last follow-up or death. OS was defined as the time in months between the first day of sunitinib treatment and the date of death or the date at which the patient was last known to be alive. SNPs and additional covariates age at start of sunitinib treatment, gender, country, and Heng prognostic risk group (favourable, intermediate or poor) were included in the cox regression for outcomes PFS and OS using an additive genetic model [30]. Statistical analyses were performed in R statistics version 3.2.3, using base package survival to evaluate Cox regressions. To impute missing values for the Heng variables (i.e., WHO performance status, haemoglobin, neutrophil count, thrombocytes, calcium, and time from diagnosis until start of sunitinib), R-package mice was used with 100 imputations. From these 100 imputations, the most likely Heng score was imputed as a single imputation. Associations with a p-value ≤ 5 × 10 −8 were considered genomewide significant. Associations between p = 5 × 10 −8 and p = 5 × 10 −7 were considered suggestive. Post association QC was performed by visual inspection of p-values in the Quantile-Quantile (QQ) plots and computation of the inflation factor λ. RIKEN cohort: GWAS summary statistics (HRs and standard errors) in the RIKEN cohort were tested for association on PFS and OS. Association analyses were adjusted for age, gender, ECOG performance and RCC histology [23]. Patients and Genetic Data Clinical data were available for 713 sunitinib treated patients in the EuroTARGET cohort. In total, 85 patients were removed from the analysis because their blood sample contained insufficient DNA. The remaining 628 patients entered the QC prior to association analyses ( Figure 1) [21]. The observed individual genotype call rates varied between 99.2 to 100% and met the quality criteria. Based on further quality control steps, 24 patients were excluded from analysis. A sample mix-up rate of 0.2% was observed resulting in the removal of two patients as well as 20 individuals recognized as outliers by the multidimensional scaling (MDS) analysis ( Figure S1a,b). The mean inbreeding coefficient was F = 0.01 (95% CI: −0.02, 0.04), leading to the exclusion of two patients with an inbreeding coefficient of F > 0.1. Pairwise IBS scores are plotted in Figure S2. For efficacy analysis, 54 patients with a non-clear cell subtype of RCC were excluded. This resulted in a total of 550 mRCC patients for whom information on efficacy data and genotypes were available, and these were included in the EuroTARGET cohort analysis (Figure 1). The starting dose of sunitinib was 50 mg/day in most patients (n = 482, 87.6%) in a 4-weeks-on/2-weeks-off schedule. Patient characteristics for both the EuroTARGET cohort and the RIKEN cohort are shown in Table 1. In total, 1210 mRCC patients were included in EuroTARGET, of which 748 were collected prospectively and 462 were available as historical (retrospective) series at the start of EuroTAR-GET [21]. Of the 1210 patients, we selected the 979 patients (81%) who received sunitinib, sorafenib, or pazopanib as first TKI (remainder of patients did for example have no treatment or were treated with an mTOR inhibitor or other TKI). We did not exclude patients who used cytokine therapy before the TKI. To allow for informative analyses, we only focused on the subset of 920 patients for whom outcome could be assessed for at least 6 months (24 weeks). Patients with missing genotypes (N = 85) were excluded for GWAS purposes. 24 patients were excluded after Quality Control (QC) checks. For efficacy analyses, 54 non-clear cell patients were excluded resulting in 550 patients available for the EuroTARGET GWAS [21]. An additional 204 patients from 15 Japanese medical institutes, the RIKEN cohort, was included to test efficacy endpoints in a genome-wide meta-analysis on mRCC patients treated with sunitinib. For the EuroTARGET cohort, median follow-up times of PFS and OS were 7.6 months (range: 3 days-112.5 months) and 17.0 months (range: 9 days-112.5 months), respectively. The quality criteria for statistical analysis were met for 679,324 SNPs based on measured genotypes (Table S2). This number was supplemented using SNP imputation procedures using the 1000 Genomes data as reference panel [29]. A total of 8,148,675 SNPs with a minor allele frequency (MAF) of >2% were analysed for the EuroTARGET cohort. For the RIKEN cohort, median follow-up times of PFS and OS were 10.6 months (range: 0.4-69.7 months) and 12.3 months (range: 0.5-69.7 months), respectively. For the 204 individuals from the RIKEN cohort, QC procedures were performed prior to association analyses. A total of 5,518,066 SNPs with a minor allele frequency (MAF) of >2% were analysed for the RIKEN cohort. Duration of prior drug treatment refers to the number of months that a patient has received an antitumor treatment prior to start with sunitinib that is not a TKI or TKIlike drug as mentioned in Table S1, because these patients have already been excluded from analyses. Genetic Association Analysis For the meta-analysis, results of statistically significant or suggestive association with PFS or OS are presented in Tables 2 and 3, respectively. The GWAS results for the metaanalysis and separate cohorts are visualized in Manhattan plots in Figures 2 and 3. The associated SNPs in the meta-analysis come from imputed SNPs in the EuroTARGET cohort and are not present in the Japanese dataset. The annotation and interpretation of our findings therefore apply only to European populations. In the meta-analysis, SNP rs28520013 in PDLIM3 (p = 4.02 × 10 −10 , HR = 7.26), and SNPs rs2205096 (p = 5.60 × 10 −9 , HR = 2. in DSCAM was associated with an inferior PFS compared to non-carriers (p = 5.60 × 10 −9 , HR = 2.50) with a median PFS of 1.5 months for the AA genotype, 6.8 months for AT, and 12.6 months for the TT genotype. Also, the variant A-allele of rs111356738 in DSCAM was associated with an inferior PFS versus non-carriers (p = 4.77 × 10 −8 , HR = 2.51) with a median PFS of 1.5 months for the AA genotype, 5.6 months for AT, and 12.7 months for the TT genotype. Significant or suggestive associations with PFS and OS in the RIKEN and EuroTARGET cohort separately are presented in Tables S3 and S4. The QQ plots from the EuroTARGET cohort are shown in Figure S3, with inflation factors of 1.08 and 1.05. Discussion This GWAS identified novel germline DNA variants

in PDLIM3 and DSCAM for PFS and OS in sunitinib treated mRCC patients. The most significant finding with a large effect size on both PFS and OS was found for SNP rs28520013 in PDLIM3. Variants in PDLIM3 and DSCAM may well modify p21-associated kinases (PAKs) activity and influence the PI3K/AKT signalling pathway and thereby modify drug resistance and decrease sunitinib efficacy through NF-κB/IL-6 activation ( Figure S4) [31][32][33][34][35][36][37][38][39]. Yet, this mechanism is hypothetical, based on previous literature findings. The underlying link between the identified novel candidate genes and the molecular mechanisms of sunitinib action remains to be elucidated. This is the largest pharmacogenetic association study for outcome in sunitinib-treated mRCC patients to date. Our current knowledge on the pharmacology of sunitinib and its impact on efficacy is not represented in this GWAS, and thus may involve other mechanisms that contribute to efficacy. The suggestively associated SNP rs595883 with PFS in the metaanalysis was located close to LOXL4, which is in the same lysyl oxidase-like gene family as the earlier reported LOXL2 gene in the GWAS by Motzer et al. [19]. Furthermore, both the identified SNP associations for DSCAM, PDLIM3, and CACNA2D3 in this study as well as the earlier reported SNP associations for IL2RA in the GWAS of Motzer et al. may act via the PI3K/AKT pathway [19]. As opposed to earlier studies, we aimed to confirm our findings in a meta-analysis, which emphasizes robustness. However, rs28520013 in PDLIM3 was analysed only in the EuroTARGET cohort. On the other hand, rs28520013 was associated with both PFS and OS lending support to its importance. The associated SNPs in PDLIM3 and in DSCAM are intronic variants. PDLIM3 encodes the PDLIM3 protein from the LIM family and contains a PDZ and LIM domain. This protein is found in muscle cells and polymorphisms in PDLIM3 were earlier associated with systolic blood pressure and an increased risk of cardiomyopathy [31]. It is assumed that PDLIM proteins negatively regulate NF-κB by inhibition of p65 activation. PDLIM1 deficiency in mice results in augmented production of cytokines [32]. Furthermore, a subfamily of the PDZ-LIM proteins (LIMK1) possibly interacts with receptor tyrosine kinases [33]. The DSCAM gene is located on chromosome 21q22.2-q22.3 in the Down Syndrome Critical Region (DSCR) and encodes the Down Syndrome Cell Adhesion Molecule (DSCAM), an immunoglobulin-superfamily member adhesion molecule. DSCAM regulates the function of p21-associated kinases (PAKs) that belong to the serine/threonine intracellular protein kinases [34][35][36]. Furthermore, expression of CACNA2D3 was reported to enhance chemosensitivity to cisplatin therapy by inducing Ca 2+ -mediated apoptosis and blocking the PI3K/AKT signalling pathways [37]. LOXL4 expression was related to an improved OS in liver cancer patients with wild-type p53 tumours [38]. A theory that fits with our findings is 'phenoconversion', in which an increased cytokine expression could inhibit the metabolism of sunitinib and thereby increase actual drug exposure, resulting in favourable PFS and OS outcomes [39]. Differences in associated loci or SNPs between the two cohorts may be explained by possible ethnicity-specific effects, including differences in MAFs. Also, the number of analysed SNPs and hence genome coverage differed between the two cohorts. When comparing SNPs across the cohorts allowing for some physical distance, more overlap can be identified in an explorative way. While other approaches are possible, such as gene-based analyses, they were outside the scope of this study. The frequency of the variant T-allele of rs28520013 in PDLIM3 in this study was 2.3% while the frequency reported in Asians in the NCBI database is 0.1% [40]. This suggests that an Asian population can hardly contribute to this SNP association. For the variant A-allele of rs2205096 in DSCAM the MAF reported in this study is 6.3%, whereas the reported MAF for Asians in the NCBI database is 36% [40]. SNPs rs2205096 and rs111356738 in DSCAM are moderately to highly correlated (R 2 = 0.7) and other observed SNPs in DSCAM were strongly correlated with rs2205096 (R 2 > 0.8). Hence, SNPs in DSCAM are likely not to act independently on PFS, and sequence analyses and possibly experimental systems would be needed to determine the actual causal variant. A clear distinction between the prognostic or predictive character of the current identified relevant SNPs is not yet possible. An increased PAK function is often seen in tumours and is correlated with angiogenesis, tumour progression and a poor prognosis [36]. Yet, the influence of sunitinib and genetic variants on the PAK/PI3K/AKT pathway are not clear yet. Hypothetically, pharmacogenetic effects in this pathway could lead to drug resistance or a poor response to sunitinib [31][32][33][34][35][36][37][38]. The treatment arsenal for mRCC patients has undergone a very rapid development, with many new treatments being added in recent years. Immune checkpoint inhibitors (ICI) are now an essential element of therapy and there is increasing evidence that combination therapies with two ICIs or a ICI with a TKI are highly effective in mRCC [3]. Although sunitinib is no longer first-line treatment of mRCC, for some patients it still remains the best option or provides an effective second-line treatment for patients who have progressed to first-line ICIs. In addition, sunitinib now serves as a reference standard in studies to compare with new treatment options. It is therefore still important to be able to use sunitinib in the most optimal way. Indeed, while many treatment options for mRCC available, no validated markers have been identified yet to ensure that each individual receives the most appropriate treatment tailored to their individual characteristics. Our future aim therefore remains to use the patient's genetic profile to predict the efficacy or toxicity on treatment with sunitinib, another TKI or an ICI. This GWAS serves as an important step in that direction. Likewise, it would be clinically relevant to investigate whether the variants in PDLIM3 and DSCAM will also be predictive for PFS and OS of other TKIs given in monoor combination therapy (e.g., axitinib and cabozantinib) to discover similar properties within this group of drugs. The knowledge gained from this GWAS and earlier candidate gene studies on sunitinib with regard to study design, data analysis and interpretation, will therefore be useful in follow-up studies on pharmacogenetics in other drugs used in mRCC or as a lead in new drug development. By building further on this research, we ultimately expect to know for each drug which pre-emptive genotyping test should be performed in order to optimally treat each unique mRCC patient. The use of a structured eCRF ensured consistency in data collection by all participating EuroTARGET centres. Some single variables for calculating the Heng score were not present in all patients. Using the multiple imputation procedure to infer uncertain Heng risk group was necessary for only 17% of patients which we consider to be of low impact. The genome inflation factors in this analysis were above 1.05 suggesting slightly inflated test statistics. The moderate sample size prevented us from fitting larger models, for example including several principal components. Another limitation is the relatively small sample size for both studies, which substantially reduced the overlap of imputed SNPs when filtered at the 2% MAF level. Additionally, the small sample size leads to biased effect estimates when studying the strongest associated SNPs. HRs therefore have to be interpreted with care. The findings presented in this study provide new insight into the pharmacogenetics of sunitinib with possible determinants of drug efficacy in mRCC patients ( Figure S4). Conclusions We identified germline DNA variants in PDLIM3 and DSCAM as novel determinants of PFS and OS in sunitinib-treated mRCC patients. The underlying link between the identified novel candidate genes and the molecular mechanisms of sunitinib action needs to be elucidated. Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/cancers14122838/s1, Figure S1: Multi-dimensional scaling (MDS); Figure S2: Pairwise IBS values form the basis for MDS and the IBD/IBS clustering. Figure S3: Quantile-Quantile (QQ) plots for the EuroTARGET cohort. Figure S4: Genetic variants that possibly affect PFS and OS of sunitinib in mRCC. Table S1: List of TKIs or TKI-like antitumor treatments. Table S2: Summary of exclusions of markers for QC steps. Table S3a: GWAS significantly or suggestively associated SNPs with PFS from the EuroTARGET cohort. Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Boards (or Ethics Committees) of all participating institues in the EuroTARGET consortium: A European collaborative project on TArgeted therapy in renal cell cacer-GEnetic-and tumor-related bomarkers for response and toxicity (EuroTARGET). Informed Consent Statement: EuroTARGET is an international, multicenter observational study that started in March 2011. The EuroTARGET study has been approved by the local research ethics committees of all participating centres and all patients gave their written informed consent. A total of 748 patients were recruited prospectively in 62 centers; 36 in The Netherlands, 16 in Spain, 8 in Germany, 1 in Romania, and 1 in the United Kingdom. Patient identification and invitation procedures differed per country, but at all locations, the following were the inclusion criteria: patients gave written informed consent, were at least 18 years of age, and had newly diagnosed metastatic renal-cell carcinoma. Patients were enrolled in the study regardless of RCC subtype and (pre)treatment. For this GWAS, a separate selection of patients was applied (Figure 1). For subjects of the Dutch SUTOX consortium (the 'historical patients' in the EuroTARGET cohort), DNA samples were anonymized by a third party according to the instructions stated in the Codes for Proper Use and Proper Conduct in the Self-Regulatory Codes of Conduct (www.federa.org (accessed on 24 March 2020)). For more details, we refer to van der Zanden et al. [21] in which a description of the Eurotarget cohort is given. All authors are mebers of the EuroTARGET consortium: A European collaborative project on TArgeted therapy in renal cell cacer-GEnetic-and tumor-related bomarkers for response and toxicity (EuroTARGET). Data Availability Statement: All clinical and platform data generated in EuroTARGET are freely available in an anonymized way for the research community. The data can be accessed through the European Genome-phenome Archive (EGA) which is the controlled access repository under the European Bioinformatics Institute (EMBL-EBI). Interested parties will be able to find the EuroTARGET project under the Studies section. Prevalence of Overhydration in Patients on Maintenance Haemodialysis As Determined by Body Composition Monitor and Effects of Attaining Target Dry Weight Introduction: Fluid overload in chronic kidney disease (CKD) is an independent risk factor for all-cause mortality. The volume of ultrafiltrate removed during haemodialysis is usually assessed clinically. Assessment of overhydration by body composition monitor (BCM) using bioimpedance spectroscopy is an objective method. This study was conducted to identify the prevalence of overhydration in CKD patients on maintenance haemodialysis and thereby assess the effects of BCM targeted dry weight attainment. Methods: All patients included in the study were assessed for one month before enrolment for blood pressure, intradialytic events during each dialysis and BP medications. Overhydration was defined as the ratio of overhydration to extracellular water (OH/ECW) > 1.1. Overhydrated patients were brought to BCM targeted dry weight by increasing ultrafiltrate to 500mL/week more than their routine intradialytic weight gain. The effect of attaining BCM target dry weight on blood pressure and intradialytic events were analysed. Results: Out of 110 patients, overhydration was seen in 30 (27.2%); only 20 had clinically evident overhydration. Body composition monitor guided dry weight was achieved in 28 of the 30 patients after a mean duration of 20 weeks. After achieving the target dry weight, there was a significant reduction in intradialytic hypertension events (2.37 vs 1.82 events per session, p-value 0.01). Surprisingly, there was a reduction in episodes of intradialytic hypotension as well, though this did not reach statistical significance. There was a clinically significant reduction in mean systolic and diastolic blood pressures (mean of 5.7mmHg and 2.8mmHg, respectively). Conclusion: The study underlines the importance of BCM-based hydration status assessment and target dry weight attainment in better control of intradialytic events and blood pressure in patients on maintenance haemodialysis. Introduction Achieving euvolemic status in patients on maintenance haemodialysis is extremely important. Inadequate fluid removal during dialysis leads to volume overload and chronic hypertension; excessive fluid removal leads to intradialytic hypotension. Both, increase mortality in patients with chronic kidney disease [1,2]. The dry weight is the weight at which the patient is close to euvolemia. This is the weight that needs to be achieved at the end of

the dialysis session. This has also been defined as the lowest tolerated post-dialysis weight [3]. Several clinical clues are used to identify dry weight such as the absence of oedema and achievement of normal blood pressure without the use of antihypertensive drugs. However, they all have significant limitations. Identifying the dry weight of an individual patient remains a challenge for the clinician. Atrial natriuretic peptide (ANP) and cyclic guanosine monophosphate (cGMP) were considered biomarkers of volume overload [4,5]. Several objective methods have become available. Inferior vena cava diameter [6], bioimpedance spectroscopy (BIS), relative plasma volume (RPW) monitoring, and detection of lung water using chest ultrasound are some of the promising methods [7]. BIS is a simple, inexpensive, and non-invasive method [7][8][9][10]. It is rapid, takes about two minutes and can be used for repeat observations. It has been validated against gold standard techniques such as radionuclide dilution techniques for extracellular fluid (ECF), intracellular fluid (ICF) and total body water (TBW) volume determinations and DEXA scan for estimation of adipose tissue mass and lean tissue mass [7]. There is very limited data on the usage of this technique in the South Indian population. This study was undertaken to identify overhydration in patients on maintenance haemodialysis using BIS and then to bring the overhydrated patients to their body composition monitor (BCM) targeted dry weight. By doing so, we aimed at finding the effect of the bioimpedance technique on the frequency of intradialytic complications and blood pressure control. Materials And Methods This was a prospective observational study done at a tertiary care health centre in South India. The study was approved by the Institutional Ethics Committee (Human Studies), Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry. Subsequent to the approval, adult patients who had been on maintenance haemodialysis for a period of at least three months were enrolled after informed consent. Exclusion criteria were post-renal transplantation status, active malignancy, presence of coronary artery stent or cardiac devices such as implanted cardioverter defibrillators or cardiac pacemakers, presence of metal prostheses, artificial limbs, or extremity amputation, liver failure and pregnancy or lactation. At enrolment baseline data were collected. After enrolment, during a one-month run-in period, blood pressure (BP) changes during dialysis were noted. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were checked during each dialysis session (every 30 minutes during dialysis, and immediately after dialysis), using automated BP apparatus (Fresenius Medical Care, Germany) in the non-fistula arm. Intradialytic hypotension and hypertension were noted. Intradialytic hypotension was defined as one or more of (1) SBP fall of ≥ 20mm Hg, (2) mean arterial pressure (MAP) fall of ≥ 10mmHg or (3) any fall in BP requires intervention (fluid bolus/reducing ultrafiltration/termination of haemodialysis) [11]. Intradialytic hypertension was defined as one or more of (1) SBP rise of ≥ 10mm Hg, (2) MAP rise of ≥15mmHg or more, or (3) any increase in BP that is resistant to fluid removal [12]. At the end of one month period, the study subjects underwent BCM assessment using BIS. A BCM is a portable multifrequency machine (Fresenius medical care) that determines the hydration status of patients. The machine uses electrodes placed in the non-fistula limb (one electrode above and below the wrist and one electrode above and below the ankle separated by at least 3cm). The BCM device determines whole body impedance at 50 frequencies with very high precision. The frequencies used range from 5 kHz to at least 1,000 MHz Since a range of frequencies is used it is called BIS. From the impedance data, the ECW and TBW volumes are determined. Subsequently, using a physiological body composition model that is based on tissue properties, ECF excess or deficiency is calculated. This is called fluid overload (FO) and is expressed in litres. Normal hydration is defined as −1.1 to 1.1 (according to the 10th and 90th percentile of measurements in 1,242 healthy subjects) with values below and above this value defined as under and overhydration respectively [7]. The entire study group was divided into overhydrated and non-overhydrated groups. The overhydrated patients were brought to their BCM target dry weight by slowly increasing the ultrafiltrate at the rate of 500mL/week more than their routine intradialytic weight gain. Patients would be on their regular diet for CKD and reduced water intake plans. Once dry weight, as estimated by the BCM had been attained, they were followed up for one month during which blood pressure, intra-dialytic hypotension and hypertension and the number and dose of antihypertensive drugs were closely monitored. Considering an expected prevalence of overhydration using a BCM to be 60%, with 15% relative precision and 5% level of significance the sample size was calculated as 114. Continuous variables were reported with mean or median and interquartile range (IQR). For categorical variables, the frequency with the percentage was presented. Comparisons of baseline characteristics were carried out using one-way ANOVA, analysis of homogeneity between groups or chi-squared tests for categorical variables. Post dry weight attainment variables were compared with baseline variables using paired t-test. Results were considered significant when p < 0.05. Results The study was conducted from July 2018 to July 2020. We enrolled 110 patients undergoing maintenance haemodialysis. As per the BCM measurement done at the end of the first month, 30 of the 110 patients were found to be overhydrated. The overhydration index ranged from 1.2 to 6.4. Table 1 shows the difference in baseline characteristics between the overhydrated and nonoverhydrated groups. In comparing the two groups, there was a significant difference in intradialytic hypertension events between two groups. Overhydrated group was on dialysis for a longer duration when compared to the non-overhydrated group. There was no significant difference in weight, BCM-adjusted dry weight, or systolic or DBP. The mean duration required for attaining dry weight was 20 weeks. Of the 30 patients who were overhydrated, two patients were later excluded, one underwent a renal transplant and the other did not attain dry weight. Overhydrated patients were followed up and after attainment of dry weight, the effect on different variables was noted. As shown in Table 2, there was a drop in mean SBP and DBP of 5.7mmHg and 2.83mmHg after attaining BCM targeted dry weight, however, the difference in pressures was not statistically significant. There was no significant difference in the number of BP drugs before and after attaining dry weight in the overhydrated group. There was a decrease in the intradialytic hypotension events (a mean of 0.68 events vs 1.18) in the overhydrated group after attaining targeted dry weight, however, this was not statistically significant. There was a decrease in the incidence of intradialytic hypertension in the overhydrated group (a mean of 1.82 events vs 2.37). The decrease in the number of intradialytic hypertension events after attaining BCMtargeted dry weight was statistically significant (p-value -0.017). No Variables Expression Before attaining dry weight After attaining dry weight Difference P-value Discussion This study aimed at finding out the prevalence of overhydration in patients with CKD undergoing maintenance dialysis using a BCM. All patients enrolled in the study were undergoing maintenance haemodialysis for at least three months. This three-month run-in period was considered as those initiated on haemodialysis were more prone to cardiovascular mortality when sudden changes in ultrafiltration were made. All the patients enrolled in the study were dialysed with the volume of ultrafiltrate removal based on the clinically observed dry weight. Twenty out of the 30 patients in the overhydrated group had clinical features of volume overload in the form of either pedal edema, pleural effusion or pulmonary edema. Ten of the 30 patients who were found to have overhydration by a BCM were clinically euvolemic. Hence, ultrafiltrate removal based on clinically calculated dry weight may not be accurate and would result in decreased ultrafiltrate removal resulting in persistent overhydration which is associated with high mortality. The prevalence of overhydration in our study was 27.2%. Wizemann et al. found a prevalence of 21.5% in a study conducted on 269 patients in three centres across Europe. Post HD BCM values were taken to classify patients as overhydrated or non-overhydrated [13]. Onofriescu et al. found the prevalence of overhydration was 26.7% in their study population [2]. Accurate identification of hydration status and fluid management by bioimpedance confers mortality benefits. Onofriescu et al. in a study comparing fluid management using bioimpedance and clinical methods showed a decrease in mortality, relative fluid overload and blood pressure in the bioimpedance group [14]. Vega et al. also showed that any degree of overhydration was associated with higher mortality [15]. Vega et al. found the prevalence of 85% overhydration in patients on haemodialysis with hypertension, however, the prevalence was 23% when overhydration was defined by a cut-off of OH/ECW >15% and 48% when a cut-off of 10%was used [16]. Though BIS was the means used for assessing dry weight, the assessment was done pre-haemodialysis in the study. Ideally, the BCM value calculated post-dialysis was the best method to assess how much excess fluid was present despite apparent adequate removal. In our study, there was a decrease in mean SBP and DBP by 5mmHg and 3mmHg, respectively. Machek et al. found a reduction of SBP by 25 mmHg and a 35% reduction in antihypertensive medication use [17]. The majority of patients in the study by Machek et al. had an extreme fluid overload which could have resulted in a greater decrease in mean blood pressure. Our study included patients with varied overhydration statuses, with the overhydration index ranging from 1.2 to 6.4, many being clinically euvolemic but BCM showed minimal overhydration. This could explain the lower blood pressure reduction in the study. Hur et al. showed a significant decrease in SBP, left atrial volume index and left ventricular internal dimension in the overhydrated group [18]. However, the study did not follow an objective protocol for the clinical estimation and adjustment of dry weight. Further, the number of patients with absolute overhydration as per OH/ECW ratio in BCM was too low to allow a sufficient estimate of the difference in these parameters in the pre-post dry weight adjustment measures. Onofrescu et al. showed a decrease in mean SBP, but the absolute difference was only 6.5mmHg [14]. Hence, in patients with varied hydration status and a significant proportion of patients having overhydration, the absolute reductions achievable in blood pressure values may be low. Intradialytic hypertension is a predictor of cardiovascular risk and a marker of mortality in patients on maintenance haemodialysis [12]. Our study showed a significant decrease in the number of intradialytic hypertension events in the overhydrated group, The postulated mechanisms for intradialytic hypertension are sympathetic reactivity, increased renin-angiotensin activation, endothelial dysfunction, vascular stiffness and increased evidence of left ventricular hypertrophy. These changes are mediated by an increase in intravascular volume due to overhydrated state. Hence, as the intravascular volume was corrected there was a significant decrease in the number of hypertensive events in our study. In this study in spite of ultrafiltrate removal over the interdialytic weight gain, there was a decrease in the number of intradialytic hypotension events, though not clinically significant. The reasons attributable to the decrease in hypotension events could be that once the intravascular volume got corrected, the ultrafiltrate removal rate would have also decreased. Further, as the intravascular volume decreased the preload would decrease resulting in improved cardiac function and thereby a decrease in hypotensive events [19,20]. The study also brought out the difficulties in the attainment of dry weight. Out of 30 patients in the overhydrated group, most patients reached dry weight over a mean duration of 20 weeks rather than the 12 weeks as planned. One of the patients remained overhydrated for a period of 104 weeks. There was a tendency for increased interdialytic weight gain with increased ultrafiltrate removal early in the study; hence, the subsequent volume of ultrafiltrate removed was restricted to prevent intradialytic complications. Limitations Adherence to dietary restrictions regarding salt and fluid intake could not be strictly implemented. Left ventricle function which has a bearing on intradialytic events was not assessed for all the patients in the overhydrated group. Conclusions The study validates the use of BCM in our study population. The study shows a significant decrease in intradialytic hypertension and a non-significant decrease in the mean SBP and DBP, intradialytic hypotension and a decrease in the number of antihypertensive

medications for blood pressure control. The decrease in intradialytic hypertension events was due to change in intravascular volume through BCMadjusted dry weight attainment. Further, large randomized controlled studies are needed to identify the benefits of BCM over clinical methods in target dry weight attainment and their effect on intradialytic complications and control of blood pressure. Additional Information Disclosures Human subjects: Consent was obtained or waived by all participants in this study. Institutional Ethics Committee (Human Studies), JIPMER, Puducherry issued approval JIP/IEC/2018/0154. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work. Toward New Normal: Bali Tourism Goes Extra Mile The tourism industry has undeniably received a hard hit due to the Covid-19 pandemic. Bali is one of Indonesian major tourism destinations, depending on tourism sector for its regional income. The pandemic has paralyzed tourism in Bali. This research aims at exploring how the crisis responses, especially the crisis communication strategy used to manage crisis and regulate its impacts. A qualitative approach was conducted in this research, data collected through interview, observation and literature study. Result showed that crisis history and crisis responsibility and crisis strategy contribute to behavioral intention and reputation toward tourism. Introduction When tourists talk about Indonesia, they mostly talk about Bali. For foreign and even local tourists, spending time in Bali is delightful. Bali is both offering natural and cultural beauty that has been preserved from generation to generation, which then makes the tourism sector the main livelihood of Balinese. Tourism itself relies on high mobility; in short, people should be on the move for enjoying tourism and travel activity. According to UNWTO, international tourist arrivals rose to 1.5 billion in 2019, representing the tenth year of consecutive growth. However, Covid-19 has hit from early 2020 and it is the highly mobile sectors that have been hit hardest. Covid-19 is a new virus that causes respiratory disease that was recorded to have originated in China. The novel Coronavirus is still in the same family as the viruses that cause SARS and MERS which have previously attacked the world. The difference is that the spread of the Covid-19 virus is more massive and faster with the most common transmission from human to human. Up until now, this virus takes a toll of 457,735 positive Covid-19 in Indonesia (https://www.kemkes.go.id/, 13/11/20). In Bali, the update positive cases were recorded at 12,583 with a fairly high cure rate, namely 11,555 people outside the total patients who are still in treatment (624 people) and died (404 people) [1]. While the WHO declared the 2019-nCoV outbreak to be a public health emergency of international concern on January 30, 2020, it currently "does not recommend any travel or trade restriction based on the current information available" [2]. WHO then officially announced COVID-19 outbreak as a pandemic on 11 March 2020. With the increasing rate of Covid-19 spread in Indonesia, the level of urgency for implementing travel bans and restrictions will also increase including from and to Bali until mid-2020. Calculating the impact of pandemic toward tourism in Bali was stated straightforwardly by Cok Darmawan as an official of the Badung Tourism Office, one of the most favourite tourism Regencies in Bali in early September 2020, "The number of domestic tourists on vacation last August experienced an extraordinary decline compared to last year which could reach tens of thousands per day. Last year domestic was 13,000-15,000 per day, until now it was minus 81% at the end of August" [3]. Methods This is qualitative research with an explorative approach. Creswell [12] explained that this approach for exploring and understanding the meaning individuals or groups ascribe to a social or human problem. The qualitative research method is often preferred by researchers in order to obtain a deeper understanding of phenomena that are analyzed in single-case situations, organizations, and institutions [13]. As a research technique, this qualitative research has adopted a case-study approach that is used by qualitative researchers in order to systematically examine individuals, groups, organizations or events to explain the phenomenon being explored [14]. The process of research involves emerging questions and procedures, data typically collected in the participant's setting, data analysis inductively building from particulars to general themes, and the researcher making interpretations of the meaning of the data. Data were collected from observation and in depth-interview with stakeholders in tourism sector that includes Head of Provincial Culture and Tourism Office in Bali (Putu Astawa) and Deputy Head Indonesian Hotels General Manager Association (IHGMA) (I Made Ramia Adnyana). Once all data were gathered, the data analysis technique was conducted through data reduction. The SCCT model is used to help explore the crisis communication strategy undertaken by the Government of Bali to ensure the reputation of the tourism sector remains strong during and after the pandemic. SCCT (Situational Crisis Communication Theory) evolved from a number of studies that examined how a crisis might shape the selection of crisis response strategies and/or examined the effect of crisis response strategies on organizational reputation [4] [15] The idea was to articulate a theorybased system for matching crisis response strategies to the crisis situation to best preserve the organizational reputation [4] SCCT is rooted in attribution theory which seeks to answer the causes of event especially negative and expected ones. Staring at figure 1, there is a vivid connection between crisis history, crisis responsibility and crisis strategies. The ability to read the connection will help identify the thread so the right action can be taken. The crisis history looks at similar situations that have occurred and how they were handled. If the cause of the incident is included in the preventable cluster (when stakeholders consciously put people / members at risk), it means that the reputation threat is severe. In contrast to the crisis indicated that it was a victim cluster such as natural disaster so that stakeholders are also seen as a victim, then the level of threat would be mild. In between those types is called accidental cluster, where a crisis is seen as unintentional, but in fact it can be handled better [15]. Moreover, related to how stakeholders faced the previous crisis, it also provides an overview of behavioral intentions that were formed mainly after the crisis occurred. If stakeholders are deemed to be able to solve the crisis well, the sense of responsibility given to stakeholders such as the government will be high so that the behavioral intentions that are formed will be positive, and vice versa. By identifying the trends in behavioral intentions, stakeholder (government) can determine the response and place the right responsibility in handling the crisis so that the developed strategy will achieve the desired goals. Crisis Situation and History Bali's main source of regional income and the main source of life for its people is from the tourism sector. Last year Bali had 16 million tourists, 10 million domestic and 6 million international. As of January 2020, the situation in Bali is still normal, February began to decline, and in March Ngurah Rai airport was closed. So until July 2020 Bali tourism was paralyzed (interview Made Ramia, 190920). BPS Bali noted that Bali's economic growth rate in the second quarter of 2020 or the April-June 2020 period, fell to 10.98 percent when compared to the same period last year. "Bali's economy is facing a deep decline. This double digit decline is the first to experience this, "said Head of BPS Bali Adi are among a few crisis that hit Bali that greatly impacted its tourism. SCCT model argues that information about past crises is a significant factor that can affect perceptions of a more recent crisis. Many have witnessed how Bali survived and recover in quite short time. With a crisis history indicated by mild to moderate reputation threat, the Government of Bali has the advantage of placing itself in a favorable position related to how they want to describe responsibilities borne by the government. Although nationally, at the beginning of the pandemic, public opinion was divided into categorizing the type of crisis that occurred (whether it was victim, accidental or preventable) , the Balinese government responsively used the media by not discussing much of the causes but then followup steps that would be taken to save the breath of tourism in Bali. This pandemic is a different case. Uncertainty and safety issues are so unpredictable that it requires different approach. Trust is the new currency (interview Made Ramia, 190920). Trust is the customer's expectation that the company can be relied on and trusted in delivering the values it promises (Sirdeshmukh et al, 2002). Trust is related to integrity, reliability, and competence [17], so building tourists' trust, especially those related to health protocols, is a very important issue to address. Pandemic Covid-19 has domino effect in economic and business sector, due to health risk and uncertain condition. According to Reynolds, "When health risks are uncertain, as likely will be the case during a pandemic, people need information about what is known and unknown as well as interim guidance to formulate decisions to help protect their health and the health of others" [6]. Crisis Resposibility Crisis responsibility, the degree to which stakeholders attribute responsibility for a crisis to an organization, is the centerpiece of SCCT. A crisis becomes a greater threat to an organization's reputation as attributions of crisis responsibility intensify. The relationship between attributions about crisis responsibility and reputational threat has been documented across a range of crisis types, including product tampering, human-error accidents, organizational misdeeds, and natural disasters [4], [15]. Crisis management team teams should utilize strategies that indicate a greater acceptance of responsibility for the crisis and simultaneously demonstrate concern for victims. Since the beginning of this pandemic, the provincial government of Bali has been recorded as having collaboration with the Majelis Desa Adat (Traditional Village Assembly) to issue Joint Decree concerning 'Establishment of a Mutual Cooperation Task Force for the Prevention of COVID-19 Based on Traditional Villages". This decision generally provides a legal basis for engagement and responsibilities for 1,493 indigenous/traditional villages during the COVID-19 pandemic period. Traditional villages (Banjar) were assigned to focus on public health activities, social and economic activities, as well as spiritual (niskala) activities (interview Made Ramia, 210920 and Putu Astawa 300920). Prior the success to prevent the outbreak from village level, Traditional villages in Bali are given a big role and legalized by the Governor of Bali Instruction Number 8551 year 2020 concerning Strengthening the Prevention and Handling of COVID-19 in Bali. The Governor's instruction act as ticket for customary/traditional villages (banjar) to play roles in controlling activities such as learning, working, worshiping, traditional ceremonies, tourist and entertainment, and travelling, while still coordinating with local security forces (pecalang) [18]. In addition, Head of Provincial Culture and Tourism office Putu Astawa stated that Covid19 Task Force was also formed which consisted of various components, namely the from Health office, Transportation office, Businessmen and Creative industries. The task of this task force is to regulate / manage / mitigate operations to prevent outbreak. The formation of the task force was legalized through a Governor Regulation. The formation of the Bali Covid-19 Task Force even preceded the National Task Force. So when the government issued a Circular of the Minister of Home Affairs regarding the Establishment of a Regional Covid-19 Task Force, such things had already in place in Bali, and had even been organized into traditional villages (banjar). [19]. Tourist from China filled more than 19% of all tourist visiting Bali, second position after tourist from Australia. In anticipating this crisis, a crisis Management team was formed in every hotel, especially 4 and 5 star hotels, led by General Manager. The team formulated a contingency plan to overcome the crisis. Hotel businessmen all over Bali gathered and

made a mitigation strategy as efforts to reduce risk by (1) efficiency, namely reducing unnecessary posts. (2) efforts to increase revenue by selling vouchers. Pay Now Stay Later, where the voucher can be used until 2021 (interview 21/09/20). However, all tourism sectors realize that the only way to attract tourists back to Bali is by providing a safety and healthy assurance. And this assurance must be prepared massively and standardized (interview Putu Astawa, 30/09/20). Therefore, a protocol must be set up and acknowledged by both tourists and tourism providers. Health Protocol: SIAP & CHSE The Covid-19 pandemic has changed the mindset of tourists. Now tourists will prioritize safety and health issues, after which they will visit tourist destinations [20]. The consideration of reopening tourist destinations must first ensure that these tourist destinations are able to implement strict health protocols. Bali, has initiated a campaign called SIAP (Sehat, Inovatif, Adaptif, Produktif), piloted in Badung region. Badung is the main region for tourism in Bali, with the biggest numbers of hotels and tourismrelated business are in place. SIAP means health, innovative, adaptive and productive, is a movement/campaign to ensure that Bali is getting ready to reopen. Bali is more advance in tourism initiative with SIAP. Government then followed WHO recommendation to economic recovery by implementing CHSE. The Ministry of Tourism and Creative Economy has compiled a CHSE (Cleanliness, Health, Safety and Environmental Sustainability) program as part of new normal in tourism. Quoted from CNN Indonesia [21]. "This protocol will go through several stages, starting from conducting simulations, then socializing and publishing to the public, and finally conducting trials. The implementation of these stages must be closely monitored and disciplined and take into account regional readiness, "said Wishnutama, Minister of Tourism and Creative Economy of the Republic of Indonesia. CHSE is guaranteed standard health protocol for the tourism industry. To implement the CHSE protocol, three regions in Indonesia were used as pilot areas, namely Bali, Yogyakarta and the Riau Islands [22]. Bali is considered ready as one of the pilot areas for implementing the CHSE protocol because Bali is quite successful in preventing the spread of the corona virus. In fact, Bali already initiated SIAP, which more or less similar with CHSE (interview Made Ramia, 21/09/20). The task force and the verification team, consist of stakeholders from Hotel and Restaurant Association, the Health Office, academics and religious organizations, prepare standard services based on the CHSE. The task force activities include disseminating information about health protocols for hotel general managers and tourism sectors, assisting the implementation of the CHSE in the tourism industry and issuing Health Protocol certificates. As of the end of October 2020, the Bali Provincial Government Tourism Office has issued 677 certificates of the new normal health protocol or CHSE (Cleanlines, Healthy, Safety and Environmental Sustainability) protocol for tourism businesses, namely hotels, transportation services and tourist attractions (DTW). The certification process is still on progress and is targeted for completion in December 2020 [23]. Communicating the Crisis Tourism recovery requires confidence and trust for both tourists and tourism providers. Surveys of tourist confidence in the United States show that anxiety remains high, and destination authorities and managers must work to ensure travelers are aware of protocols that are in place for their protection. One reason for this low level of trust is confusion over the security measures. Therefore, communication is the key to increasing demand [24]. Trust is the customer's expectation that the company can be relied on and trusted in delivering the values it promises [25]. Trust is related to integrity, reliability, and competence [17], so building tourists' trust, especially those related to health protocols, is a very important issue to address. President Jokowi stated that the need to disseminate information is urgent, and should be followed by trials and simulations. He also implied that it is also necessary to carry out supervision so that the standard health protocol is implemented in the field (cnnindonesia.com, 2020). Efforts to socialize or disseminate information about the development of the tourism sector need to involve the media because media has an important role in shaping the stigma of society, especially during the current pandemic. The media is a bridge of information between the government and the community, including information on the readiness and preparation of the government in starting a new life adaptation with special protocols for the tourism sector (kemenparekraf.co.id, 2020). Communicating the information about tourism preparedness and readiness in Bali can also be done through digital media. Interview from Putu Astawa confirmed that Bali is leveraging digital media to communicate and increase awareness about Bali tourism recovery. One example of activities carried out in Bali is inviting 4,400 residents who work as civil servants, influencers, and lecturers, to promote tourism with the theme 'We Love Bali'. Participants are required to have more than 2000 followers on social media. They were invited to take a tour in 9 districts / cities for three days and two nights with accommodation facilities to stay 2 nights in hotels, villas or homestays; transportation costs; entrance ticket; consumption to the cost of a rapid test. Each participant is then required to post promotional activities for 3 days 2 nights on their social media accounts in the form of photos, videos, and writings that give a positive impression on tourism in Bali. This activity was carried out in stages during October and November 2020 with a budget of 20 billion from the Ministry of Tourism and Creative Economy and the Bali Provincial Government. Another activity carried out in collaboration between the Ministry of Tourism and Creative Economy and the Provincial Government is to create a series of webinars with themes related to tourism in New Normal. This activity involves campuses / academics such as Udayana University of Bali. Academics, business people, communities, media together with the government formulate, develop and communicate the concept of tourism in the new normal era, so that public awareness / knowledge of this issue increases and is expected to foster confidence in traveling. Going the Extra Mile According to Merriam Webster dictionary, going an extra mile is an idiom means "to do more than one is required to do". In other word, going extra mile could mean providing something beyond expectation. This idiom is quite common in customer service. In tourism context, WTTC (World Travel & Tourism Council) recently used this term to show how tourism sector have done big and selfless effort to help their communities to overcome and combat the Covid-19 pandemic threat. As part of the safety assurance to community to use tourism services in Bali, some standard and verified protocol have been in place. The requirements to get CHSE certificate are quite thorough, resulted in healthy and safety environment to do travelling. The obligatory temperature check, the provision of hand sanitizer, the availability of soap and washtafel, the disinfected spray, the spatial arrangement are standard health protocol that every facilities should have. But going extra mile means providing services and experiences that exceed expectation. Bali is trying to recover, and recover fast. Many initiatives have been done by tourism provider to go extra mile by providing an exceptional level of support. According to Made Ramia, extra protection is given to guests by providing gloves, mask/face shield, energy drink/vitamin that can boost immunity, and hand sanitizer are among few of extra services. When tourists know that they are given special support and tourism providers are genuinely care about creating positive experiences, it can incentivize repeat business and differentiate from more generic programs Conclusion The Covid-19 pandemic is a crisis situation faced by the whole world. Bali as the motor of Indonesian tourism strives to develop the right strategy so that the crisis does not have a fatal and prolong impact on its tourism reputation. The identification of the crisis history that has been handled by Bali showed positive behavioral intention because stakeholders were seen as having the same interests and goals as the public. Past crises do not give negative perception due to the ability of stakeholders to overcome and the cause of crisis did not relate to lack of abilities to provide services. Furthermore, crisis responsibility is shown through the formation of a crisis management team that involves community members as well as other stakeholders to design synergy. A concrete action from this team responsibility is the strategy that focuses on encouraging and emphasizing safety feelings and positive emotions resulting on good behavioral intentions. This will later contribute to expected reputation of tourism in Bali during and post pandemic. The commitment to maintain the reputation of tourism in Bali is also shown by offering unique experiences beyond expectation. Providing extra mile services is expected to give local and international enthusiasm as well as helping Bali face the new normal era and adapt to new habits. The effect of granulocyte colony stimulating factor administration on preterm infant with neutropenia and clinical sepsis: a randomized clinical trial. Background This study was conducted to evaluate the clinical effect of Granulocyte Colony Stimulating Factor (GCSF) on prognosis of neonatal sepsis. Materials and Methods Present study is a double- blinded randomized clinical trial, conducted on 46 preterm infants with neutropenia (Absolute Neutrophil Count (ANC) ≤ 5000 / μL) and clinical sepsis. Infants were randomly allocated into two groups. In the first group (treatment group), infants were treated with GCSF for up to 5 consecutive days with 10 μg/ kg in addition to standard treatment protocols, and in other group, infants received normal saline as the placebo. Each infant was monitored for 14 days. Primary outcome was mortality during 14 days after entering the study, and secondary outcome was the incidence of positive blood culture, weight gain on the fourteenth day, the duration of hospitalization and medication side effects. Results In the treated group, only one death was observed (P-value=1.00). However, no positive results for cultures were reported. Only one case in the treatment group and 3 patients in the control group showed feeding intolerance and needed respiratory support (P-value= 0.608). Length of hospitalization was 25 ± 6 days for the treatment group and 30 ± 7 days for the control group which was statistically significant (P-value=0.042). Conclusion The results of this study demonstrated that GCSF could reduce the hospital stay, but no significant effect was observed on mortality rate, respiratory or feeding status. Materials and Methods Present study is a double-blinded randomized clinical trial, conducted on 46 preterm infants with neutropenia (Absolute Neutrophil Count (ANC) ≤ 5000 / μL) and clinical sepsis. Infants were randomly allocated into two groups. In the first group (treatment group), infants were treated with GCSF for up to 5 consecutive days with 10 μg/ kg in addition to standard treatment protocols, and in other group, infants received normal saline as the placebo. Each infant was monitored for 14 days. Primary outcome was mortality during 14 days after entering the study, and secondary outcome was the incidence of positive blood culture, weight gain on the fourteenth day, the duration of hospitalization and medication side effects. Results In the treated group, only one death was observed (P-value=1.00). However, no positive results for cultures were reported. Only one case in the treatment group and 3 patients in the control group showed feeding intolerance and needed respiratory support (P-value= 0.608). Length of hospitalization was 25 ± 6 days for the treatment group and 30 ± 7 days for the control group which was statistically significant (P-value=0.042). Conclusion The results of this study demonstrated that GCSF could reduce the hospital stay, but no significant effect was observed on mortality rate, respiratory or feeding status. Introduction Neonatal Mortality Rate (NMR) is considered as an indicator of the health status of a population. According to UNICEF reports in 2010, neonatal mortality rate was 14 deaths per each 1,000 births in Iran, while this was 4 per 1,000 in the United States (1). Prematurity (birth before the end of 37th weeks of gestation) is considered as the main cause of 60 to 80% of mortality in infants without congenital anomalies (2). Despite numerous advances in the identification of new antibiotics and improved neonatal intensive care, neonatal sepsis remained as an important cause of mortality and morbidity in infants. Incidence of neonatal sepsis is reported to be1 to 5 cases per each 1,000 live births.

According to reports, case fatality rate of neonatal sepsis in early (during the first 7 days of birth) and late sepsis (from day 7 to day 28) are 5 to 20% and 5%, respectively (3). Prematurity is the most important factor that increases the risk of infection in neonates and finally leads to death. The overall incidence of neonatal sepsis is 3 to 10 times greater in premature infants compared to infants with normal weight (4,5).According to report from the National Institute of Child Health and Human Development (NICHD) Neonatal Research Network, infants with Extremely Low Birth Weight (ELBW)who have experienced a neonatal infection in the neonatal period , compared with infants who have not sepsis attack at follow up, are at higher risk of adverse neurodevelopmental outcome and poor growth (6). Therefore, diagnosis and appropriate treatment of sepsis in this group is essential to reduce mortality rate and improve the quality of their life. Premature infants have an increased susceptibility to infection (7). In the presence of severe neutropenia (ANC ≤ 500/μL), mortality rate followed by sepsis increases by more than 50% (8).The average range of ANC, which is a standard criterion for definition of neutropenia, in neonatal period, is 11,000 cells/µL, but it varies between 6,000 and 26,000cells /µL. Therefore, according to the reported values of absolute neutrophil counts and based on similar studies (4), we described neutropenia as ANC of less than 5,000 cells /µL. In the past two decades, researchers have tried to design methods to improve the immune system of premature infants with neutropenia by immunotherapy (use of subcutaneous GCSF or intravenous immunoglobulin (IVIG)) (9, 10, and 11). Based on previous studies, GCSF administration was associated with increased neutrophil count, and improved bactericidal function of neutrophils (12,13,14). In this study, we tried to evaluate the clinical efficacy of GCSF on prognosis of premature infants with neutropenia. Materials and Methods This study was a double-blind, randomized , clinical trial conducted on preterm infants who were admitted to the Neonatal Intensive Care Unit (NICU) of Shahid Sadoughi Hospital (Yazd-Iran) from October 2012 to March 2013 . Eligible participants were infants with: • gestational age between 30 -37 weeks • chronological age less than 10 days • clinical manifestation of clinical sepsis • neutropenia (ANC ≤ 5000 / μL) Sample size was assessed on 23 infant per group, based on Z formula and confidence interval of 95% with 80% power and type one error of 5%. Clinical sepsis is defined by any one of the followings in the absence of an alternative explanation: either fever (central temperature of > 38˚C) or two or more of the following :poor perfusion; persisting metabolic acidosis (base excess > −8 mmol/l ); increasing ventilation or supplemental oxygen to maintain adequate gas exchange over a minimum of four hours; > 25% reduction in platelet count from baseline or lower limit of normal; persisting glucose imbalance (<40 />180 mg/dl for four hours in spite of corrective measures); abdominal signs (abdominal distension, blood in stool, or bilious aspirates) (15). Infants with major anomalies, total leukocyte count ≥ 20.000/ mm³ (15), intra ventricular hemorrhage (grade ≥ 3), thrombocytopenia (Plt≤150,000/ μL), anemia (Hb≤10g/dL), metabolic acidosis (pH≤7.2) or sever asphyxia (grade 2 or 3) were excluded from study. After approval of study by the research ethics committee and informed written parental consent, infants who had the inclusion criteria, were enrolled in this study. First, laboratory tests of CBC (Diff), ANC, CRP and blood and urine culture were requested, and BD BACTEC Peds Plus/F culture vials (containing resin) were used for blood culture (in the laboratory of Sina). In order to eliminates any possibility of bias, infants were randomly (using table of random numbers) divided into two groups, and GCSF or placebo (normal saline solution) were identified to the investigators by only a code. For infants in case group, 10μg/kg/day of GCSF (Darou Pouyesh Co) was injected subcutaneously in the anterior aspect of the thigh using a 27 French gauge needle for 5 days, while for infants in control group an equivalent amount of normal saline solution was injected as the placebo. All the necessary clinical and para-clinical diagnostic and therapeutic proceedings were under the supervision of physicians. During the study period, infants were monitored for their respiratory status (required oxygen and required assisted ventilation such as nasal Continuous Positive Airway Pressure or mechanical ventilation), feeding tolerance (ml/Kg), abdominal distention and incidence of adverse reactions such as fever, restlessness, thrombocytopenia, and oxygen dependency. To evaluate the prevalence of documented sepsis, on the fourteenth day of study, blood culture and urine or spinal fluid specimens cultures (in necessary cases) of infants in both groups were obtained and also the information of final status of infants including mortality, Necrotizing Entrocolitis (NEC) , feeding tolerance, weight gain and respiratory status was recorded in the questionnaire. Laboratory assistants or other assessors of the results in this study did not know which participants are subject to which procedure. Statistical Analysis The data were analyzed using SPSS statistical software (version 15). Chi-square test or Fisher exact test was used for data analysis of qualitative variables and mean values were compared using independent ttest. Differences were considered significant at Pvalue <0.05. Results Among the 46 infants (Figure 1), 26 (56%) were males, and 20 (44%) were female which is not statistically significant. There were no significant difference between treated and control infants in birth weight, gestational age, apgar score at the first and fifth minute and ANC at the beginning of study (Table I).The mean gestational age in GCSF and control group were 33±2and 32±2 weeks ,respectively. Mean of ANC in GCSF and control group were 2014 and 2595 per micro liter, respectively. In the GCSF group, one death was reported at 7 th day of study, however, no mortality was observed in the control group (P-value = 1.00). None of the blood cultures were positive in both on the fourteenth day. The mean weight gain for GCSF group was 172 gr and 205 gr in the control group on the fourteenth day, which was not statistically significant (P-value = 0.982).The mean of hospital stay in GCSF group was 25 (SD = 6) days and in control group was 29 (SD = 7) days, and this difference was statistically significant (P-value = 0.042) (Table II). No possible drug side effects were observed on daily checks. Only one case with WBC of30800/mm³was reported in GCSF group in the second week of study. The mean ANC in GCSF group was 4,062/μl (SD = 2498) and 3,034/μl (SD = 1150) in control group, which the difference between two groups was not statistically significant (P-value = 0.067).However, the change in ANC on fourteenth day after inclusion in the study, Compared to the first day of enrollment, was significant for both groups (P-value < 0.05). Only one case in treatment group and three cases in control group needed respiratory support which showed feeding intolerance, but the difference was not significant (P-value = 0.608). Discussion Based on the results of the present study, the addition of GCSF to conventional treatment schedule of premature infants with neutropenia and clinical sepsis could shorten the length of hospitalization. Despite advances in neonatal intensive care and advancement in the production of broad-spectrum antibiotics, sepsis is still an important cause of mortality and morbidity in newborns, especially in premature infants, so reducing the mortality of sepsis is a great interest for researchers. According to findings, neutropenia was transient in neonates, and the mean duration of neutropenia without treatment was reported to be about 36 hours (16), but this time might be sufficient for occurrence of sepsis. So, several studies have been conducted to assess the effects of GCSF. The use of GCSF first reported in 1991 to a 654 gram weight premature infant with multiple episodes of sepsis and absolute neutrophil counts of less than1,000 cells/μL. The infant was treated subcutaneously with10 μg/kg per day of GCSF, so the ANC kept between 8,000 to 12,000. Finally, the infant discharged from hospital with good general condition and ANC higher than 2,000 cells /μL (17). Afterward researchers in several studies have evaluated the molecular and experimental effects of GCSF, and confirmed that this factor could improve the quality and quantity of neonatal neutrophils (20, 21, and 22). Subsequently, researchers have design studies to evaluate the clinical effect of GCSF in prognosis or reduction in mortality of premature infants. Although long term antibiotic-therapy, due to some limitations such as maintaining sterile conditions particularly in preterm infants with neutropenia is criticalin developing countries. But, at the present study ,high concentrations of antibiotics in the culture medium is considered as a negative factor for the growth of micro-organisms (23) and so a confounding factor in the assessment of sepsis by blood culture in the present study. Therefore due to the different therapeutic managements of neonatal sepsis and administration of antibiotics in developing countries, it is recommended to assess the results of blood culture inattention to the other clinical and Para-clinical results. In a similar study conducted by Gathwala and colleagues in India, GCSF treatment, could significantly reduce all-cause mortality rate (21). In another study conducted in London, Russel et al studied 28 neonates with birth weight of 500-1500 grams, ANC ≤5000/mm³ and clinical evidence of sepsis, the number of deaths was significantly fewer in the group receiving GCSF (15). In another study in Brazil on44 preterm neonates with sepsis, who were <5 days old and weighing 500-2000 gr, the rate of mortality was not significantly different between the two groups, but the occurrence of a subsequent nosocomial infection was significantly reduced in the treatment group (22). Since the results are conflicting, some researchers have deduced that perhaps this drug is effective in certain groups (Small for Gestational Age infants, BW less than 1500 or GA less than 32 weeks) (24). Therefore, additional well-designed trials are needed to confirm these early results. Conclusion While the effects of GCSF on blood indexes and neutrophils function is of agreement, the results of this study showed that a 5 day period of GCSF therapy in premature infants with neutropenia that present with clinical sepsis is safe and can reduce the length of hospitalization. In other studies it is needed to be designed with different methods to confirm its therapeutic effect. Tumor regression patterns by follow-up duration in patients with nasopharyngeal carcinoma treated with concurrent chemoradiotherapy Abstract The aim of this study was to describe the patterns of tumor regression with respect to follow-up duration after chemoradiotherapy in patients with nasopharyngeal carcinoma. A total of 27 patients with nasopharyngeal carcinoma were included and received definitive concurrent chemoradiotherapy. Patterns of primary tumor regression and development of locoregional recurrences were evaluated by imaging studies every 1 to 2 months. Primary tumors gradually regressed over the period of follow-up. The median time to full regression was 4.9 months (range, 1.5–19.4). In 61.5% of patients, the primary tumor continued to regress for >4 months after completion of chemoradiotherapy. Six patients experienced locoregional recurrence during follow-up, all of which occurred after full regression of the primary tumor. A patient group with delayed regression did not have poorer prognosis than a patient group with early regression. Older age, non-current-smoker status, advanced T stage, and higher daily radiation dose were significantly associated with delayed primary tumor regression. Nasopharyngeal carcinoma continued to regress for >4 months after chemoradiotherapy in a considerable number of patients. We recommend waiting for >4 months for full regression of nasopharyngeal carcinomas after chemoradiotherapy, if signs of persistent or recurrent disease are not evident on follow-up examination. INTRODUCTION Radiotherapy (RT) with or without chemotherapy is the mainstay treatment for patients with nasopharyngeal carcinoma. Accurate evaluation of RT response is important for increasing the efficacy of salvage treatment for persistent or recurrent disease. To accurately evaluate the response to RT in patients with nasopharyngeal carcinoma, deciding appropriate evaluation timing is important. Too early evaluation of the response to RT could result in overtreating some patients whose disease is regressing slowly, whereas too late evaluation of the response could decrease the efficacy of the salvage treatment for potentially persistent disease. Some studies have proposed cut-off times for evaluating RT response in patients with nasopharyngeal carcinoma [1,2]; however, no definite consensus exists on the proper time for evaluation. Determining the appropriate timing

of RT response evaluation requires an understanding of the patterns of tumor regression with respect to follow-up duration after RT in patients with nasopharyngeal carcinoma. Until now, no study has addressed patterns of tumor regression in nasopharyngeal carcinoma after RT or chemo-RT. In this study, we have described the patterns of tumor regression with respect to follow-up duration after chemo-RT in patients with nasopharyngeal carcinoma. MATERIALS AND METHODS Inclusion criteria were histologically proven nasopharyngeal carcinoma, receipt of definitive concurrent chemo-RT with or without induction chemotherapy, Eastern Cooperative Oncology Group performance status ≤2, no previous history of head-and-neck area irradiation, no distant metastasis, follow-up ≥12 months, and available follow-up data. Patients who received adjuvant chemotherapy and patients who received palliative RT were excluded. From January 2007 to March 2015, 51 patients with nasopharyngeal carcinoma received RT or chemo-RT at our institution. Of these patients, 27 met the required criteria and were included. Pretreatment evaluation consisted of complete history and physical examination, nasopharyngeal fiberscopy, complete blood and biochemistry counts, liver and renal function tests, dental evaluations, computed tomography (CT) scans and magnetic resonance imaging (MRI) of the head-and-neck region, and positron emission tomography (PET). Bone scans and CT scans of the chest and/or abdomen were performed only when clinically indicated. For each patient, cancer stage was restaged according the 7th edition of the American Joint Committee on Cancer staging system. Histology was classified according to the World Health Organization system. We retrospectively reviewed hospital records, laboratory records, and imaging studies. The Institutional Review Board of our institution approved this study, and all research was carried out in compliance with the Declaration of Helsinki. All patients received CT-planned RT with either 3D conformal RT (3D-CRT) or intensity-modulated RT (IMRT). The choice between 3D-CRT and IMRT was determined by the physician based on tumor spread, and the patient's preference and general condition. The gross tumor volume (GTV) included the gross extent of the primary tumor and grossly involved cervical lymph nodes visualized on CT, MRI and/or PET. The high-risk clinical target volume (CTV) was defined as the GTV plus a 1-1.5 cm margin to account for subclinical tumor spread. The CTV usually encompassed the entire nasopharyngeal mucosa together with areas suspected of being at risk in the skull base, parapharyngeal spaces, inferior sphenoid sinuses, posterior nasal cavity and posterior maxillary sinuses. The low-risk CTV was defined as the total volume of prophylactically treated neck lymph nodes. The planning target volume (PTV) was created by adding an additional 5 mm margin to the CTV. The prescription dose was determined by the physician, based on tumor stage, the patient's general condition and the probability of RT-induced toxicity. The high-risk PTV was treated with a daily dose of 1.8-2.2 Gy and a total dose of 63-73.5 Gy. The lowrisk PTV was treated with a daily dose of 1.65-2 Gy and a total dose of 45-54 Gy. For standard comparison of various RT dose schedules, biologically equivalent doses were calculated using a linear quadratic model with α/β ratio 10. The 3D-CRT used a Clinac iX (Varian Medical System Inc., Palo Alto, CA, USA) and IMRT used a TomoTherapy (Accuray Inc., Madison, WI, USA) with the simultaneous integrated boost technique. Treatment plans were evaluated from dose-volume histograms and by visually inspecting isodose curves. In general, we considered plans to be acceptable if the PTV was covered by 95% isodose curves, inhomogeneity for the PTV ranged from 95 to 107%, and doses to critical normal organs were limited in their tolerances. All patients received concurrent chemotherapy during the course of the RT as a regimen of intravenous administration of cisplatin (100 mg/m 2 ) every 3 weeks, starting on the day of RT initiation. The decision to use neoadjuvant chemotherapy before concurrent chemo-RT was made by a multidisciplinary team after discussion between radiation, surgical and medical oncologists. The neoadjuvant chemotherapy regimen was a docetaxel/cisplatin/5fluorouracil combination. Primary tumor regression patterns were evaluated by CT and/or MRI with intravenous contrast agent every 1 to 2 months. All images were interpreted by two radiologists with >10 years of experience reviewing CT and MRI of the head and neck regions. Discrepancies in interpretation were resolved by a multidisciplinary team after discussion between the two radiologists. Full regression was defined as the stage at which the enhanced primary tumor lesion did not decrease any more, or disappearance of the enhanced primary tumor lesion. Total regression was defined as disappearance of the enhanced primary tumor lesion. All patients were evaluated until their primary tumor reached full or total regression. The times to full regression and total regression were calculated from the date of RT completion to the date of the imaging study used for final regression status determination. In-field locoregional recurrence was defined as increased size of arterial enhancing lesions or appearance of new lesions within the PTV. Out-field locoregional recurrence was defined as appearance of new lesions outside the PTV in the head-and-neck region. Distant metastasis was defined as evidence of tumor in any other area. The patients who experienced locoregional recurrence or distant metastasis received salvage treatment, such as RT, surgery, or chemotherapy if it was possible. Actuarial rates were estimated using the Kaplan-Meier method, and groups were compared by log-rank test for univariate analysis. Factors that influenced time to full regression were analyzed. Parameters with a P-value of less than 0.50 in a univariate analysis were further assessed in a multivariate analysis, using a Cox proportional hazard model. For all analyses, a P-value < 0.05 was considered statistically significant. All analyses were performed using PASW ver. 18.0 (SPSS Inc., Chicago, IL, USA). Table 1. The most commonly prescribed dose fractionation schedule was a total dose of 70 Gy, with daily dose of 2 Gy; eight patients (29.6%) were treated with this fractionation schedule. Six patients (22.2%) experienced temporary RT interruption because of treatment toxicity. In two patients (7.4%), RT was interrupted for 3 days because of Grade 3 mucositis. RT was interrupted in three patients (11.1%) for 14 days because of Grade 3 hematologic toxicity. One patient experienced RT interruption for 23 days because of Grade 3 mucositis, general weakness, and poor oral intake. The median follow-up period was 59.7 months (range, 12.3-110.0). During the follow-up period, 24 patients remained alive, and the 2-and 5-year overall survival rates were 96.0% and 87.5%, respectively. Four patients experienced distant metastases. The metastatic sites were lung in three patients, and bone and brain in one patient. The 2-and 5-year distant metastasis-free survival rates were both 84.7%. Patient and tumor characteristics are summarized in Primary tumor regression status after chemo-RT is summarized in Fig. 1. In one patient, the total diameter of the viable primary tumor increased on the first follow-up imaging study. The other 26 patients showed primary tumor regression after chemo-RT. The median time to full regression was 4.9 months (range, 1.5-19.4). Except for 4 patients whose primary tumors fully regressed within 2 months, the primary tumors continued to regress for >2 months after treatment in 22 patients (84.6%). Of the 26 patients who showed primary tumor regression, 21 eventually experienced total primary tumor regression during the follow-up period. The median time to total regression of the primary tumor was 4.1 months (range, 1.5-15.2). Of the 21 patients with total primary tumor regression, 16 (80.9%) showed total regression after 2 months of chemo-RT completion (Fig. 2). Of the 26 patients who showed primary tumor regression, 5 did not reach total regression. The followup periods and clinical outcomes at last follow-up of these 5 patients are summarized in Table 2. Six patients experienced locoregional recurrence. The locoregional recurrence-free survival rates were 80.8% for 2 years and 76.8% for 5 years. Development patterns for locoregional recurrences are summarized in Table 3. Except for one patient who experienced primary tumor progression on the first follow-up imaging, all patients had in-field and/or out-field locoregional recurrences after full primary tumor regression. The survival rates according to speed of primary tumor regression were analyzed for the 26 patients with primary tumor regression (Table 4). Compared with a patient group with early primary tumor regression (time to full regression ≤5 months), the patient group with delayed regression (time to full regression >5 months) had lower rates of overall survival, locoregional recurrence-free survival and distant metastasis-free survival. However, the differences between the groups were not significant. We also analyzed factors that influenced the length of time to full regression ( Table 5). In univariate analysis, age, smoking status, and T stage were significantly associated with length of time to full regression. In multivariate analysis, smoking status (hazard ratio, 0.206; 95% confidence interval, 0.102 to 0.725; P = 0.018) and T stage (hazard ratio, 0.086; 95% confidence interval, 0.036 to 0.349; P = 0.020) remained significant factors. In addition, daily RT dose was significantly associated with length of time to full regression in multivariate analysis (hazard ratio, 0.139; 95% confidence interval, 0.039 to 0.786; P = 0.041). Older age, non-current smoker status, advanced T stage, and higher daily RT dose were associated with delayed primary tumor regression in patients with nasopharyngeal carcinoma. DISCUSSION A previous study reported tumor regression patterns according to follow-up duration after RT in patients with nasopharyngeal carcinoma, using repeated nasopharyngeal biopsies [2]. In that study, 803 patients with nasopharyngeal carcinoma underwent serial biopsies after definitive RT. Those patients with positive histology underwent repeated biopsies every 2 weeks for 3 months after completion of RT until biopsy results were negative. In that study, 617 (76.8%) patients showed negative histology in the first biopsy session. The other 186 (23.2%) showed continuous spontaneous histological remission on repeat biopsies after initial positive histology during follow-up. With increasing follow-up time after RT, the histologic remission incidence increased, and 131 patients subsequently attained negative histology; 55 patients had persistent disease at 3 months after RT completion, and salvage treatment was initiated for these patients. However, post-RT multiple biopsies of heavily irradiated tissue may cause trauma and superimposed infection, and may exacerbate post-RT toxicities [3]. Therefore, for analyzing tumor regression patterns after RT in patients with nasopharyngeal carcinoma, additional study is needed using methods that are alternative or complementary to multiple biopsies. Imaging is important for post-treatment evaluation of patients with head-and-neck cancer. Among the various imaging modalities, CT and MRI are the most popular because of their rapid image acquisition and superior contrast resolution [4,5]. Our study used CT and MRI to describe tumor regression patterns with respect to follow-up duration after chemo-RT in patients with nasopharyngeal carcinoma. In our results, primary tumor regression patterns evaluated with CT and/ or MRI seemed to be slower than patterns evaluated with repeated biopsies. In our study, the median time to full regression was 4.9 months, and only 8 patients (30.8%) showed full primary tumor regression within 3 months of chemo-RT completion. The other 18 patients showed full regression after 3 months of chemo-RT completion (Fig. 2). In Kwong et al.'s study [2], 93.2% of patients showed complete histological remission within 3 months after RT. The histologic processes of radiation begin immediately after radiation exposure, although the clinical features evaluated by imaging studies may not become apparent for weeks or months after radiation exposure [6]. The other possible reason for different regression patterns between our study and that of Kwong et al. is the frequency of evaluation for treatment response. In a study by Kwong et al., the histologic remission status was evaluated every 2 weeks. Because we evaluated primary tumor regression patterns every 1 to 2 months, we might have detected full primary tumor regression later than their actual occurrence. In addition, all patients in our study received concurrent chemo-RT, whereas patients in Kwong et al.'s study received RT alone. In our previous study, headand-neck cancer patients treated with concurrent chemo-RT showed delayed primary tumor regression compared with patients treated with RT alone, although these differences were not statistically significant and the exact mechanism remains unclear [7]. Several studies have reported treatment outcomes for patients with nasopharyngeal carcinoma after RT or chemo-RT. However, the cut-off times for treatment response evaluation vary substantially among those studies, ranging from 1 to 4 months [4,5,[8][9][10][11][12][13]. Our study described primary tumor regression patterns according to follow-up duration and calculated time from chemo-RT completion to full primary tumor regression in patients with nasopharyngeal carcinoma. According to our results, although time to

full regression varied between individuals, primary tumors continuously regressed for >4 months after chemo-RT completion in 61.5% of the patient population (Fig. 2). Except for one patient who experienced primary tumor progression on the first follow-up image, all locoregional recurrences developed after full primary tumor regression (Table 3). In addition, survival outcomes for patients with delayed regression were not significantly different from those of patients with early regression (Table 4). Although the exact radiobiological mechanism by which tumor regression speed influences prognosis remains unknown, several previous studies have also reported that delayed tumor regression is not a factor associated with poor prognosis in nasopharyngeal carcinoma [2,8]. Primary tumors must be allowed to fully regress after RT for exact evaluation of treatment response. Because a substantial number of patients showed continuous regression of primary tumors without additional treatment for >4 months after chemo-RT, and all locoregional recurrences developed after full tumor regression, we recommend that frequent biopsies should be carefully implemented early in the course of follow-up. We also recommend waiting for full primary tumor regression for >4 months after chemo-RT completion if signs of persistent or recurrent disease are not evident on clinical and/or imaging follow-up examinations. In our analysis, age, smoking status, T stage, and daily RT dose were significant predictive factors for length of time to full primary tumor regression. Older age (≥50 years), non-current smoker status, advanced T stage (T3-4), and higher daily RT dose were significantly associated with delayed primary tumor regression. We also analyzed predictive factors for delayed primary tumor regression in our previous studies on patients with head-and-neck squamous cell carcinoma and hepatocellular carcinoma [7,14]. Older age and higher daily RT dose were also associated with delayed regression in those studies. Advanced T stage was associated with delayed regression in our previous study on patients with head-andneck squamous cell carcinoma [7]. In our previous study of hepatocellular carcinoma, T stage was not analyzed as a potential predictive factor for delayed regression of primary tumor [14]. However, the results for smoking status are contradictory in our current and previous studies. In this study, non-current-smoker status was significantly associated with delayed primary tumor regression in univariate-and multivariate analyses, whereas in our previous study, current smoker status was associated with delayed primary tumor regression in patients with head-and-neck squamous cell carcinoma (but without statistical significance). At the present time, we are unable to draw conclusions about the predictive factors for tumor regression speed because of so few existing relevant studies. To confirm our results, further studies are warranted. This study had some limitations. First, the retrospective design may have inherent biases. For instance, tumor regression was evaluated at the physician's discretion rather than with timing based on established protocol. Therefore, the time of imaging study acquisition varied among patients. However, we frequently conducted imaging studies on all patients to effectively evaluate regression patterns. Second, the sample size was small, so we may not have detected minor differences in our statistical analysis. Third, because RT fractionation schedules and the implementation of neoadjuvant chemotherapy were decided by physicians rather than by established protocols, patient and tumor characteristics were heterogeneous. However, we believe our results address some unresolved issues regarding the management of nasopharyngeal carcinoma. In conclusion, nasopharyngeal carcinoma continued to regress for >4 months after chemo-RT in a considerable number of patients, and all locoregional recurrences developed after full primary tumor regression. We recommend waiting for >4 months after completion of chemo-RT for full regression of nasopharyngeal carcinoma if signs of persistent or recurrent disease are not evident on follow-up examinations. Chlamydia pneumoniae Clinical Isolate from Gingival Crevicular Fluid: A Potential Atherogenic Strain Chlamydia pneumoniae has been associated to atherosclerotic cardiovascular diseases. The aim of our study was to characterize, for the first time, a C. pneumoniae strain isolated from the gingival crevicular fluid of a patient with chronic periodontitis, described as a risk factor for cardiovascular diseases. C. pneumoniae isolate was characterized and compared to the respiratory AR-39 strain by VD4-ompA genotyping and by investigating the intracellular growth in epithelial and macrophage cell lines and its ability to induce macrophage-derived foam cells. Inflammatory cytokine levels were determined in the gingival crevicular fluid sample. C. pneumoniae isolate showed a 99% similarity with the AR-39 strain in the VD4-ompA gene sequence and shared a comparable growth kinetic in epithelial cells and macrophages, as evidenced by the infectious progeny and by the number of chlamydial genomic copies. C. pneumoniae isolate significantly increased the number of foam cells as compared to uninfected and LDL-treated macrophages (45 vs. 6%, P = 0.0065) and to the AR-39 strain (45 vs. 30%, P = 0.0065). Significantly increased levels of interleukin 1-β (2.1 ± 0.3 pg/μL) and interleukin 6 (0.6 ± 0.08 pg/μL) were found. Our results suggest that C. pneumoniae may harbor inside oral cavity and potentially be atherogenic, even though further studies will be needed to clarify the involvement of C. pneumoniae in chronic periodontitis as a risk factor for cardiovascular diseases. INTRODUCTION Chlamydia pneumoniae (C. pneumoniae) is an intracellular obligate pathogen with a unique developmental cycle consisting of an extracellular infectious form (elementary body, EB) responsible for transmitting the infection and an intracellular replicative form (reticulate body, RB) responsible for growth and multiplication within host cell. A chlamydial persistent form has recently been described as a strategy to escape the host immune response, resulting in a long-term infection. Chlamydial persistent forms are viable but not infectious, as indicated by continuous genomic DNA replication and reduced production of EBs (Schoborg, 2011;Di Pietro et al., 2012). In the last two decades, C. pneumoniae, a common cause of respiratory tract infections, has been widely associated with atherosclerosis, a chronic inflammatory disease of the vascular wall, by seroepidemiological studies, C. pneumoniae DNA detection in the atherosclerotic plaque and by the isolation of viable bacteria from the atheroma (Campbell and Rosenfeld, 2015). C. pneumoniae persistent form is believed to mediate the chronic inflammatory state, as evidenced by an increased production of pro-inflammatory cytokines, contributing to chronic inflammatory diseases such as cardiovascular diseases (Atik et al., 2010;Campbell et al., 2010;Schoborg, 2011). C. pneumoniae is presumed to play a role in the pathogenesis of atherosclerosis for its ability to disseminate systemically from the lungs through peripheral blood mononuclear cells (PBMCs) and to localize in extra-pulmonary sites such as the vascular wall (Moazed et al., 1998;Watson and Alp, 2008). Once inside the vascular tissue, C. pneumoniae has been shown to induce endothelial dysfunction and low density lipoprotein (LDL) oxidation, resulting in the accelerated uptake of cholesterol by macrophages, and the subsequent foam cell formation, considered as the hallmark of early atherosclerotic lesions (Kalayoglu et al., 1999;He et al., 2009). C. pneumoniae has also been demonstrated to contribute to platelet adhesion and aggregation and smooth muscle cell proliferation and migration, all events responsible for progression and rupture of vascular lesion and, hence, for acute cardiovascular events (Di Pietro et al., 2013a;Chatzidimitriou et al., 2014). Several risk factors for atherosclerosis have been identified, including traditional (smoking, hypertension, hyperlipidemia, and diabetes) and non-traditional factors (inflammation, oxidative stress, and infections; Balagopal et al., 2011;Di Pietro et al., 2013a). Recently, chronic periodontitis has also been described as a predisposing factor for atherosclerotic cardiovascular diseases (Kholy et al., 2015). Indeed, it has been reported that patients with chronic periodontitis have a 19% greater risk of atherosclerotic cardiovascular disease than healthy individuals (Kurita-Ochiai and Yamamoto, 2014). Chronic periodontitis, an inflammatory disease of periodontal tissue resulting from oral infections, is characterized by the formation of a periodontal pocket where gingival crevicular fluid drastically increases in response to oral pathogens, resulting in local severe inflammation, and destruction of the periodontium. The major pathogen responsible for periodontitis is Porphyromonas gingivalis, known to cause gingival ulceration, epithelial barrier destruction and, hence, to translocate into the systemic circulation, contributing to endothelial dysfunction, first step of the atherosclerotic process (Kebschull et al., 2010). C. pneumoniae has also been suggested to harbor into the oral cavity, since it has been shown to infect gingival fibroblasts, resident cells of the periodontium, and to increase the inflammatory state underlying chronic periodontitis (Rizzo et al., 2008a,b). Following the destruction of the periodontium, C. pneumoniae may enter the bloodstream, migrate into the vascular wall and induce the production of circulating cytokines and chemokines, contributing directly or indirectly to atherogenesis and, hence, to atherosclerotic cardiovascular diseases. Here we isolated and characterized, for the first time, a C. pneumoniae strain from the gingival crevicular fluid of a patient with chronic periodontitis via specific gene typing. Furthermore, the phenotypical characteristics of C. pneumoniae clinical isolate were also investigated, followed by a comparative analysis to the reference strain AR-39. Gingival Crevicular Fluid and Peripheral Blood Samples Specimens of gingival crevicular fluid and peripheral blood were obtained from a 61-year old man suffering from chronic periodontitis diagnosed in accordance to the criteria proposed by the 1999 International World Workshop for a Classification of Periodontal Disease and Conditions (four sites with probing pocket depth ≥ 6 mm and attachment loss ≥ 4 mm; Armitage, 1999). The patient, referred to George Eastman Dental Hospital for dental or periodontal treatment, received neither professional cleaning nor antibiotic treatment in the last 6 months. He was free from any cardiovascular and respiratory disease; he was an ex-smoker and had hypertension, diabetes and a family history of cardiovascular diseases. A total of 16 gingival crevicular fluid samples, eight from the deepest periodontal pocket and eight from four healthy periodontal sites, were collected by using sterile paper strips (#30PerioPaper). Before sampling, the sites for gingival crevicular fluid collection were gently air-dried, isolated from saliva with cotton rolls and the supra-gingival plaque was removed; then, paper strips were inserted in the sites for 10 s. Four paper strips were pooled in a sterile microcentrifuge tube containing sucrosephosphate-glutamate buffer (SPG, 0.2 mol/L sucrose, 3.8 mmol/L KH 2 PO 4 , 6.7 mmol/L Na 2 HPO 4 , 5.5 mmol/L glutamic acid at pH 7.4) and four paper strips in a sterile microcentrifuge tube containing phosphate buffered saline (PBS) for culture and realtime PCR assays respectively. The ultimate volume of the pooled gingival crevicular fluid samples from the diseased and healthy sites were about 4 and 1.3 µL, respectively. Strips contaminated with blood were discarded and a new site was selected. All gingival crevicular fluid samples were stored at −80 • C until further processing. Peripheral blood specimen (5 mL) was used for the isolation of PBMCs through Ficoll-Hypaque density gradient centrifugation. Written informed consent was obtained from the patient and the study was approved by the International Review Board of "Sapienza" University of Rome. C. pneumoniae DNA Detection by Real-time PCR Genomic DNA was extracted from 200 µL of diluted gingival crevicular fluid sample and from 10 6 PBMCs using the QIAamp DNA Mini Kit (Qiagen) according to the manufacturer's instructions. C. pneumoniae AR-39 infected HEp-2 epithelial cells (ATCC CCL 23) and mock-infected HEp-2 cells were used as positive and negative extraction controls respectively. Detection and quantification of C. pneumoniae DNA were performed by real-time PCR targeting MOMP gene using the Primerdesign ™ genesig R Kit according to the manufacturer's instructions. Each PCR-run contained the PCR-negative control (ultrapure water PCR grade) and positive and negative extraction controls. DNA sample, positive and negative extraction controls were analyzed in triplicate. The sample was considered positive if all of three assay results were positive in the replicate test. C. pneumoniae Detection by Direct Fluorescence Assay The gingival crevicular fluid samples from the diseased and healthy periodontal sites were centrifuged on cytoslide by cytospin for 5 min at 400 rpm (Thermo Scientific Cytospin 4, Thermo Fisher Scientific). Then, the cells were fixed with methanol, and stained with fluorescein isothiocyanate (FITC)-conjugated monoclonal antibody against chlamydial lipopolysaccharide (Pathfinder Chlamydia Culture Confirmation System, Biorad). The presence of C. pneumoniae inclusions was determined by fluorescence microscope (400x magnification). Isolation of C. pneumoniae Clinical isolate was recovered in HEp-2 cells as previously described by Dowell et al. (2001). Briefly, 200 µL of diluted gingival crevicular fluid sample was inoculated on HEp-2 cells grown in 24-well plates in Dulbecco's Modified Eagle's medium high glucose (DMEM, Euroclone, Italy) supplemented with 10% (v/v) fetal calf serum (FCS), 100 µg/mL streptomycin, 250 µg/mL amphotericin B, 1% non-essential amino acids, and 1% sodium pyruvate (complete growth medium). Infected HEp-2 cells were centrifuged for 1 h

at 1250 g at 37 • C, and then incubated at 37 • C and 5% CO 2 for 3 h. Infected cell monolayers were then overlaid with complete growth medium supplemented with 2% FCS and 1 µg/mL cycloheximide, and incubated at 37 • C and 5% CO 2 for 72 h. Then, infected cells were further passaged to fresh HEp2 cell monolayers. In order to evaluate the development of chlamydial inclusions, infected HEp-2 cells, after each growth cycle, were stained with FITC-conjugated monoclonal antibody against chlamydial lipopolysaccharide. C. pneumoniae inclusion forming units (IFUs) were determined by counting all microscope fields using a fluorescence microscope (400x magnification). C. pneumoniae VD4-ompA Genotyping The VD4 region within ompA gene was selected as a target for the typing of C. pneumoniae clinical isolate. A nested PCR assay targeting a 366 bp fragment of the C. pneumoniae ompA gene was performed as previously described by Bodetti et al. (2002). The ompA PCR products were separated by gel electrophoresis and excised from the gel using a Gel Extraction Kit (Qiagen). Sense and anti-sense strands were sequenced with an automated DNA sequencer using the BigDye Terminator v1.1 Cycle sequencing Kit (Applied Biosystems). The sequence obtained was analyzed using BLAST 2 (http://www.ncbi.nlm. nih.gov/blast) and compared to C. pneumoniae VD4 sequences available in the GenBank database including AR-39 and TW-183 strains (GeneBank accession numbers AE017159, AE002161, AE001363, BA000008, AF131889, AY426606, AY426607). Growth Characteristics of C. pneumoniae Clinical Isolate HEp-2 and J774A.1 macrophage cells (ATCC TIB-67) (1 × 10 5 cells/well) were infected with C. pneumoniae clinical isolate or AR-39 strain at a multiplicity of infection (MOI) of 1.0 by centrifugation for 1 h at 1250 g at 37 • C. After the removal of chlamydial inoculum, infected cells were incubated in DMEM supplemented with 2% FCS and 1 µg/mL cycloheximide at 37 • C and 5% CO 2 for up to 72 h. At 24, 48, and 72 h post-infection, the infectious progeny and genomic copy number of C. pneumoniae were detected. The infectious progeny was determined by the development of chlamydial inclusions after passage to fresh HEp-2 cell monolayers. Briefly, cell monolayers were disrupted and passaged to fresh HEp-2 cell monolayers grown on glass coverslips in 24 well-plates. After 72 h of incubation at 37 • C and 5% CO 2 , the number of IFUs/mL was determined by counting all microscope fields using a fluorescence microscope (400x magnification). The genomic copy number of C. pneumoniae DNA was detected by real-time PCR using the Primerdesign ™ genesig R Kit as above described. Foam Cell Analysis J774A.1 macrophages (1.0 × 10 5 cells/well) were infected with C. pneumoniae clinical isolate and AR-39 strain at a MOI of 2.0 as above described. Next, infected cells were washed with PBS and cultured for 2 days in the presence or absence of human LDL (100 µg/mL; Sigma-Aldrich, St. Louis, MO). Foam cell formation and intracellular cholesterol levels were determined as previously described (Di Pietro et al., 2013b). Cytokine Analysis Interleukin (IL)-1β and IL-6 concentrations were measured in gingival crevicular fluid samples by quantikine HS human enzyme-linked immunosorbent assay (ELISA) according to manufacturer's instructions (R&D systems, Europe). The detection limits for IL-1β and IL-6 were 0.14 and 0.11 pg/mL respectively, and, if the cytokine concentrations were below the limits of detection, a value of 0 was scored. Statistical Analysis Statistical analysis was performed by using SPSS 13.0 (SPSS Inc. Chicago, IL, USA). Data were expressed as mean ± standard deviation of three replicates from three independent experiments. Comparison of means was performed by using a two-tailed Student's t-test. For the foam cell formation and the cholesteryl ester to total cholesterol ratio, the Kruskal-Wallis H test and the Mann-Whitney U test with the Bonferroni's correction were used. P ≤ 0.05 was considered statistically significant. C. pneumoniae Clinical Isolate C. pneumoniae DNA was detected in gingival crevicular fluid collected from diseased periodontal site by quantitative real-time In addition, the gingival crevicular fluid from the diseased periodontal site was positive to C. pneumoniae when subjected to direct fluorescence assay as evidenced by the presence of intracellular Chlamydia (Figure 1). Conversely, no C. pneumoniae DNA, as well as chlamydial inclusions, was detected in gingival crevicular fluid obtained from healthy periodontal site. Next, the crevicular gingival fluid sample positive to C. pneumoniae was subjected to culture in HEp-2 cells. An average of 50 chlamydial inclusions was detected in gingival crevicular fluid after three growth cycles of 3 days. The presence of C. pneumoniae in HEp-2 cell monolayers was confirmed by real-time PCR assay targeting C. pneumoniae MOMP gene. Further characterization of clinical isolate was performed via C. pneumoniae VD4-ompA genotyping. As a result of this analysis, the VD4 segment of ompA gene sequence from C. pneumoniae clinical isolate was found to be 99% identical to the human C. pneumoniae AR-39 and TW-183 sequences. C. pneumoniae DNA Detection in PBMCs No C. pneumoniae DNA was detected in PBMCs from the patient with chronic periodontitis, despite the quantitative real-time PCR revealed the presence of C. pneumoniae DNA in the gingival crevicular fluid. Growth Characteristics of C. pneumoniae Clinical Isolate The intracellular growth of C. pneumoniae clinical isolate was first analyzed in HEp-2 epithelial cells. Specifically, the infectious progeny as well as the genomic copy number of C. pneumoniae were detected at 24, 48, and 72 h post-infection. Figure 2A, C. pneumoniae clinical isolate and AR-39 strain displayed a similar kinetic growth with increases of IFUs of three orders of magnitude for both strains. Although C. pneumoniae clinical isolate showed a higher growth titer than AR-39 strain, there was no statistically significant difference in the infectious progeny between the two strains at 24, 48, and 72 h post-infection. No significant difference in inclusion morphology and size was also observed between C. pneumoniae clinical isolate and AR-39 strain (Figure 3). The quantitative detection of MOMP gene of C. pneumoniae by realtime PCR of infected HEp-2 cells further revealed a similar intracellular growth of the clinical isolate to the AR-39 strain ( Figure 2B). As shown in Next, we examined the intracellular growth of C. pneumoniae clinical isolate in a macrophage cell line since the latter has been widely used to investigate the aspects of chlamydial host cell infection related to the atherosclerotic process. C. pneumoniae clinical isolate did not replicate efficiently in macrophages as evidenced by a low number of infectious EBs detected at 24, 48, and 72 h post-infection as compared to that detected in HEp-2 cells (P < 0.00001). Specifically, the number of infectious EBs remained unaltered at 24 and 48 h while it increased significantly at 72 h post-infection (P < 0.01). However, the levels of infectious EBs produced by C. pneumoniae clinical isolate were similar to those produced by the AR-39 strain (Figure 4). C. pneumoniae Clinical Isolate-induced Foam Cell Formation In order to evaluate the pro-atherogenic effects of the C. pneumoniae strain isolated from the gingival crevicular fluid, we determined the number of macrophage-derived foam cells as well as the ratio of intracellular cholesteryl ester to total cholesterol after 48 h incubation in the presence of LDL. A Kruskal-Wallis H test showed a statistically significant difference in the foam cell formation and the ratio of cholesteryl ester to total cholesterol between the different groups [uninfected macrophages, macrophages infected with C. pneumoniae clinical isolate and macrophages infected with the AR-39 strain, χ 2 (2) = 15.16, P = 0.0005]. Compared to uninfected and LDL-treated macrophages, C. pneumoniae clinical isolate significantly increased the number of foam cells (6 vs. 45%; P = 0.0065). Moreover, a significant difference in the number of foam cells between the C. pneumoniae clinical isolate (45%) and the AR-39 strain (30%; P = 0.0065) was observed (Figures 5, 6A). Lastly, C. pneumoniae clinical isolate significantly increased the ratio of intracellular cholesteryl ester to total cholesterol as compared to uninfected LDL-treated macrophages (76 vs. 28%; P = 0.0065). A significant difference in the ratio of intracellular cholesteryl ester to total cholesterol between the C. pneumoniae clinical isolate (76%) and the AR-39 strain (58%; P = 0.0065) was also found ( Figure 6B). DISCUSSION The main result of our study is the isolation, for the first time, of C. pneumoniae from the gingival crevicular fluid of a patient with chronic periodontitis, suggesting that this microorganism may harbor inside the oral cavity, acting as a reservoir of the infection. Indeed, other intracellular microorganisms have been detected in the gingival crevicular fluid, supporting the hypothesis that this body fluid could be the intraoral source of the pathogens (Maticic et al., 2001;Suzuki et al., 2005). This may be explained by the characteristics of the gingival crevicular fluid, an inflammatory exudate containing substances from the host, as well as from supra-and sub-gingival located bacteria. Inflammatory and immune cells that have infiltrated into the periodontal tissues are also found in the gingival crevicular fluid together with markers of inflammation, including cytokines and interleukins (Rahnama et al., 2014;Atram et al., 2015). The significant genomic copy number of C. pneumoniae, detected in the gingival crevicular fluid, excludes the transient oral colonization, and the isolation by culture of chlamydial infectious EBs, together with the evidence of intracellular Chlamydia, confirms the presence of an active infection able to contribute to periodontal tissue damage. Interestingly, the detection of a high number of genomic copies paralleled by a low number of infectious EBs suggests the presence of live C. pneumoniae and chlamydial persistent forms that seem to be involved in chronic inflammatory diseases (Hogan et al., 2004;Kern et al., 2009). The low number of C. pneumoniae infectious EBs and the high amount of chlamydial DNA may also be due to the presence of dead bacteria. The C. pneumoniae strain that we successfully isolated came from a patient who was free, at the time of the specimen collection, from any documented acute or chronic respiratory and cardiovascular disease. However, we cannot rule out the presence of asymptomatic atherosclerotic plaques, such as those of early atherosclerosis, since the patient was at increased risk for cardiovascular diseases. In fact, the estimated 10-year cardiovascular risk according to the Framingham Heart Study was 42%, whereas the normal 10-year risk was 15.1% (D'Agostino et al., 2008). We investigated the molecular and phenotypical characteristics of the C. pneumoniae clinical isolate and we compared them to the AR-39 strain, also known as TWAR as it was isolated in Taiwan in a patient with pharyngitis (Kuo et al., 1995) and whose association with atherosclerosis has been well documented (Watson and Alp, 2008;Campbell and Rosenfeld, 2015). In our study, a 99% similarity was found in the sequence of the VD4 ompA gene between C. pneumoniae clinical isolate and the AR-39 strain. A high molecular similarity between the two strains is not surprising, since the genomic data from all the sequenced C. pneumoniae strains showed a marked genetic conservation (Rattei et al., 2007). Notably, the phenotypical characteristics of the two strains were also similar. In fact, a comparable growth kinetic in epithelial cells of the C. pneumoniae clinical isolate as compared to the AR-39 strain was observed, as evidenced by the infectious progeny and by the number of genomic copies. The similarity of the phenotypical characteristics between the two strains resulted also from a comparable size and morphology of chlamydial inclusions. Further analysis of the phenotypical features of the C. pneumoniae clinical isolate revealed, similarly to the AR-39 strain, its ability to survive and mainly generate infectious EBs within macrophages. The production of infectious EBs in macrophages is of great pathophysiological significance, since it supports the potential ability of C. pneumoniae isolate to systematically disseminate through monocytes-macrophages and translocate to the vascular tissue, contributing to the atherosclerotic process. In this regard, several studies have provided the evidence that C. pneumoniae disseminates through the PBMCs to the vasculature and to other extra-pulmonary sites (Gieffers et al., 2004;Little et al., 2005;Rupp et al., 2005;Sessa et al., 2007;Watson and Alp, 2008;Di Pietro et al., 2013c). In our study, C. pneumoniae DNA was not detected in the PBMCs of the patient with chronic periodontitis. However, we cannot rule out the potential dissemination of C. pneumoniae clinical strain from the oral cavity to the vasculature. Indeed, the low amount of chlamydial infectious EBs isolated from the gingival crevicular fluid may not be enough to allow the translocation of C. pneumoniae into

PBMCs. The lack of chlamydial DNA in PBMCs may also be due to the putative presence of chlamydial persistent forms in the gingival crevicular fluid, that are not-infectious and, thus, unable to translocate into the systemic circulation. Furthermore, as recently suggested by Zafiratos et al. (2015), only chlamydial antigens may be carried by PBMCs to the vasculature where they become targets of attack by antigen-specific CD8+ T cells, exacerbating the atherosclerotic process. Therefore, monitoring the patient over the time will be needed to demonstrate C. pneumoniae dissemination. Of particular clinical relevance is the foam cell formation following the infection of macrophages, suggesting the potential atherogenic features of C. pneumoniae clinical strain. The enhanced foam cell accumulation is considered a key event in the initiation of atherosclerotic plaque development. In this regard, C. pneumoniae infection of macrophages has been shown to trigger the oxidation and accumulation of LDL through the release of reactive oxygen species, the increased expression of lipoprotein lipase via chlamydial lipopolysaccharide and the dysregulation of receptors involved in cholesterol efflux via nuclear receptor peroxisome proliferator-activated receptorγ (Di Pietro et al., 2013a;Cheng et al., 2014;Zhao et al., 2014). The high similarity of C. pneumoniae clinical isolate with the AR-39 strain, usually associated to atherosclerosis (Watson and Alp, 2008;Campbell and Rosenfeld, 2015), emphasizes the importance of the isolation of a potential atherogenic C. pneumoniae strain from the oral cavity although further investigations are needed to prove this evidence. In our study, a further interesting finding is the possible involvement of C. pneumoniae in the local chronic inflammation, as suggested by the increased levels of IL-1β and IL-6 detected in the gingival crevicular fluid of the patient with chronic periodontitis. Both these cytokines are major players in the periodontal inflammatory process underlying chronic periodontitis (Faizuddin et al., 2003;Ebersole et al., 2014). Thus, we can hypothesize that, upon C. pneumoniae infection, fibroblasts, epithelial cells and macrophages, typically present in the periodontium, may secrete pro-inflammatory cytokines involved in the disease progression and the subsequent destruction of the periodontal tissue. In conclusion, the isolation of a potential atherogenic strain of C. pneumoniae from the gingival crevicular fluid of a patient with chronic periodontitis provides the basis to make some compelling hypothesis. First, C. pneumoniae may take part to the initiation and/or the development of chronic periodontitis and, perhaps, contribute to the local chronic inflammatory state. Second, C. pneumoniae, similarly to other periodontal pathogens, under favorable conditions such as the destruction of the peridontium, that occurs during periodontitis, may systematically disseminate and localize in the vascular wall, increasing the risk for cardiovascular diseases. However, the data presented in our paper must be interpreted with caution until validated by additional studies in order to clarify the involvement of C. pneumoniae in chronic periodontitis as a risk factor for cardiovascular diseases. Restoration of Fingerprints from a Mummified Cadaver Fingerprints are widely used as the most reliable means of individual identification in forensic science. However, postmortem changes of the skin always make it difficult to obtain fingerprints. To restore fingerprints of mummified cadavers, various reagents have been used. In recent years, commercially available embalming agents for cadaver restoration and preservation have been evaluated, but they have not been sufficiently compared. In this study, we successfully restored fingerprints from a highly dried, almost mummified, unidentified cadaver. Five methods were attempted to restore fingerprints: three used previously reported reagents and two used commercially available embalming solutions at room temperature. The fingers were observed grossly after immersion for 1, 2, 3, 5, and 7 days. When all the specimens were well restored, fingerprints were taken by the inked impression method and by an indirect method using silicone rubber. The results indicated that Na2CO3, and Sofner ® were more effective to restore clear fingerprints. The other solutions failed to produce optimal tissue softening and swelling, and the dermal ridges were ill-defined. The conventional Na2CO3 and the newly tested Sofner ® were useful in that they restored better fingerprints in a shorter duration. Na2CO3 has to be prepared before use, whereas Sofner ® can be used by simply diluting with water. Introduction Several methods are used in forensic sciences for individual identification of cadavers, such as sex, age, physical characteristics, blood type, DNA test results, dental findings, and fingerprints. In particular, fingerprints are widely used as the most reliable means of personal identification, because no two persons have identical dermal ridge patterns, and the patterns of any one individual remain unchanged throughout life [1][2][3][4]. However, postmortem changes of the skin of fingers present problems with fingerprinting. Therefore, methods of taking fingerprints appropriate for the state of rigor mortis, putrefaction, mummified, and burned bodies were investigated [5]. To restore fingerprints of mummified cadavers, various reagents have been reported. In recent year, commercially available embalming agents for cadaver restoration and preservation have been evaluated [6,7], but they have not been compared sufficiently. In this study, we compared three conventional reagents and two embalming solutions for restoring fingerprints of a highly dried, almost mummified, unidentified cadaver. Materials and Methods Background A male cadaver was found in an empty house in winter. The body was in various stages of advanced decomposition and profusely infested by fly maggots. Large portions of the integument, including that of the hands and feet, had mummified. Autopsy was required by the police for diagnosing the cause of death. The results of our judicial autopsy indicated that the remains were those of a middle-aged male, estimated to have been dead for approximately half a year. The identity of the man was not known, and individual identification was needed. Investigation of the fingerprints was the first choice, because there was nothing that could be used to identify the individual. However, the cadaver had mummified, and the skin of all fingers was too dry and rigid to take the fingerprints. Therefore, restoration of fingerprints was required as the first step. Materials Both hands of the mummified cadaver were examined ( Figure 1). After carefully cleaning the hands with physiological saline, definite injury was not observed in the right palm and six fingers: thumb, index finger, middle finger, ring finger, little finger of the right hand and little finger of the left hand. Because these fingers were likely to retain their dermal ridge patterns, we decided to use them in our attempt to examine the fingerprints. The embalming solutions were diluted to 50%, 25%, 12.5% and 6% before use. The fingers were divided into various portions for testing different solutions at various concentrations as follows: distal and proximal phalanges of right thumb; distal and proximal thenar regions of right palm; distal, middle and proximal phalanges of right index finger; distal, middle and proximal phalanges of right middle finger; distal, middle and proximal phalanges of right ring finger; distal and middle phalanges of right little finger; and distal and middle phalanges of left little finger. Each phalanx was wrapped in gauze material soaked with each reagent at room temperature, and observed grossly after treatment for 1, 2, 3, 5 and 7 days. When all the specimens were well restored, fingerprints were taken by the inked impression method and by an indirect method using silicone rubber. Results The important precaution taken in recreating the fingerprints of this case was to allow the dried and rigid skin of the mummified fingers to hydrate and elevate sufficiently, and prevent injury to the skin of the fingers during the experimentation. The five restoration solutions yielded different results. The finger portion treated with solution A softened rapidly one day later, although the dermal ridges remained ill-defined. After two days of treatment, the skin swelled, the tissue cleared, and the dermal ridges became well-defined. However, no clear fingerprints could be taken ( Figure 2). The finger continued to imbibe and swell and, became gelatinous beyond recognition after treatment for 7 days. The finger portion treated with solution B gradually changed from dark brown to flesh color, and softened 1 day later. The dermal ridges became well-defined two days later (Figure 3), and allowed the impression of clear fingerprints ( Figure 4). From five days onward, the finger continued to swell, and the skin grooves became shallow, making the dermal ridges ill-defined. The finger portion treated with solution C became stained with the reagent (pink). Regardless of the dilution of the solution, tissue softening was slow. Seven days later, softening and swelling remained insufficient, and the dermal ridges were ill-defined ( Figure 5). The finger portion treated with Sofner ® gradually became bleached. Regardless of the dilution of the solution, treatment produced well defined dermal ridges. At a concentration of 25% or lower, the phalanges softened properly three days later (Figure 6), and clear fingerprints were obtained ( Figure 7). Thereafter, softening progressed slowly until day 7. The finger portion treated with LITHOL Index32 ® became stained with the reagent (pink). Regardless of the dilution of the solution, treatment resulted in well defined dermal ridges. Softening of the skin became slower as the concentration of the reagent increased. Only the fingers treated with a 6% dilution of the reagent exhibited slight softening from 1 to 7 days (Figure 8), but clear fingerprints could not be obtained after treatment for 3 days. Therefore, solutions B and Sofner ® both produced good results in the restoration experiment. Discussion A number of techniques to obtain fingerprints from mummified cadavers have been proposed in the literature. Although the reagents and procedures have been reported to produce good results, reagent preparation and the procedures are time-consuming. "Tanning solution" involves the removal of tissue from the glycerin-resistant phalanges, followed by the action of a 50% sulfuric acid in saturated saline solution on the specimens for 72 hours [8]. A second method uses a detergent solution containing disodium ethylenediamine tetracetic acid (pH 7.5) [9], but the method requires reagent preparation and pH adjustment. Alkaline solutions have been used relatively frequently. For example, the action of 1N potassium hydroxide solution on skin specimens for 48 hours at 30°C results in epidermolysis, and the exposed dermis can be observed [10]. This method requires preparation of the reagent and temperature management during testing. Furthermore, it has been noted that an alkaline solution at a high concentration or temperature may destroy the dermis. Another method uses NaOH-glycerin, an alkaline solution that can be prepared and used relatively easily. A comparative experiment reported that NaOH-glycerin was more effective than water, physiological saline, and antifoaming solution in restoring fingerprints [11]. Thus, NaOH-glycerin was tested in this study (solution A), but softening and swelling progressed before dermal ridges became welldefined, and the specimen became gelatinous 2 days later, with swelling of the tissue. This was probably due to the excessive corrosive action of sodium hydroxide on the skin. Therefore, the use of an alkaline solution requires prior determination of the optimal concentration. To avoid tissue destruction, Na 2 CO 3 solution in 95% ethanol (solution B) was used. Treatment with solution B for 24 hours has been reported to soften skin specimen [12]. In this study, softening progressed favorably during treatment with solution B, and clear fingerprints were obtained 2 days later. Since its corrosive action on the skin is not strong, it restores the ridges in the epidermis but does not affect the dermis, thereby facilitating the impression of fingerprints suitable for routine fingerprint investigation. In recent years, the use of commercially available embalming solutions has been studied to eliminate the need for the complicated solution preparations and temperature management. Embalming is a procedure that repairs, preserves, disinfects, and maintains a dead body safely and cleanly for certain periods by replacing the blood with preservatives. Overnight immersion in a 1: 1 mixture of Metaflow ® and Restorative ® has been reported to provide sufficient tissue softening for 20 hours, and subcutaneous injection of this solution allows impression of good fingerprints [6]. Metaflow ® is a reagent for the drainage of blood, and Restorative ® is a product for the repair and preservation of a dead body. Both reagents were manufactured by Dodge Chemical Company, Cambridge, Massachusetts. Later, methods using only reagents corresponding to Restorative ® were studied. A comparison of FLESHTONE ® (formalin 28%, glutaraldehyde 14%; IMS Co.) and TIOAR-330 ® (solution C in the present study) reported that solution C softened and denuded the epidermis, and was useful to expose the dermis [7]. However,

Metaflow ® and Restorative ® are currently not commercially available. Thus, in this study, we used reagents equivalent to Metaflow ® and Restorative ® to test methods of restoring dermal ridges in a mummified cadaver. From the commercially available embalming Figure 5: The proximal phalanx of the right middle finger treated with solution C for seven days (right) compared with before treatment (left). The finger became softened, but swelling remained insufficient, and the dermal ridges were illdefined. solutions, Sofner ® and Special Arterial Chemical-LITHOL Index32 ® were selected as equivalent reagents for Metaflow ® and Restorative ® , respectively. Since both solutions are used for embalming in undefined concentrations, the optimal concentrations for use were not known. Therefore, we used serial dilutions of each solution. While LITHOL Index32 ® was expected to be suitable for the restoration of dermal ridges, our results showed that Sofner ® was more useful. In particular, LITHOL Index32 ® at a concentration of 25% or higher did not cause tissue softening, probably due to the potent fixative effect of formalin. To find a useful method for restoring the dermal ridges (fingerprints) of a mummified cadaver, five reagents were tested in this study. Not all methods that have been reported to give good results produced useful changes during 7 days of observation. This was presumably due to the degree of dryness and the shape of the specimens used. Therefore, it is desirable to perform a preliminary study to determine the optimal concentration and duration of action of the reagents before application to the specimen. In this study, the conventional solution B and the newly tested Sofner ® were considered more effective in that they restored better fingerprints in shorter durations than the others. Solution B must be prepared before use, whereas Sofner ® can be used conveniently by simply diluting with water. Commercially available products such as solution C may be removed from the market at any time. Moreover, their formulae are not known, making it impossible to prepare these reagents in the laboratory. On the other hand, the composition of solution B is known. Thus, solution B is superior in that it can be prepared easily as long as the two ingredients are available. Fingerprints were taken by the inked impression method or an indirect method using silicone rubber. If the dermal ridges are restored not on fingertips, but after separation of the skin from the bone, special technique is needed to impress fingerprints [9]. For this purpose, a method using T pins has been developed [8]. Since the reported restoration method using an embalming solution exposes the dermis, the dermal ridges are stained with 0.05% toluidine blue solution for observation [13]. When a specimen is taken with the epidermis partially sloughing and the dermis exposed, a single dermal ridge may appear as a double fine line, requiring particularly careful handling. However, the present methods allowed us to restore the dermal ridge patterns and obtain clear fingerprints easily by the inked impression method. In this respect also, it is an excellent method of fingerprint restoration. Finally, the police checked the fingerprints in their files, and successfully identified the cadaver. The Big Breakfast Study: Chrono‐nutrition influence on energy expenditure and bodyweight Abstract A growing body of evidence highlights the importance of the biological clock as a modulator of energy balance and metabolism. Recent studies in humans have shown that ingested calories are apparently utilised more efficiently in the morning than in the evening and this is manifest through improved weight loss, even under iso‐energetic calorie intake. The mechanisms behind this enhanced morning energy metabolism are not yet clear, although it may result from behavioural adaptations or circadian driven variations in physiology and energy metabolism. A major objective of the newly funded Big Breakfast Study therefore is to investigate the mechanistic basis of this amplified morning thermogenesis leading to enhanced weight loss, by exploring behavioural and physiological adaptations in energy expenditure alongside the underlying circadian biology. This report briefly discusses the current research linking meal timing, circadian rhythms and metabolism; highlights the research gaps; and provides an overview of the studies being undertaken as part of the Medical Research Council‐funded Big Breakfast Study. Introduction The UK has been reported to have one of the highest evening energy intakes, with the proportion of daily energy intake increasing gradually across the day and dinner providing on average 40% of daily calories (Almoosawi et al. 2016). Similar patterns of increasing energy intake over the day, albeit with slightly smaller dinner intakes of approximately 33%-34%, have been reported across a number of other nations, including the US, Canada, Germany, Denmark, The Netherlands and Belgium (Almoosawi et al. 2016). To date, surprisingly little attention has been paid to the importance of time of day on the nutritional response or energy balance. The recent Nobel Prize awarded to Jeffrey Hall, Michael Rosbash and Michael Young for their discoveries of the molecular basis of biological rhythms highlights the profound importance of circadian rhythms in biology (chronobiology). Over the last 15 years, there has been increased recognition of how chronobiology impacts on health and disease. Chrononutrition extends chronobiology research and defines the emerging discipline of science surrounding the complex interactions between circadian biology, nutrition and metabolism. Clock genes are now recognised for their indisputable role in coordinating nearly all biological and physiological processes of the body. The suprachiasmatic nucleus (SCN) of the hypothalamus, the 'master clock', is primarily regulated by light/dark cycles in order to synchronise the body to the light cycle or solar day (Takahashi 2017). Additionally, peripheral clock genes have been identified throughout the body in nearly all individual tissues and organs, which regulate the timing of physiological functions within these specific tissues. Critically, rhythms persist in tissue/cell culture, indicating that these peripheral clock gene rhythms reflect local clocks. The SCN acts as the master timekeeper, keeping the peripheral clocks in synchrony to the central 24-hour circadian rhythm. Nonetheless, other external factors, including food and physical activity, can influence the timing of peripheral clocks (Bass 2012;Jiang & Turek 2017). Circadian rhythmicity influences the essential processes of metabolism and energy expenditure, with rhythmic expression of clock genes identified in tissues of the gut, liver, endocrine organs, adipose tissue and skeletal muscle. These in turn control the timing of digestion, nutrient uptake and metabolism, hormonal and metabolite regulation, appetite, ingestive behaviour and physical activity (Bass 2012;Jiang & Turek 2017) (Fig. 1). The relationship between circadian rhythms and metabolism involves a Gut Regulation of the timing of physiological and metabolic processes including: Energy balance and metabolic health Figure 1 The role of circadian rhythms in regulating metabolic processes and energy balance. Clock genes in peripheral tissues are primarily regulated by the central 'master clock' in the hypothalamus (the suprachiasmatic nucleus; SCN), which is predominantly under control by the light/dark cycle. Clock genes are also entrainable by other external factors including food intake and exercise. Clock genes have been established in the brain, liver, gastrointestinal tract, endocrine system adipose tissue and skeletal muscle. They regulate the timing of physiological processes, specifically those involved in the digestion of food, nutrient uptake and nutrient metabolism. These in turn are likely to affect energy expenditure through regulating resting energy expenditure, thermic effect of food and physical activity. Behavioural implications include an influence on food intake and food choice as well as exercise. [Colour figure can be viewed at wileyonlinelibrary.com] complex feedforward and feedback system. In addition to postprandial responses being influenced by circadian rhythms, food intake itself can entrain circadian clocks in tissues such as the liver, intestines and adipose tissue (Damiola et al. 2000;Hara et al. 2001;Froy et al. 2005;Wehrens et al. 2017), modulating both gene expression and physiological functions. Despite the growing knowledge of the interactions between nutrition and circadian biology, much remains to be understood about how meal timing may impact on health and predominantly nutritional-based diseases such as obesity, type 2 diabetes and cardiometabolic disorders. The current literature is dominated by pre-clinical studies, and there is strong need for more translational studies in humans. The proposed work addresses this gap, providing a novel and timely project, which draws upon the existing literature in animal models, yet sets up mechanistic, hypothesis driven intervention studies in human models. Timing of eating (calorie distribution): Effects on energy balance and metabolic health Dietary advice for weight management in humans is based on the assumption that 'a calorie is a calorie' and that meal timing is inconsequential. However, recent evidence from chrono-nutrition studies questions this assumption and verifies the importance of meal timing in energy balance and cardio-metabolic health and disease (Antunes et al. 2010;Garaulet et al. 2013;Jakubowicz et al. 2013Jakubowicz et al. , 2017. Humans are a diurnal species with the light cycle stimulating wakefulness and feeding, and darkness initiating sleeping and fasting (Fig. 2). Misalignment between normal feed/fast, day/night and sleep/wake cycles may desynchronise central and peripheral regulations of metabolic processes and contribute to obesity and metabolic disorders (Scheer et al. 2009;Antunes et al. 2010). Increased risk of obesity and related health conditions has been associated with breakfast skipping and late night feeding (Ma et al. 2003;Cleator et al. 2012;Fong et al. 2017), indicating morning energy intake may have substantial health benefits. A recent meta-analysis of observational studies demonstrated an association between evening energy consumption and higher BMI (Fong et al. 2017) andMcHill et al. (2017) found that, on average, obese individuals consumed most of their calories an hour closer to melatonin onset (biological marker of impending sleep onset) compared to lean individuals. In addition to significantly increasing the risk of obesity, a recent study observed that acute breakfast omission altered clock genes expression and resulted in an increased postprandial glycaemic response (Jakubowicz et al. 2017). Additionally, shift workers are predisposed to weight gain and metabolic disorders, which has been suggested to arise from circadian misalignment (Antunes et al. 2010). Intentionally inducing misalignment in sleep/wake and feed/fast times in mice models through feeding during the light phase (normal fasting period) resulted in significantly greater weight gain compared to mice fed during the dark phase. This was despite equivalent calorie consumption and locomotion, demonstrating the capacity of meal timing to modify energy balance and bodyweight (Arble et al. 2009). Preliminary dietary intervention studies in humans seem to suggest that calories ingested at different times of the day have different effects on energy utilisation, leading to differential weight loss, even at iso-caloric amounts (Garaulet et al. 2013;Jakubowicz et al. 2013). Garaulet et al. (2013) found that late lunch eaters lost significantly less weight (2.1 kg) than early lunch eaters over a 20-week protocol. This was despite no reported differences in energy intake, dietary composition, estimated energy expenditure, appetite hormones or sleep duration. Similarly, Jakubowicz et al. (2013) reported that during a 12-week submaintenance diet in 93 overweight women, morning calorie consumption (50% calories at breakfast and 14% at dinner) resulted in a 5.1 kg greater weight loss relative to evening calorie consumption (14% calories at breakfast and 50% at dinner), with weight loss differences reaching statistical significance by week 4. Morning calorie consumption was also associated with greater improvements in fasting glucose, insulin and triglycerides, glucose tolerance as well as lower hunger scores. The mechanisms involved in this mealtimedependent differential weight loss are unclear, but they may include the following: (1) behavioural adaption such as altered (increased or decreased) physical activity or energy expenditure at other times of the day, and/or (2) the influence of normal biological circadian/ diurnal rhythms on energy metabolism at different times of the day. Significantly greater satiety was an additional outcome of morning compared to eveningloaded calorie consumption (Jakubowicz et al. 2013). While these studies point to new and interesting roles of meal timing in energy balance, the effects observed may simply have been due to higher energy intake and/or non-compliance in the later lunch and evening predominant feeding patterns, which was unaccounted for with their methods of assessing dietary intake. Despite this evidence, clinical trials comparing meal timing in humans are extremely limited. To date, no randomised, controlled crossover studies comparing large breakfast meals vs. large evening meals have been conducted. The Big Breakfast Study will address this gap in research by implementing a randomised control trial comparing morning-loaded vs. evening-loaded weight loss diets in overweight and obese individuals, in which all components

of energy intake and energy expenditure will be monitored over 4-week periods. Physiological mechanisms and circadian influence on energy metabolism Rhythmic gene expression has been identified in nearly all tissues and organs of the body. In addition, many of these rhythmic genes have identified roles in the regulation of metabolic processes and energy expenditure, such as digestion, nutrient absorption, lipid and glucose metabolism and locomotion (Bass 2012;Sahar & Sassone-Corsi 2012;Jiang & Turek 2017) (Fig. 1). Importantly, a large number of these genes are involved in the rate-limiting steps of metabolic pathways (Sahar & Sassone-Corsi 2012) providing a clear theoretical basis for a chronobiological influence on metabolism. A number of postprandial metabolic processes show time of day variations, with faster gastric emptying, enhanced intestinal absorption, superior glucose tolerance and higher postprandial energy expenditure [Thermic Effect of Food (TEF): the increase in energy expenditure after meal consumption associated with the energy costs of nutrient digestion and storage] observed in the morning compared to the evening. A number of studies have shown a strong time of day effect of TEF; specifically it has been demonstrated to be significantly higher in the morning relative to the evening (Romon et al. 1993;Bo et al. 2015;Morris et al. 2015). However, diurnal differences in the TEF are not consistently found in all studies (Weststrate et al. 1989). The TEF consists of both obligatory (essential energy expenditure for digestion, nutrient absorption and nutrient storage) and facultative components (energy expenditure associated with increased postprandial sympathetic nervous system activity) (Ravussin et al. 1985). Thus, the higher TEF in the morning, found in a number of studies, may be a result of circadian influences associated with either higher costs of essential energy requirements for digestion or increased sympathetic nervous system activity, or simply a result of meal size. The TEF response also appears to be under endogenous circadian control, as shifts in day/night and sleep/wake times alters the timing of TEF accordingly. This is evident through the use of phase shift protocols, where the light/dark cycle is either abruptly advanced or delayed, which temporarily desynchronises an individual's internal body clocks from the ambient light/dark cycle. The effects of this desynchrony can then be seen in terms of the timing of sleep/wake and feed/fast cycles. This mimics what an individual would experience on a transatlantic flight or is regularly experienced by shift workers following night shift work. Morris et al. (2015) studied the effect of a 12-hour phase delay on TEF in human subjects. They showed that normally TEF is higher in the morning compared to the evening. This was maintained 1 day after the phase delay, but after 3 days, this difference was lost. It is important to note that the time points for all TEF measurements were locked onto the initial light/dark cycle and were not changed to follow the phase delay. The TEF measurements then reflected the status of the body's internal biological clock (and rhythms). The loss of the clear morning/evening difference by day 3 reflects the gradual resynchronisation to the new light/dark cycle and readjustment to establish a greater morning TEF. It is also important to note that TEF in this study was only measured for 2 hours, where in fact the TEF response may last as long as 6 hours (Reed & Hill 1996). Therefore, differences in the timing of the morning vs. evening TEF response, as a result of changes in the rate of gastric emptying and nutrient absorption, may have been missed and have influenced the results. Further research which measures TEF over longer durations to capture the entire response is necessary to address diurnal variations in the TEF and circadian influences. Diurnal variations are evident in gastrointestinal absorption rate and expression of gastrointestinal genes involved in nutrient transport, which are both typically higher during the active phase and following fasting (Sotak et al. 2011;Hussain & Pan 2015). Rates of gastric emptying have also been shown to be under circadian control, with slower emptying of the stomach in the biological evening (Goo et al. 1987). These factors may contribute to the observed elevated morning TEF, by influencing the release of nutrients into the intestines for absorption, and also affecting the release of hormones and metabolites required for energy consuming processes of nutrient digestion and storage (Weststrate et al. 1989;Romon et al. 1993). It is not yet clear whether the day/night rhythm in gastrointestinal absorption rate is driven by the behavioural cycle or endogenous circadian biology, and no studies have considered how 24-hour variations in gastric emptying following a meal may differentially influence postprandial energy metabolism across a day. Reduced evening insulin release and glucose tolerance may further impact on the thermogenic costs associated with glycogenesis following carbohydrate intake and reduce evening TEF (Ravussin et al. 1985;Van Cauter et al. 1997). Differential weight loss between morning and evening feeding may also be a result of behavioural influences involving voluntary and incidental physical activity, as well as appetite and food choice. For example, Betts et al. (2014) found higher levels of physical activity in breakfast-consuming individuals relative to those who skipped breakfast. It is also plausible that the difference in energy expenditure between morning and evening meal consumption may reflect altered basal metabolic rate. Thus, in addition to TEF, daily changes in basal metabolic rate and physical activity require careful monitoring in the study of the mechanisms underpinning the relationship between meal timing and bodyweight. In summary, there is evidence that timing of eating has a clinically meaningful influence on weight loss, energy balance and metabolic health. However, the underlying mechanisms contributing to meal-timeinduced differential energy expenditure are not yet clear and the variable components of daily energy expenditure have never been explicitly studied in terms of daily rhythms. Objectives of the Big Breakfast Study Growing evidence suggests some truth to the adage 'Breakfast like a king and dine like a pauper', with meal timing appearing to influence energy balance and bodyweight (and thus, disease risk). The Big Breakfast Study is funded by the Medical Research Council to investigate the underlying biological and/or behavioural drivers that influence energy balance, and thus bodyweight in overweight and obese persons, relative to daily energy distribution. The key objectives of the project are schematically represented in Figure 3. The project will investigate how the components of energy expenditure (i.e. total daily energy expenditure, resting metabolic rate, TEF, physical activity) are influenced by meal timing, circadian and behavioural effects. The aim is to understand the underlying mechanisms (i.e. hormones/metabolites/gastric emptying), that determine time of day differences in energy expenditure and Figure 3 Key objectives of the Big Breakfast Study are to understand how altering meal size (calorie intake), specifically morning vs. evening distribution of energy intake, affects energy balance. We will determine the underlying mechanisms of energy balance (through assessing energy expenditure and appetite) and the influence of circadian biology. [Colour figure can be viewed at wileyonlinelibrary.com] thereby make consuming the largest meal of the day at breakfast (and smaller evening meal), important in influencing daily energy balance. The project will combine specialised techniques (i.e. use of stable isotopes for measuring total daily energy expenditure, gastric emptying and total body water; and circadian control, through the use of controlled light and dark exposure, and sleep and meal times) and protocols with complete dietary control to assess the physiological and behavioural factors influencing the relationship between external clock time, internal circadian rhythms, energy expenditure and energy balance (body mass). Two studies will explore potential behavioural and circadian/diurnal influences on energy expenditure and energy balance. Specifically, the project will address two overriding objectives: (1) to assess the impact of timing of eating on mechanisms associated with energy expenditure and substrate utilisation; (2) to test the contribution of biological circadian influence on energy expenditure and related endocrine pathways during a fixed feeding phase shift protocol. These studies will extend current knowledge about the interaction of diet and the body's circadian rhythms ('chrono-nutrition') and help to inform future development of nutritional guidelines for weight control, based on optimising the timing of energy consumption. An overview of the current literature, research gaps and aims of the current project are reviewed in Figure 4. Objective 1: To assess the impact of timing of eating on mechanisms associated with energy expenditure and substrate utilisation: The Mealtime Study The Mealtime Study aims to answer the questions: 'Does morning-loaded energy consumption significantly influence energy balance and therefore weight loss compared to evening-loaded energy consumption?' and 'What are the underlying mechanisms leading to differential weight loss due to meal timing?' The study will implement a 10-week randomised, crossover energy restrictive dietary intervention study designed for weight loss in overweight or obese, but otherwise healthy, adults comparing morning-and evening-loaded feeding. The dietary intervention will involve two 4-week weight loss phases with calories distributed predominantly in the morning (45%, 35%, 20% of energy intake at breakfast, lunch and dinner, Current Research Theoretical evidence for the role of circadian biology in regulation of metabolism and energy expenditure. • Clock genes identified in nearly all tissues and organs and identification of their role in key rate limiting steps of metabolism. • Circadian/diurnal rhythms identified in rates of gastric emptying, nutrient absorption and nutrient metabolism (i.e. lipogenesis, glycogenesis). Complex feedforward/feedback interaction between food intake and clock genes. Food intake can entrain peripheral clocks and result in synchrony or desynchrony between clocks regulating metabolic processes. Irregular food consumption leads to increased obesity and metabolic health disorders. • Shift work, breakfast skipping and late eating are associated with increased risk of obesity and disease. Preliminary human interventions demonstrate superior weight loss when meals and energy distribution are earlier in the day. The current literature is dominated by pre-clinical trials and observational studies. No published studies have measured the rhythmic variation in humans in all areas of total daily energy expenditure (TDEE, RMR, TEF and physical activity). Lack of human interventions which extricate circadian rhythms and behavioural influences on metabolic and digestive processes, and their contribution to differential energy expenditure and energy balance. Lack of clear evidence regarding the underlying mechanisms for superior weight loss with earlier meal consumption. No cross over studies in humans looking at the effects of meal timing on weight loss and energy balance. To implement human clinical trials. To assess the impact of timing of eating on mechanisms associated with energy expenditure and substrate utilisation, which may lead to superior weight loss with morning feeding. To investigate the contribution of biological circadian influences on energy expenditure and related endocrine pathways. To determine circadian rhythms in mechanisms of energy balance [i.e. energy intake and appetite and the individual components of energy expenditure (RMR, TEF, physical activity)]. Contribution to the development of scientific research on chrono-nutrition. Bringing human intervention studies looking at circadian biology and nutrition into the limelight. Provision of evidence-based data for translation to improve dietary guidelines directed at meal timing as an alternative strategy to promote bodyweight control. respectively) or the evening (20%, 35%, 45% of energy intake at breakfast, lunch and dinner, respectively) with 1-week weight maintenance diets at baseline and mid-study between the two weight loss phases (washout). All diets will be prepared at the Rowett Institute for participants to collect and consume outside the Institute. The primary outcome measure, bodyweight, will be measured three times per week throughout the 10-week protocol, when participants attend the Institute's human nutrition unit for measurement and food collection. All other outcome measures will be assessed at the end of each study phase (weight maintenance 1, energy restriction diet 1, weight maintenance 2 and energy restriction diet 2). Changes in body composition will be assessed using the four compartment model (bone mineral, water, fat mass and fat-free mass). Doubly-labelled water, which remains the gold standard for assessing total energy expenditure (Buchowski 2014), will be used for the 8 weeks of energy restriction to objectively measure total energy expenditure. This will provide a precise assessment of whether meal timing affects total daily energy expenditure during energy restriction. We will also assess all components of energy expenditure. This will include the use of actigraphs to assess physical activity as well as indirect calorimetry to measure resting metabolic rate (RMR) as well as TEF following breakfast meals [calorically matched to the corresponding study phase (i.e. weight maintenance 1 or 2, big breakfast or small breakfast energy

restriction diet)]. This will enable us to determine whether differences in energy expenditure and energy balance in relation to timing of energy intake are due to behavioural changes (i.e. variations in incidental physical activity) or changes in physiological energy expenditure (RMR and TEF). Breakfast skipping has been correlated to lower levels of physical activity (Aarnio et al. 2002;Sandercock et al. 2010;Betts et al. 2014) and increased sedentary leisure time (Amigo-V azquez et al. 2016), and it is therefore possible that morning feeding will promote activity. Although participants will be instructed not to alter their physical activity throughout the study, incidental and subconscious increases in activity may occur following morning feeding and result in increased non-resting energy expenditure and greater energy deficit. It has been proposed that the lower TEF in the evening found in previous studies may be as a result of slower gastric emptying or reduced nutrient uptake. We will therefore measure gastric emptying by stable isotope technique ( 13 C Octanoic Acid) at the same time as assessing TEF and postprandial changes in glucose, insulin and gut hormones. While previous studies have indicated a greater morning TEF (Morris et al. 2015), the use of just 2 hours of measures is insufficient to determine the entire TEF response. Sixhour measures of TEF and gastric emptying will be applied based on the methodology by Reed and Hill (1996), which is a more discriminating way to measure the entire TEF response. In line with previous research, we will also assess measures of metabolic health on test days at the end of each study phase. This will include blood pressure and fasting and postprandial glucose, insulin and lipids to determine other health benefits associated with morning-loaded feeding. Blood glucose will be further assessed over the final 3 days of each study phase using continuous glucose monitors (CGMs). It has previously been shown that morning feeding resulted in significantly greater reductions in fasting glucose, insulin, homeostatic model assessment-insulin resistance and serum triglyceride, and significantly greater improvements in high-density lipoprotein (HDL)-cholesterol, compared to evening feeding (Jakubowicz et al. 2013). The Mealtime Study will help to solidify this evidence by implementing a crossover design for within-individual comparisons of metabolic blood substrates. The inclusion of CGMs will allow detailed assessment of the impact of morning-loaded feeding on acute postprandial glucose responses and also daily glucose fluctuations. Lastly this study will assess the participants' subjective appetite using Visual Analogue Scales (Flint et al. 2000) measured hourly for three consecutive days during the last week of each study phase, during free living conditions and concurrent with continuous glucose assessment and actigraph assessment. Appetite ratings will also be taken every 30 minutes for the entire test day simultaneous to the measures of gastric emptying and TEF. From this we aim to determine how meal timing affects daily appetite, as well as establish complex relationships between blood glucose, physical activity, gastric emptying and energy expenditure. Objective 2: To test the contribution of biological circadian influence on energy expenditure and related endocrine pathways during a fixed feeding phase shift protocol: Effects of a 5-hour phase delay of light and behaviour on daily rhythms of human metabolism Separating human environmental and behaviour influences from endogenous circadian physiology will assist in understanding the underlying mechanisms associated with the rhythmic expression of energy expenditure. Specifically, the use of phase shift protocols, which alter an individual's relative time of day to earlier or later, by advancing or delaying the light/ dark, sleep/wake and feed/fast cycles, can be used to ascertain the relative contribution of endogenous circadian rhythms vs. behavioural cycles. This study aimed to answer the question 'How are the patterns of energy expenditure, metabolism and gastric emptying and related endocrine pathways affected by circadian rhythms during a fixed feeding phase shift protocol and how do endogenous circadian rhythms influence energy expenditure and energy balance?' Participants will attend the research facility for a 7-day in-house stay, including 2 baseline days and 5 days following an acute 5-hour phase shift. The 5-hour phase shift will involve a 5-hour delay in timing of light and dark exposure, sleep and wake times and all meal times so that during baseline, sleep will be permitted from 23:00 to 07:00, while following the phase shift, sleep will be permitted from 04:00 to 12:00. Breakfast will be 1 hour after waking, lunch 5 hours later and dinner 5 hours after lunch. This will permit the retaining of an 8-hour sleep opportunity and thereby minimising any possible effect of acute sleep deprivation. Outcome measures will be assessed on day 2, prior to the phase delay, and on days 3, 5 and 7 (days 1, 3 and 5 after the phase delay), which will allow us to investigate whether metabolic rhythms realign to the new behavioural and light/dark rhythms over the 5 days following the phase delay. The study design allows postprandial responses to be assessed at the same clock time immediately before and after the phase shift (i.e. breakfast and lunch on day 3 occur at exactly the same clock time as lunch and dinner on day 2). Daily energy intake for participants will be set at 1.1 times RMR, which is used as the energy intake required to meet weight maintenance requirements under test conditions. Energy intake will be consumed as three iso-caloric meals at breakfast, lunch and dinner (20% protein, 35% fat and 45% carbohydrate). By analysing participants over the 5 days following the phase shift, we will be able to follow the realignment of each participant's internal rhythms of energy expenditure, metabolism and related endocrine pathways with the newly imposed light/dark cycle. Light and dark exposure (both time and lux) will be controlled on all days with participants blinded to time of day so as not to interfere with their natural circadian rhythm. The gold standard marker of human circadian phase, plasma melatonin concentration, will be measured every hour for up to 15 consecutive samples (e.g. between 16:00 and 06:00). Data will be analysed by calculating the timing of melatonin signal onset, according to validated methodologies (Benloucif et al. 2008). Continuous glucose monitoring and measurements of physical activity using actigraphs will also be undertaken as per the Mealtime Study and worn for the entire 7-day protocol. Resting metabolic rate will be assessed on the morning of all test days and TEF assessed over 5 hours following all three meals of the day: breakfast, lunch and dinner. This will enable us to quantify TEF to specific meals, as well as total TEF across an entire day, and determine changes in response to the phase shift. By simultaneously measuring gastric emptying and metabolites (glucose, insulin, gut hormones and lipids) at the breakfast meals, we will be able to identify whether there are differences in the rate or magnitude of the TEF response in relation to the phase shift and whether these are attributable to differences in gastric emptying, substrate uptake and utilisation. This phase shift study will enable us to assess the influence of the endogenous circadian clock in the regulation of these digestive and metabolic processes and on the individual components of energy expenditure (RMR, TEF, physical activity). Beneficiaries and public health message Our current work aimed to investigate whether the typical meal consumption pattern in the UK, of having a small breakfast and large evening meal, is working against internal biological rhythms and exacerbating difficulties in successful weight management. Complementary research supported by the Scottish government's Rural and Environmental Science and Analytical Services is currently being undertaken at the Rowett Institute to examine how breakfast meal composition (45% calories consumed at breakfast, comparing high fibre vs. high protein) may also affect energy balance and assist in weight management in a similar 10-week weight loss crossover study. Currently, there are no dietary guidelines specific to meal timing and particularly, no guidelines in relation to shift workers. Together these studies will provide evidence-based data for translation to improve dietary guidelines directed at meal timing as an alternative strategy to promote bodyweight control. Dissemination Findings from the Big Breakfast Study will be disseminated to an extensive audience including the scientific community, industry, public and independent bodies and the general public. Specifically, we will produce infographics, short video summaries, press release statements, and written guidelines and media for presentation and distribution to industries (e.g. Scottish Food and Drink Federation), health bodies (e.g. NHS) and independent bodies, as well as presenting information at local and UK-wide public events (e.g. Aberdeen's Caf e Med and Food Matters Live). These broadcasts will be used to highlight the study findings, educate important stakeholders and provide evidence for development of health policy and support opportunities for future studies. Conclusions Early evidence supports morning-loaded energy distribution as a beneficial strategy for weight control. The Big Breakfast Study aims to explore the mechanistic basis for such findings and determine the contribution of the endogenous circadian system to energy expenditure and energy balance. This under-researched area of nutritional science may lead to innovative knowledge, which could pave new ways of addressing metabolic health and obesity via implementing dietary guidelines directed at meal timing. Nuclear and mitochondrial DNA repair in selected eukaryotic aging model systems. Knowledge about the different mechanisms underlying the aging process has increased exponentially in the last decades. The fact that the basic mechanisms involved in the aging process are believed to be universal allows the use of different model systems, from the simplest eukaryotic cells such as fungi to the most complex organisms such as mice or human. As our knowledge on the aging mechanisms in those model systems increases, our understanding of human aging and the potential interventions that we could approach rise significantly. Among the different mechanisms that have been implicated in the aging process, DNA repair is one of the processes which have been suggested to play an important role. Here, we review the latest investigations supporting the role of these mechanisms in the aging process, stressing how beneficial the use of different model systems is. We discuss how human genetic studies as well as several investigations on mammalian models and simpler eukaryotic organisms have contributed to a better understanding of the involvement of DNA repair mechanisms in aging. Introduction Our cells are constantly exposed to endogenous and exogenous agents that induce damage to the cellular macromolecules such as DNA, RNA, proteins, and lipids. The sources of this damage include a broad range of agents such as industrial chemicals and combustion products present in our environment, UV radiation from the sun, and endogenous metabolic byproducts. In contrast to damaged lipids and proteins, damaged DNA, which carries the inherited genetic information of the cell, cannot be replaced. Therefore, formation of DNA lesions can have profound consequences for genomic stability due to the effect that these lesions can have on polymerase fidelity and processivity. Spontaneous reactions, such as hydrolysis, are the major sources of DNA damage. They can lead to deaminated bases and abasic sites in the DNA. Another very prominent type of endogenous DNA damage, oxidative DNA damage, is caused by reactive oxygen species (ROS), which are formed continuously as a consequence of normal aerobic metabolism during mitochondrial respiration but also by inflammatory responses. ROS can also be formed by a number of external factors including UV-and ionizing radiation and chemical mutagens. DNA repair mechanisms have evolved to remove the majority of all DNA lesions, but if these mechanisms are not sufficiently efficient, it will lead to DNA damage accumulation, which is likely to result in mutations and cellular dysfunction. Due to close proximity of the mitochondrial DNA to the inner mitochondrial membrane, the mitochondrial genome is more heavily exposed to ROS than the nuclear DNA and therefore also more likely to experience DNA damage. Thus, the mitochondrial free radical theory of aging [1] postulates that organisms age due to the accumulation of DNA damage and mutations in the mitochondrial DNA, leading to mitochondrial and eventually cellular dysfunction. This paper explores some of the recent research, which has been performed in order to uncover the relationship between DNA damage, DNA repair 2 Oxidative Medicine and Cellular Longevity mechanisms, and the aging process, and emphasis is given to the use of eukaryotic model systems for this area of research. DNA Damage and Aging Among the wide variety of known DNA lesions, 8-oxodeoxyguanosine (8oxoG) has received

a lot of attention due to its mutagenicity and because of the possible correlation between its accumulation and pathological processes like cancer, degenerative diseases, and aging. However, an increasing number of studies also include other types of DNA lesions. Numerous studies report measurement of DNA damage in nuclear and mitochondrial DNA from tissues of young and old organisms, with variable outcomes. Although still controversial, several careful studies do show that 8oxoG accumulates with age. Thus, in a recent study Gan and coworkers used a sensitive LC-MS/MS method to demonstrate that 8oxoG increases with age in DNA in a number of different mouse tissues, with the largest age-dependent increase in brain [2]. Likewise, it was shown in another recent study that the oxidative DNA lesion 8,5 -cyclopurine-2 -deoxynucleoside accumulates with age in a tissue specific manner in mouse [3]. Using a high-performance liquid chromatography-electrochemical-detector Lee and coworkers showed a positive correlation between the level of 8oxoG in DNA and age in human gastric tissue [4]. Importantly, Hudson and coworkers have shown that 8oxoG increases three-fold with age in mitochondrial DNA of rat heart [5] and a number of other studies have reported similar results for mitochondria of other tissues including postmitotic tissues (reviewed in [6]). Beside being exposed to endogenous ROS, the DNA of for example skin cells may also be heavily exposed to environmental factors such as UV irradiation due to sun light exposure. Photodamage leads to thymine dimers, 6-4 photoproducts, and ROS that damage genomic DNA and give rise to mutations in coding or regulatory DNA sequences of critical genes. The protective repeated DNA sequences at the end of our chromosomes, the telomeres, are disproportionately damaged by both UV and ROS, due to their greater proportion of target TT and G bases compared with the chromosomes overall. Such damage is postulated to disrupt the telomeric loop, expose the TTAGGG overhang, and promote aging (reviewed in [7]). UV radiation produced ROS may also activate cell surface receptors, which eventually leads to reduced dermal matrix formation. In dermal fibroblasts, UV irradiation also induces mitochondrial DNA deletions, leading to compromised synthesis of mitochondrial proteins, further increase of reactive oxygen species (ROS), and decreased ability of the cell to generate energy. Epidemiological studies suggest that smoking is another important environmental factor in skin aging. Exposure to tobacco smoke causes DNA single-strand breaks, aromatic adducts, and oxidative damage to DNA, chromosome aberrations, and micronuclei (reviewed in [8]). ROS in tobacco smoke also increases the expression of matrix metalloproteinases, and the elevated enzyme levels are suggested to lead to the degradation of collagen and elastic fibers in the skin [9]. Finally, DNA double strand breaks pose severe problems for cells and this type of DNA damage also seems to increase with age in various tissues [10,11]. Nuclear and Mitochondrial DNA Repair Pathways Due to the serious consequences that DNA damage accumulation may have on cellular function and survival, different pathways of DNA repair have evolved in order to prevent it. DNA repair pathways have mainly been investigated in the nucleus; however, some of the known pathways have also been described in mitochondria ( Figure 1). Nucleotide Excision Repair (NER). In nuclear DNA, the NER mechanism can remove numerous types of helix distorting and bulky lesions. Additionally, NER is central for the repair of DNA cross-links. Briefly, the NER pathway includes damage recognition, opening of the DNA helix, incision of the nucleotides surrounding the lesion, gap filling replication, and ligation. NER has two subpathways with different ways of detecting lesions: the global genome (GG) NER and transcription coupled (TC) NER. Damage recognition of the NER is accomplished through sequential actions of multiple proteins. For GG-NER destabilization of the base pairing is detected by xeroderma pigmentosum complementation group C (XPC) protein in complex with the human homologue Rad23B (hHR23B) protein, which is suggested by many studies to be the first protein factor to arrive at the lesion, and it ensures a broad spectrum of substrate specificity. Additionally, UV-damaged DNAbinding protein (UV-DDB) recognizes particular types of lesions, such as UV-induced photoproducts, thereby recruiting XPC and extending the substrate specificity [12]. For TC-NER, damage recognition is believed to be caused by the blockage of the transcribing RNA polymerase II on the damaged DNA template. TC-NER is then initiated by the Cockayne Syndrome complementation group B (CSB) protein, later followed by the CSA gene product. In both GG-NER and TC-NER, the lesion recognition step is followed by recruitment of TFIIH. The XPB and XPD helicases from the 10-subunit TFIIH complex unwind the DNA around the lesion. The initial open complex is stabilized by XPG and XPA, verifying the lesion, and by RPA, which binds the opposite intact single-stranded DNA. The structure-specific endonucleases XPG and ERCC1/XPF cleave 3 and 5 of the lesion, respectively. The resulting 24-32 nucleotide fragment, containing the lesion, is removed and the remaining singlestrand gap filled by the replication machinery and the resulting nick is sealed by ligase I or ligase III [13,14]. NER does not seem to take place in mitochondria (reviewed in [15]). Base Excision Repair (BER). The BER pathway is responsible for the repair of a broad spectrum of DNA base adducts. BER takes place both in nuclei and mitochondria and is therefore the main guardian against endogenously derived DNA lesions in the nucleus as well as the mitochondria [16,17]. Thus, the BER pathway is very critical for the Base maintenance of genomic stability [18]. As described in the introduction, one of the most prominent theories of aging, the mitochondrial free radical theory of aging, states that free radicals generated in mitochondria are involved in the intrinsic aging process, mainly due to the accumulation of oxidative damage and derived mutations in mtDNA [19,20]. The relevance of BER mechanisms have been highlighted by studies in yeast and animal models reporting that defects in BER enzymes shorten chronological life span and are associated with aging or age-related diseases [21,22]. Briefly, the BER pathway is initiated by removal of the modified base by a lesion-specific mono-or bifunctional DNA glycosylase, which leaves an apurinic/apyrimidinic site (AP site). AP sites are incised by AP endonuclease 1 (APE1) generating single-strand breaks (SSBs). End processing of SSBs is necessary, since they contain obstructive 3 or 5 termini, and this is performed by polymerase β (Polβ), APE1, or polynucleotide kinase 3 -phosphatase (PNKP) depending on the specific terminus. Completion of the BER pathway is performed by either of two subpathways: short-patch BER or long-patch BER [23]. In the nucleus, the final steps of the short-patch BER pathway include filling of the single nucleotide gap by Polβ assisted by the scaffold protein XRCC1, and subsequently ligation by ligase 3α. In the longpatch BER pathway, one or two polymerases (Polβ and Polδ/ε) fill in the 2-13 nucleotides gap assisted by additional proteins (PCNA, RFC, and Fen1) followed by ligation by ligase I. Recently, both subpathways have been described to take place in mitochondria as well [24,25]. In mitochondria, the only polymerase in charge of the gap filling is the polymerase γ (polγ) (reviewed in [18]). Mismatch Repair (MMR). Mismatched nucleotides cause genomic instability and are generated when errors of DNA polymerase escape their proofreading activity or, for example, polymerase slippage occurs at repetitive sequences. The MMR pathway was previously considered exclusively to take place in the nucleus, but several reports have indicated some form of mitochondrial MMR activity (reviewed in [15]). Briefly, the eukaryotic nuclear MMR pathway can be divided into four consecutive steps. (i) Recognition and binding of a mismatch by either a MSH2-MSH6 or MSH2-MSH3 heterodimeric ATPase complex. MSH2-MSH6 preferentially recognizes base-base mismatches and insertion-deletion loops of 1-2 nucleotides while MSH2-MSH3 has preference for larger insertion-deletion loops. The mismatch-bound MSH2-MSH6 (or MSH2-MSH3) complex recruits the MLH1-PMS2 complex in order to form a ternary complex. A proliferating cell nuclear antigen (PCNA) clamp recruits MMR proteins to the replication fork while the clamp loader replication factor C (RFC) loads PCNA. A strand-specific nick or gap, which may reside either 5 or 3 to the mismatch, is sufficient to direct repair in 5 -and 3 -directed MMR, respectively. (ii) Excision is performed by the exonuclease EXO1 in both 3 -and 5 -directed MMR. RPA binds to protect the single-stranded DNA during the excision and to facilitate the following DNA repair synthesis. (iii) Repair synthesis is accurately performed by Polδ. (iv) Ligation of the remaining nicks after DNA synthesis is performed by ligase I (reviewed in [26]). MMR proteins have been identified in yeast and coral mitochondria but MMR complexes, as we know them from the nucleus, have not yet been detected in human mitochondria. Still, human mitochondria do seem to have mismatch-repair activity, which involves proteins distinct from nuclear MMR. One of these proteins is the repair factor YB-1 [27]. Recombinational Repair. DNA double-strand breaks (DSBs) are some of the most hazardous DNA lesions, since they can lead to genome rearrangements. The DSB repair pathway is regulated by several phosphorylation events, starting immediately after DSB formation, where large numbers of the histone protein H2AX are phosphorylated (γH2AX) and accumulate in the chromatin around the break [28,29]. Several DSB damage response proteins accumulate in foci around DSBs and send signals via signal transducers to a set of downstream effectors, which affect events like DNA repair, cell cycle checkpoints, telomere maintenance, and transcription. Two major mechanisms exist to repair DSBs: homologous recombinational repair (HRR) and nonhomologous end joining (NHEJ). The main difference between the two major DSB repair pathways is the error-prone nature of NHEJ in contrast to the error-free HRR. The balance between the DSB repair pathways differs among species, cell types, and during the phases of the cell cycle [30]. The NHEJ pathway takes place throughout the cell cycle, whereas HRR repairs DSBs during the S and G2 phase of the cell cycle [31]. Recognition of DSBs in NHEJ is performed by the Ku70/80 heterodimer, which also recruits DNA PKcs forming a DNA PK complex on both sides of the DSB [32,33]. The DNA ends are processed followed by autophosphorylation of DNA PKcs that regulates the final ligation [34]. HRR uses homologous sequences in sister chromatids to repair DSBs, especially those formed at collapsed replication forks. Phosphorylation of BRCA1 (by ATM, ATR, and CHK2) regulates the MRN end processes. Then the 3 ssDNA ends are bound to RPA, and following several phosphorylation steps and the action of different enzymes (Rad52, BRCA2, and CDKs), the 3 ssDNA ends are bound to Rad51 leading to the formation of a nucleoprotein filament that invades a homologous sequence. The invading and complimentary strands extend and once all intermediates are repaired, the HRR pathway is terminated. DSBs are believed to contribute to mtDNA rearrangements observed during aging [35]. Although some reports have suggested mitochondrial recombinational repair in model organisms (yeast and Drosophila melanogaster) [36][37][38], our knowledge of mammalian mtDNA recombination is still limited (reviewed in [39]). Human Aging and Single-Nucleotide Polymorphisms (SNPs) in Genes Related to DNA Repair Mechanisms The involvement of genetic factors on longevity has been investigated by heritability studies using twin cohorts. The Oxidative Medicine and Cellular Longevity 5 concept of heritability is valuable for identifying to which extend individual genetic differences contribute to observed individual differences for a specific trait in a study population [40]. Several of those heritability studies have suggested that additive genetic factors account for a quarter to one-third of the variation in human lifespan [41][42][43]. Thus, epidemiological geneticists have been searching for genes involved in longevity, and recent population studies have investigated correlations of numerous single-nucleotide polymorphisms (SNPs) with longevity in order to identify longevity genes. One gene that has been described to strongly relate to longevity is the forkhead box O3A (FOXO3) [44,45], which is a transcription factor involved in apoptosis and protection from oxidative stress [46]. Additionally, FOXO3 regulates the stress resistance of cells by facilitating the repair of damaged DNA [47]. Similar studies with other genes have led to the conclusion that it may be possible to identify genetic variants that affect lifespan, inspiring human geneticists to investigate different candidate genes that may be involved in human longevity. Genes related to the maintenance of DNA stability are among those candidate genes. Initial findings were obtained by analyzing single or a few SNPs in selected candidate genes. The human exonuclease 1 (EXO1) gene was identified as a potential

longevity candidate gene by investigating SNPs in approximately 400 German and French centenarians [48]. EXO1 is a 5 -3 exonuclease participating in MMR and homologous recombination [49]. Interestingly, EXO1 also interacts with the WRN protein. As will be described in more detail later, WRN protein is crucial for the maintenance of genomic stability [50]. Additionally, an association study on SNPs in the WRN gene suggested associations between WRN polymorphisms, longevity, and age-associated diseases in Mexican and Finnish populations [51]. Hence, WRN is suggested to be a longevity candidate gene. The antioxidant enzymes superoxide dismutases (SOD1 and SOD2) are responsible for converting superoxide radicals, which are harmful to macromolecules and to oxygen and hydrogen peroxide. Variations in SOD1 and SOD2 were shown to influence human longevity, and thus also suggested as candidate genes for longevity [52]. Despite that some studies suggest central DNA repair and antioxidant genes as candidate longevity genes, it has been difficult to replicate these findings in independent study populations. Thus, identification of universal longevity polymorphisms is a difficult task, due to the fact that genetics of longevity seems to be extremely complicated. It is now widely accepted that complex traits, such as longevity, are determined by numerous genes with small effects, and results from single SNP analysis provide limited biological insight. Instead of analyzing single SNPs, recent studies have investigated combined effect of a group of SNPs located in genes involved in the same biological pathway. Successive to the HapMap project [53], the tagging SNP approach is considered a stronger approach than investigating few gene variations, since the most common gene variations in the entire gene is covered. The most comprehensive study of large collections of longevity candidate variations to date has identified novel SNPs to be associated with human longevity [54]. By a case control design, including 1089 oldest-old and 736 middle-aged, Danes, Soerensen and coworkers investigated several rare allele variants in genes involved in DNA metabolism, such as BER genes (NTHL1, Polβ, and WRN) and DSB repair genes (RAD52, H2AFX, XRCC5, and WRN). By a longitudinal study approach, SNPs located in genes coding for DNA repair and antioxidant gene products were identified to associate with longevity [54]. Rare allele variants of MLH1, involved in MMR, and XRCC5, involved in DSB repair, as well as rare allele variants of XDH and TXNRD1, pro-and antioxidant enzymes, were advantageous, whereas the presence of rare allele variants in H2AFX, related to nucleosome formation and DNA damage signaling, appeared disadvantageous for longevity. Together, the studies suggest new candidate variations for human longevity located in pro-/antioxidant, DNA damage signaling and DNA repair genes, and highlight the importance of functional studies of the molecular effects of these newly presented candidate variants [54]. Increased telomere length has been associated with longevity in human leukocytes [55], and decreased telomere length in leukocytes has been associated with increased mortality [56]. At the telomere ends, T-loops are formed, which stabilize the telomeric region and prevent the ends from being recognized as DNA breaks by DNA repair proteins. The shelterin complex holds the T-loop together, protecting the telomeres [57]. Absence of T-loops will allow NHEJ at the telomeric ends, resulting in chromosomal fusion. The telomere length is regulated by telomerases and associated factors [58]. Recent studies have investigated the associations between telomere length and SNPs in telomerase and shelterin genes [55,[59][60][61][62]. The most promising results have been reported in relation to TERC and TERT genes; interestingly two of these studies have also described associations between the TERT and TERC genes and human longevity [55,61]. Age Regulation of DNA Repair in Human Population Studies Previous studies investigating SSBR in peripheral blood mononuclear cells (PBMCs) from differently aged donors suggest minor or no effect of age [63][64][65][66]; however, the endogenous level of SSBs was found to be significantly higher at old age [67][68][69]. An age-related decline of NHEJ functions in brain tissue has been suggested from animal studies [70,71]. In line with these results, PBMCs from elderly humans showed reduced nuclear localization and DNA binding of the NHEJ specific Ku70/80 complex compared to PBMCs from young humans [72]. In another study, PMBCs showed an age-related decline of Ku70 levels [73], and a different study reported declining levels of Ku80 with age [74]. Using a host cell reactivation assay, Wei and coworkers found that the human NER capacity in PMBCs declines with approximately 0.6% per year [75]. Together, these studies suggest biological changes in DNA repair with age, while powerful functional studies are missing. Animal Models as a Useful Approach to Human Aging As previously described, DNA repair pathways have evolved as important systems for maintenance of DNA stability and cell survival. Proteins in the main DNA repair pathways are highly conserved [76,77], and such high degree of conservation indicates that DNA repair pathways are fundamental mechanisms in cell survival. As observed in other DNA repair pathways, many of the genes involved in the BER pathway are highly conserved from bacteria to humans [78][79][80]. Since aging mechanisms have been proposed to be universal [81], animal models have become an excellent tool for investigation of the molecular mechanisms involved in the human aging process, including DNA repair pathways. One of the main advantages of animal models is that most of them have relatively short life span and that genetic modification is possible. Along with mammalian models, aging research studies and DNA metabolism include unicellular organisms and multicellular eukaryotes such as D. melanogaster, Caenorhabditis elegans, [82][83][84][85], or filamentous fungi like Podospora anserina [80,86]. Investigations in these models have contributed notably to the understanding of the role of DNA repair mechanisms in the aging process in humans, particularly those taking place in mitochondria. One of the first studies using mammalian models for investigating the relation between aging and DNA repair mechanisms was the one performed by Hart and Setlow [87]. They investigated the repair of UV-light induced DNA damage in fibroblasts of different mammalian species, reporting that DNA repair activity was inversely correlated to the maximum life span potential (MLSP) [87]. In a similar recent investigation on C. elegans strains showing different longevities, long-lived strains showed higher rates of UV-induced DNA damage repair than the wildtype nematodes [83]. Comparative studies using different mammalian species have also been used in order to investigate the correlation between BER mechanisms and MLSP. Brown and Stuart reported no correlation, when nuclear BER activities were analyzed in mammalian dermal fibroblasts [88]. Up to now, no investigation has been performed analyzing the correlation between mitochondrial BER and MLSP. Compiling evidence supports that during aging alterations in BER capacity occur, age-related deficiencies in those mechanisms play an important role in cell function and survival, particularly in postmitotic tissues. As mentioned above, the mtBER pathway is highly conserved among mammalian species, and mice are widely used for investigating the role of mtBER in the aging process. Mitochondrial BER capacity has been described to be organ-specific, with the brain being one of the tissues with the lowest capacity [89]. Various studies have investigated the role of changes in mitochondrial BER in age-related functional decline, showing tissue specific age-related changes. Although some studies have observed a reduction in mtBER with aging in rat liver mitochondria [90], most of the investigations in murine mitochondria from hepatic and cardiac tissues have reported increases in APE1 activity and increases or no changes in DNA glycosylase activities during aging [91][92][93]. On the other hand, a general decline in DNA glycosylase activity has been observed in brain cortical mitochondria in rats [94] and mice [95,96]. These results support the idea that mtBER plays a critical role in the maintenance of the central nervous system during aging [97]. We have reported significant differences in mtBER among various mouse brain regions during aging. Thus, we found that in cortical mitochondria, DNA glycosylase activities peaked at middle age followed by a significant drop at old age. However, only minor changes were observed in hippocampal mitochondria during the whole lifespan of the animals. Mitochondrial AP endonuclease activity increased in old animals in both brain regions [96]. The cortical region and the cerebellum have been described to accumulate less mtDNA lesions with aging and to be more resistant to oxidative stress conditions [98][99][100]. Interestingly, those regions showed higher BER capacity than hippocampus, which has been described to be a much more vulnerable region in the brain [98,99]. A recent investigation also supports the relevance of mtBER in brain aging and stresses the importance of the central nervous system heterogeneity in these processes, since the age-related decline in brain mtBER seems to occur specifically at the synapses [101]. Although investigations on mtBER in humans are scarce, results obtained on mitochondrial, nuclear, or total BER from central nervous system cell cultures or even postmortem neuronal human tissue suggest that the results obtained from mouse studies can be transferred into humans. Thus, increasing Ogg1 activity in mitochondria from oligodendrocytes after targeting hOGG1 into mitochondria increases cell survival and protects against induced-oxidative stress [102]. Moreover, Weissman and coworkers reported that a significant decline in total BER takes place in the cortical area of Alzheimer's patients [103]. Postmitotic tissues are specially affected during aging, and an age-related decline has also been reported in mtBER in skeletal muscle [104], which has been suggested to contribute to age-related sarcopenia. Studies in the aging model P. anserina have also shown that aging is associated with a decrease in mitochondrial BER [80], likely contributing to the observed mtDNA instability in the aged fungi [105]. An important approach in the study of the role of DNA repair in the aging process is the development of several knockout (KO) mice. Among them, those models being deficient in essential enzymes in the BER pathway have resulted in embryonic lethality, such as APE1 or Polβ or ligase III [106][107][108], revealing the importance of these enzymes in cellular survival. Since DNA glycosylases have a certain grade of overlapping activity, KO mice for these enzymes generally result in elevated levels of DNA lesions but no apparent aging phenotype, although some KO mice show higher incidence of cancer [109][110][111]. Mice mutated in Ku70 or Ku80, proteins involved in repair of DSBs, display an early aging phenotype [112], and are therefore an interesting model for studying the role of NHEJ in aging. Also, Ercc1 and Xpf mutant mice, with a defect in NER and cross-link repair, display reduced lifespan and a broad range of aging-associated changes at an early age, and thus provides another valuable model for studying the role of DNA repair mechanisms in aging [113]. Mice carrying a specific XPD point mutation found in several patients suffering from trichothiodystrophy (TTD) recapitulate the human disorder to a great extent, but in addition they display pathology consistent with accelerated aging (reviewed in [114]). A mouse model developed in the last decade, the mitochondrial mutator mouse, appears as an interesting model in which to investigate the causative link between mtDNA mutation accumulation and aging, and the role that mtBER may play in the process [115,116]. Moreover, the generation of this knock-in mouse expressing proof-reading deficient Polγ, but conserved replicative function, is considered by some authors as an important support of accelerated mtDNA mutation rate resulting in increased aging rate [117,118]. In various tissues of this mouse model, mtDNA point mutations as well as mtDNA deletions accumulate at a much higher rate than in the wildtype mice [115,116]. However, whether it is the accumulation of mtDNA deletions or point mutations that drive the premature aging phenotype and the precise mechanisms are still discussed [119,120]. Some animal models have also been used in order to investigate the role of DNA repair mechanisms on agerelated diseases, mainly age-related neurodegenerative diseases. Thus, different mouse models have been created in attempts to elucidate the underlying molecular mechanisms for disorders such as Alzheimer's (AD), Parkinson's (PD), or Huntington's disease (HD), and some of them have been used to investigate the potential role of DNA repair in those disorders [14,121]. Investigations of age-related neurodegenerative diseases on humans are normally limited to postmortem tissue samples; consequently, animal models of those diseases are very valuable. However, the results observed in animal models do not always match those found in humans. For instance, although a general decline in BER has been described in postmortem cortical tissue in AD patients [103], no changes have been observed in BER mechanisms when

the investigations have been performed in the APP and 3xTgAD mouse models [101,122]. Interestingly, these particular models, unlike humans, do not display neurodegeneration despite the fact that both amyloid-β plaques and neurofibrillary tangles accumulate. Two well-established mouse models for HD have related DNA repair mechanisms with the progression of the disease. Whereas investigations on the HdhQ111 knock-in mice have supported the role of mismatch repair proteins in HD [123,124], studies on R6/1 mice have revealed the contribution of BER enzymes, particularly OGG1, to CAG expansion in somatic cells that takes place in HD [121]. A recent report suggests that CSB may also be involved in promoting CAG repeat expansion in HD [125,126]. Premature Aging Syndromes Finally, another important approach to human aging is the study of genetically inherited premature aging syndromes. Such syndromes have been widely used as valuable tools in understanding the normal aging process [127]. Similarly to age-related neurodegenerative diseases, the investigation of human tissues in these syndromes is limited due to scarcely available tissue samples. Thus, research on mouse models and established human cell lines has been critical for understanding some of the mechanisms involved in premature aging syndromes and furthermore increased the understanding of the normal aging process in humans. The DNA repair defective disease Cockayne syndrome (CS), which is a segmental premature aging syndrome, is associated with severe developmental deficiencies and neurodegeneration. Although transcription coupled NER (TC-NER) is a prominent DNA repair pathway affected in this syndrome, an increasing number of investigations indicate that BER is affected as well [128]. In the last years, the investigations that have been carried out on different models of CS, particularly on the models of CSB, have dramatically improved our knowledge about this syndrome and the several roles that the CSB protein plays in genomic stability and cellular survival. Along with the alterations in TC-NER, deficiency in the repair of 8oxoG was initially reported both in whole cell extracts [129] and in mitochondria from mammalian CSB-deficient cells [130]. Moreover, CSB seems to play a role in general mitochondrial maintenance [131]. In accordance, the CSB protein, which was thought to be present exclusively in the nucleus, has recently been shown to localize to mitochondria [132]. This investigation suggests that CSB protein plays a direct role in mtBER by interacting and stabilizing BER proteins in the protein-DNA complexes associated with the inner mitochondrial membrane when mtDNA repair takes place. In addition, it has recently been reported that CSB-deficient cells show higher free radical production and accumulation of damaged mitochondria together with altered mitochondrial autophagy [133]. Thus, the authors suggest that CSB may act as an mtDNA damage sensor, inducing mitochondrial autophagy in response to stress. Werner syndrome (WS) is another genetically inherited premature aging syndrome, which has been studied intensely with regard to the molecular role of the affected gene product, WRN. The syndrome is characterized by premature graying and thinning of hair, cataracts, diabetes mellitus, osteoporosis, and a number of other typical age-associated deficiencies. The affected WRN protein is a member of the so-called RecQ helicases and orthologs exist in a wide variety of organisms such as Saccharomyces cerevisiae, Schizosaccharomyces pombe, C. elegans, and Xenopus laevis (reviewed in [134]). Based on cellular and biochemical studies of WRN-deficient cell lines, the WRN protein has been suggested to have multiple roles in DNA repair. Hence, the protein interacts with several DNA repair proteins, which are involved in BER, NHEJ, or HHR. This is in agreement with the fact that WS cells show phenotypes such as nonhomologous chromosome exchanges and large chromosomal deletions, caused by deficiency of DSBR [135], and accumulation of, for example, Fapy lesions, which are induced by ROS [136]. In conclusion increasing evidence suggests that DNA repair mechanisms are involved in the aging process. Additional studies using various model systems will help us gain an even better understanding on the functional relationship between these associations. Sustaining University Operations During the COVID-19 Pandemic Colleges and universities around the world engaged diverse strategies during the COVID-19 pandemic. Baylor University, a community of ˜22,700 individuals, was 1 of the institutions which resumed and sustained operations. The key strategy was establishment of multidisciplinary teams to develop mitigation strategies and priority areas for action. This population-based team approach along with implementation of a “Swiss Cheese” risk mitigation model allowed small clusters to be rapidly addressed through testing, surveillance, tracing, isolation, and quarantine. These efforts were supported by health protocols including face coverings, social distancing, and compliance monitoring. As a result, activities were sustained from August 1 to December 8, 2020. There were 62,970 COVID-19 tests conducted with 1435 people testing positive for a positivity rate of 2.28%. A total of 1670 COVID-19 cases were identified with 235 self-reports. The mean number of tests per week was 3500 with approximately 80 of these positive (11/d). More than 60 student tracers were trained with over 120 personnel available to contact trace, at a ratio of 1 per 400 university members. The successes and lessons learned provide a framework and pathway for similar institutions to mitigate the ongoing impacts of COVID-19 and sustain operations during a global pandemic. To provide a framework and pathway for colleges and similar institutions to mitigate the impact of novel coronavirus disease 2019 and sustain operations, here we reflect on our experience operating during a pandemic. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, which is driving the COVID-19 pandemic, is unique and particularly challenging for institutions to manage and control. This reality is the result of a combination of SARS-CoV-2 virus biology and epidemiology, as well as the behaviors of college students. The virus has a short latency period and is effectively spread by means of both asymptomatic and symptomatic transmission. Enabling spread among large groups of socially interacting individuals, sometimes in relatively confined spaces. COVID-19 is both similar and different from the recent Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS) outbreaks. 1 The global challenge posed by COVID-19 was recognized by the World Health Organization (WHO) when the outbreak was declared a Public Health Emergency of International Concern (PHEIC) on January 30, 2020, and then a pandemic on March 11, 2020. 2,3 A national emergency was declared in the United States on March 13, 2020. 4 Before this, Baylor University actively began addressing COVID-19 risks in January 2020 by postponing University-sponsored travel to China and then South Korea in February 2020. This was soon followed by travel restrictions to other countries and across the United States. Baylor University formally moved to online instruction on March 16 until commencement of the Fall semester on August 24, 2020. 5 To resume and sustain operations during the COVID-19 pandemic, Baylor University established multidisciplinary teams to develop, guide, and support implementation of public health measures. Baylor University, chartered in 1845 in Waco, Texas, United States, is a private nonprofit Christian university. As of Fall 2020, Baylor had 19,297 students (14,399 undergraduates and 4898 students in graduate and professional programs) with 4736 living on campus. Overall, the in-session Baylor community of students, faculty, and staff was approximately 22,700 individuals. Baylor University is considered 1 of the major employers in the city of Waco and McLennan County, which has an estimated 256,600 residents. 6 There was recognition soon after going online in March that the university needed to find a way to safely reopen for the Fall 2020 semester to help students, staff, faculty, contractors, and the Waco community navigate the challenges presented by COVID- 19. In appreciation of these challenges, a "Swiss Cheese" risk mitigation model was applied. 7 This type of model accounts for the complexities associated with reducing inherent risks by applying multiple layers of protection to mitigate or eliminate hazards. 8 For example, the presence of any weakness or hole in any layer (face covering noncompliance) is offset by the strengths of another layer of intervention (social distancing). 8 Also embedded in the method we used was the principle of population-based management. 9 This multidisciplinary approach recognizes no one authority or organization possesses all the resources and expertise required to mitigate COVID-19 risks, sustain operations, and address the unprecedented lateral communications and decision-making processes required to succeed. 9,10 Planning for the semester commenced with development of strategic priorities using a multisectoral team. Sub-teams were subsequently established, which included representatives with expertise in public health, infectious disease, epidemiology, critical care and clinical medicine, environmental health, emergency management, education, employment, sociology, law, procurement, laboratory management, toxicology, student support services, facilities management, information technology, wastewater, and residential accommodation. This approach was complemented by tabletop exercises, scenario planning, and ongoing engagement with city and county representatives at operational and leadership levels. Our teams focused on analyzing data and trends, contact tracing, testing, support services, and compliance, and evaluating public health measures, alternative strategies, and proposed campus events. Baylor University applied a hybrid instruction model, with students having the options to attend class on campus (with face-toface or hybrid instruction) or remain remote (with complete online instruction). Approximately 1600 course sections (39% of total offerings) were held in-person with face covering and social distancing requirements. Of all offered sections, 25% were taught in a hybrid format and 36% were fully online. Crowd capacities were limited to 25% for athletic events. 11 To mitigate transmission, there were limitations on nonuniversity events. At the center of the mitigation measures were health protocols. This included face coverings and social distancing supported by universal entry screening, testing before arrival on campus, randomized testing (surveillance), testing of symptomatic and exposed individuals, and wastewater (sewage) monitoring for SARS-CoV-2 viral RNA. The overall strategy was selected because transmission risks in colleges are complex and unique. For example, transmission could occur in college classroom settings if there was no mandatory face coverings, insufficient physical distancing, or inadequate hand hygiene; residential and social settings also posed a significant risk. 12 Further information about the methodology is provided here. Methods All descriptive data presented were available to the Baylor teams overseeing strategies to mitigate the impact of COVID-19. Most of the data (except isolation, quarantine, and sewage data) were publicly available on Baylor's external website. Microsoft Power BI and Microsoft Excel were used to collect, collate, and display these data, which were de-identified and actively analyzed to inform decision making and situational awareness throughout the Fall 2020 semester. These activities, as part of public health surveillance, met exclusion criteria for institutional review board approval per 45 CFR 46.102(e) & (l). Baylor University used a multisectoral systems approach to mitigate COVID-19 risks and sustain operations ( Figure 1). This included teams focused on governance, health protocols, sewage surveillance, testing (surveillance, symptomatic, and contact), contact tracing, data analysis and trends, support services, and communications. Further detail about the methodology used to mitigate COVID-19 risks and sustain operations (teams and the roles) is described in the following. Governance Baylor's Board of Regents (BOR) has fiduciary responsibility for the university. Because of the potential impact of the COVID-19 pandemic, the Chair of the BOR convened the Executive Committee of the BOR weekly and the full BOR monthly throughout the summer of 2020. This allowed the President and the President's Council (PC) to update and inform the BOR of planning for the Fall 2020 semester and provided an opportunity to address any concerns. The PC is led by the President and consists of senior university leadership including the Provost, General Counsel, Chief Business Officer, Special Advisor to the President for Equity and Campus Engagement, and Vice Presidents for Advancement, Athletics, Human Resources, Marketing, and Student Life. This continued with less frequency throughout the Fall semester. Externally, the President and nominated representatives from Baylor attended the Waco and McLennan County COVID-19 health briefings, which were held 3 times weekly. Throughout the pandemic, the President convened her council at least 3 times weekly to learn about campus conditions and to review and act on proposals across the university. PC was responsible for all final approvals of decisions that had campus-wide impact, such as the testing plan and large on-campus events, as well as budgetary reductions; PC functioned similar to a local board of health. Project 8.24 was formed, which involved a campus-wide team that worked with the Provost's Office, Division of Student Life, and other groups to develop and evaluate plans and decision timelines for the Fall semester.

13 This was co-chaired by the Provost and General Counsel. After Project 8.24, this work was completed, and implementation became the focus. A Dashboard task force was formed, reviewed data daily, and provided a daily summary of conditions to the Provost, highlighting notable changes. The Provost convened weekly with academic leadership of the university, including Vice Provosts, Deans, Associate Deans, Registrar, and Faculty Senate Chair to create a schedule of classes meeting social distancing requirements, address technology and professional development needs for online teaching modalities, create and evaluate academic policies on issues such as attendance and face coverings, and communicate decisions made by the PC. As the semester commenced, a multidisciplinary health management team was formed and met daily to work through emerging policy issues, recommend intervention strategies, and review proposed events. The recommendations from this group were presented to PC for decision. Facilities Management An extensive analysis of heating, ventilation, and air conditioning (HVAC) of all buildings was conducted by Baylor's facility management team. Many HVAC systems were upgraded with an ultraviolet (UV) light and increased minimum efficiency reporting value (MERV) filtration, and all were modified to maximize external air flow intake and circulation. Cleaning protocols were reviewed for each facility and were increased in terms in both intensity and frequency. Particular attention was paid to residence halls and other higher-density communal areas. This was complemented by multiple external tents for study, approved small events and testing, disinfection supplies in all classrooms, and installation of 600 hand sanitizer stations campus wide with 12 million doses available. Health Protocols As recommended by the CDC and others, face coverings and social distancing were central to our implemented health protocols. Faculty, students, and staff were required to wear face coverings (prohibiting coverings like bandanas, neck gaiters, or masks with valves; and enforcing proper usage with a secure fit over both the mouth and nose) inside, at events, and wherever social distancing was not possible outdoors. Electrostatic sprayers were procured and used to disinfect high traffic areas in buildings twice daily. Residence hall rooms, classrooms, and offices were disinfected on the same day positive COVID-19 tests were reported from occupants in each room. Dining facilities were disinfected after every meal. A Campus Safety Ambassador Program was used to rally 2 dozen volunteers at key high traffic locations across campus in the first few weeks of the Fall semester. The volunteers modeled safe distancing practices, assisted with questions, and positively reinforced a clean campus as students returned. This effort included directing students to resources and information as well as offering hand sanitizer and masks as needed. A private company was contracted to support monitoring of compliance with the Disaster Medicine and Public Health Preparedness 3 safety protocols throughout the semester. This was complemented by providing students, faculty, and staff with hygiene kits (including 2 face coverings, hand sanitizer, thermometer, and COVID-19 disease information), campus wide signage, and ongoing information about safety measures. Sewage Surveillance Sewage (or wastewater-based) epidemiology represents an established, integrative, and equitable population health surveillance approach. Spatially resolved examination of "sewersheds" supports population understanding of drugs of abuse consumption, 14 disease burdens (eg, polio 15,16 ), and socioeconomics. 17 Because SARS-CoV-2 is shed in feces 18 before presentation of clinical symptoms, 19 sewage surveillance systems may provide lead indicators of COVID-19 emergence within a community, inform effectiveness of public health interventions, and examine implications of phased reopening of businesses or on campus activities. [20][21][22] During Fall 2020 semester, there was weekly sewage sampling of campus student residence halls and an isolation facility (hotel) using time composited auto-sampling. Initially, wastewater collection systems were reviewed. Through this process, sampling locations were identified, and weekly collection of 24-h composite sampling was implemented. Sewage samples, along with duplicates and field blanks, were examined for SARS-CoV-2 viral RNA, which was normalized to respective hall occupancy. Because sewage detection of SARS-CoV-2 RNA precedes clinical symptoms, this data stream was integrated within our internal COVID-19 dashboard and supported decisions for targeted testing of specific on-campus locations. During Spring semester 2021, we continued sewage surveillance efforts parallel to our externally supported research examining sewersheds and COVID-19 epidemiology in local communities. Pre-arrival Commercially available test kits were shipped to students, staff, and faculty before returning to campus. The university contracted with a company to provide an at home-sample kit, which was mailed to a laboratory after collection. The pretesting involved a self-administered nasal swab followed by quantitative polymerase chain reaction (qPCR) analysis (with US FDA emergency use authorization) for the SARS-CoV-2 virus. A negative test result was required before coming to campus and attending in-person classes. Symptomatic and Exposed Symptomatic individuals and those who had been exposed to someone confirmed positive with COVID-19 were tested onsite through university provided services. This was generally coordinated through the university health center with testing at the respiratory clinic, which was at a separate location. This strategy used a rapid antigen test (with US FDA emergency use authorization) with results in approximately 1 h. Surveillance A surveillance testing program was used through a contracted provider to determine infection incidence and to, therefore, implement targeted intervention strategies. Incentives were provided for students to complete surveillance testing. All students who completed surveillance testing received an $8 voucher to a local eating establishment. In addition to increasing compliance, this was a way to invest in local businesses impacted by COVID-19. Tests were available every weekday and participants were notified by means of email to make an appointment. The test involved a nasal swab with qPCR to determine SARS-CoV-2 presence. Students, faculty, and staff were randomly selected with replacement (eg, testing in 1 wk did not change their likelihood of being selected in the following week). Several surveillance strategies were originally considered, including required weekly sampling of all Baylor community members. However, due to limited access to testing locally and nationwide the Fall 2020 semester began with 5% (random sample) of off-campus residence students sampled weekly and 10% of oncampus residence students, faculty, and staff sampled weekly. All tests used an external provider located on campus with results normally provided between 24 and 72 h after sample collection. Testing of off-campus student tests was increased to 10% following a campus visit from Dr. Deborah Birx, then-White House Coronavirus Response Coordinator, on September 24, 2020. Contractors working on campus were tested on a bi-weekly basis (50% each week) through the same testing provider. Surge Testing An opportunity presented to collaborate with the federal, state, and local governments to conduct "surge" testing on campus. The university was allocated 5000 tests for use within a 2-wk period (October 19-30, 2020). This testing capability was sponsored by the federal government in conjunction with the Texas Department of Emergency Management (TDEM) and the City of Waco. It was implemented by the National Guard and a government contracted nursing service, who also oversaw administration of cheek and saliva swabs for qPCR testing. Targeted Targeted testing was used after continuously observing data from the respiratory clinic, surge testing, surveillance testing, and sewage results. This option allowed the health management team to identify specific locations where viral transmission was thought to occur. Examples include residence halls, intramural sports teams, students attending athletic events, and specific student organizations/groups. Targeted testing frequently included health center staff testing residence halls on site using the rapid antigen tests for quick results, providing us the opportunity to identify viral transmission and take appropriate isolation and quarantine actions as needed. Athletics Testing within the intercollegiate athletics department was conducted in accordance with NCAA and Big 12 Conference requirements. The tests were provided by both the health center by means of the respiratory clinic and external providers. The university health center was primarily used for symptomatic or exposed individuals. Contact Tracing Our contact tracing program mirrored that used by the Waco-McLennan County Public Health District. Tracers were required to complete online training from Johns Hopkins University as well as the Health Insurance Portability and Accountability Act (HIPAA) training from the university. Tracers were instructed to complete their investigations and tracing on the same day a positive case was identified. If the positive case identified a close contact (defined as anyone who was within 6 ft of a contact for 15 min or more [cumulatively]), then the tracer called the contact and requested they quarantine for 14 d. The tracers additionally determined which rooms and facilities on campus had been visited by positive cases. All identified spaces were subsequently cleaned and disinfected by a rapid response team. More than 60 student tracers were trained with over 120 personnel available to trace, at a ratio of 1 tracer per 400 university members. This ratio was achieved through rapid recruitment of personnel and training of graduate students from social work and public health with their contact tracing activities counting as internships, a major part of their experience. Tracers were instructed to be empathetic and assist the person with their needs while in isolation (for positive cases) or quarantine (for contacts). Those in isolation or quarantine typically requested assistance with retrieving materials such as books, contacting professors and financial aid, and delivery of groceries, medicine, and other supplies. In September 2020, the contact tracing team established a follow-up process calling people in isolation and quarantine; positive cases were called daily and contacts in quarantine were called every other day. Contact tracing was expanded to include a wellness team specifically tasked to contact all cases of students, faculty, and staff in isolation to monitor their health (signs and symptoms) and to provide assistance required to maintain isolation, groceries, textbooks, medication, etc. An anonymous survey was sent to all positive and close contact cases to document their experience of isolation and quarantine. A Microsoft Teams page was established for contact tracing, which allowed multiple tracers to compile and update tracing information in a single, accessible site. The site grew to include dedicated pages for tracking isolation cases, quarantine cases and follow-up wellness checks. The site also served as a valuable resource for documenting and resourcing requests for assistance and tracking response. Dashboard The dashboard team daily reviewed de-identified data and provided a summary of conditions to the Provost. This was complemented by a weekly report. Data from each team were entered into Microsoft Excel and collated, analyzed, and presented using Microsoft Power BI. An external dashboard (Figure 2) was created for public viewing while an internal dashboard was used by the team to guide recommendations and strategies. This included information on case numbers, active cases, isolation availability, testing details by providers, outbreak, and cluster monitoring for both on-and off-campus housing and university facilities, and teaching availability of faculty members. All data points were important for successful and safe operations, however, instructional continuity throughout the semester was vital. Departments were asked to identify back up instructors for all courses in case of faculty member illness, quarantine, or isolation. This was complemented by establishment of a survey to collect data directly from each department related to instructional capacity. Departments daily reported the number of individual instructors (faculty as well as staff scheduled to teach) who fell into each of the following categories: teaching at least 1 section face-toface; teaching fully online and not in quarantine or isolation; teaching fully online and in quarantine or isolation; or unavailable to teach. Support Services A respiratory clinic was established on campus for students who were either experiencing COVID-19 signs and symptoms or were Disaster Medicine and Public Health Preparedness in close contact with an individual who tested positive for the virus. This clinic primarily used a nasal swab with a rapid antigen test, yielding results within 30 min. As the semester progressed and processes strengthened, testing was extended beyond students to also include faculty and staff. Shortly before Thanksgiving, this testing was offered to all students, faculty, and staff, and this continued until December 18, 2020 (before the holiday break). Baylor Student Life provided support services for students in isolation or quarantine, including advice, encouragement, exercise, mental health services, meal delivery, spiritual guidance, and a comprehensive set of programs and experiences to help students learn, grow, and develop. 23 Examples of these experiences included new student orientation, move in support, welcome week and Homecoming. Isolation for cases was offered at serviced hotels that we secured (in excess capacity) for on-campus residents. It was

recommended that students avoid returning home to isolate to prevent the spread of COVID-19 to family, guardians, and friends. Off-campus students isolated at their place of residence, however, were offered a serviced hotel room if they lived with a housemate who was at increased risk of severe COVID-19 disease. Students in isolation or quarantine received meals, laundry services, and other needed care. Communication In preparation for and throughout the Fall 2020 semester, multiple communication methodologies were used. This included weekly communiques from the President, complemented by detailed emails/communication from the Provost, other leadership, and public health experts. There were panel discussions with faculty, staff, students, and parents. Targeted discussions occurred when groups of students were asked to reside in place for 3 d to allow contact tracing and rapid testing to be completed. Social media and traditional media were used to communicate messages, answer questions, and share information. A specialized telephone hotline team was created to support emerging COVID-19 challenges and issues (eg, pre-arrival testing and queries about students asked to reside in place). Results From August 1 to December 8, 2020, there were 62,970 COVID-19 (SARS-CoV-2) tests conducted among Baylor faculty, staff, students, and contractors. This is presented in Figure 3, which includes daily cases reported and a smoothed line representing the 7-d average. Within this group, 1435 people tested positive, with a positivity rate of 2.28%. Overall, there were 1670 cases, including 235 self-reports. The following tested positive for COVID-19: 1416 students, 107 staff, 90 athletes, 33 faculty, 22 contractors, and 2 others. This included 235 self-reports (155 students, 58 staff, and 22 faculty). This date range was bounded by start of activities to prepare for the semester commenced (August 1) and conclusion of the semester (December 8). This timeframe included pre-arrival testing, faculty preparation for the semester (began August 24, 2020), and students progressively returning to campus and Waco. The mean number of tests per week was 3500 with approximately 80 of these positive, or 11 positive cases per day. As can be seen in Figures 3 and 4, when students, faculty, staff, and contactors returned to campus, there was an increase in positive cases, with a particular increase between August 9 and 22. During this period, there were 154 cases reported (mean of 11/ d). This was followed by the first of 3 clusters. The first cluster was characterized by an increase in cases (507 cases averaging 36 per day) between August 23 and September 5 (associated with students returning to campus). The peak number of active cases during this cluster was 475 on September 3. This was followed by a decline of cases (135 cases) from September 6 to 19, dropping to 81 active cases by September 20. The lowest number of active cases on any day throughout the semester was 64 on December 6 (including students, staff, faculty, contractors, and athletics). The second cluster occurred between October 4 and 15, including 142 cases with a mean of 12 cases per day. The peak number of cases was 134. This cluster was attributed to a combination of athletic-related travel and increased cases among staff. The third cluster occurred between November 3 and 19, including 282 cases with a mean of 17 cases per day. The peak number of active cases was 205. This cluster was attributed to social gatherings associated with Halloween. As described above, several testing and reporting mechanisms were used for identifying positive cases including pre-arrival, respiratory clinic, surveillance, surge, athletics, and contractors (Table 1). There were 13,621 pre-arrival tests completed (positivity rate of 0.99%). The decision to test before campus arrival identified 135 cases who were required to isolate at home before returning to campus. At the respiratory clinic, 11,188 rapid antigen tests were administered for symptomatic individuals and potential close contacts, with 798 people positive (positivity rate of 7.13%). Surveillance resulted in 21,435 tests of faculty members (1024), staff (4395), students (15,726), and other people (290), with 360 testing positive (positivity rate of 1.68%). Among Athletics students and staff, 8901 tests identified 91 positive cases (90 student athletes and 1 staff member) (positivity rate of 1.02%; 1.14% for student athletes and for 0.15% staff). The 4362 surge tests identified 29 positive cases (positivity rate of 0.66%). For contractors, there were 22 positive cases from the 3463 tests conducted (positivity rate of 0.64%). There were 235 self-reported positive cases (155 students, 58 staff, and 22 faculty members). The number of tests conducted per week was dependent on need and availability. For example, from August 13 to 26, there were 10,646 tests (including pre-arrival and testing shortly after arrival). In contrast, 12,466 tests were conducted from October 19 to 30, when surge testing was available. Targeted testing occurred in residence halls, intramural sports teams, students attending athletic events, and specific student organizations/ groups. The number ranged from groups as small as 4 to as large as 91 students. At the end of the semester, 19 student groups were tested, with 1741 tests identifying 33 positive cases. Within these groups, 2 were advised to quarantine for 3 d to allow contact tracing and testing to be completed. The targeted testing was conducted by the respiratory clinic and is included in the overall numbers provided in Table 1. Most student cases were off campus (76%). In comparison approximately 66% of students lived off campus. Of the 1416 students who tested positive, 246 used our isolation facilities, with the highest number at any time being 52 on September 3 (approximately 30% of our isolation capacity). Of the 1766 contacts that quarantined, at least 277 (15.7%) eventually tested positive for COVID-19. Analyses of the isolation and quarantine data are ongoing. Contract tracing identified all offsite sources of infection for faculty members, staff, and contractors (with no suspected transmission to these groups happening on campus). In terms of instructional continuity, no classes were canceled. However, 43 of 62 total departments reported 1 or more instructors who were in quarantine or isolation but still teaching online at some stage during the semester. Thirteen departments also reported 1 or more instructors who were unavailable to teach. In most cases, other faculty members would teach those courses because preparations for replacement instructors were made before the semester began. Transmission among students was traced back primarily to social gatherings or residences. SARS-CoV-2 viral RNA appeared to increase in effluent sewage 1 to 2 wk before a cluster of cases. This progressively decreased as interventions (eg, isolation and quarantine) were implemented. As expected, there was a decline in the amount of SARS-CoV-2 viral RNA in sewage 3 to 5 wk following a reduction in cases. Data analysis for sewage effluent is ongoing. Discussion The establishment of multidisciplinary teams combined with direct engagement and visible support of the President and Provost was vital to resume and sustain Baylor University operations during the COVID-19 pandemic. This allowed teams to work seamlessly with leadership to develop, guide, and support implementation of public health measures. This was demonstrated by the rapid detection and control of clusters of cases within the Baylor community. For example, each of the 3 clusters lasted approximately 11 d between the first spike in cases until the rapid decline. Also, the team developed a targeted strategy of 3 d reside in place orders for clusters on campus (rather than building or campus wide). This allowed the university to safely continue operations while contact tracing and testing was completed. Resources were never stretched beyond capacity, and this was only possible due to the measured preparations in the summer, which included numerous tabletop exercises and scenario planning activities, surveillance tests, health protocols, and the rapid contact tracing, isolation, and quarantine processes. A major consideration before reopening was the potential for spillover of COVID-19 cases into the Waco community. This was discussed among leadership, the health management team, and representatives of the Waco-McLennan County Public Health Department (health department) before the Fall semester. We were collectively confident the strategies in-place would mitigate impacts on the Waco community. Throughout the semester there was no evidence of a link between Baylor University Disaster Medicine and Public Health Preparedness reopening and a significant increase in cases in the Waco community. This finding was demonstrated on the Waco-McLennan County COVID-19 Dashboard, which indicated there were surges of cases in the community during the summer (while the university was closed) followed by a slight decline and then holding steady until around October 31, 2020 (Halloween). 24 Cases in the community then continued to increase and remain high through Thanksgiving, Christmas, and the New Year. The Waco case trends were similar with what occurred across Texas. 25 Based on this experience, implementing a "Swiss Cheese" risk mitigation model and using a multidisciplinary team approach to guide decisions and interventions is vital to reduce the risk of COVID-19 spread from colleges and similar institutions into the broader community. As cases began to rise early in the summer, Baylor worked with the health department to identify ways to best support the local community. It was agreed that the best option was for Baylor University to contact trace using its own personnel (students, faculty members, and staff), a process that began in July 2020. While easing the burden on the local health department, it also allowed the university to conduct same-day contact tracing following positive case determination. Positive cases were isolated immediately, and contacts quarantined within 24 h, allowing clusters to be rapidly controlled. For this reason, it is recommended that colleges and other similar institutions prioritize testing and contact tracing capabilities to mitigate the impact of disease outbreaks and sustain operations. A lesson from this experience is the need for rapid results from surveillance testing. Surveillance testing was a vital component for success, however, a disadvantage of using the qPCR test with a nasal swab was relatively long turnover for results (24-72 h). Once notified of the results, the university continued the same protocols, including contact tracing, isolation, quarantine, and followup with students for medical attention. In recognition of this challenge, Baylor established on-campus qPCR testing and lab processing for the Spring 2021 semester, permitting much faster test results. The benefits of rapid antigen testing at the on-campus respiratory clinic helped to protect both university associates and the local community. If a student received a rapid positive diagnosis, they immediately received a phone call from a medical professional who notified them of their isolation responsibilities, advised about treatments for signs and symptoms, and answered any questions they might have about the result. Within hours a contact tracer collected information about close contacts the students may have had in the previous 48 h. Because this was all happening in near real time, the university was able to isolate the student who was positive and quarantine close contacts. All these measures took place to lessen the impact on the university and surrounding community. Involvement of parents in communication was vital. Multiple methods were used to connect with parents. This included emails, call centers, and for those affected by reside in place orders direct engagement with representatives from leadership and the health management team. This helped get their buy-in and reinforce student compliance. Based on this experience, it is recommended that other colleges and similar institutions prioritize parent communication during an outbreak, pandemic, or other crises. There is a need for an increased focus on testing and enforcement of public health recommendations in off-campus students. This was a known challenge before the semester commencing; however, strategies to actively mitigate the risks beyond existing structures (eg, County and State mechanisms) were unknown. As the semester progressed, the need to address this challenge was identified. Most Baylor students live off campus (approximately 66%), and proportionally, this is where most cases occurred. Efforts were made throughout the semester to engage private residential property managers on the situation and to recommend mitigation measures. This took longer than anticipated; however, progress was made toward the end of the semester, and property managers were grateful for the engagement. Based on this experience, it is recommended that active relationships be established and maintained with off-campus accommodation managers to help mitigate the spread of COVID-19 and other diseases, particularly within the greater community outside of the university. This consideration appears particularly relevant in regions with limited delivery of local public health services and

areas with a high percentage of highly susceptible individuals (eg, large minority populations, many living below the poverty line and without access to adequate health insurance). Throughout the semester we actively investigated cases to determine pathogen transmission. Spread of cases was generally associated with informal student social gatherings. Early in the semester, Baylor became aware of some planned social events and worked with organizers to cancel them. For any of these canceled events that still took place, disciplinary action was taken, particularly early in the semester. This enforcement combined with constant messaging, monitoring of safety measures on campus, and strict health protocols were effective in mitigating COVID-19 and sustaining university operations. This demonstrates that a combination of testing, compliance monitoring, and sustained implementation of public health measures (face coverings and social distancing) can minimize the impact of COVID-19 and other potential pathogen outbreaks. Conclusions The establishment of multidisciplinary teams was vital for Baylor University to resume and sustain operations during the COVID-19 pandemic. Our population-based team approach along with implementation of a "Swiss Cheese" risk mitigation model enabled development of comprehensive mitigation strategies and priority areas for action. As a result, the university was able to sustain activities, even during multiple case surges. These situations were addressed rapidly through testing, surveillance, tracing, isolation, and quarantine. There was no evidence of transmission within classes or lecture rooms due to our intensified safety protocols. A key lesson from this experience was the need for rapid results from surveillance testing because qPCR test results took 24 to 72 h. In recognition of this challenge, Baylor worked to establish high throughput qPCR testing on campus (including in-house laboratory processing), which further enhanced our capability to identify and control clusters and subsequently expand operations. Although resources were highly used, they were never stretched beyond capacity. This result was only possible due to the measured preparations in the summer, which included numerous tabletop exercises, scenario planning activities, and addressing priority areas for action. The successes and lessons learned at Baylor University provide a framework and pathway for other colleges and similar institutions to mitigate the ongoing impact of COVID-19 and sustain operations during a global pandemic. α2,3-sialyltransferase type I regulates migration and peritoneal dissemination of ovarian cancer cells Epithelial ovarian cancer (EOC) has the highest mortality rate among gynecologic cancers due to advanced stage presentation, peritoneal dissemination, and refractory ascites at diagnosis. We investigated the role of α2,3-sialyltransferase type I (ST3GalI) by analyzing human ovarian cancer datasets and human EOC tissue arrays. We found that high expression of ST3GalI was associated with advanced stage EOC. Transwell migration and cell invasion assays showed that high ST3GalI expression enhanced migration of EOC cells. We also observed that there was a linear relation between ST3GalI expression and epidermal growth factor receptor (EGFR) signaling in EOC patients, and that high ST3GalI expression blocked the effect of EGFR inhibitors. Co-Immunoprecipitation experiments demonstrated that ST3GalI and EGFR were present in the same protein complex. Inhibition of ST3GalI using a competitive inhibitor, Soyasaponin I (SsaI), inhibited tumor cell migration and dissemination in the in vivo mouse model with transplanted MOSEC cells. Further, SsaI synergistically enhanced the anti-tumor effects of EGFR inhibitor on EOC cells. Our study demonstrates that ST3GalI regulates ovarian cancer cell migration and peritoneal dissemination via EGFR signaling. This suggests α2,3-linked sialylation inhibitors in combination with EGFR inhibitors could be effective agents for the treatment of EOC. INTRODUCTION Epithelial ovarian cancer (EOC) is the second most common type of gynecologic cancer and a leading cause of gynecological cancer deaths in the United States. In 2016, there were 14,240 EOC related deaths and 22,280 new cases diagnosed in the United States [1]. Despite intensive treatment with cytoreductive surgery and postoperative adjuvant chemotherapy with/without antiangiogenesis agents, EOC has the highest mortality rate among gynecological cancers because it is diagnosed in an advanced stage and has high recurrence rate [2][3][4]. The estimated average disease-free survival (DFS) time for EOC patients is 18 months with a 5-year overall survival (OS) rate below 30% [5]. EOC is characterized by advanced-stage presentation, multiple organ metastases, peritoneal dissemination and refractory ascites at diagnosis [6]. Currently, the diagnosis of metastasis and/or recurrence is still dependent on imaging clues and detection of carbohydrate antigen 125 (CA125) [7], both of which are limited in sensitivity and specificity. Therefore, the development of novel biomarkers is urgently required for accurate and early prediction of metastasis and treatment outcomes in EOC patients. Sialic acids belong to a family of 9-carbon amino sugars that are widely distributed in nature as terminal sugars of oligosaccharide chains of glycoconjugates (glycoproteins and glycolipids) [8]. The sialyltransferases (ST) and sialidases regulate sialylation, which is an important posttranslational modification reported during progression of many cancers [9][10][11]. The ST family consists of three subfamilies with 20 anabolic enzymes [12], namely, α2,3sialyltransferases that mediate the transfer of sialic acid with an α2,3-linkage to terminal Gal residues (ST3GalI-VI) and α2,6-sialyltransferases that mediate the transfer of sialic acid with an α2,6-linkage to terminal Gal (ST6GalI-II) or GalNAc residues (ST6GalNAcI-VI) [13,14]. The link between the ST family and EOC was reported previously by few studies [15][16][17]. For example, Christie et al reported that sialylation of β1 integrins mediated by ST6Gal-I altered the adhesion and migration characteristics of ovarian cancer cells through the extracellular matrix leading to peritoneal metastasis [17]. In our previous study, we showed altered expression and significant increase of α2,3-linked sialylated proteins in ovarian cancer patients and the enhanced α2,3-linked sialylation was directly linked to increased expression of ST3GalI [16]. The competitive ST inhibitor, soyasaponin I (SsaI, K i = 2.3μM) was shown to affect CMP-Neu5Ac binding to ST, but did not inhibit other glycosyltransferases and glycosidases [18]. Further, SsaI inhibited α2,3-linked sialic acid expression in B16F10 melanoma and MDA-MB-231 breast cancer cell lines that resulted in increased adhesion and decreased migration and invasiveness of the two cell lines [19,20]. Epidermal growth factor receptor (EGFR), also known as ErbB-1 or HER1, is a transmembrane receptor tyrosine kinase (RTK) and a member of the human epidermal receptor (HER) family, which is involved in many cell signaling pathways. EGFR is overexpressed in many cancers and regulates cancer invasion, metastasis, and angiogenesis [21][22][23][24][25]. After binding to specific ligands (EGF or TGF-α), EGFR undergoes conformation changes and forms homoor hetero-dimers with other HER family members [26][27][28][29][30][31]. After autophosphorylation, the dimeric EGFR recruits and activates various downstream cytoplasmic and nuclear signaling proteins, which regulate multiple cellular processes, including proliferation, migration, differentiation, survival, and apoptosis [26][27][28]. Overexpressed EGFR is associated with poor prognosis in ovarian cancers [32][33][34]. Although EGFR is an attractive therapeutic target, clinical trials with several EGFR inhibitors have demonstrated modest antitumor effects on ovarian cancer [34][35][36]. Therefore, in this study, we investigated the prognostic value of ST3GalI and its relationship with EGFR signaling in ovarian cancer using both in vitro and in vivo models including human ovarian cancer patient microarray datasets. ST3GalI is a prognostic factor for migration and peritoneal dissemination of human ovarian cancer cells First, we analyzed the correlation between overall survival (OS) rate and expression data of sialyltransferases (high, moderate or low) using the Human Genome U133A Array (562 tumor cases) available from The Cancer Genome Atlas (TCGA) at the Oncomine website. We observed that ST3GalI played a more critical role in disease progression than ST6GalI (α2,6-sialyltransferase) and ST8SIAI (α2,8-sialyltransferase). Kaplan-Meier analyses of TCGA cohort specimens showed that EOC patients with high ST3GalI expressing tumors demonstrated poor survival rates ( Figure 1A and Table 1). Furthermore, immunohistochemical (IHC) staining using the human EOC tissue array (CJ2 provided by SUPER BIO CHIPS, Seoul/South Korea) showed that higher intensity staining of ST3GalI ( Figure 1B) positively correlated with lower overall survival rate (Figure1C). These findings demonstrated that ST3GalI had significant prognostic value in human ovarian cancer. We further investigated the association of ST3GalI expression with EOC progression. Compared to early stages, ST3GalI expression was significantly higher in advanced stages among the various ovarian cancer datasets tested (Supplementary Figure 1A). This suggested that overexpression of ST3GalI was associated with advanced stage EOC (peritoneal seeding and distant metastases), especially in advanced serous-or clear-type cell carcinoma (Supplementary Figure 1B). Further, we investigated the role of ST3GalI in ovarian cancer cell migration by either knocking down or overexpressing ST3GalI in human ovarian cancer ES2 cells and performing Transwell assays. We observed that downregulation of ST3GalI significantly suppressed cancer cell migration and invasion, whereas overexpression of ST3GalI enhanced cell migration and invasion ( Figure 1D-1E, and Supplementary Figure 2). Interestingly, altered ST3GalI expression (knockdown or overexpression) did not significantly affect tumor growth (Supplementary Figure 3). These findings suggested that ST3GalI regulated the migration and invasiveness of ovarian tumor cells without altering tumor growth. ST3GalI interacts with EGFR signaling pathway in ovarian cancer To identify the signaling pathways regulated by ST3GalI, we analyzed important cell receptors in the (A) Using Oncomine TCGA ovarian cancer genomics (562 ovarian carcinoma samples analyzed on an Affymetrix Human Genome U133 array; 12,624 measured genes), we compared different ST mRNAs, including α2,3-, α2,6-, and α2,8-linked ST, with survival time using a tercile approach. Patients with an upper one-third mRNA expression were defined as the high subgroup, while others with lower twothirds mRNA expression were defined as the low subgroup. (B-C) IHC analysis of ST3GalI was performed on commercial human ovarian cancer tissue array samples (Super Bio Chips, CJ2, Korea). The intensity scores were as follows: 0, no staining; 1, weak; 2, moderate; 3, strong. Low ST3GalI included weak, moderate or no staining; high ST3GalI was defined as strong staining. Scale bars representing 20μm were added from an image taken at identical magnification and resolution. The percentage was determined in the early stage (FIGO stage I &II) or late stage (FIGO stage III&IV) disease groups. The Fisher's exact test was used to statistically analyze the percentage for the early and late stages. Kaplan-Meier survival curves were used to analyze OS in low-and high-ST3GalIgroups. (D-E) Transwell migration and matrigel invasion of ES2 human ovarian cancer cells with either ST3GalI knocked-down or over-expressed was assayed. Total numbers of cells in 7 random fields were counted. Data shown are the mean ± SD of 3 separate experiments (*: p< 0.05, **: p<0.01.). Data on the Y-axis represented relative value compared to control. Immunoblots were quantified using Image J software. human ovarian cancer ES2 cell line using the L1000 mRNA microarray. Our analysis showed that ST3GalI expression was significantly associated with expression of the EGFR genes ( Figure 2A). Also, the EGFR signaling pathway was overexpressed and associated with poor prognosis in more than 70% of ovarian cancer patients [32]. We further analyzed three ovarian cancer genomic datasets (TCGA, Bittner, and Lu) and found a linear relationship between ST3GalI and EGFR ( Figure 2B, upper panel). We observed that ovarian cancer patients with a high ST3GalI expression demonstrated increased EGFR levels simultaneously ( Figure 2B Next, we analyzed the mRNA levels of the different STs, namely, ST3GalI-VI in response to EGFR inhibitor treatments (erlotinib, lapatinib, ZD-6474, TKI258) in different ovarian cancer cell lines listed in the Cancer Cell Line Encyclopedia (CCLE) database. We observed that the anti-tumor effect of EGFR inhibitors was more pronounced when the mRNA expression of STs was lower ( Figure 2C, left side of heat-map). However, EGFR inhibitors demonstrated poorer anti-tumor effect in cell lines with higher expression of STs ( Figure 2C, right side of heat-map). These results demonstrated synergy between ST3GalI levels and EGFR. To understand the relationship between ST3GalI and EGFR, we investigated the EGFR expression in the ovarian cancer cells with ST3GalI either knocked down or overexpressed. We observed that ST3GalI knock down decreased EGFR expression, whereas ST3GalI overexpression enhanced EGFR levels ( Figure 2D-2E). In addition, we observed that ST3GalI associated with epithelial mesenchymal transition (EMT) markers, such as E-cadherin or N-cadherin (Supplementary Figure 5) since we observed increased E-cadherin and decreased N-cadherin in the ST3GalI knock-down. Co-Immunoprecipitation analysis demonstrated that EGFR and ST3GalI were physically present in the same protein complex since ST3GalI was found in the complex immunoprecipitated from ES2 ovarian cancer cell lysates with anti-EGFR antibodies and EGFR was immunoprecipitated with anti-ST3GalI antibody ( Figure 2F). Further, in the ST3GalI knock-down, we observed decreased ST3GalI immunoprecipitating with anti-EGFR antibody ( Figure 2G). Interestingly, we also observed that ST3GalI regulated EGFR transcriptionally in a time-dependent manner ( Figure

2H). We observed that when ST3GalI was down regulated by shRNA knockdown, an immediate and profound reduction of ST3GalI expression was followed by a stable and longer down regulation of EGFR. This finding suggested that ST3GalI may regulate the EGFR pathway via regulate factors that were upstream of EGFR in the signaling pathway or even a negative feedback mechanism. Taken together, these findings suggested that ST3GalI positively regulated EGFR. α2,3-sialylation inhibitor SsaI suppresses ovarian cancer cell migration and peritoneal dissemination Next, we investigated if the α2,3-sialylation inhibitor, SsaI, inhibited peritoneal seeding and carcinomatosis of ovarian cancer and the mechanism by which SsaI modified the behavior of cancer cells. We observed that SsaI treatment down regulated ST3GalI in three ovarian cell lines (MOSEC, ES2, and OVCAR3) compared to the DMSO control ( Figure 3A). Further, Transwell assay demonstrated that SsaI treated MOSEC, ES2, and OVCAR3 ovarian cancer cells demonstrated significant inhibition of Figure 3B). These results indicate that ST3GalI may regulate tumor cell motility and hence a potential prognostic marker of human ovarian cancer. More than half of ovarian cancer patients are found in an advanced stage where the ovarian cancer cells have disseminated into the peritoneal cavity to form peritoneal seeding and sometimes carcinomatosis. To investigate this, we injected MOSEC cells into the peritoneal cavity of 8 week-old female C57BL/6 mice along with continuous delivery of either 100μM SsaI or DMSO control from ALZET Micro-Osmotic pumps. We observed peritoneal carcinomatosis with a large amount of ascites in the control mice, mimicking the clinical symptoms of human ovarian cancer ( Figure 3C). In contrast, the SsaI-inoculated mice were asymptomatic and demonstrated significantly lower peritoneal carcinomatosis and ascites ( Figure 3C). Interestingly, SsaI mildly inhibited cell proliferation in the MOSEC cell line as analyzed by MTT assay (Supplementary Figure 6A), and showed negligible decrease in mouse body weight (Supplementary Figure 6B). Taken together, these data suggested that SsaI, the ST3GalI inhibitor, significantly reduced tumor migration and peritoneal dissemination without significantly affecting growth. SsaI inhibits EGFR signaling and shows synergistic effect with TKI To examine if SsaI inhibited the EGFR signaling pathway through ST3GalI, we treated the ovarian cancer cell lines with SsaI and found that EGFR expression was down-regulated ( Figure 4A). Besides inhibiting the sialylation of EGFR, SsaI interfered with the proteinprotein interaction between ST3GalI and EGFR. The intraperitoneal tumor tissues from the B6 mice that were treated with SsaI showed decreased expression of ST3GalI and EGFR compared to the control mice based on DuoLink in situ double staining ( Figure 4B). This suggested that SsaI suppressed tumor migration and peritoneal dissemination in ovarian cancer via ST3GalI-EGFR signaling. Further, we investigated the synergy between ST3GalI and EGFR. Towards this, we treated ES2 cells with SsaI in presence or absence of the EGFR inhibitor, AG1478. We observed that cells treated with both SsaI and AG1478 showed significant inhibition of tumor invasion in the Transwell invasion assay compared to cells treated with SsaI alone or the negative control ( Figure 4C). Also, we noted that EGF stimulation was suppressed by SsaI treatment in the Transwell matrigel assay (Supplementary Figure 7). Moreover, we demonstrated synergestic effects of the SsaI and AG1478 inhibitor combination over several concentrations ( Figure 4D, Table 2). Hence, these data demonstrated that α2,3-sialylation inhibitors may be useful in future ovarian cancer therapy to synergize with TKI (tyrosine kinase inhibitors). ST3GalI is specific for α2,3-sialylation of Galß1, 3GalNAc on the O-linked chains of glycoproteins and glycolipids and has an important role in sialyl-Lex/ Lea biosynthesis and sialylation of the Thomsen-Friedenreich antigen [40][41][42]. In previous studies, the expression of ST3GalI was altered in cancers such as colon, bladder, ovary and breast cancer [43]. Videira et al found that the overexpression of ST3GalI was associated with the initial oncogenic transformation of bladder [44]. Kudo et al showed that ST3GalI was up-regulated in colorectal cancer [45]. Burchell et al showed that ST3GalI was elevated in primary breast carcinomas, compared to normal or benign breast tissues [43]. In our previous work, we found that increased ST3GalI expression contributed directly to increased α2,3-linked sialylation in ovarian serous carcinoma [16]. Therefore, in this study we investigated the mechanistic role of ST3GalI in ovarian cancer. Initially, we investigated the relationship between ST3GalI expression, advanced cancer stage and overall survival rate. Using different microarray datasets, we found that ST3GalI was significantly higher in late-stage cancer patients compared to early-stage cases. Furthermore, in vitro and in vivo studies revealed that ST3GalI down regulation significantly suppressed cancer cell migration and invasion. Conversely, ST3GalI overexpression enhanced the migratory ability and invasiveness of the cancer cells. Taken together, our data demonstrated that ST3GalI played a significant role in ovarian cancer cell migration and peritoneal dissemination and suggested a potential prognostic role. Since enhanced sialylation was observed in oncogenic transformation, tumor metastasis, and invasion, inhibition of ST may be a potential treatment strategy. A cell permeable ST inhibitor, SsaI, exhibited inhibition of cellular α2,3-sialyltranserase activity [18,46]. Our previous study showed that SsaI significantly decreased breast cancer cell (MDA-MB-231) migration [19,20]. In the present study, we demonstrated inhibitory effects of SsaI on migration and invasion of ovarian cancer cell lines, as well as decreased peritoneal tumor ascites in mice. Interestingly, SsaI downregulated the expression of ST3GalIV in breast cancer cells and not ST3GalI and ST3GalIII [19,20], but inhibited ST3GalI in ovarian cancer cells. This suggested a probable negative feedback regulation of ST3GalI that needs to be investigated along with the ability of SsaI to inhibit different STs in different cancer types. Studies on non-small-cell lung cancers and others have revealed that several mechanisms like mutation (T709M) of EGFR receptors or activation of alternative signaling pathways or sialylation regulate EGFR function and inhibitor resistance [47][48][49][50]. Further, studies found that Asn420 and 579on the glycans prevented ligandindependent dimerization of EGFR [51][52][53]. Liu et al showed that sialylation and fucosylation suppressed dimerization and autophosphorylation of EGFR and EGFinduced lung cancer cell invasion [54]. Yen et al showed and phospho-EGFR in ES2 cells treated with 100μM SSaI or DMSO control for 72h; GAPDH was used as control (same GAPDH as in Figure 3). (B) Intraperitoneal tumors from B6 mice treated with either SsaI or DMSO control were stained by the Duolink in situ IHC staining kit to analyze for ST3GalI and EGFR. (C) ES2 cells were treated with 100μM SsaI and 5μm AG1478 (EGFR inhibitor) were subjected to Transwell matrigel invasion assay. Total numbers of cells were counted in 7 to 10 random fields. Data shown are the mean ± SD of 3 separate experiments. (D) Synergy between ST3GalI and EGFR were determined by treating ES2 cells with either SsaI orAG1478 (EGFR inhibitor) or both for 48h followed by determination of their effects on cell proliferation rate. Data shown are the mean ± SD of 3 independent experiments. (E) A proposed mechanism of the interaction between ST3GalI and the EGFR signaling pathway. that sialylation partially suppressed the phosphorylation of EGFR at Y1068, Y1086, and Y1173 in a TKI-resistant lung cancer cell line with L858R/T790M mutations on EGFR and enhanced EGFR sensitivity to TKI [30]. Therefore, in contrast to lung cancer, our data with ovarian cancer cells suggested that sialylation was positively associated with EGFR function. Further, our co-IP data demonstrated that ST3GalI and EGFR interacted with each other ( Figure 2F and 2G), and EGFR expression decreased in the ST3GalI knocked-down cell line. Interestingly, ST3GalI also regulated the transcription of EGFR ( Figure 2H). These data demonstrated that sialylation in ovarian cancer may be functionally different than in lung cancer. There are limitations to our study. First, only serous histology was available in the TCGA dataset and small number of case studies in other genomic datasets. Therefore, a larger-scale investigation of different histologic types in ovarian cancer is necessary. Second, previous studies showed that SsaI was a competitive inhibitor of CMP-Neuc5Ac, but, we found that SsaI downregulated ST3GalI. This implied that SsaI suppressed α2,3sialylation via a negative feedback regulation that needs to be investigated further. Third, although the results showed that α2,3-sialyltransferases increased EGFR expression in EOC, the effect of sialylation on EGFR structure or conformation was not directly explored. Moreover, the detailed mechanism by which ST3GalI regulated EGFR is not clear in this study. A marked reduction of ST3GalI expression was observed soon after transfection with the ST3GalI knock-down plasmid, whereas EGFR down regulation as a consequence was found to be relatively stable and long-lived. This implied that ST3GalI may regulate factors upstream of EGFR or induce a negative feedback inhibition of EGFR signaling pathway. Fourth, we used only one EGFR inhibitor, AG1478, which is a specific reversible inhibitor of EGFR that selectively inhibits the ligand-induced autophosphorylation of EGFR and downstream signal transduction events [55]. Moreover, this compound has not been evaluated in clinical trials. Other EGFR inhibitors such as gefitinib, erlotinib, lapitinib and anti-EGFR antibodies that are used in cancer therapy need to be considered in combination with ST inhibitors and their efficacy and safety for ovarian cancer patients needs to be evaluated. In conclusion, our study showed that ST3GalI was a poor prognostic factor in epithelial ovarian cancer (EOC), especially with regard to survival and metastasis. We demonstrated crosstalk between ST3GalI and EGFR that regulated the migration and invasiveness of ovarian cancer cells. Further, our study demonstrated that α2,3-linked sialylation inhibitors such as SsaI in combination with EGFR inhibitors may be potentially future therapeutic targets for EOC treatment. Thiazolyl blue (MTT) assay To estimate cell survival and proliferation, the ovarian cancer cell lines (5x10 3 ) were grown in RPMI1640 medium in 96 well plates supplemented with 5% charcoal-stripped/heat-inactivated FCS for 24h Then, the cells were treated with either DMSO (control) or 100μM SsaI (Soyasaponin I, S9951 Sigma Soyasaponin I Sigma-Aldrich) for 48h. Further, 200μl thiazolyl blue (MTT, 5mg/ml, Sigma-Aldrich) was added into each well with 1ml of medium for 4h at 37°C followed by 2 ml of 0.04N HCl in isopropanol. After thorough mixing by pipetting and 5 min of incubation at room temperature, the absorbance was read at 570nm and subtracted from background absorbance at 600nm. Results were expressed as the mean ± SD of 3 independent experiments. Cell migration assay Transwell cell migration assay was used to estimate the effect of SsaI on the migration of the ovarian tumor cells. The Transwell consisted of an upper and a lower chamber that were separated by a polycarbonate filter of 8μm pore size with a surface diameter of 6.5mm. The ovarian cancer Cell invasion assay In vitro invasiveness of the ovarian cancer cells was assessed by quantifying the number of cells that invaded the Matrigel. Polycarbonate Transwell filters was coated with ~100μg/100μL of diluted Matrigel solution. Then, the cells (2 × 10 4 ) were added to the upper chamber with either DMSO or 100μM SsaI and 10% FBS medium was added as a chemoattractant in the lower chamber followed by incubation at 37°C for 24 h. The cells that travelled through the filter were stained and counted from 7 to 10 random fields of view at 400 × magnification. SoyasaponinI preparation SsaI was prepared from a commercial preparation of soybean saponins. The purification process was performed as described with some modifications. Briefly, nonsaponin constituents were extracted from the preparation by gently agitating the saponins (4g) in acetone (25ml) at room temperature followed by centrifuging the mixture at 2000xg for 30 min. This acetone extraction was repeated thrice. The residue was then extracted in distilled water thrice and then washed in acetone to facilitate drying. The final purification was carried out on a preparative HPLC C18 column (10×250mm, Phenomenex). HPLC conditions were as follows: solvent A, acetonitrile/TFA (100:0.1, v/v); solvent B, H2O/TFA (100:0.1, v/v). Elution was done with the following mixtures: 40~45% solvent A (40 min), 45~65% solvent B (10 min). The flow rate was set to 3ml/min and the products were detected at 205nm. The soyasaponin I in this study was >99% pure as determined by an analytical HPLC C18 column (4.6mm×250mm, Phenomenex). In vivo mouse model We followed the guidelines for animal experimentation adopted by the Animal Subjects Program (ASP) at Taipei Veterans General Hospital (VGH-TPE). At the day of implantation, MOSEC cells (2×10 6 ) were injected into the abdominal/peritoneal cavity of 8 week old female C57BL/6 mice (National Laboratory Animal Center, Taipei, Taiwan). Alzet osmotic miniature pumps (model 1004;

DURECT Corporation Charles River Laboratories, L'Arbresle, France) with constant delivery rates of 0.11 l/h for about 4 weeks were filled with either 100μl SsaI in PBS or DMSO as control. The pump had a delayed starting time of approximately 2 days after filling. The osmotic mini-pumps filled with either SsaI or DMSO were implanted under the skin of the mice under sterile conditions and started when no cartilage destruction was detectable (days 0-4). Since the reagents circulated for a few days after the pump was empty, an experimental setting of 28 days was selected. Gene transfection The lentiviral plasmid vectors harboring specific short hairpin RNA (shRNA) sequences for human ST3GalI and a non-target scrambled control were purchased from the RNAi Core Facility (Academia Sinica, Taiwan). The ST3GalI shRNA sequence was RNA isolation and real-time quantitative PCR (RT-qPCR) The ovarian cancer cells were lysed by TRIzol and centrifugation at 12,000 x g for 10 minutes after adding bromochloropropane (Sigma-Aldrich). Total RNA was precipitated with isopropanol, followed by washing with ethanol to remove impurities and finally dissolved in RNAase-free water (Invitrogen). Total RNA was quantified spectrophotometrically using A260/A280 values. The cDNA synthesis was performed using SuperScript TM II reverse transcriptase (Invitrogen) according to the manufacturer's instructions. The 12μL volume of one reaction with oligo(dT) 12-18 (500μg/mL), 1 μL dNTP Mix (10 mM each), 1 ng to 5 μg total RNA and sterile distilled water to perform 65°C for 5 min and quick chill on ice. Add 7μL volume of buffer mix with 5X First-Strand Buffer, 0.1 M DTT and RNaseOUT™ (40 units/μL) to perform 42°C for 2 min. Add 1 μL (200 units) of SuperScript™ II RT to perform 42°C for 50 min and 70°C for 15 min. The PCR primers and probes designed using the Roche Online Assay Design Centre for the ST3GalI and EGFR genes and control 18S RNA were as follows: ST3GalI, Forward 5'-TGGTCCTGGAGCTCTCCGAGAA-3', Reverse 5'-GACTGTCTATCTCAGGCCCATAAGAAGA-3'; www.impactjournals.com/oncotarget EGFR, Forward 5'-ACTCATGCTCTACAACCC-3', Reverse 5'-CCAATACCTATTCCGTTACAC-3'; and 18S, Forward 5'-GACCAGAGCGAAAAGCAT-3', Reverse 5'-TCGGAACTACGACGGTATC-3'. The cDNA samples were amplified by real-time PCR using a LightCycler 480 Instrument (Roche). The 20μL volume of one reaction with 10ng/μL cDNA, 50nM Forward and Reverse primer, 2xSYBR reagent and sterile distilled water to perform PCR amplification and Melting curve program. Quantification cycle values (crossing point, Cp) for each gene were calculated as the cycle number at which the reporter fluorescence passed a fixed threshold above the base line. The expression levels of the genes of interest, ST3GalI and EGFR, were normalized in relation to the housekeeping control (18S). All experiments were performed thrice. Protein isolation and western blot analysis For western blot analysis, ovarian cancer cells that were treated with or without SsaI were lysed in a buffer containing 1% Triton X-100 in PBS and protease inhibitor mixture tablets (Roche, Barcelona, Spain). Following 30 min incubation on ice with vortexing, lysed cells were centrifuged (14000 rpm, 20 min, 4°C) to pellet cell debris, and protein concentrations of the resulting cell supernatants were determined by the Bradford Assay (Bio-Rad, Hemel Hempstead, UK), relative to a standard curve prepared from serial dilutions of bovine serum albumin (0-4mg/mL) with absorbance readings at 595nm. 100μg total protein was diluted in equal volumes of 2x protein sample buffer (125mM Tris-HCl (pH 6.8), 4% SDS, 0.02% bromophenol blue, 0.2M DTT, 20% glycerol) was electrophoresed on a 10% ~ 15% SDS-PAGE run 100 voltage, 3hrs and transferred onto Immobilon polyvinylidene difluoride membranes (Millipore, Bedford, MA) 90 voltage, 2hrs. Then, the membranes were incubated 30mins at room temperature in blocking solution (5% nonfat dry milk/0.1% Tween-20/1xPBS) followed by incubating the membranes overnight with the appropriate primary antibodies namely, ST3GalI (Abcam, ab96129, 1:500), EGFR (CST, #4267, 1:1000) or phospho-EGFR (CST, #2234, 1:1000). Then, the membranes were washed 10min trice with 0.05% Tween-20/PBS followed by incubation 2hrs at room temperature with anti-Rabbit HRP-conjugated secondary antibody (Geneisland, #G701120, 1:5000). The blots were developed with enhanced chemiluminescence reagent (Amersham Pharmacia Biotech) followed by exposure to X-ray film to visualize the protein bands. The protein bands were quantitated using ImageJ analysis by determining the relative intensity for each experimental band by normalizing its absolute intensity to that of the control. Immunohistochemistry IHC specimens (59) from the CJ2 human ovarian cancer tissue array were obtained from a commercial tissue array (Super Bio Chips, Seoul, S. Korea) with complete clinical data, including clinical stage, grade and overall survival (OS). Tissue sections were immersed in a coplin jar filled with 1x Dako target retrieval solution (Dako, Denmark; Code S1699), heated for 5 min at 121°C and then cooled to 85°C. Then, the endogenous peroxidase activity was quenched by treating the specimens with 0.6% hydrogen peroxide/methanol mix. The sections were further blocked with goat serum (BioGenex, San Ramon, CA, USA) for 30 min at room temperature to prevent non-specific binding. Then, the sections were incubated overnight with anti-ST3GalI Ab (Abcam, ab96129, 1:50) at 4°C followed by staining with AEC Substrate-Chromogen (DAKO, Denmark) and counterstained with hematoxylin. For the negative control, sections were treated with PBS instead of the antibody. The IHC staining was quantified based on the staining intensity score (0, no staining; 1, weak; 2, moderate; 3, strong). A strong intensity score indicated high expression of ST3GalI, whereas, other intensity scores indicated different grades of lower expression. Duolink In Situ staining Protein-protein interactions were detected using a Duolink In Situ Kit (Olink Bioscience, Uppsala, Sweden; PLA probe anti-rabbit plus; PLA probe anti-mouse minus; Detection Kit orange). In brief, tissue specimens from the in vivo mouse experiment were incubated with primary antibodies against ST3GalI and EGFR for 2h at room temperature. Then, the slides were washed twice in suitable buffer 1x wash buffer A (0.01 M Tris, 0.15 M NaCl and 0.05% Tween 20) for 5 min followed by incubation with the 2 PLA probes (1:5 in appropriate buffer antibody dilution) for 60 min at 37°C. Then, the specimens were incubated with ligase (1:40 in buffer high purity water). After washing twice in 1x wash buffer A for 2 min, the amplification procedure was carried out with the polymerase (1:80) for 100 min at 37°C. Then, the specimens were washed twice in 1x Wash Buffer B for 10 min and 0.01x Wash Buffer B for 1 min. The slides were finally incubated for 15 min with Oregon green phalloidin antibody (1:50, Invitrogen) at room temperature and visualized under a light microscope (Nikon, Ci). Analysis of ovarian cancer and prognosis in the TCGA project The clinical and protein expression data of ovarian cancer (high-grade serous cystadenocarcinoma) from the TCGA were downloaded from the Oncomine website (http://www.oncomine.org/). The patients in the ovarian serous cystadenocarcinoma dataset (Human Genome U133A array, 12,624 measured genes, 562 cases) were categorized using a total of 20 STs including α2,3-, α2,6-, and α2,8-sialyltransferases with a tercile approach. www.impactjournals.com/oncotarget The patients were categorized as high or low expressing if the mRNA of interest was in the upper one-third or in the lower two-thirds, respectively. We analyzed the disease free survival (DFS), overall survival (OS) and the correlation between ST3GalI and EGFR using this dataset. Furthermore, different datasets (Schwartz ovarian, HumanGeneFL array [56]; Hendrix ovarian, Human Genome U133A array [57]; Denkart ovarian, Human Genome U133A array [58]; Lu ovarian, Human Genome U95 array, [59]) from the Oncomine website were used to investigate if ST3GalI regulated ovarian cancer dissemination. Further, the patients were sub-divided into either early stage (stages 1 and 2) or late stage (stages 3 and 4) and the expression of ST3GalI was compared between these 2 groups. Microarray analysis The microarray experiments were conducted using the L1000 Operating Procedure (L1000 SOP). In brief, a human ovarian cancer cell line, ES2, was grown in commercial 96-well plate for one day and the cells lysed with lysis buffer (L1000 kit) for 30 mins. The lysate was stored at 80°C overnight and then transferred to a 384-well plate for the L1000 assay that was conducted according to the commercial protocol (http://s3.amazonaws.com/ support.lincscloud.org/protocols/data_generation/L1000_ SOP.pdf). Gene expression profiles in the control and study group were detected by L1000 array technology. Up and down probe sets were selected by 2-sample t-test with a p value lower than 0.01 and fold change greater than 1.5fold considered as significant. The up and down probe sets were input into GeneE software to run the analysis and interpret the transcription profile data. The expression of sialylation and significant cell receptors, including EGFR, IGFR, VEGFR and PDGFR was determined. In Vitro cell viability assays To assay the synergy between ST3GalI and EGFR, ES2 cells were treated with 100μM SsaI in presence or absence of EGFR inhibitor (Sigma, AG1478) in 96-well plates (4x10 3 per well) and cultured for 48h. Then, the cells were collected and counted by staining a sample with trypan blue and the cell proliferation was measured with the MTT assay. Following 20μl of a sterile, filtered 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) solution (5 mg/ml) in 1xPBS (pH 7.4) was added to each well and incubated for 4 hrs at 37 °C, and adding 150 μL dimethyl sulfoxide (DMSO) and incubating 10mins at 37 °C. Absorbance was read at 560 nm on a microplate reader. The results were analyzed using the CompuSyn software (http://www.combosyn.com/). The IC50 of each drug was determined by interpolation from the doseresponse curves. The resulting combination index (CI) determined the quantitative degree of interaction between different drugs (CI=1 was denoted additivity; CI>1 was denoted antagonism; CI<1 was denoted synergism). For interpretation, the combination was plotted as Log 10 CI versus Fa (fraction affected defined as 1 -survival fraction). Based on these plots, additivity was defined as logCI = 0; synergy was defined as log 10 CIN<0; antagonism was defined as log 10 CIN>0. Immunoprecipitation (IP) Immunoprecipitation of ST3GalI and EGFR was performed using a Pierce Crosslink IP kit (#26147) according to the manufacturer's protocol. In brief, 10µg of Erbitux (Merck, 2mg/mL) antibody was coupled and cross-linked to protein A/G plus agarose resin (0.55mL of settled resin supplied as a 50% slurry). 1×10 8 cells ES2-shST3Gal1 and ES2-scramble infected cells were rinsed with PBS, scraped and incubated in lysis buffer (0.025M Tris, 0.15M NaCl, 1mM EDTA, 1% NP40 and 5% glycerol supplemented with 1× EDTA-free protease inhibitor, Roche) for 1h at 4°C. The cell lysate was centrifuged at 10,000xg for 15min. The protein concentration in the supernatant was quantified (Bio-rad protein assay). Then, 1mg total protein was incubated with the cross-linked antibody overnight at 4°C. The immunoprecipitated proteins were washed trice with 200μL IP Lysis/Wash Buffer (0.025M Tris, 0.15M NaCl, 0.001M EDTA, 1% NP-40, 5% glycerol; pH 7.4), eluted with 60μL elution buffer (pH 2.8, contains primary amine) form protein A/G plus agarose resin binding identify EGFR protein column and resolved with 5x nonreducing lane marker sample Buffer (0.3M Tris-HCl, 5% SDS, 50% glycerol, lane marker tracking dye; pH 6.8) on a 12% SDS-PAGE. Then, western blot analysis was performed to detect either EGFR or ST3GalI using the appropriate antibodies previously mentioned (western blot section of methods). Statistical analysis Statistical analysis was performed using the SPSS software program. For cell invasion assay data, nonpaired Student's t-test was used for comparisons between groups. The Kaplan-Meier survival curves were plotted for ovarian cancer patients and the P values were determined using the log-rank test for censored survival data. Survival time was censored if the patient was alive at the time of evaluation. The relationship between IHC expression and other clinical or tumor parameters was calculated using the χ2 test. A P <0.05 was considered significant. Author contributions KC Wen and PH Wang performed the experiments and analyzed the data. KC Wen, PL Sung, SL Hsieh, YT Chou, OKS Lee, CW Wu and PH Wang contributed reagents/materials/analysis tools; KC Wen, SL Hsieh, and PH Wang wrote and revised the paper. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank the Clinical Research Core Laboratory and the Medical Science & Technology Building of Taipei Veterans General Hospital for providing experimental space and facilities. We also thank Dr. Tsui-Ling Hsu (Genomics Research Center, Academia Sinica, Taipei, Taiwan) for her technical support. Cholinesterase assay by an efficient fixed time endpoint method Highlights • An end-point method for cholinesterase determinations is performed.• This method is based on stopping the reaction after a fixed reaction time.• A large number of samples can be

processed for complex kinetic assays.• This assay can also be applied for manual, or with, automated workstations.• This procedure allows to avoid undesired reactions by DTNB and TNB. Solutions The "phosphate buffer" mentioned throughout the paper contained 0.1 M phosphate, pH 7.4, 1 mM EDTA. The "phosphate buffer/6 mM DTNB" mentioned throughout the paper contained 0.1 M phosphate, pH 7.4, and 6 mM DTNB. The "phosphate buffer/1% BSA" mentioned throughout the paper contained 0.1 M phosphate, pH 7.4, and 1% BSA. The solution used to stop the AChE reaction contained 2% SDS and 6 mM DTNB, was prepared in the phosphate buffer, and is cited as "2% SDS/6 mM DTNB solution". Acetylthiocholine iodide was dissolved in ultrapure water at the desired concentration. Thiocholine was obtained from the chemical degradation of acetylthiocholine iodide. A solution of 15 mM acetylthiocholine, pH 10, was incubated at 37 C for 5 h. The resulting thiocholine preparation was neutralised at pH 7. 4 and was diluted with ultrapure water at the desired concentration before use. Hen tissue preparation and subcellular fractioning Hen tissues were obtained from a commercial slaughter house immediately after sacrifice. Brains were removed and stored in cold (0-5 C). Tris buffer (50 mM Tris-HCl buffer at pH 8.0 containing 1 mM EDTA) until use (before 1 h). Brains were homogenised in a Polytron homogenizer (Kinematica GmbH, Germany) using a PTA 10S head at 70% power (3 Â 3 s) in Tris buffer at a concentration of 200 mg fresh tissue/ml. The homogenised tissue was centrifuged at 1000 Â g for 10 min at 4 C to yield a precipitate containing fibres and nuclei. The supernatant was then centrifuged at 100,000 Â g for 60 min to precipitate mitochondrial and microsomal fractions. The pellet (containing fibres and nuclei) was resuspended with Tris-Triton buffer (50 mM Tris-HCl buffer at pH 8.0 containing 1 mM EDTA and 1% Triton X-100). The supernatant (soluble fraction) and the resuspended pellet (membrane fraction) were kept in liquid nitrogen until use. Samples were thawed at room temperature before use. This concentrated enzyme preparation is cited through the paper as the "soluble enzyme preparation" or "membrane enzyme preparation" and was diluted with phosphate buffer at the desired concentration expressed as ml preparation/ml solution. Method details In the following described procedure, each step was performed in all the test tubes before starting the next step. In this way, a large number of samples and blanks were simultaneously tested in parallel. A 20-ml volume containing phosphate buffer (for blanks), or another reagent, was added to 1 ml microtubes. This volume may contain inhibitors or other factors that need to be tested. Then 200 ml of the diluted membrane or soluble enzyme preparation (phosphate buffer in blanks) were added. The mixture was incubated at 37 C for the desired (preincubation) time. This preincubation time can be shortened substantially if inhibitors or other factors are not tested. After this time, 200 ml of substrate acetylthiocholine in water were added for a final concentration of between 1 and 14.3 mM in 420 ml of the reaction volume. The mixture was incubated at 37 C for 10 min to run the enzymatic reaction. The reaction was stopped by adding 200 ml of 2% SDS/6 mM DTNB solution. Then 200 ml of phosphate buffer (diluted enzyme preparation in blanks) were added. The final assay volume was 820 ml. After mixing and waiting at least 5 min, a 300-ml volume from each microtube was transferred to a 96-well microplate, and absorbance was read at 410 nm. An Automated Work Station (Beckman Biomek 2000) was employed, but the process can also be performed manually. By reducing all the volumes proportionally to 1/4, for a final volume of 205 ml, the full process can be performed directly in a thermostat 96-well microplate. The data recorded by the microplate reader were processed and graphic adjustments were made with the Sigma Plot software (Systat Software Inc. Chicago, USA) for Windows. Fig. 1 shows the timing of the procedure, while Table 1 provides a schematic summary of the assay protocol. Linearity of the colorimetric measure with a thiocholine concentration A 220-ml volume of phosphate buffer and 200 ml of 2% SDS/6 mM DTNB were added to 200 ml of the indicated thiocholine solution. Absorbance was read at 410 nm. Fig. 2 shows that the absorbance at 410 nm was directly proportional to the thiocholine concentration (up to around 0.93 mM). Stability of absorbance Figs. 3 and 4 illustrate the stability of absorbance versus time in soluble or membrane preparations once the enzymatic reaction was stopped by adding the 2% SDS/6 mM DTNB solution according to the procedure described in Method details. Blanks of acetylthiocholine chemical hydrolysis in which the diluted enzyme preparations was added after adding the 2% SDS/6 mM DTNB solution were also tested. If the absorbances of the diluted enzyme preparations and the blanks remained constant versus time, the reaction was considered to have been completely stopped. Therefore, the colorimetric measurement can be taken at any time to at least 30 min for soluble preparation and at least 60 min for membrane preparation after stopping the reaction without altering colour. Assay linearity with reaction time and amount of sample A 20-ml volume of the phosphate buffer was incubated in 1 ml minitubes with 200 ml of different diluted enzyme preparations (21, 52.5 and 105 ml preparation/ml corresponding to 10, 25 and 50 ml soluble preparation/ml, respectively, in the 420-ml reaction volume) and with 200 mL of substrate (acetylthiocholine iodide at 30 mM corresponding to 14.29 mM in the 420 ml of reaction volume). After the reaction time (0, 2.5, 5, 10, 20 and 30 min) at 37 C, 200 mL of 2% SDS/6 mM DTNB solution were added. Samples with the same diluted enzyme preparation concentration, but with water with no substrate, were incubated at different reaction times. Spontaneous hydrolysis controls (samples without the diluted enzyme preparation) and controls of the colour produced by the 2% SDS/6 mM DTNB solution were included in the procedure. Fig. 5 shows the linear dependence of activity versus reaction time for the different diluted soluble enzyme preparations (Fig. 5A), and versus the enzyme concentration for the various times (Fig. 5B). The response with the concentration of the Table 1 End-point protocol for measuring acetylcholinesterase. Each step is performed with each sample/tube to be tested before starting the next step. This strategy allows testing many samples in parallel. Step Action 1 2 0 ml of buffer (or inhibitors/activators/cofactors) a 2 2 0 0 ml of diluted enzyme preparation (buffer in blanks) and mixing b (Total preincubation volume: 220 ml) 3 Preincubation time (as needed) (see Fig. 1) 4 2 0 0 ml of substrate and mixing c (Total enzyme reaction volume: 420 ml) 5 Enzyme reaction time (see Fig. 1): 10 min at 37 C 6 Stop enzyme reaction (see Read absorbance at 410 nm (see Fig. 1 diluted enzyme preparation was linear and time until absorbance was reached up to about 3.5 since the reaction was limited by the stoichiometry of the chromogenic reagent. Slight absorbance was observed at 0 min of the reaction when the enzyme concentration increased. This was interpreted as being due to the reaction between DTNB and the thiol groups of the proteins in the diluted soluble enzyme preparation. Increased absorbance was also observed for the 0 ml preparation/ml due to some spontaneous hydrolysis of the substrate. Reproducibility assay The proposed acetylcholine-hydrolyzing activity assay described in Method details was used to determine the activities of 12.5, 25, and 50 ml soluble preparation/ml with a substrate concentration of 14.28 mM acetylthiocholine in the reaction volume to study the variability of the intra-experiments values ( Table 2). Variability was less than 0.8% for the highest tissue concentration and up to 4% for the lowest one. [ ( F i g . _ 2 ) T D $ F I G ] Fig. 3. Stability of absorbance after stopping the enzyme-substrate reaction with soluble preparation. The absorbance (n = 3) of the enzyme-substrate reaction was measured. Black circles represent the absorbance of samples (50 ml soluble preparation/ml) according to the procedure described in Method details. White circles represent the absorbance of the blanks. All the points represent the main value of three replicates and standard deviation is also represented. [ ( F i g . _ 3 ) T D $ F I G ] Three independent experiments were performed on different days with a diluted soluble enzyme preparation of 25 ml soluble preparation/ml in the reaction volume and with a substrate concentration of 1 mM acetylthiocholine in the reaction volume to study the variability of the inter-experiments (inter-die) values (Table 3). The variability of each independent experiment was between 1.6 and 5.0%, whereas the variability of the averages among the three experiments was 6.45%. When considering all the data globally (n = 24), variability was 4.19%. [ ( F i g . _ 4 ) T D $ F I G ] Table 2 Intra-assay reproducibility. The experiment was performed according to the assay described in Method details. The substrate concentration was 14.28 mM acetylthiocholine in the reaction volume and the reaction time was 10 min. The activity was estimated according to the linear regression parameters obtained in the thiocholine calibration curve (Fig. 2). Comparison between the usual kinetic Ellman's method and the proposed method Kinetic Ellmans's method: 100 ml of 0.2 nM hButChE in phosphate buffer/1% BSA were mixed with 100 ml of phosphate buffer/6 mM DTNB and 20 ml of ultrapure water. After that 200 ml of 2.1 mM acetylthiocholine in water were added and incubated at at 25 C. Absorbance at 410 nm was read every 2 min since 3 min of starting the reaction until 17 min. The absorbance versus reaction time was lineal. The increase of absorbance between 5 and 15 min reaction time was 1.063 AE 0.047. A calibrate curve was performed in the same conditions. The lineal regression parameters were y 0 = 0.004, m = 11.693 and R 2 = 0.9896 from which the estimated specific activity was to 0.37 AE 0.02 mmol thiocholine/nmol hButChE/min. Proposed fixed time endpoint method: 100 ml of 0.2 nM hButChE in phosphate buffer/1% BSA were mixed with 100 ml of phosphate buffer and 20 ml of ultrapure water for samples, or 100 ml phosphate buffer/1% BSA were mixed with 100 ml of phosphate buffer without EDTA and 20 ml of ultrapure water for blanks. After that 200 ml of 2.1 mM acetylthiocholine in water were added. The reaction was at 25 C. After 10 min, the reaction was stopped adding 200 ml 2% SDS/6 mM DTNB and then, 100 ml phosphate buffer/1% BSA and 100 ml of phosphate buffer without EDTA were added to samples, and 100 ml of 0.2 nM hButChE in phosphate buffer/BSA and 100 ml of phosphate buffer without EDTA were added to blanks. The absorbance was read at 410 nm. The corrected absorbance (difference with blank) was 0.862 AE 0.010. The activity was estimated to be 0.66 AE 0.03 mmol thiocholine/nmol hButChE/min. The activity obtained by the proposed fixed time endpoint method is higher than the activity obtained through the usual kinetic Ellman's method. This difference of activities can be explained because DTNB interacts with the protein [5] in the usual kinetic Ellman's method because DTNB is in the medium during the enzymatic reaction. Proteinaceous effector discovery and characterization in filamentous plant pathogens Abstract The complicated interplay of plant–pathogen interactions occurs on multiple levels as pathogens evolve to constantly evade the immune responses of their hosts. Many economically important crops fall victim to filamentous pathogens that produce small proteins called effectors to manipulate the host and aid infection/colonization. Understanding the effector repertoires of pathogens is facilitating an increased understanding of the molecular mechanisms underlying virulence as well as guiding the development of disease control strategies. The purpose of this review is to give a chronological perspective on the evolution of the methodologies used in effector discovery from physical isolation and in silico predictions, to functional characterization of the effectors of filamentous plant pathogens and identification of their host targets. | INTRODUC TI ON If people think Nature is their friend, then they sure don't need an enemy. Kurt Vonnegut, Letter in Time magazine

| The threats from filamentous phytopathogens Our expanding global population forces us to intensify our crop production as we prepare to feed 2.2 billion more people by 2050. One of the main biotic challenges facing society to meeting these evergrowing demands are filamentous plant pathogens. Oomycetes and fungi are the causal agents of some of the most notorious plant diseases and are a true threat to our global food security and community structures. Plant disease outbreaks have occurred throughout human history, some of the most infamous include the Irish potato famine caused by the oomycete Phytophthora infestans (Turner, 2005), Panama disease caused by Fusarium oxysporum f. sp. cubense (Gordon, 2017), and wheat stem rust caused by Puccinia graminis f. sp. tritici (Roelfs, 1985;Singh et al., 2011). | Effectors and the plant immune response The elegantly described "zig-zag" model by Jones and Dangl (2006) reveals a two-tier immune response where pathogen-associated molecular patterns (PAMPs) are first detected on host cell surfaces | The importance of effector research Hundreds of small proteins, predicted to be effectors, are secreted by filamentous phytopathogens during host colonization (Dean et al., 2005;Kämper et al., 2006;Yoshida et al., 2009;Duplessis et al., 2011). We have little understanding of the function of most of these putative effectors and each typically shares minimal or no sequence homology to proteins with previously defined functions. However, the effector repertoire of a pathogen is a major determinant of host specialization and can greatly impact whether the plant-pathogen interaction is successful or not based on the genotype of the host (Raffaele et al., 2010;Sánchez-Vallet et al., 2018a). Molecular studies have characterized over 60 fungal effectors across multiple species; however, this barely makes a dent in the candidate effector repertoire for each pathogenic species (Sperschneider et al., 2015). For example, the barley powdery mildew fungus Blumeria graminis f. sp. hordei alone is suspected to have roughly 7% of its genome encoding candidate secreted effector proteins (CSEPs) (Pedersen et al., 2012). Identifying and characterizing the function of effector proteins will improve our understanding of their role in disease formation and influence our future strategies to combat pathogen infections. Fundamental effector research is a key part of devising new plant disease control strategies and this is detailed further in Sections 3.2 and 6 of this review. Effectors play an important role in crop breeding where, as well as being used to detect resistance genes in new cultivars, characterized effectors can be used to locate susceptibility loci in vulnerable crops (Vleeshouwers and Oliver, 2014). The development of mobile sequencing technology means that genes encoding effectors can also be used to detect the emergence of new strains of crop pathogens in the field and elude the severity of future disease outbreaks (Radhakrishnan et al., 2019). Effectors function in multiple ways, including inhibiting host enzymes, modulating plant immune responses, and targeting host gene-silencing mechanisms. All features of effectors described in this article are summarized in Table 1 Sohn et al. (2007) Avr1b-1 204 G5A9E5 Uncharacterized Phytophthora sojae Stem and root rot of soybean Soybean (Glycine max) Shan et al. (2004); Dou et al. (2008) Has been shown to reduce heterologously induced plant cell death Avr1-C039 89 NA Uncharacterized protein that is recognized in the host by direct binding of the NB-LRR proteins RGA5, which together with RGA4 induces ETI a Number of amino acids including signal peptide. TA B L E 1 (Continued) that become important in many subsequent effector identification stories (van Kan et al., 1991). | Homology searches Once an effector has been cloned, the sequence can be used to identify homologous candidates in closely related species. Three elicitins were isolated from Phytophthora spp. using proteomics techniques: cryptogein (P. cryptogea), cinnamomin (P. cinnamomi), and capsicein (P. capsici) Pernollet, 1989, Ricci et al., 1989). Primers were deigned based on conserved regions of the elicitin amino acid sequences and used to probe cDNA libraries from P. parasitica, leading to the discovery of the host-specific elicitor protein PARA1 (Kamoun et al., 1993). | Genetic mapping Prior to the genomics era, the isolation of Avr proteins from intracellular colonizing fungal pathogens such as Magnaporthe oryzae and haustoria-producing pathogens was unsuccessful using the proteomics approach. Instead, in the case of the rice blast fungus M. oryzae, map-based cloning techniques were used to clone Avrs such as Avr1-CO39 (Farman and Leong, 1998). Avr1-CO39 was mapped to a region on chromosome 1 by a series of backcrosses of the progeny of the virulent isolate Guy11 and the avirulent isolate 2539 (Smith and Leong, 1994). Later, a chromosome-walking strategy led to the physical mapping and identification of Avr1-CO39. The identity of the Avr1-CO39 locus was confirmed by transforming the virulent Guy11 strain with cosmids from the Avr1-CO39 genetic interval. This resulted in a loss of pathogenicity on rice cultivars containing the corresponding functional CO39 resistance gene (Farman and Leong, 1998). | Always lagging behind By the end of the 20th century, over 30 bacterial Avr genes had been cloned and characterized by screening cosmid libraries, with almost all of these coming from two host-specific species of Pseudomonas and Xanthomonas (Leach and White, 1996;De Wit, 1997). In comparison, using proteomics and genetic mapping, only eight fungal phytopathogen Avr genes had been successfully identified and confirmed to be effectors (Laugé and De Wit, 1998). But all this was about to change. | Sanger and next-generation sequencing of pathogen genomes In the early 2000s, the Fungal Genome Initiative (FGI) was established following the publication of a white paper (Birren et al., 2003) F I G U R E 1 A timeline showing the progression of filamentous plant pathogen effector prediction and identification from the pregenomic era to the present day. The first effectors identified using these methods are included as well as the elicitins used for homology-based searches. Increasingly, pangenome data are used to predict core and novel candidates but as yet none have been characterized using this technique. For a recent review of pangenomics see Golicz et al. (2019). Details on individual effectors named are given in Table 1. to promote the sequencing in the public domain of fungal genomes belonging to species important to human health, agriculture, and industry. By 2017 a total of 191 genomes of fungal plant pathogens had been sequenced, including the economically important M. oryzae, Fusarium graminearum, and Botrytis cinerea (Dean et al., 2005(Dean et al., , 2012Cuomo et al., 2007;Amselem et al., 2011;Aylward et al., 2017). This, together with the publication of numerous oomycete genomes, including the late potato blight pathogen Phytophthora infestans (Haas et al., 2009), as well as extensive in planta and in vitro transcriptome data sets, has led to an explosion in effector discovery. These techniques for effector discovery are summarized in Table 2. | REFINING EFFEC TOR PRED I C TI ON Truth, like gold, is to be obtained not by its growth, but by washing away from it all that is not gold. | Secretion As the de Wit et al. studies demonstrated, a key feature of effectors is secretion by the pathogen into the host (De Wit et al., 1985;Asai and Shirasu, 2015). Therefore, early studies in effector discovery using sequencing data focused on the predicted secretome. In a bid to identify extracellular effector proteins, Torto et al. (2003) used their PEX-finder algorithm to mine transcript datasets of the potato pathogen P. infestans. The algorithm searched for a specific amino acid sequence known as a signal peptide followed by a cleavage site commonly found at the N-terminus of secreted proteins (Nielsen and Krogh, 1998;Torto et al., 2003). Of the 261 cDNAs predicted to code for secreted proteins, 78 had no matches to those found in the public databases, a feature common to candidate effectors. Using high-throughput functional expression assays this study led to the discovery of a large complex family of effectors called crinklers (CRNs), which are found throughout the pathogenic oomycetes (Schornack et al., 2010;Amaro et al., 2017). However, some characterized secreted effectors lack a signal peptide. For example, the effectors, PsIsc1 and VdIsc1, produced by Phytophthora sojae and Verticillium dahliae, respectively, have been shown to be unconventionally secreted into the respective host to suppress salicylate (SA)-mediated defences in planta (Liu et al., 2014). Another difficulty is that such broad criteria leaves a large pool of possible effector candidates that are demanding in both time and resources to functionally characterize, with studies often having low discovery rates. The Magnaporthe grisea effector MC69, essential for appressoria formation (Motaung et al., 2017), was the only candidate from 1,306 putative secreted proteins that was found to be required for pathogenicity following large-scale gene disruptions (Yoshida et al., 2009;Saitoh et al., 2012). | Domains The C. fulvum effector Ecp6 sequesters the fungal cell wall protein chitin, preventing chitin fragment detection by the host PRRs, and thereby evades a host immune response (De Jonge et al., 2010). Ecp6 contains LysM domains that bind to chitin with ultrahigh affinity, therefore outcompeting host immune receptors (Sánchez-Vallet et al., 2013). The LysM domain found in Ecp6 has now been identified in over 302 putative effectors from 62 published fungal genomes, and is conserved among effectors targeting the chitin detection aspect of plant immunity (De Jonge and Thomma, 2009;Lee et al., 2014). On the other hand, the Avr2 effector from C. fulvum and the EPIC1 and EPIC2 effectors from P. infestans both target the tomato defence protease Rcr3 (Song et al., 2009) yet are unrelated and share no sequence similarity, thus relying on the presence of conserved domains could cause many possible candidates to be overlooked. | Motifs The first four oomycete Avr effectors cloned, ATR13 and ATR1 NDWsB from the downy mildew Hyaloperonospora parasitica (Allen et al., 2004;Rehmany et al., 2005), Avr3a from P. infestans , and Avr1b-1 from P. sojae (Shan et al., 2004), showed no sequence similarity except for two conserved motifs at the N-terminus. These RxLR and DEER motifs have since been identified as N-terminal host targeting domains and, in P. infestans, the RxLR motif in the Avr3a effector is required for translocation into potato cells (Whisson et al., 2007;Bos et al., 2010). RxLR effectors have been identified in multiple Phytophthora, Albugo, and Hyaloperonospora species, with 568 RxLR genes being found in P. infestans alone, making this the largest oomycete effector family to date (Anderson et al., 2015). Rapid variation and host specialization are attributed to the general lack of sequence similarity in filamentous pathogen effectors, yet this mostly contributes to the variation in the C-terminus of oomycete effector sequences, leaving the N-terminal motifs largely conserved . Conserved motifs such as RxLR and the more downstream DEER are used as powerful bioinformatic tools to isolate putative effector repertoires from genomic sequences (Jiang et al., 2008;Raffaele and Kamoun, 2012). Within pathogenic fungi there is limited evidence for conserved translocation motifs. One possible exception is the [YFC] xC motif found in Blumeria graminis f. sp. hordei and Puccinia spp., members of the phyla Ascomycota and Basidiomycota, respectively (Godfrey et al., 2010;Duplessis et al., 2011). The evolutionary distance between these two fungi suggests a deep homology in the conservation of this motif, linked to a biotrophic lifestyle that uses haustoria-based feeding. However, the general lack of sequence similarity or conserved domains means that bioinformatic approaches to effector prediction need to go beyond sequence homology. | Structure The structural properties of proteins are more highly conserved than amino acid sequences (Illergård et al., 2009) and therefore could be used as a tool for effector prediction. The structural similarities between the two sequenced M. oryzae effectors Avr1-CO39 and Avr-Pia were found using two-and three-dimensional nuclear magnetic resonance (NMR) experiments (de Guillen et al., 2015) and led to the discovery of the Magnaporthe Avr and ToxB-like effector family (MAX), which contains half of all cloned M. oryzae Avrs despite sharing less than 25% sequence identity (de Guillen et al., 2015). The structural analysis of four RxLR oomycete effectors showed the presence of a conserved C-terminus 3-α-helix fold (Boutemy et al., 2011;Yaeno et al., 2011). This WY domain, named after the interacting tryptophan and tyrosine residues, hints to a core, stable protein scaffold as a source of protein function (Wirthmueller et al., 2013). Resolving the structure of known effector proteins provides a useful tool for supporting the candidacy of putative effectors. One of the early effectors to be structurally resolved was ToxA produced by the

tan spot fungus, Pyrenophora tritici-repentis. The ToxA crystal structure was resolved using X-ray crystallography (1.65 Å) and revealed a novel β-sandwich fold (Sarma et al., 2005). Later, the resolution of the flax rust, Melampsora lini, effectors AvrL567-A and -D showed a similar β-sandwich fold hinting at the structural homology of unrelated effector proteins (Wang et al., 2007). Recently the structures of two candidate effectors in the poplar rust fungus, Melampsora larici-populina, were resolved using NMR. One, MLP124266, is the first fungal protein to present a knottin-like structure (Postic et al., 2017) | Rich in cysteines but not in size The additional criteria for candidate effector selection often require secreted proteins to be small and cysteine-rich (Sperschneider et al., 2015). The presence of multiple cysteines enables the formation of stabilizing disulphide bridges (De Wit et al., 1986;Doehlemann et al., 2009). Relying on such broad criteria can be problematic as, despite many known effectors sharing these features, these are not universal requirements. NIS1, first described in the cucumber anthracnose fungus Colletotrichum orbiculare (Yoshino et al., 2012), is conserved across both Basidiomycota and Ascomycota (Irieda et al., 2019), but contains no cysteines. Relying on the size of mature peptides as a parameter for effector identification can also be problematic. The maximum size of a small protein in effector discovery can be anything from 150 to 400 amino acids (Bowen et al., 2009;Saunders et al., 2012b). However, even the larger size limits would exclude the P. graminis f. sp. tritici effector AvrSr35 with a mature length of 578 amino acids (Salcedo et al., 2017). With these issues in mind, bioinformatic pipelines have been developed to encompass multiple criteria to refine effector prediction. Saunders et al. developed an in silico analysis pipeline that moved away from reliance on sequence similarity-based methods for effector identification and included physiological functions such as expression profiles, taxonomic information, and genomic features of potential candidates (Saunders et al., 2012b). To identify the repertoire of potential effectors within two rust fungus genomes, a clustering algorithm grouped candidates into families and ranked their likelihood of being effectors based on the knowledge that filamentous pathogen effectors have a least one of eight specific properties. | Bespoke bioinformatic pipelines These properties included the absence of recognized Pfam domains, similarities to haustorial proteins, and the presence of internal repeats. The number of candidates continued to functional analysis using this pipeline was greatly reduced (Saunders et al., 2012b). This approach has limitations as it is dependent on the thresholds based on a priori assumptions about effector properties; the number of missed effectors remains to be seen. (Pierleoni et al., 2008;Armenteros et al., 2019). The subcellular localization of candidate effectors can also be predicted by searching for chloroplast or mitochondrial transit peptides or nuclear localization signals using tools such as WoLF-PSORT (wolfpsort.hgc.jp/) or LOCALIZER (localizer.csiro.au/) (Horton et al., 2007;Sperschneider et al., 2017). Machine learning has also resulted in the development of web-based tools that can predict with 89% accuracy whether proteins in the predicted secretome are effectors or not. EffectorP2.0 (effectorp.csiro.au/) takes into account the net charge and serine/cysteine content of proteins to prioritize candidate effectors for further functional validation (Sperschneider et al., 2018). | Genomic landscape and transposable elements Many fungal plant pathogens exhibit a two-speed genome, with distinct genomic compartments evolving at different rates. Alongside core stable regions, which are slow to evolve and often contain genes involved in metabolism, are hypervariable areas with high recombination and richness in repetitive sequences, including transposable elements (TEs). This genomic landscape and the presence of TEs serve to drive adaptive evolution (Faino et al., 2016) and these hypervariable regions often are the location of genes associated with pathogenicity, including effectors (Fouché et al., 2018;Jones et al., 2018). In M. oryzae and Zymoseptoria tritici, TEs are associated with pathogenicity clusters and are seen to flank the first characterized Z. tritici effector, AvrStb6 (Bao et al., 2017;Zhong et al., 2017). TEs have also been shown to interfere with effector gene expression via epigenetic control. For example, AvrLm1 in Leptosphaeria maculans, located in a TE-rich genomic region, showed distinct histone methylation that acts to temporarily suppress expression during colonization to evade host recognition (Soyer et al., 2014;Fouché et al., 2018). This suggests that the variability of the genomic region or the proximity to TEs maybe useful factors in refining the search for candidate effectors. Following the sequencing, genome assembly and annotation of the tumour-forming maize smut fungus Ustilago maydis, c.18% of genes encoding secreted proteins were found to be arranged into 12 discrete clusters within the genome (Kämper et al., 2006). These clusters were co-regulated by a central pathogen-development regulator and expression induced in tumour tissue. Deletions of five clusters caused clear changes in virulence, including the largest cluster, 19A, which caused a strong attenuation in virulence and reduced tumour formation upon deletion (Kämper et al., 2006;Brefort et al., 2014). Subsequent subdeletions of 19A members led to the identification of the effector Tin2, required for anthocyanin production Tanaka et al., 2014). | Comparative genomics By comparing the genomes of U. maydis and Sporisorium reilianum, Schirawski et al. (2010) found that effector clusters and pathogenicity-related regions were more highly diverged between the close relatives than the rest of the genome. This comparison led to the identification of the pit gene cluster involved in tumour formation in U. maydis . Within this cluster the secreted effector Pit2, involved in plant defence suppression and cysteine protease inhibition, was found Mueller et al., 2013). This same comparison was used to locate gene clusters and candidate effectors in S. reilianum, and whilst genes that have a partial impact on disease severity have been identified, as yet no candidates strongly attenuate virulence (Ghareeb et al., 2019). | Lineage-specific elements Novel effectors were identified in the asexual fungus V. dahliae, where chromosome reshuffling has led to the formation of lineage-specific (LS) regions of plasticity in the genome (de Jonge et al., 2013). These LS regions are enriched with retrotransposon and repetitive sequence elements, as well as being the location of many candidate effectors. Contrary to the two-speed genome hypothesis, these LS regions show strong levels of conservation with little to no single nucleotide polymorphisms (SNPs) being identified, even within the intergenic regions . In one such LS region, four putative effectors were identified, including the LysM domain containing effector Vd2LysM, which was only found in the VdLs17 strain (de Jonge et al., 2013). | Sequence divergence Molecular variation in filamentous phytopathogen genes is known to be essential for altering pathogen-host interaction outcome and can provide insight into the evolution of virulence (Allen et al., 2008). Polymorphisms in effector sequences among isolates can impact on virulence and are involved in host adaptation; this makes them promising targets for disease control strategies. The genomes of four isolates of the wheat yellow stripe rust fungus Puccinia striiformis f. sp. tritici were resequenced and assessed for SNPs. Proteins that displayed nonsynonymous substitutions between isolates that differed in virulence on specific wheat cultivars were identified (Cantu et al., 2013). This led to five secreted polymorphic candidate effectors being nominated for further characterization from a predicted secretome of 2,999 proteins. This sequence divergence has also proved useful in identifying pathogens in the field. Using the Oxford Nanopore MinION sequencer, 242 highly variable genes were used to collect real-time population dynamics data of P. striiformis f. sp. tritici isolates in Ethiopia (Radhakrishnan et al., 2019). This Mobile And Real-time PLant disEase (MARPLE) diagnostic system can be used to monitor the emergence of plant pathogen strains, but can also be adapted to include newly characterized effectors within the panel of genes. Going forward, MARPLE will allow for the monitoring of mutations and the detection of effector evolution that may be linked to gain of virulence of phytopathogens, all within the confines of the field. | Association mapping in the sequencing era In silico predictions of effectors, whilst allowing us to rapidly screen whole genomes for candidates, lack discriminatory power and often result in candidate effectors having no clear impact on pathogen virulence. Genome-wide association studies (GWAS) and quantitative trait locus (QTL) mapping can identify loci associated with heritable phenotypic variation, such as virulence, thereby complementing techniques to identify and clone Avr effectors recognized by known host resistance proteins . The Zymoseptoria tritici effector AvrStb6 was isolated in this way . Using crosses between two Swiss strains of Z. tritici, QTL mapping found a confidence interval containing nine candidates for AvrStb6. Combining this with a GWAS study from over 100 different natural isolates led to one candidate, a small cysteine-rich secreted protein that was not present in the original Z. tritici genome annotation ). An additional benefit of using GWAS in effector discovery is that the natural variation in SNP calling identified in wild populations can be used to quantify how each SNP contributes to pathogen virulence (Sánchez-Vallet et al., 2018b). Integrating GWAS with transcriptome dataset, referred to as transcriptome-wide association studies (TWAS) (Wainberg et al., 2019), identified the link between genes and traits across populations and has been used to discover Blumeria graminis f. sp. hordei Avr a effectors, including Avr a9 (Saur et al., 2019a). | FUN C TIONAL CHAR AC TERIZ ATION Make your work to be in keeping with your purpose. | Knock out or knock down: let's be disruptive One of the simplest ways to determine the pathogenicity of a candidate effector is to disrupt the encoding gene and determine whether the virulence on a susceptible host or the Avr phenotype on a resistance genotype is compromised. Early transformation studies of the C. fulvum effectors relied on double homologous recombination to insert a selectable marker into the target gene encoding a known effector such as ecp1 and ecp2, thus disrupting them (Laugé et al., 1997). Later sequencing technology allowed transformations without the need for cloning. Mutants of the corn smut fungus Ustilago maydis were made using PCR-based protocols combined with protoplast transformation to generate candidate effector knockout mutants (Schulz et al., 1990;Kämper, 2004). This method is widely used and has successfully facilitated the functional characterization of U. maydis effectors, including Rsp3 and Cce1 (Ma et al., 2018a;Seitner et al., 2018). Agrobacterium tumefaciens-mediated transformation (ATMT) is another method to disrupt genes and is widely used in plant transformations. ATMT was first used in fungi in budding yeast in 1995 and then the technique was adapted for use in filamentous fungi, including M. oryzae (Bundock et al., 1995;Rho et al., 2001). This method relies on the targeted insertion of a selectable marker into the fungal genome from a disarmed Ti plasmid of transformed Agrobacterium to disrupt the gene of interest. The selectable marker is incorporated into the fungal genome via homologous recombination, a process that occurs easily in yeast. This mechanism, however, is highly variable in filamentous fungi, where nonhomologous end-joining (NHEJ) appears to be the dominant DNA repair pathway over homologous recombination (Meyer et al., 2007;Villalba et al., 2008). The Ku70 protein is part of a complex that regulates the NHEJ pathway (Ninomiya et al., 2004), and its deletion has led to the increase of homologous recombination in M. oryzae from <25% to 80% (Kershaw and Talbot, 2009). Combining ATMT with the generation of ∆Ku70 mutants led to the characterization of the Z. tritici Avr effector AvrStb6 . Another, more recent, method of gene disruption is using the genome-editing system CRISPR-Cas9. Originally identified as an immune mechanism in bacteria and archaea, the CRISPR-Cas9 system is used as a genome-editing tool in plants and animals, and was adapted by Nødvig et al. (2015) for use in filamentous fungi (Mali et al., 2013;Fauser et al., 2014;Nødvig et al., 2015). This technique has led to targeted gene disruption and consequent characterization of effectors in the oomycete P. sojae and the fungal pathogen U. maydis (Fang and Tyler, 2016;Schuster et al., 2018). There are, however, difficulties in producing stable transformants in phytopathogens that are obligate biotrophs (Thomas et al., 2001;Lorrain et al., 2019). In these cases, knockdown technologies | In planta expression When a candidate effector is heterologously expressed in planta various functional assays can be used to determine the virulence activities of the protein. Necrosis assays monitor for the induction of HR-like cell death, which can be a result of Avr/R protein/guardee protein interactions or be directly induced by the candidate effector. These assays

were first carried out using the model plant Nicotiana tabacum (tobacco), which is infiltrated with transformed Agrobacterium that delivers the effector gene expressed from an inducible promoter into the plant cell for transient protein production (Kamoun et al., 1999;Qutob et al., 2002;Ma et al., 2012). In 1999 the P. infestans and C. fulvum effectors Inf1 and Avr9, respectively, were transformed into either wild-type or Cf-9 transgenic N. tabacum using this method. The assay showed that INF1 was capable of inducing necrosis in wild-type tobacco whilst Avr9 could only do so in transgenic tobacco expressing the corresponding R gene Cf-9 (Kamoun et al., 1999). Later Avr9 and Cf-9 were transiently coexpressed in N. tabacum using agroinfiltration to confirm the induction of HR in the nonhost plant following expression of the Avr/R gene pairs (Van der Hoorn et al., 2000). Effector characterization in nonhost dicotyledonous model plants maybe more suited to high-throughput screening than in cereal hosts. However, these highly artificial scenarios do have several limitations. A negative screen with no visible phenotype upon recombinant expression may indicate either the candidate is not an effector or the effector target/receptor is lacking in the model species. On the otherhand, HR-induced necrosis in an effector screen may not be caused by a specific effector/target interaction but by nonhost resistance (NHR) triggered by detection of the candidate (Kettles et al., 2017). Although of interest, by definition the latter F I G U R E 2 The host-induced gene silencing (HIGS) construct encodes an inverted sequence that forms a hairpin double-stranded (ds) RNA following transcription and is introduced into the host plant either by transient or stable transformation. The dsRNA is processed to form small interfering RNA (siRNA), either before or after delivery to the pathogen cell using the plants innate RNAi machinery. Once inside the fungal cells the siRNA silences the target effector genes by interfering with the target mRNA transcripts (Koch et al., 2018). The movement of small RNA between host and pathogen is detailed by Wang and Dean (2020). scenario would not occur in native host interactions. Therefore, expression assays in the native host maybe the more useful for functional characterization. Candidate effectors can be transiently expressed in protoplast cells and cell death monitored via the reduction in expression of a co-transfected reporter gene such as β-glucuronidase (GUS) or luciferase (Chen et al., 2006;Lu et al., 2016). This approach was used to identify the cell death-inducing properties of five M. oryzae effectors, including MoCDIP4 (M. oryzae cell death inducing protein 4), in rice protoplasts (Chen et al., 2012) and the NLR-mediated recognition of four newly identified barley powdery mildew avirulence effectors, including AVR a9 , in barley (Saur et al., 2019a). Cell-death suppression assays are used to detect the alteration of the plant immune response induced by a known cell death elicitor. The overexpression of the stem rust candidate effector PSTha5a23 in Nicotiana benthamiana suppresses P. infestans INF1-triggered cell death, indicating that PSTha5a23 plays a role in controlling plant defence responses (Cheng et al., 2017). An alternative method of expressing effectors in plant cells uses the bacterial type III secretion system (T3SS) derived from the tomato bacterial speck pathogen Pseudomonas syringe pv. tomato DC3000 (He et al., 2004). This system was first adapted for filamentous plant pathogens by Sohn et al. (2007) (Whisson et al., 2007;Fabro et al., 2011). Despite T3SS being used to screen effector candidates of stem rust (P. graminis f. sp. tritici) and bean rust (Uromyces appendiculatus), this system is rarely used for fungal effector characterization and has limited success on cereals (Upadhyaya et al., 2014;Qi et al., 2019;Saur et al., 2019b). These problems are linked to the required unfolding and refolding of effectors prior to insertion, especially those rich in cysteine-cysteine bridges. As well as monitoring for necrosis, or lack thereof, the in planta growth of another pathogenic species can be used as a proxy to | The viral overexpression system Due to the limited effectiveness of both T3SS and Agrobacteriummediated transient expression in most cereal species, viruses have been developed as efficient vectors for heterologous protein expression (viral overexpression, VOX) (Lee et al., 2012). The barley stripe mosaic virus (BSMV) was first verified as a tool for protein expression when used to overexpress the luciferase reporter gene in protoplast cells and later to express green fluorescent protein (GFP) in planta (Joshi et al., 1990;Haupt et al., 2001;Lawrence and Jackson, 2001). The BSMV vector was adapted for use in the VOX system and used to characterize the function of the fungal effector ToxA (Manning et al., 2010) (Figure 3). However, the compact nature of the virus results in a negative correlation between fragment size and stability of the viral vector (Avesani et al., 2007;Bruun-Rasmussen et al., 2007). BSMV-VOX has been widely used for heterologous expression of proteins up to 150 amino acids; however, as previously stated there is no agreed size limit for an effector (Figure 3a; Bouton et al., 2018). Another limitation of BSMV for use in effector discovery is that this virus has a tripartite RNA genome (Figure 3b). The heterologous protein is inserted into the γ genome yet all three subgenomes are required to combine for successful expression in planta making BSMV-VOX unsuitable for high-throughput screening assays. The foxtail mosaic virus (FoMV) has been adapted for use in VOX systems in cereals (Bouton et al., 2018). Vectors derived from FoMV such as PV101 avoid many of the caveats of those from BSMV. FoMV has a monopartite RNA genome and the PV101 vector can be used to successfully express proteins up to 600 amino acids in size. In addition, unlike BSMV vectors, PV101 allows for heterologous expression of proteins in their native form, including possible signal peptides, without the need for processing from proteases that may only be 90% efficient (Bouton et al., 2018). In situations where the effector expressed from the VOX vector rapidly triggers R protein-mediated defences, virus spread is halted and therefore the phenotypic readout in the bioassay is the lack of systemic spread of the recombinant virus (Saintenac et al., 2018). | Where do they go? Knowing the localization of candidate effectors within host tissues not only demonstrates that the protein can be translocated from the pathogen to its host, but also suggests where the effector target(s) may be found. Traditionally in situ hybridization assays were done where antibodies were raised against the effector or an added epitope tag and detected using transmission electron microscopy (TEM). Translocation of fungal effectors into the host cell was first shown using an immunocytochemical approach in rusts. The goldand fluorescence-labelling of four independently raised antibodies to the RTP1p protein in Uromyces fabae and its homolog in Uromyces striatus showed that in later stages of infection RTP1p translocated from the extrahaustorial matrix to inside the plant cell itself (Kemen et al., 2005). For apoplastic effectors, localization was often determined by means of their isolation. The C. fulvum effectors Avr2, Avr4, Avr9, and Ecp6 were directly isolated from the apoplastic fluid, whereas the P. infestans protease inhibitor EPIC1 was isolated from the apoplast after antibodies were raised Rooney et al., 2005;Tian et al., 2007;Bolton et al., 2008). Whilst successful, these approaches are laborious, expensive, and not suited to high-throughput screening of either apoplastic or cytoplasmic effector candidates (Dalio et al., 2017). The nuclear localization of the P. infestans CRN effectors was determined using N-terminal GFP tagging and confocal microscopy. By overexpression five GFP-CRN (without the signal peptide) fusion proteins in planta the effectors were shown to accumulate within plant cell nuclei (Schornack et al., 2010). High-throughput screening of 61 candidate effectors (ChECs) from the anthracnose fungus Colletotrichum higginsianum using this method found that whilst nine of the ChECs were imported into the nucleus, others localized to the Golgi bodies, microtubules, and peroxisomes, all novel targets for fungal effectors (Robin et al., 2018). The U. maydis effectors Cmu1 and Tin2 have been shown to localize to the maize cytoplasm; however, this could not be demonstrated when fluorescently tagged (Djamei et al., 2011;Tanaka et al., 2014;Tanaka et al., 2015). This may be due to the tags inhibiting the partial unfolding of the effectors, thereby preventing their translocation, or the incorrect refolding of the tags themselves upon entering the cytoplasm (Lo Presti et al., 2015). Whilst investigating the translocation of M. oryzae effectors into rice cells, fluorescent-tagged cytoplasmic effectors were seen to first accumulate in the plant-membrane derived infection structure, the biotrophic interfacial complex (BIC), prior to delivery into the cytoplasm, whereas tagged apoplastic effectors localized to the invasion hyphae (Mosquera et al., 2009;Khang et al., 2010). The BIC's role in effector translocation could only be confirmed by the addition of a nuclear localization signal (NLS) to cytoplasmic effectors, causing artificial accumulation in the nucleus of the neighbouring rice cells. This approach concentrated the fluorescent signal into discrete foci observable using live cell imaging (Khang et al., 2010). For apoplastic effectors it is difficult to distinguish between apoplastic or cytoplasmic localization when the fluorescently tagged candidates appear to localize to the plasma membrane or cell wall. and was evenly distributed throughout the enlarged space (Oparka, 1994;Doehlemann et al., 2009 | A shot in the dark: unbiased screening Unbiased "forward" screening to find protein-protein interactions (PPI) is a common technique used in many aspects of molecular biology. The yeast two-hybrid system (Y2H), first developed 30 years ago, allows for the large-scale screening of cDNA libraries derived from pathogen-infected plants for effector target identification (Fields and Song, 1989;Mukhtar et al., 2011). Interactions detected by Y2H screens must be validated by additional PPI assays as this approach is prone to false positives. The most common Y2H validation technique is co-immunoprecipitation (Co-IP). Co-immunoprecipitation is used to screen effector interactors in heterologous systems. When 20 candidate poplar rust fungus (M. larici-populina) effectors were tagged with GFP and expressed in N. benthamiana, five were found to specifically interact with plant proteins by pull-down assays using anti-GFP followed by protein purification (Figure 4a) (Petre et al., 2015). Biotinylation is also used for proximity labelling based on tools such as BioID . A benefit of proximity labelling over co-immunoprecipitation is the possibility of identifying proteins that only weakly or transiently interact with the target (Figure 4b). Recently a new proximity labelling tool, TurboID, has been shown to provide more efficient labelling in planta compared to BioID and can also reduce the biotin incubation time from 16 hr to 10 min (Branon et al., 2018;Zhang et al., 2019). These new advances in PPI technology pave the way for higher-throughput effector interaction screening in planta. | Split-marker complementation The effector Pep1 is essential for the pathogenicity of the corn smut fungus U. maydis (Doehlemann et al., 2009). The direct interaction between Pep1 and the plant peroxidase POX12 was validated using the bimolecular fluorescence complementation (BiFC) assay ( Figure 4c), which involves two parts of a fluorescent marker being fused to candidate interactors. Only when the interactors meet can the full-length fluorescent marker assemble and be detected. Alternatively, the firefly-derived enzyme luciferase can be used for split-marker complementation. This has the advantage over BiFC for in planta studies because luciferase does not require excitation by light for detection, thereby eliminating autofluorescence interference . However, using split-marker complementation for PPI validation is not infallible as heterologous overexpression of proteins in N. benthamiana can affect protein localization and therefore interactors. | Structural interactions: pinpointing the surface contacts and their strengths Knowledge of effector structures whilst in complex with their targets gives us a greater insight into the molecular basis of these crosskingdom interactions. The C. fulvum effector Avr4 was one of the first to be characterized from a family of effectors that bind to and protect fungal cell-wall chitin from host chitinase van den Burg et al., 2006). Recently the crystalline structure of Avr4 in complex with its chitin ligand (resolved to 1.95Å) has highlighted the residues required for this function (Hurlburt et al., 2018). Structural mutant studies have also shown that recognition of the Avr4 by the cognate Cf-4 immune receptor does not depend on the same ligand binding as previously thought (Hurlburt et al., 2018). The crystal structure of the rice intracellular NLR immune receptor Pik in complex with the M. oryzae effector Avr-Pik (1.6Å resolution) reveals molecular details of the recognition event that leads to HR-induced cell death (Maqbool et

al., 2015). The effector surface involved in this interaction was also identified as being involved in the surface interactions between Avr-Pia and the NLR-RATX1 in M. oryzae (Ortiz et al., 2017). In the past decade protein structures are increasingly being resolved without the need to form crystals or use damaging X-rays but by using cryo-electron microscopy. This technique is widely used to resolved proteins in complexes and has been used to show both inactive Arabidopsis NLR complex ZAR1-RKS1 and the intermediate form when the complex interacts with a protein modified by the bacterial effector AvrAC (Xanthomonas campestris pv. campestris) . Cryo-e, despite gaining popularity in structural biology, is unable to resolve proteins smaller than 65 kDa, a size exclusion that would include many fungal and oomycete effectors (Muench et al., 2019). The strength of effector-target interactions can be determined using isothermal titration calorimetry whereby direct measurement of the heat that is either released or absorbed during the molecular binding event gives a complete thermodynamic picture of the reaction, including affinity, enthalpy, and stoichiometry (Duff et al., 2011). For the conserved M. oryzae MAX effector Avr1-CO39, isothermal titration calorimetry was used to confirm that direct interaction with the heavy-metal associated (HMA) domain of the rice NLR RGA5 was required for effector binding (Guo et al., 2018). A greater understanding of how structural interactions aid the specificity of Avr recognition is vital for future work in developing sustainable disease resistance in important food crops. | E XPLOITING EFFEC TOR D ISCOVERIE S TO CONTROL CROP PL ANT D IS E A S E S Knowing is not enough; we must apply. Willing is not enough; we must do. Johann Wolfgang von Goethe, Wilhelm Meister's Journeyman Years F I G U R E 4 Protein-protein interaction techniques. (a) Co-immunoprecipitation, effectors are tagged with a peptide sequence such as green fluorescent protein (GFP) and expressed in planta. Antibodies are used to pull down the protein complexes that can then be analysed using liquid chromatography and mass spectrometry (LC-MS/MS) . (b) Biotinylation, effectors are fused to mutant biotin ligase enzymes and expressed in vivo. The fusion protein catalyses the biotinylation of interacting and proximal proteins in the presence of biotin. The biotinylated proteins are captured using streptavidin beads (Roux et al., 2012). (c) Bimolecular fluorescence complementation, the effector and putative interactors are tagged with nonfluorescent fragments of yellow fluorescent protein (YFP). Direct interaction of the tagged effectors results in YFP reassembly visualized in vivo or quantified using flow cytometry (Kerppola, 2008;Graciet and Wellmer, 2010;Miller et al., 2015). The ultimate goal of effector discovery, from identification to characterization to target interactions, is to apply this knowledge to the control of multiple pathogens that threaten our food security. | "Effectoromics" For over 100 years disease resistance loci have been introduced into crops and subsequently shuffled through traditional breeding techniques, whether that be as individual genes or stacked to achieve often only short-lived resistance to pathogens (Vleeshouwers et al., 2011;Langner et al., 2018). Despite this, the search for novel R genes with durable or broad-spectrum resistance remains ongoing. The term "effectoromics" is used to describe the use of effectors in high-throughput screening for R protein function in either the germplasm of crop cultivars or a sexually compatible species. Avr effectors can be harnessed to screen rapidly for HR phenotypes, a hallmark of an ETI response (Vleeshouwers and Oliver, 2014 Solanum species (Takken et al., 2000;Du et al., 2014). The search for broad-spectrum or more robust R genes for breeding purposes maybe more nuanced than previously thought as multiple unrelated R genes can recognize the same pathogen effector (Aguilera-Galvez et al., 2018). | Screening with necrosis-inducing effectors to remove host susceptibility loci The necrosis-inducing effector ToxA was isolated from the wheat tan spot fungus P. tritici-repentis in 1996. Infiltration of purified ToxA into the apoplastic space of a susceptible wheat cultivar containing the Tsn1 susceptibility (S) gene is itself sufficient to induce tan spot symptoms (Tomas et al., 1990;Ballance et al., 1996;Ciuffetti et al., 1997;Welti and Wang, 2004). Wheat breeders routinely use the purified toxin to screen all new wheat germplasm to eliminate susceptible lines from their breeding programmes. This method is preferred over screening for molecular markers linked to the corresponding Tsn1 locus due to the ease of application and speed of results (Vleeshouwers and Oliver, 2014). Tsn1 removal from all newly commercially released wheat varieties has improved resistance to tan spot disease and Australia has seen a 26% reduction in ToxAsensitive wheat grown in the 10 years prior to 2016 (See et al., 2018). | K EEPING TR ACK OF EFFEC TOR D ISCOVERIE S IN MULTIPLE S PECIE S IN AN IN CRE A S ING LY DATA-RICH WORLD A place for everything, and everything in its place. Idiom from 17th century In the past two decades effector discovery and characterization have exploded with regard to crop pests and pathogens. This key information is found in multiple original research publications, review articles, UniProt, individual pathogen genome browsers, and species-specific websites. However, to aid future research and guide the direction of work the genotype and fine phenotyping data surrounding these discoveries and new insights needs to be FAIR (Findable, Accessible, Interoperable, and Reusable) to molecular plant pathologists as well as the wider life sciences communities. Publicly available repositories of curated data regarding proteins with confirmed roles in pathogenicity and virulence are a fundamental tool for effector study. The Pathogen-Host Interactions database (PHI-base, www.phi-base.org) is a manually curated database comprising over 6,780 genes from 268 pathogens of over 210 hosts (September 2019), of which 60% are plants (Urban et al., 2020 | CON CLUS I ON S AND OUTLOOK "Would you tell me, please, which way I ought to go from here?" "That depends a good deal on where you want to get to," said the Cat. Lewis Carroll, Alice in Wonderland Effectors are the mysterious molecular tools evolved and used by plant pathogens in multiple ways. Effector studies are of vital importance in addressing the global food security challenge, yet the explosion in research efforts aimed at understanding effector biology over the last few decades has left us with a dichotomy in our knowledge. (McGrann et al., 2016;Lopez et al., 2018). The arrival of full genome sequencing almost two decades ago has been a double-edged sword. Bioinformatic pipelines and the development of prediction software has sped up the refinement of putative effectors whilst simultaneously highlighting the vastness of the gene repertoires to be investigated. For effector characterization, the future efficiency not only depends on the development of ultrahigh-throughput functional assays but also their use in combination with lower-throughput novel and well-established techniques such as QTL mapping and GWAS . Whilst multiple developments in effector discovery have increased our understanding of these enigmatic proteins, arguably the explosion in effector research can be attributed to the development of three approaches: genome sequencing, bespoke bioinformatic pipelines, and Agrobacterium-mediated transient expression in planta. Armed with only an annotated genome, even understudied conifer-infecting fungal pathogens can be screened for the presence of putative effector proteins (Raffaello and Asiegbu, 2017). With this in mind, genome reannotations and improvements to prediction algorithms continuously widen the pool of effector candidates available, especially in well-studied crop pathogens Frantzeskakis et al., 2018). Therefore, perhaps the greatest roadblock to effector discovery is the accuracy of genome assembly and annotation, an issue that will take at least 5-10 years to resolve with the inclusion of pangenomes (Cissé and Stajich, 2019). The genome annotation of multiple isolates through the construction of pathogen pangenomes allows for intraspecific genome analysis and will provide insight into the links between high polymorphisms and host specificity. The use of pangenome analyses has already led to the differentiation between core candidate effectors and novel candidate effectors in Z. tritici and M. oryzae (Singh et al., 2019;Badet et al., 2019). Machine-learning-based prediction tools as well as the robotic implementation of practical molecular techniques should help to fast track the progress from effector prediction to characterization. This anticipated progress will undoubtedly erode some of the disparity in our interspecies knowledge and lift the veil on the enigmatic filamentous phytopathogen effector repertoire. Many novel functions, locations, interactions, and generic underlying themes remain to be discovered. ACK N OWLED G M ENTS We would like to acknowledge the invaluable input given by friends Grant (BB/P016855/1). The PHI-base is funded from two UK BBSRC grants BB/K020056/1 and BB/S020020/1. DATA AVA I L A B I L I T Y S TAT E M E N T Data sharing is not applicable to this article as no new data were created or analysed in this study. Immunity and the role of selected plants as immunomodulators: A Review : The immune system is an incredible constellation of cells, tissues, organs and molecules that provides protection against a wide spectrum of pathogens and particles keeping us healthy within the challenging microbial environment. Immune system is capable of neutralizing most of the pathogenic attacks without leaving any trace of disease or abnormality in normal functionality of the body. However, some pathogens are strong enough to cause infectious diseases. In the battle against pathogens the immune system adopts two distinct pathways namely, innate immunity and adaptive immunity. Nonspecific innate immunity elicits the same generic response regardless of the pathogen and it mediated by key phagocytic cells. Adaptive immunity elicits pathogen specific immune responses carrying immunological memory. In therapeutic approaches the immune system is fine-tuned with the aid of external agents called immunomodulators. Immunomodulation refers to any alterations in the immune system involving induction, expression, amplification or inhibition of any part or phase in the immune response in order to achieve a better immune response. In clinical perspective immunomodulators appear in three categories including Immuno adjuvants, immune stimulants, and immune suppressants. A diverse array of synthetic and natural agents is applied in therapies. Plants are a rich source of bioactive substance exerting their effects on almost all the systems of the body while playing as immunomodulators. Thus the present review is focused on the immunemodulating activity of various plants in experimental perspective In therapeutic approaches the immune system is fine-tuned with the aid of external agents called immunomodulators. Immunomodulation refers to any alterations in the immune system involving induction, expression, amplification or inhibition of any part or phase in the immune response in order to achieve a better immune response. In clinical perspective immunomodulators appear in three categories including Immuno adjuvants, immune stimulants, and immune suppressants. A diverse array of synthetic and natural agents is applied in therapies. Plants are a rich source of bioactive substance exerting their effects on almost all the systems of the body while playing as immunomodulators. Thus the present review is focused on the immunemodulating activity of various plants in experimental perspective Keywords: Immune system, Immunomodulators, phytochemicals Host defense mechanisms against infections Within the environment a wide spectrum of organisms carries the potential to infect us and, if they do so, can cause us harm in many different ways. As hosts for these aggressors animals are equipped with sophisticated host defense mechanisms referred to as immunity in order to neutralize these potential threats. Bacteria, Viruses, Fungi and Parasites may act as potential pathogens. In terms of infection capability primary pathogens can infect host at its presence or activity and opportunistic pathogens usually occur with the host and tend attack only when the host defense become weak (Ryan & Ray;. In order to stay safe from challenging microbes animals are armed with a sophisticated defense system known as the immune system. Architecture of immune system is summarized in figure 1. Within the territory of microbes in astronomical numbers vertebrates are protected by two systems of immunity as innate and adaptive (Owen, et al., 2013). Innate immunity Innate immunity constructs the first line of the defenses against infection that is ready for immediate activation prior to attack by a pathogen. The innate immune system is armed with physical (skin and mucous membranes), chemical (pH and microcidal molecules), and biological barriers (Commensal microbes colonizing the skin and gastrointestinal tract) in order to eliminate the threats at the origin (Thao, et al., 2008;Playfair & Chain, 2013). Innate immune function If infectious agents are skilled to cross the first line of defense or the mechanical, chemical, and biological barriers the second line of defense the

innate immune system retains in an activated or nearly activated state to battle the infection. Innate immune system undergoes identification of pathogens, activation of phagocytic cells, localized protective response known as inflammation in order to eliminate the pathogens rapidly. Phagocytosis, Oxygen independent and dependent killing and inflammation are the key mechanisms in innate immunity. In contrast to the adaptive immune response the innate immune response is rapid and nonspecific (Thao, et al., 2008) Adaptive immunity In contrast to the innate immune system the adaptive immune system or third line of defense is characterized by diversity, antigen specificity and immunological memory. The innate immune system is required to trigger the adaptive immune response against a particular antigen. In turn the adaptive immune can recognize targets within a wide spectrum. Adaptive immune system carries two distinct branches humoral immunity and cell mediated immunity. Humoral immunity Antibodies, the key elements in humoral immunity are the major fraction of serum proteins and often called immunoglobulin. Plasma cells (differentiated B lymphocytes) produce antigen specific antibodies upon activation. Antibodies can specifically bind to antigens on microbial cells or molecules such as toxins leading to opsonization (Playfair & Chain, 2013). Immunoglobulin family is occupied by five distinct classes including IgM, IgG, IgD, IgA and IgE (Raven, et al., 2014). Cell mediated immunity T (Thymus cells) lymphocytes and B (Bursa derived cells) lymphocytes act as the key cellular mediators of adaptive immunity (Alberts, et al., 2002). The way T and B lymphocyte recognizes its antigen is critically different. B cells recognize their cognate antigen in its native form. They can identify free (soluble) antigens in the blood or lymph using their surface receptor. In contrast, T cells recognize their cognate antigen via T cell receptor in a processed form such as a protein fragment presented by an antigen presenting cell on its MHC molecule. B cells mainly engaged in humoral branch while T cells handle cellular branch of adaptive response (Kenneth, et al., 2012). White blood cells White blood cells or leukocytes act as the key cellular mediator of the immune system. Based on the presence of granules in the cytoplasm leukocytes are characterized as granulocytes and agranulocytes (LAFleur, 2008). Granulocytes/ (Polymorphonuclear leukocytes) Granulocytes are characterized by polymorphic nuclei and differentially staining granules in cytoplasm under light microscopy. The granules are membrane bound containers of enzymes that facilitate lysis of foreign invaders. Neutrophils, eosinophils and basophils are the major constituents of the family (Witko, et al., 2000). Neutrophils Neutrophils are the major occupant of WBC family in mammals and play an essential role in the innate immune response. They are short lived and highly mobile (Witko, et al., 2000;Nathan & Carl, 2006). Neutrophils are the first responders to the foreign challenges and reach the affected site within minutes and act as the hallmark of acute inflammation (Cohen, et al., 2002). Neutrophils carry a variety of specific cell surface receptors for chemokines, cytokines, leptins and proteins, and Fc receptors for opsonin. Chemokine receptors capable of detecting chemical gradients of chemotactic molecules such as IL-8, C5a, fMLP, and Leukotriene B4 usually produced by resident cells in tissues in response to infection and lead neutrophils to the site of infection. The migration of neutrophils is facilitated by surface adhesion molecules that can be expressed upon stimulation by cytokines. Opsonin receptors enable the cells to destroy opsonized or antibody coated pathogenic targets (Cassatella, 2010). In addition to phagocytosis neutrophils also attack microbes by releasing soluble anti-microbial including granule proteins, and generating neutrophil extracellular traps (NETs) comprised of chromatin and serine proteases that trap and kill microbes extracellularly (Hickey & Kubes, 2009;Clark, et al., 2007). Eosinophils Same as neutrophils, eosinophils are mobile phagocytic cells having the ability to migrate from the blood into the tissue spaces. Although the phagocytic role of eosinophils is significantly less important in contrast with neutrophils they play an important role in the killing of multicellular parasites (Owen, et al., 2013). The granules in mature eosinophils contain several proteins including major basic protein, eosinophil cationic protein, eosinophil derived neurotoxin and eosinophil peroxidase (Male, et al., 2007). Major basic protein, eosinophil peroxidase, and eosinophil cationic protein exert cytotoxic effects on tissues (Rothenberg & Hogan, 2006). Eosinophil cationic protein and eosinophil-derived neurotoxin are ribonucleases with potent antiviral activity. The toxic pores created by eosinophil cationic protein on target cell membranes allow other cytotoxic molecules to enter the cell (Morgan & Costello, 2005). Reactive oxygen species nitrogen intermediates developed by eosinophil peroxidase promote oxidative stress in the target causing cell death by apoptosis and necrosis (Rothenberg & Hogan, 2006). Upon activation eosinophils release these granules in order to kill pathogens that are too large to be phagocytosed. Eosinophils are therefore thought to play a specialized role in immunity to parasitic worms using this mechanism (Male et al., 2007). Basophils Basophils are non-phagocytic granulocytes that function by releasing pharmacologically active substances from their cytoplasmic granules. These substances play a major role in certain allergic responses (Owen et al., 2013). Agranulocytes/ Mononuclear leukocytes Agranulocytes are characterized by single lobed nuclei and apparent absence of cytoplasmic granules. Lymphocytes, monocytes and macrophages (differentiated monocytes) are the major occupants of the agranulocyte family (Gartner & Hiatt, 2007). Monocytes Monocytes are the largest cell type of WBC and play an important role in innate immune response. Monocytes in circulation migrate into tissues and undergo differentiation into resident macrophages and dendritic cells in order to maintain the level of these cells within the tissues under normal states. Migration and differentiation occur at higher rates in response to signals of inflammation in order to elicit the immune attack (Swirski, et al., 2009). Macrophages Macrophages are phagocytic cells derived from monocytes and act a key mediator in both innate and adaptive immune responses. Macrophages also contribute the removal of aged cells, dead cells and cellular debris through phagocytosis (Owen et al., 2013). Macrophage-like cells serve different functions in different tissues and are named based on their location and collectively construct the mononuclear phagocytic system. Alveolar macrophages in the lung, Histiocytes in connective tissues, Kupffer cells in the liver, Mesangial cells in the kidney, Microglial cells in the brain and Osteoclasts in bones are some players of the mononuclear phagocytic system (Owen, et al., 2013). In the presence of antigens different stimuli result activation of macrophages and the activity may be augmented by other inflammatory mediators such as inflammatory cytokines, components of bacterial cell walls. In contrast with resting macrophages activation results up regulation of phagocytic activity, secretion of inflammatory mediators, expression of MHC class II molecules and secretion of various cytotoxic proteins capable of eliminating a broad range of targets such as pathogens, virus-infected cells, tumor cells, and intracellular bacteria. Enhanced expression of MHC proteins enables the macrophages to function as effective APCs (Playfair & Chain, 2013). In addition Macrophages can metabolize the amino acid arginine to form either a killer molecule (Nitric Oxide) or a repair molecule (Ornithine). The killer phenotype known as M1 Macrophages are activated by LPS and IFN-γ, and secreted in high levels of IL-12 and low levels of IL-10. The repair phenotype M2 mediate repair activities such as wound healing and tissue repair and they produce high levels of IL-10, TGF-β and low levels of IL-12 (Mills, 2012;Owen et al., 2013). Dendritic cells Dendritic cells are characterized by long membrane extensions that resemble the dendrites of nerve cells and get their origin from both myeloid and lymphoid lineages. Hematopoietic stem cells give rise to four different types of dendritic cells including Langerhans cells, interstitial dendritic cells, myeloid cells and lymphoid dendritic cells via different pathways. All the four types express MHC Class II molecules and co stimulatory molecules of B7 family enabling them to function as more powerful APCs for T helper cells resulting activation (Owen, et al., 2013). Dendritic cells express pattern recognition receptors such as the toll-like receptors for pathogenic antigen recognition. In the encounter with an antigen immature DCs internalize the antigen via phagocytosis the DC becomes activated and attain maturity. Mature DCs migrate into lymph nodes and the processed antigen on MHC molecules is presented to T helper cells. Activation of DCs also drive up regulation of cell surface receptor molecule CD40 and co receptor molecules of B7 family including B7-1 (CD80) and B7-2 (CD86) that deliver activation signals to the T cell (Kenneth, et al., 2012;Owen, et al., 2013). Conventional dendritic cells (Myeloid dendritic cells) express TLR-2 and TLR-4 surface receptors and occur in several subsets. They are professional APCs whose major function is priming T cells and secrete IL-12 (Sallusto & Lanzavecchia, 2002). In contrast plasmacytoid dendritic cells express TLR-7 and TLR-9 receptors. These are not much effective at priming T cells and mainly take care of viral infections and secrete Class I interferons (Vanbervliet, et al., 2003;Liu, 2005). Follicular dendritic cells are special type of cells that do not arise in bone marrow and found in lymph follicles B cell zone in lymph nodes. These cells are not phagocytic and do not express MHC class II molecules. Although they are not functioning as APCs follicular dendritic cells express high levels of membrane receptors for antibody which facilitate binding with antigen-antibody or antigencomplement complexes. The resultant combination remains intact and more accessible for B cells. It is also important for the development of B cell follicles (Kenneth, et al., 2012;Owen, et al., 2013) Lymphocytes Lymphocytes are the class of WBC that acts as the key players of adaptive immune response. B Lymphocytes, T lymphocytes and NK cells are the major occupants of the lymphoid lineage. B Lymphocytes The principal functions of B cells are to make antibodies against antigens contributing humoral branch of immunity, to perform the role of APCs and to develop into memory B cells after activation by antigen interaction (Mauri, et al., 2012). Each B cell is characterized by a surface membrane-bound immunoglobulin known as BCR. BCR allows the distinction of B cells from other lymphocytes and act as the main protein involved in B cell activation. In order to produce antibodies B cells should be fully activated. Activation may occur T cell independently or T cell dependently. When a native B cell encounters an antigen B cell gets activated in T cell dependent or Independent manner. Activation induces rapid proliferation of the cell and the resultant progeny undergoes differentiation into memory B cells and Plasma cells (Mauri, et al., 2012). Plasma cells produce antibodies specific to the original antigen that resulted B cell activation. Antibodies produced by the plasma cell may be in secreted or membrane bound form and result subsequent elimination of antigen via opsonization. In contrast with native B cells Memory B cells have a longer life span and express the same membrane bound specific antibody same as the parent B cell of the progeny. Immunological memory is maintained by the memory B cells (Owen, et al., 2013). T Lymphocytes Cellular arm of adaptive immune response is handled by T lymphocytes that are characterized by surface protein T cell receptor. Progenitor T cells originated at the sites of hematopoiesis migrate to thymus and attain maturity. Within the thymus the developing T cells or thymocytes undergo rearrangements of the germ-line TCR genes, expression of various membrane markers, proliferation and differentiation giving rise to functionally distinct subpopulations of mature T cells (Owen, et al., 2013). In contrast with B cells TCR cannot recognize antigens alone and it is capable of identifying only the antigens that are presented on MHC molecules of B cells or other APCs. TCR of majority of T cells is composed of two glycoprotein chains known as α and β. There are several sub populations of T cells. T helper cells Helper T cells are characterized by the glycoprotein CD4 on the surface and also referred to as CD4+ T cells. The major function of helper t cells is to assist activation of other cell types such as B cells, Cytotocic T cells and macrophages (Alberts, et al., 2002). Cytotoxic T cells The cells are also known as CD8+ T cells due to the presence of CD8 glycoprotein on the surface. Cytotoxic T cells mainly engage in elimination of virally infected cells, tumor cells and foreign tissue grafts (Male, et al., 2007). Memory T cells Memory T cells are a subset of long lasting antigen specific T cells that originate in

the exposure to a particular antigen for the first time and maintain immunological memory. Memory T cells may be CD8+ or CD4+ and typically they express the protein CD45RO on their cell surface (Akbar, et al., 1998). Regulatory T cells Regulatory T cells are involved in the maintenance of peripheral immunological tolerance. As the major role these cells suppress the functionality of self-reactive T cells (T cells having TCRs that recognize selfcomponents other than self MHC and potentially attack normal cells leading to auto immunity) that survived from the deletion mediated by negative selection in thymus (Kenneth, et al., 2012;Male, et al., 2007). Natural Killer T Cells The subset of NK T cells exists in thymus and peripheral lymphoid organs. In contrast with conventional T cells NKT cells are capable of recognizing glycoprotein antigens presented on MHC molecules. Activated NKT cells secrete cytokines such as IL-4, IL-10 and IFN-γ (Kenneth, et al., 2012) and share the function of NK cells (Jerud, et al., 2006). Gamma-delta T Cells This subset of T cells express a distinctive TCR composed of a γ chain and a delta chain. γδ T cells are much less abundant and occur at highest abundance in the gut mucosa, within a population of lymphocytes known as intraepithelial lymphocytes (Holtmeier & Kabelitz, 2005). Studies suggest that γδ T cells act as potent eliminator of tumor cells via direct or indirect on other cells (Kenneth, et al., 2012). Natural killer cells Natural killer cells which are a type of cytotoxic lymphocyte and act as a key mediator in innate immune response and it also impart in adaptive immune response (Owen, et al., 2013). They share the same killing mechanism with NK T cells. NK cells carry surface receptors for MHC class I molecules expressed on almost all the cells and this recognition creates negative signals that inhibit killing mechanism of NK cell leading to self-recognition. Metabolic stress in infected cells with pathogens such as virus and bacteria results altered expression of MHC class I molecules on surface and altered self MHC molecules are incapable of making inhibitory signals. Thus such cells are attacked by NK cells (Viver, et al., 2011). In contrast uninfected cells promote the expression of MHC class I molecules in response to cytokines such as IFN-α and IFN-β in order to resist NK cell mediated killing (Kenneth, et al., 2012). In addition NK cells express a Fc receptor CD16 for IgG. With the aid of this receptor NK cells can attach and destroy target cells coated with antibodies exhibiting antibodydependent cell mediated cytotoxicity (Owen, et al., 2013). In addition to receptor signaling NK cells get activated in response to cytokines including IL-12, IL-15, IL-18, IL-2, and CCL5 and NK cells also secrete IFN-γ and TNF-α that coordinate the immune responses. NK cells keep cytoplasmic granules containing cytotoxic proteins known as granzymes including perforin and proteases. Upon attachment to a target NK cell release these proteins to initiate killing. Perforin make pores on target cell membrane creating an aqueous channel for cytotoxic molecules or other destructive molecules to enter the cell and kill the target via either apoptosis or osmotic cell lysis. Osmotic lysis of virally infected cell may only release the virions within destroying cell whereas apoptosis eliminate the target with internal virons. NK cells also release an antimicrobial substance namely αdefensins that can kill bacterial cells by disrupting cell walls (Iannello, et al., 2008). Organs of the immune system Origin, growth, development and deployment of immune cells including lymphocytes occur within specialized anatomic microenvironments known as lymphoid organs. These structurally and functionally diverse lymphoid organs and tissues are interconnected by the blood vessels and lymphatic vessels to facilitate circulation of lymphocytes. Primary lymphoid organs The organs where lymphocytes arise and mature are referred to as primary or regenerative lymphoid organs. Bone marrow Bone marrow supports self-renewal and differentiation of hematopoietic stem cells either mature cells or precursors of cells that migrate out of the bone marrow to continue their maturation in thymus. It gives rise to B cells, natural killer cells, granulocytes and immature thymocytes, in addition to red blood cells and platelets. The proliferation and maturation of precursor cells in the bone marrow occur under the influence of cytokines, many of which are colony stimulating factors (Kenneth, et al., 2012) Thymus Final stages of T cell development, selection and maturation occur in the thymus. T cell precursors (still capable of producing multiple hematopoietic cells) travel from bone marrow to the thymus through blood stream. In the thymic environment immature T cells generate unique antigen receptors (TCR) and are then selected based on their reactivity to self MHC-peptide complexes expressed on the surface of thymic stromal cells. Thymocytes having too high affinity to self MHC are subjected to negative selection (death) and cells having intermediate affinity are subjected to positive selection resulting in their survival, maturation, and migration to the thymic medulla (Owen, et al., 2013). The developmental strategies occur in two distinct regions, outer cortex and inner medulla. The cortex contains mostly immature thymocytes, some of which mature and migrate to the medulla. T cells leave the medulla to enter the peripheral blood circulation, through which they are transported to the secondary lymphoid organs. A huge majority of thymocytes entering the thymus is negatively selected and a few leaves the thymus as mature T cells (Kenneth, et al., 2012). Secondary lymphoid organs The organs where mature lymphocytes respond to foreign antigens are referred to as secondary or peripheral lymphoid organs. Lymph nodes Lymph nodes are small nodular aggregates of lymphoid tissue located along lymphatic channels throughout the body. They are the most specialized secondary lymphoid organs dedicated for immune response and the first organized lymphoid structure to encounter antigens entering the tissue spaces. Lymph nodes are composed of networks of stromal cells packed with lymphocytes, macrophages, and dendritic cells and connects with both lymphatic and blood vessels. Antigen presentation to the native T cells by APCs occurs in lymph nodes. In addition it act as the site where B cells are activated and differentiate into high-affinity antibody-secreting plasma cells. In the cases of adaptive immune response against infection, lymphocytes migrate to lymph nodes in elevated counts and proliferate into antigen specific T and B cells. This intense activity results swelling and pain of lymph nodes particularly during those first few days after infection (Kenneth, et al., 2012). Spleen In contrast to lymph nodes dealing with responses to antigens in the lymph, spleen acts as the major site of immune responses to blood borne antigens. Spleen does not connect with lymphatic vessels and connects with blood stream via splenic artery and vein. The events that initiate the adaptive immune response against antigens resemble the same in both lymph nodes and spleen (Playfair & Chain, 2013). Mucosa-associated lymphoid tissue Internal surfaces such as digestive, respiratory, and urogenital tracks are lined by mucous membranes. The mucous membranes are more vulnerable for the entry of pathogens. Thus protection of mucous membranes is provided by lymphoid tissues associated with them. These lymphoid tissues are collectively known as mucosa-associated lymphoid tissue (MALT). Depending on the location MALTs are given specific names. Lymphoid tissue associated with intestinal epithelium is referred to as gut-associated lymphoid tissue (GALT) and epithelium of respiratory track is referred to as bronchus-associated lymphoid tissue (BALT) or nasal-associated lymphoid tissue (NALT) (Playfair & Chain, 2013). Immunomodulation Immunomodulation is the therapeutic approach that adjusts the activity of a patient's immune response, either up or down, until a desired level of immunity is reached (Hall & Virella, 2007). The major interests of immune modulation are the specific components of the immune response such as T and B lymphocyte clones, which can hopefully be selectively fine-tuned in their function to promote the better health of the patient. Bioactive agents engaged in this process are commonly referred to as immunomodulators. The landscape of immunomodulation deals with three clinical scenarios including immunopotentiation, immunosuppression and induction of immunological tolerance and the responsible therapeutic agents are referred to as immune stimulants, immune suppressants and tolerogens respectively (Bhardwaj & Waldmann, 2009;Hall & Virella, 2007). Immunopotentiation Immunopotentiation is the therapy of enhancing the immune response. The attempt is to boost the overall neutrophil, B lymphocyte, and/ or T lymphocyte functionality of the patient. Physiologically this can be accomplished either by actively stimulating the patient's own immune system to higher performance levels through immunization techniques or by passively introducing protective immune system components such as gamma globulin from outside sources into the patient's body (Hall & Virella, 2007). In immunotherapy immunopotentiation is achieved via cytokine therapy, adoptive immunotherapy and vaccination (Bhardwaj & Waldmann, 2009). Immunosuppression Immunosuppressive therapies deal with the retardation of functionality of immune system resulting a lowered immune response. Suppressive measures are utilized when specific T and B lymphocytes of the patient's immune system have become activated against the patient's own body organs, such as in autoimmune diseases or in order to avoid rejection of organ or tissue transplantation (Hall & Virella, 2007). Induction of immunological tolerance Immunologic tolerance or hypo responsiveness is the capability of the immune system to avoid immune attacks on own tissues. Induction of tolerance in immune system has the advantage of targeting the undesirable immune response rather than inducing a generalized immunosuppression and commit the immune system not attack own cells and tissues by mistake and to accept foreign transplantations (Romagnani, 2006). Plant based immunomodulators For thousands of years plants have been playing an integral part of different healthcare systems all over the world. The term alternative medicine refers to a wide variety of healthcare practices, products and therapies engage in maintenance of normal health status against diseases in the place of conventional medicine. Alternative medicine used together with conventional medical treatment in a belief, not proven by using scientific methods is referred to as complementary medicine (Ernst, 1995;Joyce, 1994). Integrative medicine is the combination of the practices and methods of alternative medicine with conventional medicine for therapies on a scientific basis (May, 2011). The healing power of plants is mediated by a wide variety of plant derived secondary metabolites such as proteins, flavonoids, alkaloids, steroids and phenolic substances (Perianayagam, et al., 2004). Recognition of the value of alternative therapies has raised the involvement of herbalists and pharmacologists to explore medicinal plants from traditional herbal pharmacopeias. Already most of the drugs applied in conventional chemotherapy are initially of plant origin (Astal, et al., 2005;Adeboulu & Salau, 2005). The impact of medicinal plants on immune system has been extensively tested in vivo and in vitro and many plant species are found to be potent immune boosters in both cellular and humoral aspects. ii. Shows anticancer activity against D11 and Ehrlich ascites carcinoma cells. iii. Enhances humoral immune response to Sheep red blood cells and response to Con A was suppressed. iv. Increases granulocyte macrophage colony forming units in mice serum. v. Mitogenic to splenocytes and lymph node cells. vi. Inhibits cyclophosphamide induced immunosuppression. vii. Induces resistance to infection and reduces mortality in mice in response to E. coli. viii. Inhibits ochratoxin a induced suppression of IL-1 and TNF-α and macrophage chemotaxis. (Gulati, et., 2002) Allium sativum i. Up regulate -Enhances capillary skin perfusion. Experimental investigations on immunomodulatory properties of herbal plants -Humoral immune response. -Oxidative burst of macrophages and blastogenesis of T lymphocytes. -Protection from UV induced suppression of contact hypersensitivity. -IL-2 production ii. Inhibit the growth of cancer cell lines and tumors. iii. Modulates the activity of chemical carcinogens. iv. Protects heart, liver and pancreas against isoproterenol induced cytotoxicity. i. Aqueous leaf extract -Found as a potent immune restorative or anti-immunosuppressive agent in response to malathion exposed immunosuppression. -Up regulated suppressed immunological parameters (humoral and cell mediated immunity, numerical values of immunocytes and functions of phagocytes) towards normalcy. ii. Inhibit activity of microbes such as Staphylococcus sp. and Candida sp. iii. Prevents UV-induced suppression of DTH. iv. Serves as oxygen radical scavenger showing anticancer activity. vi. Causes regression of tumors. ii. Flavones fraction from fruits stimulated production of IL-6 and TNFα,NF-κB and p-I-κBin peripheral blood mononuclear cells with suppressed expression of CD 25. iii. Leaf extract inhibited chromium induced free radical production, apoptosis and DNA fragmentation. iv. Leaf extract inhibited chromium induced immunosuppression and related oxidative stress.. (Singh,et al., 2005) Discussion Modulation of immune response with plant based drugs is

a popular concept in most traditional health care systems such as Ayurveda. Within the scope of scientific findings, it has revealed that a lot of plant species possesses various immune pharmacological properties including immune stimulant, immune suppressant, and immune adjutant properties. Potential immune stimulants can be successfully integrated in therapies as immune boosters in order to treat impaired immune functionality. Selective immunosuppression becomes preferable in the treatments for autoimmune diseases As suggested by the studies plant species carry potentially bioactive compounds that can enhance both innate and adaptive immune functions. Cytokines are a diverse group of products of immune cells that play a vital role as signaling molecules in cellular communication. According to the analysis a lot of plants are capable of up regulating inflammatory cytokines including IL-1β, IL-4, IL-6, IL-10, IL-12, IFN-γ and TNF-α. In addition to innate immunity cytokines also play a vital role in adaptive immune response. With recent technological advancements a plenty of synthetic drugs including immunomodulators are flooding into the market. Although these synthetic agents seem to be fast acting and convenient, they are often carrying undesirable side effects, overdose complications and potential health risks in the long run. In contrast, herbal medicines are reputed enough as safer therapeutic agents than the existing synthetic stuff. Thus research activities on herbal medicines have become dominant especially in recent years. There is a plenty of epidemiological studies and experimental evidences to establish the relationship between herbal medicines and immune system and this article illustrates a few studies on immunomodulators. Such studies illustrating immunologically active herbs will contribute the populations to adopt safe, effective and more accessible therapies for immunity related healthcare needs. On the other hand, it will be an incentive for herbal drug manufacturers to develop more effective herbal drugs. Conclusion The use of plant derivatives for therapeutic purposes may be as old as the human civilization. This is further evidenced by traditional healthcare systems that date back to ancient times. Although these plant based medicines are employed in therapies, most of them have not been scientifically validated for their bioactivity at mechanistic level. Thus the major highlight of this review is immunological effects of common herbal medicines and their mechanisms of action in relation to current scientific findings. In this perspective we believe that the content might be useful for scientific community for drug design and to establish effective herbal therapies. Merging Problem-Based Learning with Simulation-Based Learning in the Medical Undergraduate Curriculum: The PAIRED Framework for Enhancing Lifelong Learning Lifelong learning is an essential trait that is expected of every physician. The CanMeds 2005 Physician Competency Framework emphasizes lifelong learning as a key competency that physicians must achieve in becoming better physicians. However, many physicians are not competent at engaging in lifelong learning. The current medical education system is deficient in preparing medical students to develop and carry out their own lifelong learning curriculum upon graduation. Despite understanding how physicians learn at work, medical students are not trained to learn while working. Similarly, although barriers to lifelong learning are known, medical students are not adequately skilled in overcoming these barriers. Learning to learn is just as important, if not more, as acquiring the skills and knowledge required of a physician. The medical undergraduate curriculum lacks a specific learning strategy to prepare medical students in becoming an adept lifelong learner. In this article, we propose a learning strategy for lifelong learning at the undergraduate level. In developing this novel strategy, we paid particular attention to two parameters. First, this strategy should be grounded on literature describing a physician’s lifelong learning process. Second, the framework for implementing this strategy must be based on existing undergraduate learning strategies to obviate the need for additional resources, learner burden, and faculty time. In this paper, we propose a Problem, Analysis, Independent Research Reporting, Experimentation Debriefing (PAIRED) framework that follows the learning process of a physician and serves to synergize the components of problem-based learning and simulation-based learning in specifically targeting the barriers to lifelong learning. Introduction Lifelong learning has emerged as one of the major challenges that physicians face. Accreditation organizations, certification boards, employers, educators, and the general public view the drive for lifelong learning as an essential trait of physicians. The Canadian Medical Association Code of Ethics states that it is the responsibility of physicians to "engage in lifelong learning to maintain and improve their professional knowledge, skills, and attitudes" [1]. The CanMeds 2005 Physician Competency Framework emphasizes lifelong learning as a key competency a physician must achieve to fulfill the scholar role in becoming better physicians [2]. However, most physicians are not prepared to develop and carry out a self-directed lifelong learning plan, such as identifying their own learning needs and establishing learning goals to meet these needs. This disparity may be explained by the unfamiliarity of physicians with the lifelong learning process. They also lack the skills required to overcome the barriers to lifelong learning. Barriers to lifelong learning include unawareness of knowledge deficits, failure to formulate the right question, and inadequate researching skills, which are known to impede lifelong learning [3][4]. In addition, lack of time is often cited by the busy physician as a hindrance to learning [3]. Being competent and comfortable with developing and carrying out a self-directed lifelong learning plan could significantly reduce the task load and effort of learning, hence, minimizing time spent on learning and overcoming some of these barriers. Although the learning process of the practicing physician [5] and the barriers to lifelong learning [3][4] are well characterized in the literature, a gap exists in translating this knowledge into a learning strategy that physicians can develop for lifelong learning. The undergraduate years present an excellent opportunity to train medical students to become physicians skilled in lifelong learning. The adult learner paradox, in the context of medical education, is a phenomenon whereby adult learners revert back to the learning strategies they acquired during their undergraduate years when learning [6]. Adult learners are problem-and goal-oriented, focusing on practical solutions, and are autonomous and self-directed in their learning. Yet, when these adults are placed in a learning environment, they immediately revert back to the strategies they were exposed to and became competent in during their undergraduate years. Accordingly, equipping medical students with skills to overcome these barriers to lifelong learning and inculcating a learning strategy at the undergraduate level that is similar to the learning process of a physician may promote lifelong learning [6][7]. In this article, we propose a learning strategy for lifelong learning at the undergraduate level. In developing this novel strategy, we paid particular attention to two parameters. First, this strategy should be grounded in literature describing a physician's lifelong learning process. Second, the framework for implementing this strategy must be based on existing undergraduate learning strategies to obviate the need for additional resources, learner burden, and faculty time. We will first examine the literature on how physicians learn at work and identify the potential barriers they face to lifelong learning. Next, we discuss the strengths and weaknesses of current undergraduate teaching/learning methods in meeting the challenges of inculcating lifelong learning skills in medical students, focusing on two of the leading educational strategies in undergraduate education, namely, problem-based learning (PBL) and simulationbased learning (SBL). Building on these two educational strategies, we propose a framework for lifelong learning that incorporates the strengths and overcomes the weaknesses of both strategies. Finally, we will explain how this framework could be implemented to effectively prepare the graduating medical practitioner for lifelong learning. PAIRED framework We developed a framework that is built on Slotnick's Four-Stage Theory of Physicians' Self-Directed Learning Episodes by merging PBL and SBL for lifelong learning (Table 1) [5]. The framework is a learning strategy consisting of six sequential phases: Problem, Analysis, Independent Research, Reporting, Experimenting, and Debriefing (PAIRED). The learning exercise starts with the "Problem" phase that corresponds to Slotnick's Stage 0: Scanning for Problems. Importantly, for PAIRED, the problem should retain the essential characteristics of that in a PBL exercise. A good PBL problem must be realistic and complex with no clear-cut answers, and one that students feel are relevant and they are likely to encounter. However, unlike a typical paper-based PBL exercise, in PAIRED, the problem should be presented to the students through active exploration via simulated clinical encounter. Presenting the problem through simulation will better contextualize the problem for the students and mimics the way physicians identify problems in real life when working. The simulated clinical encounter not only helps students identify learning needs and gaps in knowledge and skills, it also exposes learners to the physical, emotional, environmental, and time constraints of a clinical encounter and, thus, focuses their research and reading towards more practical solutions and approaches. In fact, using a simulated clinical encounter as the clinical trigger and context for PBL has been suggested recently, albeit more research is required to assess the impact of this approach in medical education [8]. Business education literature provides evidence that simulation indeed meets the requirements of a good PBL problem [9][10][11]. In contrast to a typical SBL activity, the objectives of this first simulated problem step in PAIRED are strictly for problem identification and awareness of knowledge and skill deficits. These objectives should be made very clear to the students to minimize the feeling of being overwhelmed and preoccupied with diagnosis, management, and outcomes of the SBL activity at this phase. Using a simulated clinical encounter to frame and present a problem is an important first step in overcoming the barriers of being unaware of problems in a clinical setting and being oblivious to deficits in knowledge. Next, students in the same groups as in the "Problem" phase proceed to the "Analysis" phase, where they gather in a separate room to discuss the problems that were encountered. This is very much like the initial analysis step of PBL. The facilitator should focus the students on identifying the problems encountered as well as developing their own learning needs. Facilitators should also guide students who are novice learners in formulating effective strategies to find solutions and resources to these problems. It is also important that students develop skills to address problems that are most important and relevant to their (simulated) practice. This phase is crucial for students in identifying problems and gaps in knowledge and skills because it also allows students to evaluate the problems, discuss, and decide which problems to take on. Hence, the "Analysis" phase corresponds to both Stage 0 and Stage 1 of Slotnick's theory (Table 1). Being competent in identifying and analyzing the problem in this phase is critical for students in order to become aware of knowledge deficits and to formulate questions that are important, practical, and researchable. Students conclude this phase by deciding on how to proceed with the next phase of "Independent Research". The "Independent Research" phase and "Reporting" phase for the PAIRED approach are similar to the research and reporting steps of PBL. These phases also correspond to Stage 2 of Slotnick's theory (Table 1) where students search the literature and read independently, in addition to learning through discussions with peers and experts. The "Independent Research" phase can last from under an hour to over several weeks depending on the objectives of the learning activity, the difficulty of the clinical problem, and the learning level of the students. In contrast to PBL, the "Independent Research" phase also includes learning clinical skills that learners have identified as deficiencies. It is in this phase that SBL falls short in self-directed learning as it does not incorporate any elements of independent research and reporting, other than consultation with experts and peers during debriefing. For this "Independent Research" phase to be implemented well, it is important that appropriate scaffolding, guidelines, and support are provided for students lacking experience in appraising the literature or identifying appropriate evidence from the multitude of available information. Students should be taught skills for using evidence at the point of care as this promotes learning at work [12][13] and is not a straightforward skill to attain [14][15]. As the student develops competency in identifying problems, developing learning needs, and researching skills in point of care evidence during the PAI phases of the PAIRED framework, these three initial phases can be conducted as a single session simulating clinical encounters that are

embedded with specific learning opportunities that mimics everyday learning opportunities at work. Following the "Independent Research" phase, students meet again for the "Reporting" phase (as in PBL) where discussions and sharing of knowledge and skills occur, with proposed solutions to the problems that were encountered in the "Problem" phase. The "Experimenting" phase should follow the "Reporting" phase as soon as possible so that students can proceed to test out their agreed upon and devised plans of action and management. This "Experimenting" phase follows the typical SBL activity and is the "Gaining Experience" stage of Slotnick's theory ( Table 1). The problem encountered by students in this phase should be the same problem encountered during the first "Problem" phase of the PAIRED process, allowing students to carry out their plan of action as decided in the "Reporting" phase. However, in this phase, students are expected to diagnose and manage the problems encountered. The "Experimenting" phase that follows the "Reporting" phase is crucial as the clinical outcomes simulated during the SBL exercise provide the students with immediate and contextualized feedback about the effectiveness of their "Independent Research" and "Reporting" phases. The SBL activity is an important experiential learning process that focuses students during future "Research" and "Reporting" phases on coming up with management plans that are within the practical constraints of a simulated clinical problem. This "Experimenting" phase is lacking in PBL, which is a major drawback, in our opinion, for PBL activities where students fail to make the connection between discussions and actually carrying out their solutions to see if their solutions do indeed work, thus, missing out on gaining experience through practice. The PAIRED activity finally concludes with a "Debriefing" phase, similar to the debriefing session after a typical SBL activity. The formative feedback given to students in this phase is known to be the most important factor for SBL activities in promoting effective learning [16]. This phase is where performance gaps are identified, described, investigated, and closed through discussions and targeted instructions [17]. Students will be able to learn by reflecting on their actions or inactions as well as from the performances of their peers during the debrief, an important concluding step in Slotnick's theory that is lacking in PBL. Lifelong learning in medicine and barriers to learning It has been established that practicing physicians are motivated to begin learning when a problem is encountered [18][19]. This problem may be specific, such as a clinical question arising from a patient encounter, or general, such as a gap in skills and knowledge due to the development of new techniques or medications. These problems encountered will then trigger the learning process that a physician moves through, from the problems that precipitate learning to the outcomes of that learning. In the Four-Stage Theory of Physicians' Self-Directed Learning Episodes [5], Slotnick describes this learning process as four learning episodes that are based on literature characterizing practicing physicians' learning experiences [20][21][22]. According to this model, the physician is aware that there will be problems at work and scans for these problems (Stage 0: Scanning for Problems). Once a problem is encountered or identified, he/she evaluates if there is a need for the problem to be addressed and evaluate the learning requirements for a solution (Stage 1: Evaluating the Problem). If he/she decides to take on the problem, learning objectives are developed, and he/she employs learning strategies to acquire the required skills and knowledge to solve the problem (Stage 2: Learning Skills & Knowledge). The physician applies the newly acquired skills and knowledge in clinical practice, gaining experience through the results and feedback from patients and colleagues (Stage 3: Gaining Experience). Barriers to this lifelong learning process are encountered in each of these stages. To further elaborate, at Stage 0, the problem that arises during patient encounters or a realization of a gap in knowledge and skills is the starting point that motivates learning. Stage 0 is crucial and is where the physician scans for problems and identifies learning needs. Barriers to self-directed learning at this stage are the failure to identify problems that exist and a lack of awareness of knowledge deficits [4]. These are critical barriers that hamper the start of a learning process. In the words of G.K. Chesterton, "It isn't that they can't see the solution. It is that they can't see the problem." Once the physician is able to identify a problem as a learning need, he/she moves on to the next stage (Stage 1) and reflects on how relevant the problem is to her practice. The questions he/she asks herself at this stage include, "Is there a really a problem? Is a solution to the problem available? Are learning resources available to solve the problem? Is it practical for me to engage in learning?" Stage 1 is a critical stage as the learning process will be impeded if the learning is deemed futile due to unavailability of resources. Similarly, the physician may halt the learning process if the learning resources are considered extensively effortful to undertake. Being unfamiliar with the availability of resources and inability to use the resources efficiently are the obvious barriers to the learning process at this stage, and these are often referred to as a lack of time and energy [3]. Once the problem is deemed important enough to warrant a change in practice and the learning is considered practical and convenient to engage in, the physician moves on to the next stage. In Stage 2, the physician could engage in the searching and reading of relevant literature, discussing the problem and possible solutions with colleagues or experts, and taking appropriate courses. At this stage, barriers include poor researching skills in seeking out and interpreting the relevant literature, poor communication, and collaborative learning skills, as well as limited access to relevant courses. Negative experience due to failed attempts may reinforce that learning is difficult and time-consuming, and this may impede progression and limit future learning opportunities. A positive experience, on the other hand, would reiterate to the learner that self-directed learning can be efficient, useful and self-satisfying, thus, promoting lifelong learning. Stage 2 is completed when the physician exhausts available resources, formulates a plan of action or feels that additional learning is no longer necessary. He/she will then move on to the final stage (Stage 3) of practice and gaining experience. This refers to the application and practice of the knowledge and skills acquired to resolve the perceived problem. At this stage, feedback from patients and peers on the results of the application of the newly acquired skills and knowledge are critical components of learning. The physician reflects on the feedback received and with repeated practice, integrates these skills and knowledge into everyday practice. The learning process is completed when the problem has resolved or when the physician feels that enough experience has been gained to be confident and competent in tackling similar problems in the future. Barriers to completing this stage include failure to reflect on their practice and, for conditions which are relatively uncommon, failure to gain sufficient experience due to lack of opportunities for repeated practice. In summary, the barriers to lifelong learning include failure to identify problems, lack of awareness of knowledge deficits, poor researching skills, deficient communication and collaborative skills, limited access to resources, unfamiliarity with availability of resources, inability to use existing resources efficiently, failure to self-reflect, and lack of repeated practice ( Table 2). Some of these barriers are system-based barriers, such as availability of resources and lack of opportunities for repeated practice, but most are skill-based barriers. We next examine the current learning strategies in the medical undergraduate curriculum to determine if they are suitable for overcoming skill-based barriers to lifelong learning. Strategies for lifelong learning The undergraduate medical curriculum offers a crucial window period for students to acquire a lifelong learning strategy and overcome skill-based barriers to lifelong learning. The tendency for physicians to adopt learning strategies gained during their undergraduate years, i.e. adult learner paradox, underscores the importance of an effective lifelong learning strategy at the undergraduate level. The undergraduate medical curriculum consists of a variety of teaching/learning strategies, such as lectures, clinical tutorials, mentoring, PBL, and SBL. While "traditional" teaching methods, such as lectures, are important in the medical undergraduate curriculum in providing knowledge and information in an economical and resource efficient way [23][24], both PBL and SBL are increasingly used worldwide in medical schools to promote independent thinking, self-directed learning, effective collaboration, and application of knowledge [25]. PBL and SBL can potentially address some of the shortcomings of traditional curricula in providing lifelong learning skills. Hence, we will focus on how these strategies promote lifelong learning for the practicing physician. (i) Problem-Based Learning (PBL): PBL is a learning strategy for "posing contextualized, real world situations and providing resources, instruction and guidance to learners as they develop content knowledge and problem-solving skills" [26]. Burch described PBL as a process involving four sequential steps: the problem, initial analysis, research, and reporting [27]. The PBL process typically starts with a paper-based problem that is complex and authentic. Next, in the initial analysis step, students gather in small groups to identify specific learning issues. By inventorying what is known from their prior knowledge and personal experience, students are made aware of their gaps in knowledge and skills. The research step refers to the independent self-directed learning engaged in by the student. This can be at the library, via the internet or by interviewing authoritative sources. Finally, the reporting step concludes the PBL exercise where students gather again to report their discoveries, explain concepts, clarify doubts, and field questions from members. PBL has several strengths in fulfilling the theory of lifelong learning of physicians when implemented properly. However, as shown in Table 2, PBL falls short in certain aspects. A PBL exercise typically starts with a paper-based clinical problem where students gather together in small groups to identify problems, learning needs and knowledge gaps. This only partially satisfies Stage 0 because, in reality, the physician must be able to achieve these learning goals through interaction with a patient or from a clinical experience, which is evidently different from a paper-based clinical scenario [28]. We feel that it is important that medical students develop the skills to overcome barriers at Stage 0 through more realistic interactions rather than through a paper-based problem. Furthermore, PBL only partially addresses the barrier of collaborative learning. While PBL has been shown to improve communication skills of physicians [29], it does not adequately prepare the student to learn while working with colleagues during clinical encounters. Having a discussion to come up with a solution is very different from collaborative learning work. While physicians can learn from peers through discussions about the case, learning on the job from colleagues involves not only discussions but also observations of behavior, communications, and skills that their colleagues demonstrate while interacting with a patient or dealing with a clinical situation [30]. Physicians often learn through picking up "tricks of the trade" and clinical pearls from their colleagues that are not explicitly discussed at work. The lack of practice and opportunity to reflect on one's performance in a clinical encounter is a significant drawback of PBL concerning the theory of physicians' learning. The PBL exercise typically ends with a small group discussion on the solutions to the case as well as in-depth discussion of the problems. However, students do not get a chance to practice and "act out" their solutions and approaches which are crucial. By practicing a devised approach, learners will have the opportunity to realize the many constraints that they may not be aware of. This realization will sharpen their researching skills and focus discussions towards workable solutions. Gaining experience occurs when newly acquired knowledge and skills are applied and practiced. This is the final stage of a physician's learning process. (ii) Simulation-Based Learning (SBL): SBL is defined by Gaba as "a technique to replace or amplify real experiences with guided experiences, often immersive in nature, that evoke or replicate substantial aspects of the real world in a fully interactive manner" [31]. The SBL exercise is a small group learning activity that typically starts with a pre-briefing and orientation to the simulation room, the simulator, and all other equipment used during the simulation. A simulated problem

is then presented to the students who actively participate in resolving the problem, working with one another as a team. Clinical responses and results simulated during the exercise serve as feedback to students on the consequences of their actions or inactions. The SBL activity concludes with a debriefing session, which is crucial to learn. The major shortcoming of SBL with respect to the physicians' learning process is the lack of time and skills training devoted to the crucial components for self-directed learning. Specifically, familiarity with learning resources, efficient use of learning resources, and researching skills are not addressed with SBL ( Table 2). Performing a comprehensive search and identifying the most appropriate up-to-date evidence to solve problems identified requires training and practice [6]. Similarly, filtering out non-relevant information is just as important during the learning process. These important skills are not addressed with SBL in medicine. While SBL has characteristics that target several barriers to lifelong learning, failure to address barriers at Stage 1 and 2 would halt the self-directed learning process. (iii) Integrating PBL and SBL for Synergism: Both PBL and SBL have the components essential for inculcating lifelong skills in medical undergraduate students. In fact, PBL and SBL complement each other to fulfill the theory of physicians' lifelong learning and overcome skill-based barriers to lifelong learning ( Table 2). However, is it enough to have these learning strategies as separate educational tools in the undergraduate curriculum for lifelong learning to occur? Could additional benefit be derived from integrating SBL and PBL in a coordinated strategy so that the complementary strengths of one can fill the gap left by the other? We propose that PBL and SBL should be integrated specifically to develop lifelong learning as based on Miller's pyramid of performance assessment, the importance of deliberate practice, and the value of curriculum integration. Miller's pyramid is used as a framework for the assessment of clinical competence and as a tool for the development of assessment methods [32]. However, it may also be viewed as a framework for formative assessment and the development of learning activities. In medical education, PBL targets the "knows" and "knows how" levels whereas SBL targets the "shows how" levels ( Figure 1). By integrating PBL with SBL for lifelong learning activities, students will experience increasing professional authenticity and apply the knowledge they have acquired from PBL through SBL. Learning activities should include both cognition (PBL) and behavior (SBL) levels in Miller's pyramid. These are the knowledge, skills, and attitudes that students should acquire by merging PBL with SBL for lifelong learning. From the perspective of formative assessment, Miller's pyramid argues for an integrated learning strategy in providing a holistic education in lifelong learning. FIGURE 1: Mapping SBL and PBL to Miller's Pyramid of Clinical Competence Deliberate practice refers to the repetitive practice of cognitive or psychomotor skills with the goal of improved performance and development of expertise through specific feedback and rigorous skills assessment [33]. The Four-Stage Theory of Physicians' Self-Directed Learning Episodes should be viewed as a skill set that medical students should acquire for lifelong learning. Hence, students should engage in the deliberate practice of this four-step learning process to overcome the skill-based barriers in self-directed learning to become experts in lifelong learning. Accordingly, PBL and SBL should be integrated into a learning strategy that follows the Four-Stage Theory of Physicians' Self-Directed Learning Episodes. This integrated learning strategy needs to be practiced repeatedly in various simulated clinical encounters in order to achieve expertise in self-directed learning upon graduation and promote lifelong learning as a key competency. Hence, having PBL and SBL as separate educational strategies may not be well-suited for developing the required competency in lifelong learning. Curriculum integration is a key principle for sound SBL in medical education. In a study published by McGaghie, et al. [8], the authors stated that SBL should be "carefully integrated with other education events, including… PBL…". Curriculum integration results in content integrity and enhances authenticity, enabling students to develop a unified view of the curriculum that reflects the real world. Students who engage in an integrated learning strategy of PBL and SBL will become skilled in the entire learning process of a physician and achieve an understanding of learning while working. Having to integrate the skills obtained from PBL and SBL on their own may be an impediment to lifelong learning. It is our hope that by instilling a learning strategy that follows the self-directed learning process of the practicing physician, it would promote lifelong learning in becoming better physicians, a goal of undergraduate curriculum [2]. Having both PBL and SBL as separate teaching strategies in the undergraduate in the curriculum is not sufficient to meet lifelong learning needs of medical students. To achieve this goal, we propose to synergize the two existing educational strategies, PBL and SBL, via a framework that follows the learning process of a physician and targets the skill-based barriers to lifelong learning. Conclusions Lifelong learning skills are expected of every physician and, therefore, should be addressed at the undergraduate level. Translating knowledge of how physicians learn and the barriers they face into a learning strategy for undergraduate medical students is important in preparing them for lifelong learning. Skill-based barriers to lifelong learning could be overcome with the right training and educational strategy. The PAIRED framework for implementing a novel strategy for lifelong learning closely follows the learning process of physicians and utilizes the components and resources of current undergraduate learning strategies in targeting these barriers to promote lifelong learning competency. The PAIRED framework serves to synergize both PBL and SBL to achieve the objective of acquiring lifelong learning competency. Students who become competent in the PAIRED framework in their undergraduate years may find the lifelong learning process of a physician more intuitive. Merging PBL and SBL via the PAIRED framework may also enable students to better appreciate learning in medicine through curriculum integration. By engaging in the deliberate practice of the PAIRED framework, it is our hope that students will develop lifelong learning competencies. Development of a screening algorithm for borderline personality disorder using electronic health records Borderline personality disorder (BoPD or BPD) is highly prevalent and characterized by reactive moods, impulsivity, behavioral dysregulation, and distorted self-image. Yet the BoPD diagnosis is underutilized and patients with BoPD are frequently misdiagnosed resulting in lost opportunities for appropriate treatment. Automated screening of electronic health records (EHRs) is one potential strategy to help identify possible BoPD patients who are otherwise undiagnosed. We present the development and analytical validation of a BoPD screening algorithm based on routinely collected and structured EHRs. This algorithm integrates rule-based selection and machine learning (ML) in a two-step framework by first selecting potential patients based on the presence of comorbidities and characteristics commonly associated with BoPD, and then predicting whether the patients most likely have BoPD. Leveraging a large-scale US-based de-identified EHR database and our clinical expert’s rating of two random samples of patient EHRs, results show that our screening algorithm has a high consistency with our clinical expert’s ratings, with area under the receiver operating characteristic (AUROC) 0.837 [95% confidence interval (CI) 0.778–0.892], positive predictive value 0.717 (95% CI 0.583–0.836), accuracy 0.820 (95% CI 0.768–0.873), sensitivity 0.541 (95% CI 0.417–0.667) and specificity 0.922 (95% CI 0.880–0.960). Our aim is, to provide an additional resource to facilitate clinical decision making and promote the development of digital medicine. www.nature.com/scientificreports/ in the Veterans Administration (VA) Medical centers based on EHR data to stratify suicide risk 19 . We believe that using ML to perform automated screening of EHRs which contain routinely collected longitudinal patient health information is one potentially helpful strategy to address the unmet need for the identification of possible BoPD patients who are mis-or not diagnosed. However, the application of ML in BoPD is limited, let alone realworld implementations. One study 20 investigated the risk factors for future BoPD symptoms using regularized regression on a prospective longitudinal dataset of adolescent girls, which seems to be the only ML application in BoPD to-date. To the best of our knowledge, our project to build a ML model for BoPD screening based on EHRs is the first of its kind. The proposed method follows a two-step approach by first selecting potential patients based on rules on the presence of comorbidities and characteristics commonly associated with BoPD when BoPD has not been formally diagnosed, and then narrowing down the recommendation to health care professionals (HCPs) by predicting whether the patients are most likely to have BoPD using ML. One of major challenges in the ML development for medicine is the huge gap between the scarcity of expert annotated data (referred to as gold-labels) and the overabundance of unlabelled health data majorly due to the costly annotation process by domain experts. The ML component of our screening method followed a semisupervised learning idea [21][22][23][24] and leveraged a small amount of labeled data with a large amount of unlabeled data. During the development of our ML models, we built a 90 times larger training data set with silver-labels (generated without expert annotation) than the initial gold-label training data, leading to a significant improvement in generalization performance. We also found that rather than self-reinforcing knowledge learned from the gold-label data, introducing additional knowledge in building the silver-label data can improve the model performance, and such additional knowledge should not be as expensive as domain expert annotation. We leveraged a large-scale US-based de-identified EHR database which includes 13 million adult subjects from 2015 to 2018 for the algorithm development. Our BoPD clinical expert's opinion on the likelihood of a patient having BoPD was applied to two random samples of patients' EHRs, providing necessary data for building such screening algorithm. In this paper, we examine the performance of the ML component utilizing the clinical expert's rating and report the results. Rule-based selection for potential BoPD patients in Cerner. The US Cerner Health Facts (Cerner Corp., Kansas City, MO) database was used for this study. Of the 13,257,125 adult subjects ( ≥ 18 years of age) in Cerner who had ≥ 1 ICD-10-CM diagnosis code during study period (encounter discharge date from October 1, 2015 to July 11,2018), 183,475 (5%) were identified as potential patients with BoPD based on common comorbid conditions or key characteristics associated with the disorder. Additionally, subject inclusion required sufficient medical history in order for the algorithm to predict outcomes. Specifically, 1,1811,105 out of 13,257,125 (14%) subjects were retained initially with presence of mental disorder associated with BoPD, 1,040,704 out of 1,1811,105 (57%) subjects were retained for having sufficient medical history, and finally 183,475 out of 1,040,704 (18%) subjects were retained as potential patients with BoPD if they had suicidal/intentional selfharm or a diagnosis of bipolar disorder, or a history of mental disorders in at least 3 other pre-defined groups during study period. Pull-through rates may differ across other healthcare organizations. Details on selection rule can be found in the Methods section and additional information of potential BoPD cohort in Cerner can be found in Supplementary Table 1. ML model development and performance. Our BoPD clinical expert (M.G., former President of North American Society for the Study of Personality Disorders) reviewed 456 patient records from two independent random samples (228 patients in each sample) from the potential BoPD cohort, and clinically rated each patient on the likelihood of having BoPD. Patient records were structured EHR data including routinely collected information such as demographics, diagnosis codes, encounter types and dates. Patients with rating category "Most likely BoPD" are considered as candidates for formal clinical assessment for BoPD and therefore this rating category is the positive label in the binary classification task. Other rating categories including "no potential" or "weak potential" of BoPD were combined as negative labels. The two rated sets used for training and testing were referred to as gold-label training data and gold-label testing data. The percentage of positive cases were 29% (66/228) and 27% (61/228) in gold-label training and gold-label testing data, respectively (proportion test, p = 0.676 ). A subset of positive cases were further labelled as having characteristics associated with classic BoPD (12 and 9 in gold-label training and gold-label testing data, respectively). The algorithm was expected to identify classic BoPD as much as possible and therefore sensitivity of classic BoPD is included as an evaluation metric in addition

to other performance metrics. Following a semi-supervised learning framework, we then built a 90 times larger silver-label training data, including 20, 592 patients records with 5961 (29%) silver-positives and 14,631 (71%) silver-negatives. Silverpositives were identified with a rule-based selection process from a patient cohort already with BoPD diagnosis code, which were referred to as "EHR diagnosed BoPD cohort". Some patients in EHR diagnosed BoPD cohort were excluded because they had limited diagnostic history in the medical records which precluded our ability to identify relevant comorbidities, which was necessary for building silver-positives. Silver-negatives were selected from predicted negative in the potential BoPD cohort using the logistic regression (LR) model with L-1 norm regularization trained on gold-label data. A detailed description of gold-label and silver-label data can be found in the Methods section. The demographics and encounter types in gold-label and silver-label data sets are summarized in Table 1. The gender and age distributions are identical in two gold-label sets because stratified sampling was applied, and details can be found in the Methods section. The main model was built on silver-label training data using LR with L-1 norm regularization. We then built an adjustment model based on a subset of the gold-label data using LR with L1-norm regularization to further distinguish a subset of the negative cases with rating category "severe psychotic/substance abuse" from the positive cases. We combined the predictions from the main model and the adjustment model to reduce false positives. And the combined prediction is the final prediction. The overall ML model development pipeline is illustrated in Fig. 1. More details on the development pipeline including feature engineering can be found in the Methods section. Performance of the final model was evaluated on gold-label testing data, and the area under the receiver operating characteristics curve (AUROC) is 0.837 (95% CI: 0.778-0.892), and positive predictive value is 0.717 (95% CI: 0.583-0.836) indicating that for every 10 patients identified by the algorithm, on average 7 of them are most likely to be patients with BoPD. Accuracy is 0.820 (95% CI: 0.768-0.873) and sensitivity and specificity are 0.541 (95% CI: 0.417-0.667) and 0.922 (95% CI: 0.880-0.960), respectively. In addition, the recall of classic BoPD is 1.000 (95% CI: 1.000-1.000), demonstrating that the model is capable of capturing all classic BoPD cases. We compared performance of LR with other machine learning models trained on different data sets (illustrated in Figs. 2 and 3). Our results indicate that logistic regression out-performed other models, namely, bar groups corresponding to LR in both figures are usually the tallest among other bar groups. The detailed numeric results can be found in Supplementary Table 2. In addition, to demonstrate the benefits of building silver-label training data and making further adjustments, we compared performance from models trained on gold-label training data only, silver-label training data, and silver-label training data with our adjustment model. In summary, models trained on silver-label data consistently outperform models trained on gold-label data regardless of model types, and the adjustment improves model performance further, as can be observed in Fig. 2. Taking LR for example, the AUROC is 0.783 ( 95% CI 0.716 − 0.849 ) for gold-label data, 0.836 ( 95% CI 0.776 − 0.891 ) for silver-label data and 0.837 ( 95% Table 1. Demographics and encounter types in gold-label and silver-label data sets. Figure 1. The ML model development pipeline which follows a semi-supervised learning framework by starting with small gold-label data, and then building a large silver-label data; an adjustment model was built to reduce false positives. Details can be found in the Methods section. *Refer to the Table 3 for the label categories. Moreover, our proposed way of building the silver-positives is rule-based and it brings in knowledge in addition to those learned from the gold-label training data. The model performance based on such "knowledgeenriched" silver-positives is illustrated as red bars in Fig. 3. To demonstrate the benefits, we compared the model performance with two other ways of building silver-positives by only self-reinforcing knowledge learned from the gold-label training data. And these two ways are to apply the LR model trained on gold-label data on potential BoPD cohort and EHR diagnosed BoPD cohort, respectively, to generate predicted positives. The corresponding model performances are illustrated as green and blue bars in Fig. 3. In general, the red bar is taller than the green and blue bars in each bar group in each sub-figure, with a few exceptions such as the DNN model and decision tree model, which are not good performing models anyway. Feature analysis for the ML model. When examining the important features in the main model (red bars in Fig. 4), we observed that many features, typically associated with clinical presentations of BoPD had large positive weights, such as "suicidal ideation/attempt/intentional self-harm", "personality disorders", "trauma and stressor related disorders", "personal history of self-harm/physical and sexual abuse", "bipolar and related disorders excluding severe psychotic", "eating disorder", etc. Older age (age 40+) shows negative weight which is consistent with clinical presentations of BoPD occurring at younger ages 25 . When rating clinical records, our clinical expert did not consider gender as an important factor. And gender was not selected by the LR model trained on gold-label data either. Nonetheless, there was Model performance comparison among models trained on different silver-positives. Self-potential (green bars) and self-BoPD (blue bars): silver-positives were built via applying the LR model trained on goldlabel data on potential BoPD cohort and EHR diagnosed BoPD cohort, respectively, to generate predicted positives. Silver (red bars): rule-based selection of silver-positives from EHR diagnosed BoPD cohort, also called knowledge-enriched silver-positives. Black verticle lines represent 95% confidence interval. www.nature.com/scientificreports/ a large proportion of females with BoPD in the silver-positives data and this proportion was much greater in silver-positives (83%) than in silver-negative (63%), resulting a large positive weight in the learned LR model. We attribute this to the potential bias in clinical populations that a woman with BoPD may be more likely to seek treatment than a man with BoPD 26 . For this reason, we decided to include a gender feature in the model with the provision that it does not exclude the selection of males in the result. While features such as anxiety and depression are common comorbid conditions of BoPD, they also commonly exist in other types of patients, including those with long term physical illness. As a result, the feature weights are not as large as expected. Similarly, non-compliance of medication is common for BoPD, and for other mental or physical disorders, and therefore this feature also does not have a large weight. www.nature.com/scientificreports/ Furthermore, we also observe some features with effects in different directions from our clinical expert's judgement, for example, "Agoraphobia with panic disorder" and "obsessive-compulsive disorder" were rated as negatively associated with BoPD, but their effects were positively associated in the LR model trained on silverlabel data, potentially due to the fact that their prevalence is larger in silver-positive data than in silver-negative data. However, the prevalence of such features were generally small ( < 5% ) and we consider the impact of such misalignment with clinical expert's judgement to be minimum on the prediction outcome. More discussion on features is in the Discussion section. Detailed feature information is in Supplementary Table 3. Methods Here we introduce our proposed method for screening of BoPD, which follows a two-step approach by first selecting potential patients from general EHR data and then narrowing down the results of step 1 by applying ML prediction. The end product is a list of patients "most likely" to have BoPD that can be provided to health care professionals (HCPs) for further evaluation. We describe the selection rules for potential BoPD patients, data sets and feature engineering for ML development, and ML development pipeline in detail as follows. Refer to Supplementary Figure 1 for an illustration of the two-step approach. Cerner health facts database. For this study, the US-based Cerner Health Facts database was used to obtain the large sample of de-identified EHRs required for the algorithm development process. The database contains data extracted directly from electronic medical records provided by hospitals under a data use agreement with Cerner. Encounters may include pharmacy, clinical and microbiology laboratory, admission, and billing information from affiliated patient care locations. Date and time stamps are included for all admissions, medication orders and dispensing, laboratory orders and specimens, providing a temporal relationship between treatment patterns and clinical information. Cerner Corporation has established operating policies ensure that all data in the Health Facts database are fully de-identified in compliance with the Health Insurance Portability and Accountability Act. The data was collected from 2000 to 2018, with most encounters between 2009 and 2018. Selection rules for potential BoPD patients. We used the Clinical Classifications Software Refined (CCSR) version 2020.2 27 to define the selection rules in a database queriable fashion as well as to construct features in the ML model. The CCSR aggregates over 70,000 ICD-10-CM codes into approximately 530 clinically meaningful categories. We considered default CCSR categories for each ICD-10-CM code in this study. Specifically, the selection rules for potential BoPD patients are : Inclusion criteria: • Patients had 5 or more encounters on different discharge dates or patients had 2 or more emergency visits on different discharge dates during study period; • Patients ever had any diagnosis codes in the CCSR categories in Table 2 Table 2 during study period; Exclusion criteria: or intellectual disabilities (ICD-10-CM codes F70-F79) during study period. The clinical rationale of above selection criteria is described as follows. Bipolar Disorder and suicide symptoms are key indicators of the "likely BoPD" group (referred to as potential BoPD patients). The symptoms of BoPD and bipolar disorder overlap extensively 28,29 and there is a high rate of misdiagnosis of BoPD as bipolar disorder 30 . Moreover, patients with BoPD have an increased risk of suicide 3 which can be an indicator of affective instability and impaired emotion and behaviour regulation. Intentional self-harm (also referred to as non-suicidal selfinjury (NSSI)) was included with suicidal behavior as they are in the same CCSR category (described in more details below) leading to easy data processing despite having different clinical presentations. The validity of these criteria is also supported by the observation that more than 70% of the EHR diagnosed BoPD cohort had either bipolar disorder or suicidal/intentional self-harm (Supplementary Table 1). For patients without Bipolar Disorder or suicidal symptoms including NSSI, the presence of other mental disorders in at least three pre-defined groups which are associated with BoPD was required for inclusion in the "likely BoPD" group. The intention was to capture a range of features of BoPD which may be reflected in individuals diagnosed with multiple disorders. We also aimed to avoid patients who primarily had a physical illness with secondary depression or anxiety. In addition, unlike HCPs who are able to make clinical decision based on a single encounter with the patient, ML usually requires a larger amount of data to be trained and tested. We, therefore, required a minimum number of clinical encounters to ensure sufficient information for each patient to build the ML algorithm. Moreover, we suggest the study period to be the recent 4 to 5 years in practice, and therefore including time period when ICD-10-CM codes are in use. ML model development for screening BoPD. Data sets for ML model development. The data sets to develop our ML algorithm consist of potential BoPD cohort, EHR diagnosed BoPD cohort and gold-label data sets based on Cerner data. We summarized the flowchart of obtaining the potential BoPD cohort, EHR diagnosed BoPD cohort and gold-label data sets in Cerner in Fig. 5. We considered encounters with ICD-10-CM diagnosis codes and a discharge date between October 1, 2015 and July 11, 2018 (last encounter discharge date in the Cerner database) to generate the data sets. Encounters without diagnosis codes were not considered. Applying the selection rules of potential BoPD patients to Cerner data in aforementioned study period yields the potential BoPD cohort. The EHR diagnosed BoPD cohort is defined as patients with EHR diagnoses of BoPD (ICD-10-CM code: F60.3) during study period. The additional inclusion criteria including age and minimum number of encounters, and exclusion criterion of known physiological conditions or intellectual disabilities are the same as criteria for the potential BoPD cohort. Gold-label training and

testing data sets were two random samples drawn independently from the potential BoPD cohort, each with sample size 228 (456 in total). Our clinical expert provided ratings of the likelihood of having BoPD on these 456 patient records. Stratified sampling was used since it provides a better representation of the patient cohort as compared to simple random sampling. The strata were based on three variables: gender, age group and diagnostic history of bipolar and suicidal or intentional self-harm behaviour. Figure 6 shows detailed information for the description of each stratum and the corresponding prevalence in the potential BoPD cohort. We excluded 80 patients with 'unknown or other' gender from the random sampling. www.nature.com/scientificreports/ For each patient in these two random samples, EHR data including gender, age, encounter types and dates, and diagnosis codes and the code descriptions associated with each encounter were presented to the clinical expert to be assigned to one of the mutually exclusive categories (category A-E) as shown in Table 3. Despite not having access to clinical notes, the available information was considered comprehensive enough to enable clinical judgement on the likelihood of a patient having BoPD. Pertinent information included diagnoses of suicide or self-harm, diagnoses that characterized both impulsivity and emotional instability (e.g. bipolar disorder and post-traumatic stress disorder), data implicating interpersonal difficulties (e.g. treatment non-compliance), a history of childhood trauma, or leaving the emergency room against medical advice. Patterns of treatment use were also considered, for example instability of outpatient care and multiple emergency room visits. The clinical expert reviewed patient records multiple times to ensure consistency of the ratings. The summary of our clinical expert's ratings is shown in Table 3. A subset of patients in category "E: Most likely BoPD" were rated as having characteristics associated with classic BoPD (namely, category "E1: Classic BoPD"), which was defined as demonstrating diagnoses consistent with a minimum of 4 criteria of BoPD (e.g. suicide/self-injury, affective dysregulation, impulsivity, dissociation/psychosis under stress). We further showcased a snapshot of a de-identified patient record which was presented to the clinical expert in Fig. 7. Feature engineering. We included a comprehensive list of covariates from our EHR data for predictive modeling, including: age (18-39, 40-59, 60-65), gender (Female/Male), categorization of encounters based on encounter frequency (high, median, low) and encounter types (emergency, inpatient, outpatient and others as one category), and diagnosis history. In particular, for diagnosis history, we first selected the top prevalent ( ≥ 0.05 ) ICD-10-CM diagnosis codes in both EHR diagnosed BoPD cohort and potential BoPD cohort, and then combined them to result in 571 ICD-10-CM diagnosis codes. Our clinical expert reviewed and rated these 571 diagnosis codes on their association with BoPD in the following categories: negative association, positive associa- Figure 6. Stratification of potential BoPD cohort by age group, gender and diagnosis history on bipolar and suicidal or intentional self-harm behaviour. N: No diagnosis code of bipolar or suicidal/intentional self-harm and had ≥ 3 categories in mental disorder categories in Table 2; Y1: Had diagnosis code of bipolar or suicidal/ intentional self-harm and had ≥ 3 categories in mental disorder categories in Table 2 (including bipolar or suicidal/intentional self-harm); Y2: Had diagnosis code of bipolar or suicidal/intentional self-harm but had < 3 categories in mental disorder categories in Table 2 (including bipolar or suicidal/intentional self-harm). Table 3. Clinical expert's rating in gold-label training and testing sets. Rating category Gold-label training set no. (%) Gold-label testing set no. (%) A 27 . This ensured that the grouped codes share similar clinical meaning. Next, within each CCSR category, we further divided each mapped CCSR category by association with BoPD to include such knowledge into the model. Supplementary Figure 2 illustrates the method using diagnosis codes related to depressive disorder as an example. All features were encoded as Boolean value. Detailed definition of each feature can be found in the Supplementary Table 3. ML development pipeline. Figure 1 illustrates the machine learning development pipeline to generate the screening model for step 2 (See the pseudo code in the Supplementary Algorithm 1). It follows a semi-supervised learning framework by starting with small gold-label data, and then building a large silver-label data. Model 1 was built on gold-label data as the initial binary classification model where category "E: Most likely BoPD" is the positive label, and other categories were combined to be negative labels. Model 1 was then applied to the unlabelled potential BoPD cohort (i.e. excluding gold-label sets) to generate predictions, and 14, 631 silver-negatives were randomly selected from those predicted as negative. The number of silver-negatives is determined by the number of silver-positives in order to have the same positive-to-negative ratio as in the goldlabel training data (66 : 162). In the meanwhile, 5, 961 silver-positives were selected from the EHR diagnosed BoPD cohort following the same selection rules for potential BoPD cohort while excluding the BoPD diagnosis code, namely, patients had no bipolar nor suicidal/intentional self-harm and had 2 or less categories in mental disorder categories are excluded. Model 2 was then built on silver-label data as the main binary classification model for BoPD screening. Because of the uniqueness of the rating category B (severe psychotic/substance abuse) as described in the Discussion section, Model 3 was built on a subset of the gold-label training data ( n = 94 ) which includes category "E: most likely BoPD" and "B: Not likely BoPD -severe psychotic/substance abuse" to distinguish these two categories. It was then combined with Model 2 in the following way to make adjustment to its prediction in order to reduce false positives, and therefore yielding the final model: where p 2 , p 3 and p final represent probability of positive generated by Model 2, Model 3 and final model, respectively. All models we used were logistic regression with L-1 norm regularization 31 , and in principal, any prediction model may be considered in this framework. In our case, regularized logistic regression shows its superiority in both prediction performance and interpretability and therefore was selected to be implemented in practice. Model evaluation. The final performance of the developed model was evaluated on the (out-of-sample) testing data with gold labels. To prevent over-fitting, the best model was trained and selected on the training data by 10-fold cross-validation in terms of the area under the receiver operating characteristic (AUROC) on the validation set, and the testing data was kept unseen during model training procedure. We reported different classification metrics on the testing sets, including: AUROC and accuracy which need no threshold; and the positive predictive value and sensitivity at the threshold of 0.5 with specificity 0.922 (95% CI 0.880-0.960). We reported the 1,000-bootstrapped 95% confidence intervals for the above evaluation metrics 32 . Ethics. The Cerner Health Facts database is a real-world, de-identified, HIPAA-compliant electronic health records database. The study we conducted in this paper is on secondary use of this data and thus not considered Discussion We investigated leveraging the use of EHR data and ML for screening patients who currently do not have BoPD diagnosis but may potentially have the disorder. The proposed approach was developed with the goal of providing an additional resource to facilitate clinical decision making and enabling scalable deployment of computational model in clinical practice. This approach is not meant to replace the clinical gold-standard screening (i.e. semi-structured interview with patients) nor to make a diagnostic decision, and HCPs should rely on their own judgement to make clinical decisions for an individual patient. Our results indicate that initial out-of-sample performance of ML model on the gold-label testing set is encouraging, showing high consistency with our clinical expert's rating. An important aspect of the proposed method is the two-step approach of initially rule-based selection, and then ML prediction to identify the candidate patients. The rule-based selection was used to improve the probability of identifying potentially under or misdiagnosed patients with BoPD, supported by nearly 30% patients rated as most likely BoPD in the gold-label sets. This not only creates relatively balanced training set for ML development and therefore avoids issues generated from imbalanced sample, it also made efficient use of clinical expert's time to generate useful ratings on identifying most likely BoPD patients from potential patients instead of from general subjects. The rule-based selection excludes subjects either for not having common comorbidities or key characteristics of BoPD, or not having sufficient diagnosis history for ML prediction. The clinical rationale of selection rules is explained in the Methods section. In the ML development, the construction of a larger silver-label data may improve generalizability in realworld practice with initial demonstration described in the Result section. Silver-negatives can only be selected with guidance from gold-label training data, and silver-positives, on the other hand, can be built in multiple ways. We chose to use EHR diagnosed BoPD cohort instead of potential BoPD cohort, because EHR diagnosed BoPD cohort represents a collection of clinical expert opinions which is more diversified from our clinical expert's judgement reflected in the gold-label data. We chose to use rule-based selection instead of gold-label guided selection, because the selection rules are based on common comorbidities and key characteristics of BoPD, and it potentially introduces additional information different from knowledge learned from gold-label guided selection, and therefore may improve generalizability performance of the developed ML model. The comparison of the coefficients of LR models built on gold-label data and silver-label data (blue and red bars in Fig. 4) reveals that, clinical highly relevant features stand out more in the model trained on silver-label data when they are not selected by model trained on gold-label data, such as unspecified personality disorder and bipolar disorder. This further supports the strategy of building silver-label data instead of only using goldlabel data. We noticed that several features such as Schizophrenia and Hallucinations were only highly prevalent in patients rated as "severe psychotic/substance abuse" which is a subset of the negative labels. However, these features did not stand out in the main model, because their effects have been diluted when "severe psychotic/ substance abuse" was combined with other rating categories as negative labels. Therefore, the main model may wrongly classify such patients as positive cases. To bring out such feature effects and to reduce false positive, we have built an adjustment model on a subset of the gold-label training set with ratings only in "severe psychotic/ substance abuse" or "most likely BoPD" to distinguish the two. Such features indeed showed up to be important in the adjustment model (green bars in Fig. 4). The benefit of including adjustment model seems to be marginal in the overall model performance (Fig. 2), and it may be improved by changing the rule when combining with the main model, and/or improving the adjustment model itself by expanding the training set analogous to the construction of silver label data for the main model. We have considered formulating the problem as multi-class classification instead of binary classification, however, the goal is to identify "most likely BoPD" from others which is a natural binary consideration, and due to limited sample size of gold-label data, multi-class classification is not a promising modeling direction. This study has several limitations. The observation that not all patients from EHR diagnosed BoPD cohort were not included in silver-positives due to limited comorbidities in the structured EHR reflect a limitation of our EHR data. Our data is from a single EHR provider, while patients may have encounters with different providers in different facilities using different EHR systems, raising the potential for missing data. Nevertheless, medical records may not be easily transferred between different systems and HCPs may only have access to the local EHR; thus, use of a single EHR may be more representative of the 'real-world' situation. Our primary modeling features are ICD-10-CM codes which are US-specific, and may not be directly applicable to other countries where other ICD codes are used. Additionally, medical notes were not available to us and therefore were not included within the analyses which limits the available clinical information. Moreover, there was only one clinical expert to provide gold-labels, although we tried to include diversified clinical expert opinions when constructing the silver-label data, as discussed previously. When developing the screening algorithm, model interpretability was important because providing clarity and transparency into how the algorithm makes decision is critical to us. In fact, we have explored

several machine learning models including "black-box" models, and the interpretable model stands out. Scalability was also an important factor that we considered in the design of the proposed method. We grouped the diagnosis codes to potentially overcome heterogeneity in coding behavior among HCPs. In addition, we opted for simple structured EHR data which are routinely collected in all EHR systems with standardized coding, although is a limitation of the current method, but may increase the chance for scalable deployment. www.nature.com/scientificreports/ While the ML model achieved good performance on the out-of-sample gold-label testing data, and demonstrated high consistency with our clinical expert's ratings, we were not able to confirm whether the patients identified as "most likely BoPD" are eventually diagnosed with BoPD. This would require semi-structured interviews on patients from the Cerner database which was not possible with the de-identified data that was supplied to us. When we applied the model to silver-positives which includes patients with a BoPD diagnosis code, we found that 62% of the silver-positives were predicted as "most likely BoPD" by the model. This result is from an in-sample evaluation and may not be generalizable. Nonetheless, our ML model shows a 72% positive predictive value and 100% recall of the "classic BoPD" sub-category in the out-of-sample performance. Overall, we think the proposed method is a potentially helpful strategy to identify possible BoPD patients who are otherwise undiagnosed. Application of the BoPD screening tool in a real-world setting is currently underway but does require consideration of several factors. The implementation requires access to EHR data at sites and the ability to preprocess the data with pre-determined logic and format, which may only be feasible for research-oriented health institutes. Due to data privacy concerns, we are not able to access the site data and produce results for end users; however, we have made the code available on GitHub with a user-friendly interface and have written a detailed user manual with sample SQL codes to help sites understand the data pre-processing logic in order to facilitate adoption. Intermediaries such as an EHR data aggregator or EHR system provider may be a good candidate to adopt our model in their platform, alleviating analytical burden for sites. In addition, there may be operational challenges along the way such as getting model results and patient re-identification to end users in a seamless fashion. Last but not least, end users need to follow their IRB regulations for re-identification of screened patients and subsequent contact with patients. In conclusion, we developed a machine learning-based screening model to identify possible BoPD patients who are otherwise undiagnosed using structured EHR data. Our model integrated both clinical rule-based selection and a semi-supervised learning framework, leading to better generalization performance than models learned from gold-labeled data. Our study suggested the promise of developing scalable computational tools for BoPD screening and diagnosis based on machine learning and EHR data. Data availability The data sets analyzed during the current study are not publicly available due to restrictions by Cerner; the owner of the data. Data could be accessed by signing a data sharing agreement with Cerner and covering any costs that may be involved. Code availability The BoPD screening algorithm has been integrated into a screening tool for implementation. There are two versions: a portable version which has a graphical interface and a headless version which includes executable Python source code without a graphical interface. In addition, instruction and sample SQL code for EHR data processing are included in a user manual. All are publicly available at https:// github. com/ BoPDd iseas escre ening/ Borde rline-Perso nality-Disor der-BoPD-autom atic-disea se-scree ning-tool. The portable version of the screening tool is demonstrated in https:// github. com/ BoPDd iseas escre ening/ Borde rline-Perso nality-Disor der-BoPD-autom atic-disea se-scree ning-tool/ blob/ main/ BoBP_ scree ning_ porta bleve rsion demo. mp4. A modified gene trap approach for improved high-throughput cancer drug discovery While advances in laboratory automation have dramatically increased throughput of compound screening efforts, development of robust cell-based assays in relevant disease models remain resource-intensive and time-consuming, presenting a bottleneck to drug discovery campaigns. To address this issue, we present a modified gene trap approach to efficiently generate pathway specific reporters that result in a robust “on” signal when the pathway of interest is inhibited. In this proof-of-concept study, we used vemurafenib and trametinib to identify traps that specifically detect inhibition of the mitogen-activated protein kinase (MAPK) pathway in a model of BRAFV600E driven human malignant melanoma. We demonstrate that insertion of our trap into particular loci results in remarkably specific detection of MAPK pathway inhibitors over compounds targeting any other pathway or cellular function. The accuracy of our approach was highlighted in a pilot screen of approximately 6000 compounds where 40 actives were detected including 18 MEK, 10 RAF, and 3 ERK inhibitors along with a few compounds representing previously under-characterized inhibitors of the MAPK pathway. One such compound, bafetinib, a second generation BCR/ABL inhibitor, reduced phosphorylation of ERK and when combined with trametinib, both in vitro and in vivo, reduced growth of vemurafenib resistant melanoma cells. While piloted in a model of BRAF-driven melanoma, our results set the stage for using this approach to rapidly generate reporters against any transcriptionally active pathway across a wide variety of disease-relevant cell-based models to expedite drug discovery efforts. Introduction Effective high-throughput screening (HTS) campaigns can establish a solid foundation upon which successful drug discovery efforts are built. Although automation platforms have advanced, and our collective understanding of molecular drivers of disease has greatly increased, converting such advances into therapies that induce durable patient responses has been challenging 1 . While there are many potential reasons for this, we viewed two as immediately addressable. First, cell-based assays, including reporter assays, are often developed in cell lines that are most amenable to genetic manipulation but not necessarily in models that best approximate the disease of interest. Second, the use of assays that report in the "down" or "off" direction following drug exposure often results in a limited signal-tonoise ratio leading to false positives, which can misdirect drug discovery resources 1 . To help address these issues, we set out to develop an improved reporter platform, initially focused on cancer drug development, with the following criteria in mind: First, the platform had to be HTS compatible, capable of testing thousands of samples in a reasonable time frame and cost-effective format. Second, assay development must be efficient, requiring no prior identification of promoter sites or site-specific targeting vector generation. Third, the readout must have a robust signal-to-noise ratio, ideally reporting an increase in signal upon pathway inhibition. Finally, the platform had to be flexible so that the technology can ultimately be employed to interrogate any transcriptionally active pathway in any cancer model. The platform we devised was built on the foundation of two previous approaches: 1) gene expression profiling to derive transcriptional signatures of active oncogenic signaling cascades and 2) gene trap systems to identify and harness transcriptionally active genes as reporters of pathway activity. Changes in gene transcription can accurately capture the activation status of oncogenic signaling pathways 2 . This has been well demonstrated in studies that have shown that the RAS gene signature is a more comprehensive metric of RAS functional status than RAS mutation alone 3 . While gene expression signatures can accurately measure activity of oncogenic pathways, characterization can be labor-intensive, and multi-gene signatures are not easily amenable to HTS-based drug discovery. Therefore, we hypothesized that if single transcripts can be identified which accurately report on the activity state of an oncogenic pathway, these transcripts could be harnessed as robust reporters for use in comprehensive HTS campaigns. Toward this end, we applied a modified gene trap approach. Gene traps are vectors containing a promoterless reporter cassette which is only expressed upon integration into an active gene locus [4][5][6] . While originally developed for insertional mutagenesis in the mouse, previous gene trap screens have been used to rapidly and efficiently identify transcriptionally responsive genes to exogenous stimuli such as Hepatocyte Growth Factor 7 . To test whether we could use a gene trap approach to isolate highly specific reporters of transcriptionally active oncogenic pathways for HTS, we established a scheme where random integration of a promoterless reporter into the host cell genome was followed by drug selection with a cancer pathway specific tool molecule. This approach allowed us to interrogate the genome in an unbiased manner and identify "trapped" genes where insertion of the promoterless reporter cassette highjacks the endogenous promoter and leads to increased signal, specifically in response to pathway inhibition. These reporters then provide the means to perform subsequent functional screens to identify novel oncogenic pathway inhibitors. As proof of concept, we focused on the MAP kinase network in a model of BRAF mutant (V600E) melanoma. In addition to activating mutations of BRAF being clear drivers of melanoma and other malignancies, there are a number of tools available to test our hypothesis 8 . First, a number of highly characterized small molecule inhibitors of BRAF and downstream kinases, such as MEK, are available as inducing agents for our trapping studies 9 . Second, it is well-established that perturbation of the canonical MAP kinase cascade (BRAF/MEK/ERK) results in changes in the expression of distinct gene sets [10][11][12] . Additionally, many structurally diverse specific inhibitors of BRAF and MEK are incorporated into well-characterized annotated screening libraries, thus allowing us to assess the ability of our platform to accurately detect MAPK pathway inhibitors, out of large screening collections of compounds. Therefore, a gene trap screen was performed to identify traps that were responsive to both the BRAF inhibitor vemurafenib and the MEK inhibitor trametinib [13][14][15] . Identification of drug responsive traps was followed by a subsequent HTS pilot screen of ∼6000 diverse compounds to establish specificity of the approach and utility for future HTS campaigns designed to identify inhibitors of difficult-to-drug oncogenic targets. Gene trap-based generation of BRAF/MAPK pathway-specific reporters To test the hypothesis that high-specificity HTS-compatible reporters of oncogenic function can be rapidly generated without a priori identification of pathway-specific transcripts and mapping of promoter elements, we constructed a gene trap vector called SABRE (Splice Acceptor Bi-functional REporter). The vector construct pSABRE-1, consists of two nondestructive reporter elements (green fluorescent protein (GFP) and secreted, extracellular membrane-anchored Gaussia luciferase (mGLuc)) as well as a neomycin-resistance gene flanked by splice acceptor and SV40 polyadenylation sequences ( Figure 1a). pSABRE-1 was packaged as lentiviral particles, transduced into the human BRAFV600E mutant malignant melanoma line A375, and transduced clones were selected in neomycin. Following initial drug selection, thousands of neomycin-resistant clones were identified. We then assessed whether we could employ a drug selection scheme following introduction of pSABRE-1 to identify and isolate A375 clones harboring traps that signal upon exposure to either the BRAF inhibitor vemurafenib or the MEK inhibitor trametinib. Two independent selection schemes, one based on detection of GFP, the other on luciferase signal were tested. Trametinib exposure for 24h followed by fluorescence-activated cell sorting (FACS) for GFP positive cells failed to reveal clones responsive to MEK inhibition. However, the nondestructive nature of the secreted membrane-anchored luciferase cassette provided an alternative selection scheme to identify vemurafenib and trametinib-responsive traps ( Figure 1b). Plates containing cell colonies were exposed to luciferase substrate en-masse (10 5 clones/screen), imaged to generate a pre-treatment luciferase signal, treated with inhibitor for 24 hours, then reimaged to identify drug responsive cells. Clones exhibiting ≥3-fold changes in luciferase signal (in both the "up" and "down" direction) were isolated, expanded and retested. Eleven clones were identified in the initial screen (8 up, 3 down). Upon retesting, 3 "off-to-on" clones and 1 "on-to-off" clone exhibited luciferase signaling windows and dose dependent responses to trametinib indicating sufficiency for downstream HTS studies (Figures 1c and 2). These clones were sequenced to identify the integration sites of the SABRE reporters (Table 1). Further analysis by RNA-seq demonstrated changes in endogenous transcript levels in response to trametinib exposure. Interestingly, integration of the trapping cassette in the clone with the strongest off-to-on signal (SB01, Figure 2a) occurred within a pseudogene transcript called INTS4P2, which has never been previously linked to the canonical BRAF/MEK/ERK kinase cascade. Since SB01 exhibited the strongest signal in the "on" direction, suggesting excellent potential as a reporter for HTS, we focused on this clone for further analysis.

HTS demonstrates BRAF/MAPK pathway specificity of SABRE reporter line The utility of any drug discovery assay is highly dependent on its specificity. To determine if a single gene insertion generated by our traps could accurately report on specific inhibition of the MAPK pathway, we performed a pilot scale screen on the SABRE SB01 reporter line. We first tested the NCI DTP set (version V), composed of 114 approved anti-cancer agents including 3 inhibitors of the MAPK pathway that target BRAF (vemurafenib and dabrafenib) or MEK (trametinib) 16 . Consistent with the ability of our clones to accurately detect inhibitors within the MAPK pathway, out of the 114 drugs tested all 3 known MAPK pathway inhibitors resulted in significant activation of the luciferase reporter ( Figure 2c). The only other agent exhibiting reporter activity above background was the multi-kinase inhibitor dasatinib, which has been previously shown to inhibit the MAPK pathway 17 . Based on the suggestive specificity exhibited in this small-scale assessment, we next tested whether this reporter could specifically and comprehensively identify other MAPK pathway inhibitors out of a library of thousands of compounds. To prepare for HTS, the assay was miniaturized (1536-well format), adapted to automation and validated for screening performance (Figure 3a and b). The assay maintained dosedependent luciferase signal and excellent performance in miniaturized and automated format (average Z′ values = 0.7). The miniaturized assay was used to screen an annotated library of approximately 6000 small molecules with known modes of action. The screening library was comprised of the well-characterized Library of Pharmacologically Active Compounds (LOPAC) set of 1280 compounds, ∼ 2,800 compounds from the NCGC Pharmaceutical Collection of clinically approved drugs, and 1,912 compounds from the NCATS Oncology Mechanism Interrogation PlatEs (MIPE) library composed of 745 approved drugs, 420 clinical trial-stage drugs, and 767 preclinical molecules 18 . The MIPE library was assembled with the intent to have diverse and redundant mechanisms of action represented to allow for target-based enrichment analysis of responses. The drugs were screened at either 4, 7, or 11 different concentrations, for the NPC, LOPAC and MIPE collections, respectively, to obtain dose response information for each compound, including potency and efficacy. Consistent with highly specific and comprehensive detection of RAF/MEK/MAPK pathway inhibitors, the screen yielded 40 actives (0.67% hit rate), of which 18 were MEK inhibitors, 10 were RAF inhibitors, and 3 were ERK inhibitors ( Figure 3c and Table 2). Enrichment scores using Fisher's exact test were P=2.76E-11 and P=2.99E-20 for BRAF and MEK inhibitors respectively. Actives identified in the screen were re-tested in 9-point dilution series in the SB01 reporter assay as well as the on-to-off reporter line SB03. Interestingly, the dose response curves closely mirrored each other across the 2 lines and the rank order was maintained for all compounds tested ( Figure 4, compare a to b and c to d). In addition to the RAF, MEK, and ERK inhibitors, the screen yielded several active compounds that had not been previously annotated as directly inhibiting MAPK pathway targets suggesting that our assay has potential to detect novel inhibitors of pathway signaling ( Table 2). Three of these compounds (AMG-Tie2-1, AMG47a, and bafetinib) reconfirmed in our dose response assays in both reporter lines, and resulted in decreased ERK phosphorylation (Figure 4e-g). Taken together, these results demonstrate the exquisite accuracy of the SABRE reporters for detecting bona fide inhibitors of the canonical MAPK pathway. Identification of a potential novel drug combination to address BRAF resistant melanoma Acquired drug resistance to BRAF inhibitors is a common occurrence in melanoma. We next investigated whether we could use SABRE to identify compounds that retain inhibitory activity against the MAPK pathway following emergence of BRAF inhibitor resistance. To do so we generated a vemurafenib resistant A375 SABRE reporter line (SB01-VR) through continued exposure to increasing concentrations of vemurafenib (Figure 5a and b). We then tested the ability of some of the top drug candidates identified in the screen to induce luciferase expression in the SB01-VR line. As expected, the resistant SABRE line did not respond to BRAFV600E specific inhibitors (vemurafenib, PLX-4720 and dabrafenib), but maintained responsiveness to MEK inhibitors (trametinib, cobimetinib, and PD0325901) and BRAF inhibitors (SB590885 and Takeda-6d) (Figure 5c and d). Interestingly, although less potent than the MEK inhibitor trametinib, several of the novel pathway inhibitors including bafetinib, AMG-47a, and AMG-Tie2-1 all retained activity in the SB01-VR line ( Figure 5e). This suggests that these compounds may have utility for treating BRAF inhibitor-resistant disease, either as single agents or in combination with MEK inhibitors. We focused further studies on the second generation BCR-ABL inhibitor bafetinib, since it has an established safety profile in human cancer patients and was progressed to phase II trials 19 . We assessed whether the combination of bafetinib and trametinib could outperform either drug alone in assays reflecting inhibition of MAPK signaling (pERK Western blot analysis) and tumor cell proliferation. Consistent with potential as an effective novel drug combination to investigate in BRAF inhibitor-resistant disease, the combination of the two drugs resulted in substantial decreases in ERK phosphorylation and A375 SB01-VR colony growth in vitro, as compared to either agent alone (Figure 6a-c). We also assessed the activity of the drug combination on SB01-VR xenografts in vivo (Figure 6d). Because trametinib has potent activity in this line, we first identified a dosing regimen of trametinib that reduced tumor growth rates yet enabled identification of drugs that improved efficacy when used in combination. Consistent with the results of our cell-based assays, treatment with the combination of bafetinib and trametinib, but not with either drug alone, significantly reduced tumor growth (between days 7-16 of the 21 day dosing period) compared to control mice (P=0.0159, Mann-Whitney test) (Figure 6d). In addition to demonstrating that SABRE lines can correctly identify known pathway inhibitors and identify new candidates, the in vivo studies reveal the ability to identify drug candidates that act in tumor cells rendered resistant to the drug used to first establish the SABRE line. Discussion The data presented demonstrate that a gene trap approach can be used to generate robust and highly specific reporters that accurately detect inhibitors of oncogenic pathways. The gene trap reporter we used for our screen identified nearly all the known BRAF and MEK inhibitors out of a library of ∼6000 compounds as well as several compounds that had not been primarily associated with the canonical MAP kinase pathway. The "novel" pathway inhibitors detected in our screen validated as inhibiting ERK phosphorylation in subsequent experiments, emphasizing the utility of our approach to identify and repurpose existing compounds for use in new disease areas. Importantly, unlike the conventional approach to reporter generation, ours does not require identification of pathway specific response elements prior to construct generation, assay development, and validation, dramatically increasing the efficiency of reporter generation. Moreover, a single SABRE vector can theoretically be used to generate reporters for any transcriptionally active pathway of interest. Given that oncogenic signaling networks have built in redundancies allowing for adaptive bypass of primary target inhibition, the SABRE platform has the potential to identify and develop sets of novel pathway inhibitors to cut off multiple routes leading to tumor resistance to targeted therapies. Our screen and subsequent hit validation studies revealed several compounds that could potentially address acquired resistance to BRAF inhibitors such as vemurafenib. The identification of bafetinib provides an example of how our approach can be used to repurpose a compound, originally developed as a second generation BCR/ABL inhibitor. Furthermore, our approach highlighted BRAF inhibitors such as SB590885 and Takeda-6d, that retained activity in our vemurafenib resistant model. Interestingly the chemical structure of Takeda-6d is similar to that of Pan-RAF inhibitor TAK-632 which demonstrated potent anti-tumor effects in BRAF-mutant melanoma cells with acquired resistance to BRAF inhibitors [20][21][22] . A reasonable question regarding our approach is "why not just use expression profiling data followed by CRISPR to clone into the loci of highly drug-regulated transcripts?" While this sounds efficient, there are several key problems with this strategy. First, there is no way of knowing, a priori, whether reporter insertion into a regulated transcript site will lead to deleterious tumor cell effects that could decrease cell viability or signal strength of the reporter. With SABRE, insertion into genes required for cell viability or reporter signal are automatically eliminated since we screen for increased reporter function. Only the most robust traps are selected. Second, although CRISPR is relatively efficient, novel targeting vector generation is required for every targeted insertion 23 . Therefore, the gene trap approach provides an even greater level of efficiency over a CRISPR-based approach. The insertion of our trap into the pseudogene INTS4P2 is interesting in that to our knowledge, INTS4P2 has never been reported to be associated with the MAP kinase pathway. Given that tumor cell types exhibit unique transcriptional profiles to external stimuli, the high specificity and responsiveness of the pSABRE-1 reporters, such as SB01, may be context specific to the cell type in which they are created. Early experiments performed in our lab to assess transcriptional regulation of INTS4P2 in response to trametinib across multiple cell lines, suggests that this is indeed the case. This suggests that the one-size-fits-all approach for reporter generation where a common promoter element is identified, linked to a reporter, and then artificially overexpressed will likely be limited for most drug discovery efforts due to a low signal to noise ratio. The gene trap approach described here has the potential to solve this issue. Beyond establishing proof-of-concept, this study highlighted potential ways to improve the pSABRE-1 vector and its use in isolating traps with high signal-to-noise in the "on" direction. One potential issue is inclusion of all reporter elements including the neomycinresistance gene in the trapping cassette. Since expression of neomycin currently relies on insertion into a gene with a constitutively active promoter, this design has the potential to bias for traps that report in the "off" direction (SB03) or for traps with low signal-to-noise in the "on" direction (SB02 and SB05). The identification of a high signal-to-noise clone like SB01 used here, suggests that the level of neomycin expression required for sufficient drug resistance is relatively low compared to the level of expression required for observable luciferase expression. To increase the efficiency of identification of clones such as SB01 in future studies, we are currently exploring vector designs that separate expression of the neomycin-resistance gene from the rest of the reporter cassette. While the well-defined, highly "druggable" BRAF/MEK/ERK pathway was used here to demonstrate proof of concept for the approach, the technology may be best applied to interrogate transcriptionally active but notoriously difficult to drug targets such as RAS and MYC. RAS and MYC proteins have often been labeled "undruggable" due to the relatively smooth surface structure, devoid of obvious deep pockets, which serve as targets for binding of conventional small drug-like molecules 24 . Approximately one third of all cancers are driven by activating mutations of RAS and nearly 50% of cancers display increased MYC expression 25,26 . Despite decades of research, drugs that safely curb RAS or MYC activity have yet to be discovered. Therefore, we believe that the SABRE platform provides a uniquely elegant opportunity to generate specific reporters for these more challenging oncogenic pathways and thus provide a system that can be used to more efficiently screen small molecule and/or peptide libraries. Generation of SABRE cell lines A375 cells (American Type Culture Collection, Manassas VA, USA) were RADIL tested (IDEXX Laboratories, Westbrook ME, USA) and maintained in Dulbecco's Modified Eagle's Medium (Gibco, Life Technologies, Carlsbad, CA, USA) with 10% FBS and penicillin-streptomycin. The pSABRE-1 vector was purchased from Xactagen, LLC (Shoreline, WA, USA). Lentivirus was generated by transfecting HEK293T cells with pSABRE-1, pMD2.G, and psPAX2 using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA). Lentiviral supernatant with 5ug/ml polybrene was used to infect A375 cells. Infected cells were selected with 1mg/ml Geneticin for up to 10 days. To establish individual cell colonies for screening, cells were plated at low density in 150mm dishes and allowed to grow for two weeks. Colonies were exposed to luciferase substrate en-masse (10ug/ml Coelenterazine, NanoLight Technologies, Pinetop, AZ, USA) and imaged with a Kodak-4000R image station to generate pre-treatment luciferase signals. Plates were treated with inhibitor (10uM vemurafenib or 0.1-10uM trametinib; SelleckChem, Houston, TX, USA) for 6-24 hours prior to

repeating the image-based luciferase assay. Clonal cell lines were established by serial dilution in 96-well plates. Vemurafenib-resistant SB01 cells (SB01-VR) were generated by growing cells in increasing concentrations of vemurafenib (up to 2uM). Gaussia Luciferase Assay Cells were plated (10,000 -20,000 cells/90ul/well) in white 96-well plates. The next day, 10ul of 10× drug solution was added to each well in a 9-point dilution series in triplicate. Lentiviral Integration Site Analysis Lentiviral insertion sites were determined using the Lenti-X Integration Site Analysis Kit and the SMARTer RACE 5′/3′ Kit following the manufacturer's instructions (Clontech, Mountain View, CA, USA). PCR products were sequenced (Genewiz, South Plainfield, NJ, USA) and analyzed using NCBI BLAST 27 . RNA-seq A375 cells were treated for 24 hours with 100nM trametinib or DMSO. RNA-seq libraries were prepared from total RNA using the TruSeq RNA Sample Prep Kit (Illumina, Inc., San Diego, CA, USA) and a Sciclone NGSx Workstation (PerkinElmer, Waltham, MA, USA). Library size distributions were validated using an Agilent 2200 TapeStation (Agilent Technologies). Sequencing was performed using an Illumina HiSeq 2500 employing a paired-end, 50 base read length (PE50) approach. Image analysis and base calling were performed using Illumina's Real Time Analysis v1.18 software, followed by 'demultiplexing' of indexed reads and generation of FASTQ files, using Illumina's bcl2fastq Conversion Software v1.8.4 (http://support.illumina.com/downloads/ bcl2fastq_conversion_software_184.html). Low quality reads were filtered prior to alignment to the reference genome (UCSC hg38 assembly) using TopHat v2.1.0 28 . Counts were generated from TopHat alignments for each gene using the Python package HTSeq v0.6.1 29 . Genes which did not have at least 1 CPM in at least 1 sample were discarded, followed by TMM normalization using the Bioconductor package edgeR v3.12.0. 30 . LogFC and logCPM values were calculated from the normalized results. HTS SABRE reporter assays were conducted in 1536-well white solid bottom plates. 1000 cells/ well were seeded in 4ul Opti-MEM I Reduced Serum Medium without phenol red, using a Multidrop Combi Reagent dispenser and small pin cassette (Thermo Scientific, Fisher Scientific, Fair Lawn, NJ, USA). After overnight incubation, 23nl of compound solution in DMSO was transferred using a Kalypsys pintool. Plates were covered with stainless steel Kalypsys lids and incubated at 37°C for 24 hours. Then 4ul of GLuc Assay Buffer (final concentration 40ug/ml) was added using a Multidrop Combi Reagent dispenser and small pin cassette. Relative luciferase units (RLU) were quantified using ViewLux (PerkinElmer). For library screening, compounds were transferred to columns 5-48, and controls were added in columns 1-4 of the 1536-well plate. Column 1 contained media only; column 2 contained cells with DMSO, while columns 3 and 4 contained a dose response of trametinib (starting at a final concentration of 500nM, with 2-fold dilutions) and a fixed concentration of trametinib at 100nM, respectively. Compounds were tested as dose responses starting at a stock concentration of 10mM (final concentration of 57uM) in DMSO, and diluted 3-fold, also with DMSO. RLUs for each well were normalized to the median RLUs from the DMSO control wells as 0% signal, and median RLUs from 100nM trametinib wells as 100% signal. Dose response data was analyzed as described previously [31][32][33] . Briefly, activity of the compounds from the dose response qHTS screen was determined based on two parameters: i) % activity at the maximum concentration of compound tested (MAXR); and ii) logIC 50 for those compounds with a dose response, as determined by the Curve Response Class (CRC) classification from dose response HTS, in which normalized data is fitted to a 4parameter dose response curve using a custom grid-based algorithm to generate a CRC score for each compound dose response. CRC values of 1.1, 1. We identified the annotated targets for these compounds and computed the enrichment for each target, compared to background, using Fisher's exact test. The background was defined as all targets annotated in the MIPE collection. The P-value was adjusted for multiple hypothesis testing using the Benjamini-Hochberg method. Colony and Cell Proliferation Assays For colony formation assays, cells (1,000/well) were seeded in 6-well plates and allowed to adhere overnight. Bafetinib, trametinib, combinations or 0.5% DMSO was added to the media. Cells were treated for 14 days, with media and drugs replaced after 7 days. Colonies were fixed and stained with 0.5% methylene blue (Sigma-Aldrich) in 50% EtOH. For shortterm proliferation assays, cells (8,000/well) were seeded in 96-well plates and allowed to adhere overnight. Drugs were added to each well and incubated for 72 hours. For long-term cell proliferation assays, cells (60/well) were seeded in 96-well plates and allowed to adhere overnight. Drugs were added to each well and cells were treated for 14 days, with media and drugs replaced after 7 days. Viability was assessed using CellTiter-Glo (Promega, Madison, WI, USA) or PrestoBlue (Invitrogen). In Vivo All animal procedures were approved by the Fred Hutchinson Cancer Research Center Institutional Animal Care and Use Committee. Nu/Nu female mice 4 weeks old were purchased from Envigo (East Millstone, NJ, USA). SB01-VR xenografts were established by subcutaneous injection of 5×10ˆ6 cells into the right flank. Five days after injection, mice were randomized into groups of 10 to obtain groups with similar starting average tumor size. Groups of 10 mice allowed us to observe tumor size differences of 15% or more that are 1.1 standard deviation units with 80% power in a 2-sided test with 0.05 level of significance. Bafetininb, trametinib, combination bafetinib and trametinib, or vehicle (0.5% methylcellulose, 5% DMSO, 0.2% Tween 80) was administered by oral gavage for 21 consecutive days. Bafetinib was dosed at 200mg/kg/d (100mg/kg twice daily); trametinib was dosed at 0.1mg/kg once a day 34,35 . Mice treated with drug combinations were dosed with 100mg/kg bafetinib plus 0.1mg/kg trametinib in the morning and only 100mg/kg bafetinib at night. Control mice were also dosed twice daily. Tumor sizes were assessed three times a week by caliper measurement and volumes calculated from the formula, tumor size (cm3)=(L×Wˆ2×3.14159/6) using Study Advantage Tumor Tracker software (Jenkintown, PA, USA). Supplementary Material Refer to Web version on PubMed Central for supplementary material. Inhibitor of Differentiation 1 (ID1) Facilitates the Efficacy of Sorafenib in Non-Small Cell Lung Cancer Cells through Suppressing Epithelial to Mesenchymal Transition Background Sorafenib, which is a multitargeted kinase inhibitor, has shown some antitumor effects in patients with non-small cell lung cancer (NSCLC). However, the potential target of sorafenib’s antitumor activity is largely unknown. Moreover, definitive predictive biomarkers of benefit have rarely been reported. Material/Methods The alteration in inhibitor of differentiation 1 (ID1) expression in NSCLC cells with sorafenib treatment was detected by western blotting. The sensitivity of NSCLC cells to sorafenib was observed by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium) assay. Loss-of-function and gain-of-function experiments were performed to observe the role of ID1 expression in epithelial to mesenchymal transition (EMT) progression. Results Initially, we observed that ID1 was downregulated in NSCLC cells treated with sorafenib. The response of NSCLC cells to sorafenib was inhibited by the transfection of small interfering RNAs (siRNAs) targeting ID1. In contrast, the transfection of ID1-overexpressing plasmids improved the response of NSCLC cells to sorafenib. Further experiments indicated that ID1 is expressed at high levels in epithelial H460 cells and expressed at low levels in mesenchymal H358 cells. Loss-of-function and gain-of-function experiments suggested that ID1 negatively regulates EMT in NSCLC. Conclusions The expression of ID1 is dose-dependently inhibited by sorafenib, and the overexpression of ID1 contributes to the antitumor activity of sorafenib by suppressing EMT development. Our results indicate that ID1 might be a potential target for the antitumor activity of sorafenib in NSCLC and that targeting ID1 is a feasible strategy to improve the sensitivity of NSCLC cells to sorafenib. Background Worldwide, patients with lung cancer have a high mortality rate [1]. Lung cancer is divided into 2 broad histological classes: small-cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) [2]. Patients with NSCLC are poorly sensitive to traditional chemotherapy drugs [3]. Currently, significant advances in the understanding of NSCLC treatment over the past few years have been achieved. Molecular-targeted agents have been attracting increasing attention in NSCLC therapy because they have shown promising results for improving progression-free survival and overall survival [4]. Epidermal growth factor receptor (EGFR)-targeted therapy is currently approved for lung cancer [5]. Clinical trials have proven that patients with EGFRmutated NSCLC derive substantial benefit from EGFR inhibitors, such as erlotinib [6]. However, many patients with NSCLC do not have this kind of molecular alteration [7]; therefore, the exploration of other drugs as a substitute for EGFR inhibitors in nonresponsive patients is urgently needed. As a multi-target tyrosine kinase inhibitor, sorafenib exerts encouraging antitumor activity in various types of cancers by inhibiting RAS/RAF/ERK pathway-regulated cell proliferation and VEGFR2-involved angiogenesis [8,9]. It has been identified as the standard of chemotherapy for advanced hepatocellular carcinoma [10]. Recently, several clinical trials have been conducted to observe the response of NSCLC patients to sorafenib, and stable disease was observed in 30 of 51 (59%) patients treated with 400 mg of sorafenib twice daily [11]. However, initial treatment with sorafenib is sensitive, and resistance eventually develops. Therefore, identifying effective biomarkers to stratify NSCLC patients who could be responsive to sorafenib and identifying the resistance mechanisms are necessary. Inhibitor of differentiation 1 (ID1), which belongs to the family of helix-loop-helix transcription factors, exerts diverse functions in multiple steps of cancer development, including cell proliferation, invasion and migration. Moreover, it has been demonstrated to be responsible for sorafenib resistance in hepatocellular carcinoma [12]. In NSCLC, ID1 was proven to be upregulated in tumor tissues. Patients with high levels of ID1 expression have a poor prognosis [13]. The expression of ID1 was downregulated by the treatment of paclitaxel and cisplatin through the protein ubiquitination/proteasome degradation system [14]. In this study, we discovered that ID1 expression is inhibited in NSCLC cells with sorafenib treatment, and further studies suggested that epithelial to mesenchymal transition (EMT) is responsible for ID1-regulated sorafenib efficacy in NSCLC. Western blot Cells were lysed in lysis buffer. Proteins (40 µg) were separated on sodium dodecyl sulfate (SDS)-polyacrylamide gel, then transferred electrophoretically onto polyvinylidene difluoride (PVDF) membranes (Millipore, USA). After blocked with 5% non-fat milk in TBST (tris-buffered saline plus Tween 20) at room temperature for 1 hour, the membranes were incubated with primary antibody overnight at 4°C. Then the membranes were washed with TBST and incubated with secondary antibody at room temperature for 45 minutes. The bands were visualized using the enhanced chemiluminescence detection system (Pierce). Real-time quantitative polymerase chain reaction (PCR) Total RNA was extracted using TRIzol (Beijing Solar Biotechnology Co., Ltd.) reagent according to the manufacturer's instructions. The primers used for amplification of human genes were as follow: ID1-F GATTCTCCAGCACGTCATCG, ID1-R ATGATCTAGTGGTCGG ATCTGG; platelet-derived growth factor receptors (PDGFR)-F CCCCCTTTCTGGCCTGATG, PDGFR-R CCACTTTCTTTGCGGGGGTA; EGFR-F AGCAGAGACCCACACTACCA, EGFR-R GTAGTCAGGG TTGTCCAGGC. The PCR array was performed as previously described [15]. Briefly, the reverse transcription products were loaded on a real-time PCR System (Eppendorf International). Relative messenger RNA (mRNA) levels of ID1, PDGFR, and EGFR were calculated based on the Ct values and normalized using GAPDH expression. All experiments were performed in triplicate. MTT assay Changes of cell viability were analyzed using the MTT assay. Briefly, cells were seeded in 96-well plates at a density of 2.5×10 3 cells per well. After attached overnight, cells were e922148-2 incubated with 0.5% dimethyl sulfoxide (DMSO) (vehicle control) or different concentrations of sorafenib for 4 hours or 48 hours. Then, 5 uL of 5 mg/mL of MTT in PBS was added to each well for 3 to 4 hours at 37°C. At last, 100 uL of DMSO was added to each well to dissolve formazan crystals. The absorbance was measured using a microplate reader at a wavelength of 570 nm. Wound healing assay Cells were transfected with pcDNA3-ID1 expressing vector or siRNA for ID1 using Lipofectamine 2000. Empty vector pcDNA3 or negative control siRNA served as a control. After 24 hours of transfection, a micropipette's tip was used to make a scratch, producing a clean would area. Cells were maintained in incubator and photographed at indicated time points under the microscope. Statistical analyses Statistical analyses were done using GraphPadPrism version 6.05. Data are shown as mean±standard deviation (SD). e922148-3 Differences between groups were considered significant when the P-values were £0.05. Results Sorafenib inhibited ID1 expression at both the mRNA and protein levels Initially, we treated H460 cells with different concentrations of sorafenib and observed that

cell survival was reduced by sorafenib in a dose-dependent manner ( Figure 1A). Next, we observed the effect of sorafenib on ID1 expression. In contrast to the modest downregulation of PDGFR and EGFR, ID1 mRNA expression was markedly inhibited ( Figure 1B). This result implies that ID1 might be a target for sorafenib in NSCLC. Western blot analysis confirmed that the expression of ID1 protein was suppressed by sorafenib in a dose-dependent manner ( Figure 1C). Moreover, immunofluorescence staining of ID1 protein was weak when cells were incubated with sorafenib ( Figure 1D). ID1 overexpression enhanced the efficacy of sorafenib in NSCLC The aforementioned data demonstrated that ID1 expression was prevented by sorafenib, and we speculated that ID1 expression has an effect on sorafenib efficacy in NSCLC. To verify this hypothesis, we introduced siRNAs targeting ID1 to downregulate ID1 and pcDNA3-ID1 plasmids to upregulate ID1. Cells in the experimental group and control group were treated with the same concentrations of sorafenib. MTT assays were conducted to observe the response of the cells in the different groups to sorafenib. According to the results shown in Figure 2A and 2B, the survival rate was higher in cells with ID1 knockdown than in the negative control group; in contrast, cells transfected with pcDNA3-ID1 overexpression plasmids were more sensitive to sorafenib ( Figure 2C, 2D). The results indicated that ID1 knockdown inhibited sorafenib efficacy, while the overexpression of ID1 enhanced the efficacy of sorafenib in NSCLC. It has been reported that the degradation of ID1 protein is modulated by the ubiquitin-proteasome system, in which e922148-4 ID1 protein is tagged by certain types of polyubiquitin chains and then selectively recognized and removed by the proteasome [16,17]. We observed that the reduced efficacy of sorafenib with downregulated ID1 protein expression was relieved by MG132, which is the most commonly used agent to inhibit proteasome activity ( Figure 3A). Then, we observed that the application of MG132 abolished the inhibitory effect of ID1 knockdown on sorafenib efficacy, which was evidenced as the cell survival rate was decreased when cells were pretreated with MG132 ( Figure 3B, 3C), demonstrating that the upregulation of ID1 contributed to sorafenib efficacy. ID1 expression was negatively correlated with EMT biomarkers Next, we explored the mechanisms involved in the ID1-induced enhancement of sorafenib efficacy in NSCLC. Accumulating evidence has proven that sorafenib resistance can be affected by EMT development [9]. In this study, we detected the expression levels of ID1 in different NSCLC cells with different morphologies. As shown in Figure 4A, epithelial morphology in H460 cells, mesenchymal morphology in H358 cells, and both epithelial and mesenchymal morphology in A549 cells were observed. The data were in accordance with the western blotting results showing that the expression of the mesenchymal biomarker vimentin was increased, while the expression of the epithelial biomarker E-cadherin was decreased from the level in H460 cells to that in H358 cells. Importantly, we noticed that the ID1 protein had high expression in H460 cells, had moderate expression in A549 cells, and was negative for expression in H358 cells ( Figure 4B), implying that the ID1 expression level was negatively correlated with EMT biomarkers. Immunofluorescence confirmed that the extent of ID1 staining was strong in epithelial H460 cells and low in mesenchymal H358 cells ( Figure 4C). The ID1-EMT pathway was responsible for sorafenib efficacy in NSCLC The aforementioned data suggested that EMT played a crucial role in ID1-involved sorafenib efficacy. Western blot experiments showed that the knockdown of ID1 induced an increase in vimentin and a decrease in E-cadherin, and the opposite result was observed in cells with ID1 overexpression, as vimentin was downregulated and E-cadherin was upregulated ( Figure 5A). To further confirm the role of ID1 in the EMT process, a wound healing assay was conducted to evaluate the effect of ID1 knockdown or overexpression on cell migration. As expected, ID1 knockdown led to a significant improvement in migration ability, while ID1 overexpression led to a significant reduction in migration ability, proving that ID1 knockdown promoted cell migration and that ID1 overexpression suppressed cell migration ( Figure 5B). Discussion The majority of NSCLC patients are diagnosed in advanced stages or with metastatic disease, and most of them are unresectable. For unresectable NSCLC patients, chemotherapy is the standard treatment [18]. EGFR-tyrosine kinase inhibitors (TKIs) have been shown to exert satisfactory survival benefits in clinical trials, and therefore, EGFR-TKIs have been identified as first-line chemotherapy agents to treat NSCLC alone or in combination with cytotoxic drugs [19]. However, only a small percentage of NSCLC patients have tumors carrying an EGFR mutation, a biomarker of oncogene addiction that strongly relates to the response to EGFR-TKIs; therefore, exploring other agents to treat NSCLC patients whose tumors do not have EGFR mutations is necessary. Sorafenib has shown encouraging antitumor function in clinical trials as monotherapy or combined treatment in patients with advanced NSCLC [20][21][22]. Previous cellular and molecular studies have also proven that sorafenib alone suppresses cell proliferation in NSCLC, and when combined with other drugs, the inhibitory effect is increased [23][24][25]. These studies indicate that sorafenib is likely to be a promising candidate for NSCLC treatment. However, definitive predictive biomarkers of benefit have rarely been reported. In this study, NSCLC cells with ID1 knockdown showed less sensitivity to sorafenib, suggesting that ID1 might be a promising biomarker for the application of sorafenib in NSCLC patients. It is well known that sorafenib exerts antitumor effects via VEGFR and PDGFR; however, the changes in these classical targets were modest, indicating that the specific targets for the antitumor activity of sorafenib in NSCLC still need to be elucidated. As a generally negative prognostic factor in many types of cancers, ID1 was paradoxically identified as a potential molecule for enhancing drug efficacy and preventing chemoresistance. NSCLC patients with high ID1 expression showed better disease-free and overall survival after adjuvant paclitaxel and cisplatin chemotherapy [14]. A previous report also revealed that ID1 contributed to sorafenib efficacy by modulating the p16/IL6 axis in hepatocellular carcinoma [12]. In this study, our data demonstrated that ID1 expression was negatively correlated e922148-7 Guillain-Barré Syndrome: A Rare Case Report Introduction: Guillain-Barré syndrome (GBS) is a rare neurodegenerative condition in which the immune system of the body mistakenly damages a portion of the peripheral nerve system. The initial signs are general weakness and numbness in the limbs. Initial symptoms occur within a few days or weeks of infection. These symptoms can spread fast, ultimately paralyzing the entire body. The peripheral system consists of the brain and spinal cord. The nerve network is found outside of the brain and spinal cord. GBS can range from a minor case with short weakness to a completely fatal paralysis that renders the individual unable to breathe on their own. Fortunately, even the most severe instances of GBS may be recovered from. Some people will remain feeble even after they have recovered. The majority of patients reach the peak of their weakness within the first two weeks of symptoms appearing; by the third week, 90 percent of those affected are at their weakest. Symptoms of muscle weakness include difficulty with muscles of the eyes and vision, swallowing difficulties, difficulty in speaking, or chewing, pricking or pins and needles sensations in the hands and feet, pain that can be severe, especially at night, coordination problems, and unsteadiness, abnormal heartbeat/rate or blood pressure, problems with digestion and/or bladder control, and problems with digestion and/or bladder control. Background: Guillain-Barré syndrome can affect anyone. It can attack at any age (though it is more common in adults and the elderly), and both sexes are equally susceptible to the condition. Case Study Dhanvijay and Ankar; JPRI, 33(47A): 263-267, 2021; Article no.JPRI.74193 264 GBS is predicted to afflict one in every 100,000 people each year. GBS affects between 3,000 and 6,000 persons in the United States each year. Case Presentation: A 53 years old male patient came to the hospital with the chief complaint of weakness in all four limbs for 6 days. A patient was apparently alright 6 days back later he was experience weakness in the left side of the body following covid vaccination on 4th June, weakness was gradually progressive in nature and progress to the right side of the body after 2 days. Later on, 8th of June patient got admitted to GMC yavatmal where the routine investigation was done including a CT scan brain which normal and doctors ask for an MRI brain for which the patient and his relative had taken a DAMA discharge and brought the patient to AVBR Hospital. All investigation has been done after that the physician diagnosed the patient having Guillain barre syndrome. The patient weakness has been worse and the treatment start according to the disease condition. Medical treatment including physical therapy also been started to reducing physical weakness and the patient condition is improved day by day. Intervention: The intervention was given to the patient such as injection ceftriaxone 1 gm BD, Inj pan 40 mg OD, Inj Emset 4 mg TDS, Inj optinurone 1 Amp in 100 ml normal saline. INTRODUCTION Guillain-Barré syndrome is a severe illness due to the abrupt and unexpected development of weakness and, in most cases, complete paralysis. Fortunately, 70% of patients having GBS typically recover completely [1]. Individual with respiratory failure generally survives with diligent intensive care and effective treatment of infection, autonomic dysfunction, and other medical problems [1]. Guillain-Barré syndrome is one of the numerous diseases characterized by weakness produced by immune-mediated peripheral nerve injury. While GBS develops quickly over days to weeks and typically cures on its own, other diseases develop gradually and might persist or reoccur [2]. The most frequent form of GBS observed in the United States is Acute inflammatory demyelinating polyneuropathy (AIDP). The immune system response in AIDP destroys the myelin covering and disrupts the nerve signal transmission. The immune response damages the axons in two further forms of Guillain-Barré syndrome, acute motor axonal neuropathy (AMAN) and acute motor-sensory axonal neuropathy (AMSAN) [3]. An auto-immune illness is characterized by the body's immune system attacks and destroying specific groupings of healthy tissue. Myelin sheaths protect nerve axons. Myelin aids in the transmission of signals through these long, thin extensions of nerve cells. In certain situations, GBS affects the axons of myelin sheaths. The injury stops the nerves from delivering the signals to the spinal cord and brain, such as touch sensations. This results in a numbing sensation. Furthermore, the brain and spinal cord could no longer send impulses to the body, which results in muscular weakness [4]. Patient Information A 53 years old male patient came to the hospital with the chief complaint of weakness in all four limbs since 6 days. A patient was apparently alright 6 days back later he was experience weakness in the left side of the body following covid vaccination on 4 th June, weakness was gradually progressive in nature and progress to the right side of the body after 2 days. Later on, 8 th of June patient got admitted to GMC yavatmal where the routine investigation was done including a CT scan brain which normal and doctors ask for an MRI brain for which the patient and his relative had taken a DAMA discharge and brought the patient to our hospital. On the date, 12/06/2021 was admitted to the AVBR Hospital in the department of neurology unit 1. The patient GCS -E4V5M6. The pulse rate is 87 per min regular, normal volume, condition of vessel wall normal. Blood pressure was 130/80 mmHg and Spo2 was 99% and respiration was 20 per min. After a physical examination the treatment was started according to a patient condition like injection ceftriaxone 1 gm BD, Inj pan 40 mg OD, Inj Emset 4 mg TDS, Inj optinurone 1 Amp in 100ml normal saline. Medical treatment including physical therapy also been started to reducing physical weakness and the patient condition is improved day by day. Medical/Surgical History The patient was undergoing medical management. The intervention such as intravenously Injection ceftriaxone 1 gm BD, Inj pan 40 mg OD, Inj Emset 4 mg TDS, Inj optinurone 1 amp in 100 ml normal saline BD. Psychosocial history: He maintains good interpersonal relationships between family members, neighbors, friends, and relatives. Environmental history: The patient surrounding environment is good. There is

a facility of a closed drainage system and proper disposal of waste. In Urine examination urine albumin is nil, urine sugar is nil, and pus cell is 1.2 cell /hpf. In Pharmacological Management Treatments for Guillain-Barré syndrome can help to alleviate symptoms and hasten recovery. The majority of individuals are treated in hospitals and often require hospitalization for a few weeks to several months. Intravenous Immunoglobulin (IVIG) Intravenous immunoglobulin has been the most widely used therapy for Guillain-Barré syndrome (IVIG). IVIG is a therapy produced from healthy antibodies found in donor blood. These are administered to assist in preventing dangerous antibodies from harming the nerves. Plasma Exchange (Plasmapheresis) Plasma exchange, commonly known as plasmapheresis, is utilized instead of IVIG. This involves being attached up to the machine that collects blood from a vein and filtering away the harmful antibodies that target the nerves while returning the blood to the body. The majority of patients require therapy for about 5 days [5]. Nursing Management First of all makes nursing assessment with the help of observation to check the consciousness, weakness, speech, vital sign, the reaction of a pupil, size of a pupil. Improved respiratory function, promotion of physical mobility, prevention of contractures, decreased anxiety and pain, relief of urinary retention, improvement of parental care, and prevention of complications [6]. Ineffective breathing pattern Intervention:  Assess the frequency, symmetry, and depth of the breathing. Observed Increased labor of breathing, as well as skin color, temperature, and pupil dilation.  Observed the indications of respiratory exhaustion, such as shortness of breath, poor attention span, and coughing difficulty.  Listen for changes in lung sounds and notify the doctor right once.  Check the client's arterial blood gases and oxygen saturation levels.  Maintain a 35-45° elevation of the head of the bed. Intervention:  Assess the level of pain and ability to participate in activities.  Administer analgesics based on pain assessment and respiratory status; Monitor side effects after administration.  Apply a moist warm compress to painful areas as needed.  Provide support to extremities and maintain clean, comfortable bed using eggcrate mattress and padding to bony prominences as needed; Reposition client every 2 hours, use good postural alignment, assist the patient with passive range of motion. Impaired physical mobility Intervention:  Assess the motor strength or functional level of mobility.  Monitor nutritional needs as they associate with immobility.  Place the client in a position of comfort. Provide frequent position changes as tolerated.  Administer heparin as ordered.-Low ̶ molecular-weight heparin (LMWH) is administered in the prophylaxis of deep vein thrombosis.  Provide padding to bony prominences such as elbow and heels [7]. Physiotherapy Management Aims of physiotherapy management are: 1. Regain the patient's independence with everyday tasks. 2. Retrain the normal movement patterns. 3. Improve patient's posture. 4. Improve the balance and coordination 5. Maintain clear airways 6. Prevent lung infection 7. Support joint in functional position to minimize damage or deformity 8. Prevention of pressure sores 9. Maintain peripheral circulation 10. Provide psychological support for the patient and relatives. CONCLUSION Guillain-Barre syndrome is commonly seen in the young population. The most common symptom of Guillain-Barre syndrome was ascending paralysis. The hospital mortality rate of patients with GBS was 6.45%. CONSENT While preparing the case report and for publication patient's informed consent has been taken. ETHICAL APPROVAL As per international standard or university standard written ethical approval has been collected and preserved by the author(s). How Does Diet Change with A Diagnosis of Diabetes? Protocol of the 3D Longitudinal Study Diet quality influences glycemic control in people with type 2 diabetes (T2D), impacting their risk of complications. While there are many cross-sectional studies of diet and diabetes, there is little understanding of the extent to which people with T2D change their diet after diagnosis and of the factors that impact those changes. This paper describes the rationale for and design of the 3D longitudinal Study which aims to: (i) describe diet quality changes in the 12 months following T2D diagnosis, (ii) identify the demographic, physical and psychosocial predictors of sustained improvements in diet quality and glycemic control, and (iii) identify associations between glycemic control and diet quality in the 12 months following diagnosis. This cohort study will recruit adults registered with the Australian National Diabetes Services Scheme who have been recently diagnosed with T2D. Participants will be involved in five purposefully developed telephone surveys, conducted at 3 monthly intervals over a 12-month period. Diet quality will be determined using a 24-h dietary recall at each data collection point and the data will be scored using the Dietary Approaches to Stop Hypertension (DASH) diet-quality tool. This study is the first dedicated to observing how people newly diagnosed with T2D change their diet quality over time and the predictors of sustained improvements in diet and glycemic control. Introduction Diet quality plays a vital role in helping people with type 2 diabetes (T2D) to achieve and maintain optimal glycemic control, thereby lowering their risk of developing diabetes-related complications [1]. Diet quality can be described as the extent to which food intake complies with national or international dietary guidelines or a priori diet quality score [2]. Investigating diet quality based on dietary patterns, defined as multiple dietary components operationalized as a single exposure [3], provides valuable information, beyond analyzing specific nutrients (e.g., protein) or food groups (e.g., dairy) [4]. This is because dietary patterns closely reflect actual dietary behavior and have a stronger influence on disease risk than specific nutrients or foods [5]. Findings from dietary pattern analyses may facilitate the translation of useful recommendations to health professionals and the general population [5,6]. A dietary pattern rich in whole-grains, fruits, vegetables, legumes, and nuts; moderate in alcohol; and low in refined grains, red or processed meats, and sugar-sweetened beverages has been shown to improve glycemic control in people with T2D [7]. Consequently, a key feature of international T2D management recommendations is to eat healthy foods that provide a high-quality diet [8][9][10]. However, evidence has shown that people with T2D have low-quality diets, despite these recommendations [10][11][12][13][14][15]. Our recent systematic review identified that internationally, people with T2D do not adhere to food group recommendations outlined in dietary guidelines [15]. Qualitative studies examining lived experiences report that people with T2D find it challenging to adopt and maintain healthy dietary behaviors after diagnosis [13,14]. Our previous qualitative study that investigated the experiences and perceptions of Australian adults newly diagnosed with T2D found that while participants reported making immediate, widespread changes to dietary behaviors that led to improvements in diet quality initially, they found it challenging to maintain dietary change [13]. Participants described feeling restricted in food choice, being uncertain of ideal dietary behaviors and felt unheard and rushed when speaking about their diet with health professionals [13]. Similar results were obtained in a qualitative study in Mexico where people reported making only short-term adherence to improvements in dietary intake due to difficulties with controlling appetite and eating with others [14]. While these qualitative findings of experiences raise concerns, it is important to also investigate quantitative aspects of diet quality change following diagnosis. Cross-sectional research has assessed the diet quality of people with T2D at a single-point in time [15], however, no research has quantitatively explored changes in diet quality after diagnosis. Consequently, there is no evidence as to whether diet quality remains fixed once an individual is diagnosed with T2D, or whether there are periods of marked increases or decreases in diet quality. Prospective, observational studies are valuable as they measure events in temporal sequence and can distinguish causes from effects [16,17]. Many factors influence diet quality. These include non-modifiable factors such as age and sex, and modifiable factors such as self-efficacy, perception of current diet, environmental factors such as marketing and food availability, and relationships with health professionals [11,13]. There is currently no data on the demographic and health characteristics influencing diet quality change for people with T2D [13,18]. There is a clear need to investigate how diet changes over time so targeted strategies can be developed to facilitate improved glycemic control. This paper describes the methodological protocol of the 3D Longitudinal Study, so named because seeing something in three dimensions adds clarity. In this case it refers to the 3D's of Diet, after Diagnosis with Diabetes. The study aims are to: (i) Describe diet quality changes in the 12 months following T2D diagnosis. (ii) Identify the demographic, physical and psychosocial predictors of improvements in diet quality and glycemic control. (iii) Identify associations between glycemic control and diet quality in the 12 months following diagnosis. Theoretical Framework The ability to predict and explain health-related behavior is important for developing strategies to change those behaviors [19]. The theory of planned behavior (TPB) is among the most influential and widely applied theories of the factors influencing health-related behavior [19]. According to the TPB, the single best predictor of a person's behavior is the intention to perform that behavior [20]. This is predicted by three constructs: attitude, subjective norm, and perceived behavioral control (PBC). The greater the PBC and more favorable the attitude and subjective norms, the stronger the intent will be to perform the behavior [20]. According to the TPB, people with T2D will intend to improve their diet quality to the extent that they believe the likely outcomes of consumption to be favorable, perceive social pressure from those who are important to them and feel capable of improving their diet quality without difficulty [21]. The constructs of the TPB are considered strong predictors of healthful eating and are commonly applied in the development of dietary behavior change interventions [21,22]. This study will integrate the TPB into its design in order to explore the factors that may serve as moderators in influencing the TPB constructs, thus affecting dietary behaviors and T2D management. Study Design The 3D Longitudinal Study is a prospective observational cohort study that will be conducted in Australia between 2018-2019. The study will recruit people newly diagnosed with T2D and monitor their dietary intake over 12 months. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for cohort studies was used to guide the development of the research protocol [23]. The 3D Longitudinal Study is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR) (ref: ACTRN12618000375257) and was approved by the Griffith University Human Research Ethics Committee (ref: 2017/951). Study results will be published in peer-reviewed journals and presented at scientific conferences. Potential Participants Eligible participants will be adults aged 18 years or older who have been recently diagnosed with T2D (<6 months prior to recruitment contact), are registered with the Australian National Diabetes Service Scheme (NDSS) and have indicated their willingness to be contacted for research purposes. The NDSS is an initiative of the Australian Government and is administered with the assistance of Diabetes Australia [24]. In 2017, there were approximately 1.1 million people registered with the NDSS [25]. Registration is part of usual care for people diagnosed with T2D, therefore this potential participant pool provides broad representation of the target population. People with T2D are authorized to register for free if they live in Australia or are visiting from a country with which Australia has a Reciprocal Health Care Agreement on an applicable visa [24]. Registering with the NDSS enables individuals to access a range of government approved diabetes-related products and information services [24]. All registrants have the option of consenting to being contacted for research purposes. Upon registration, patients are required to register their personal details on a form signed by a registered Australian medical practitioner, nurse practitioner or a credentialed diabetes educator [24]. The majority of T2D diagnoses in Australia are made by general practitioners (GPs), who are the usual coordinators of management [7]. A detailed participant inclusion and exclusion criteria is listed in Table 1. Participant Recruitment and Screening A convenience sample of all individuals registered with the NDSS with a new diagnosis of T2D over the previous 6-month period will be sent an initial invitation letter and a plain-language summary of the research project via email by Diabetes Australia. Interested individuals will be invited to contact the research team via email or telephone to confirm eligibility, provide informed consent and arrange data collection. Participants will be informed they can withdraw from the study at

any stage. This recruitment method has been trialed in a feasibility study conducted in 2016-2017 (unpublished) which successfully recruited 22 participants from 1000 email invitees. Of these 22, 17 completed baseline data collection, six participants had left the study by 3 months, however all participants remaining at 3 months were retained to 12 months. Data Collection Data will be collected using a purpose-developed, interviewer-administered telephone surveys at five-time points; baseline, and then at 3, 6, 9, and 12 months after commencing the study. Surveys will be conducted by Accredited Practicing Dietitians (APDs). The feasibility study found each survey takes approximately 30 min to complete. A measuring tape will be posted to all participants within two working days of recruitment to provide enough time to measure their waist circumference before data collection begins. Strategies including contact and scheduling methods have been shown to improve cohort retention in longitudinal studies [26]. Participants will be contacted 2 weeks prior to their next anticipated data collection round to schedule a time. All participants will be sent a reminder via their preferred contact method (email or text message) one day prior to the date of their next survey. The recruitment and contact process is outlined in Figure 1. consent and arrange data collection. Participants will be informed they can withdraw from the study at any stage. This recruitment method has been trialed in a feasibility study conducted in 2016-2017 (unpublished) which successfully recruited 22 participants from 1000 email invitees. Of these 22, 17 completed baseline data collection, six participants had left the study by 3 months, however all participants remaining at 3 months were retained to 12 months. Data Collection Data will be collected using a purpose-developed, interviewer-administered telephone surveys at five-time points; baseline, and then at 3, 6, 9, and 12 months after commencing the study. Surveys will be conducted by Accredited Practicing Dietitians (APDs). The feasibility study found each survey takes approximately 30 min to complete. A measuring tape will be posted to all participants within two working days of recruitment to provide enough time to measure their waist circumference before data collection begins. Strategies including contact and scheduling methods have been shown to improve cohort retention in longitudinal studies [26]. Participants will be contacted 2 weeks prior to their next anticipated data collection round to schedule a time. All participants will be sent a reminder via their preferred contact method (email or text message) one day prior to the date of their next survey. The recruitment and contact process is outlined in Figure 1. Survey Design Data from all secondary outcome measures will be recorded in an online survey management system: www.limesurvey.org [27]. Item wording and response options were composed to align with the Australian Bureau of Statistics (ABS) 2016 Census and the Australian Longitudinal Study on Women's Health (ALSWH) to allow for comparison of outcomes [28,29]. Survey questions were generated using a developmental model [30] that employs five stages of questionnaire design and testing: conceptualization, design, testing, revision, and data collection. The feasibility study allowed testing of questions to ensure they were comprehendible, relevant and appropriate to participants Survey Design Data from all secondary outcome measures will be recorded in an online survey management system: www.limesurvey.org [27]. Item wording and response options were composed to align with the Australian Bureau of Statistics (ABS) 2016 Census and the Australian Longitudinal Study on Women's Health (ALSWH) to allow for comparison of outcomes [28,29]. Survey questions were generated using a developmental model [30] that employs five stages of questionnaire design and testing: conceptualization, design, testing, revision, and data collection. The feasibility study allowed testing of questions to ensure they were comprehendible, relevant and appropriate to participants and to confirm the survey length was suitable. Revisions were then made based on the feedback provided. For example, some participants in the feasibility study felt they were being asked the same question twice in the Healthy Eating Belief Scale. Therefore, the interviewer's scripted introduction and description of the Healthy Eating Belief Scale was modified to notify participants that there would be some repetition. The second draft was then pilot tested on three adults outside of the research team to ensure comprehensibility, suitability and flow. Table 2 provides an overview of the primary (diet quality) and secondary outcomes and when they will be collected. Diet quality can be measured by a variety of purpose developed tools [31]. These are constructed by assigning higher scores within sub-scales based on more frequent or higher intakes of foods, nutrients or both [31]. Dietary Approaches to Stop Hypertension (DASH) is a dietary pattern high in whole-grains, fruits, and vegetables; moderate in low-fat dairy; and low in red and processed meats, added sugars, and sodium [32]. While originally developed to assist people in the prevention and management of hypertension, DASH is now recommended for the dietary management of T2D [18,33]. Adherence to DASH positively impacts on glycemic control, weight, and hypertension, which are key indicators of risk for diabetes-related complications [5,18,32]. A randomized controlled trial (RCT) conducted in adults with T2D showed that adherence to DASH improved glycated hemoglobin (HbA1c) (−1.2%), fasting blood glucose (−0.92 mmol/L), weight (−3 kg) and waist circumference (−4.8 cm) over 8 weeks when compared with a control diet [34,35]. Those following the DASH dietary pattern, also had a greater reduction in LDL cholesterol (difference from the control diet, −7.7 ± 3.3%). Outcome Measures A systematic review and meta-analysis of 20 RCTs found DASH significantly reduced systolic (−5·2 mmHg) and diastolic blood pressure (−2·6 mmHg) in adults with and without diabetes [36]. Another systematic review and meta-analysis of 13 RCTs revealed that adults without T2D who adhered to DASH achieved greater weight loss (−1.42 kg), reduced Body Mass Index (BMI) (−0.42 kg/m 2 ) and decreased waist circumference (−1.05 cm) compared with controls [37]. Considering the recognized impact on glycemic control, weight and hypertension, DASH was chosen as the dietary pattern used to assess diet quality in the present study. Participant DASH scores will be calculated using the DASH diet-quality tool which has been shown to have the highest correlation with health outcomes related to T2D compared to other tools that measure diet quality [38,39]. Change in DASH score from baseline to 3 months will be used to categorize participants as diet quality improvers or diet quality maintainers. Participants will be split into 2 groups; those who improved their DASH score by at least 3 DASH points (Diet quality improvers) and those who maintained their DASH score within 2.99 points or decreased their DASH score by at least 3 points (Diet quality maintainers). A change in DASH score of 3 points was selected based on findings from previous literature [40]. In a 20-year longitudinal study of over 40,000 adults, an average DASH score of 23.8 out of 40 was observed, and a change in score of approximately 3 points or more was sufficient to significantly influence long-term glycemic control [40]. Dietary intake data will be obtained through the Australian version of the Automated Self-Administered 24-h Dietary Assessment Tool (ASA-24). The ASA-24 is based on the validated Automated Multiple-Pass Method (AMPM) which is considered the optimal method for obtaining 24-h recall data due to its numerous probes, standardization of interviewer administration and validation against recovery biomarkers [41,42]. This method is also consistent with the methodology of the most recent population nutrition survey in Australia (the National Nutrition Survey) and has been shown to be a valid measure of dietary behavior at a given time point [43,44]. The ASA-24 is an online automated questionnaire that guides the individual through a system designed to maximize respondents' opportunities for remembering and reporting foods eaten in the previous 24 h [45]. The questionnaire is divided into five phases in line with published methodological guidelines; 'quick list', 'forgotten foods', 'time and occasion', 'detail cycle', and 'final probe' [45]. These phases encourage respondents to think about their intake in different ways and from several perspectives which has been shown to reduce bias in the estimation of dietary intake [45]. Once a specific food or beverage is reported, systematic questions are asked to capture more precise information about the food, cooking methods and quantity consumed. The ASA-24, usually a self-completed tool, will be adapted for use in a telephone survey; a researcher will ask the questions and enter the data. This will reduce participant burden and help decrease any bias associated with participant information technology literacy levels. This process was carried out successfully in a feasibility study with patients newly diagnosed with T2D. The data from the feasibility study was able to be used to assess changes in diet quality over a 12-month period. Following data collection, participant 24-h dietary recall data will be sent from the ASA-24 program to the research team. This data will then be manually entered into FoodWorks by an experienced dietitian to allow determination of participant DASH scores. FoodWorks is a dietary analysis software program using standardized serve sizes that allows for quantification of specific food groups (e.g., vegetables) and nutrients (e.g., sodium) obtained from reported dietary intakes, recipes and meals [46]. FoodWorks draws on the national AUSNUT database [47]. AUSNUT was developed by Food Standards Australia and New Zealand and includes complete nutrient data sets of Australian foods designed specifically for nutrition surveys and is therefore suitable for use in this project [47]. DASH scores will be calculated using the standard scoring tool created by Fung et al [39]. Every tenth DASH score will be cross-checked by a second member of the research team to ensure accuracy. The standard scoring tool determines a score between 8 and 40 points, with 40 points representing optimal accordance with the DASH dietary pattern [39]. The DASH score is calculated by summing the number of daily servings of seven dietary components; fruits, vegetables, nuts and legumes, whole-grains, low-fat dairy, red and processed meats, added sugar, and sodium intake. For each of the components, participants are classified according to their intake ranking. Higher intakes of fruits, vegetables, low-fat dairy, whole-grains, and nuts and legumes receive higher scores. For example, quintile 1 is assigned 1 point and quintile 5 is assigned 5 points. Intake of sodium, red and processed meats and added sugars are scored in reverse as these are less desirable foods [39]. The lowest quintile is given a score of 5 points and the highest quintile is given a score of 1 point. The components scores are then summed to give an overall DASH score [39]. The scoring criteria for the DASH-style diet is outlined in Table 3. Secondary Outcome Measures Secondary outcome measures will include: glycemic control, medication use, demographic factors, physical factors, psychosocial factors, and exposure to health provider support. Glycemic Control HbA1c reflects average plasma glucose over the previous six to eight-week period [48,49]. In Australia, it is best practice for GPs to conduct HbA1c testing on people with T2D every 3 months [8]. The test is subsidized by Medicare, the Australian Government's universal health scheme, up to four times in a 12-month period [50]. The GP on the research team will retrospectively obtain participants' HbA1c results over the 12-month study period from the relevant pathology laboratory. Other blood results collected will include; fasting blood glucose, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and C-reactive protein. Medication Use Information on all medication use (name of medication and dosage) will be collected, including over-the-counter, and complementary medicines. Demographic Factors Demographic factors collected at baseline including; age, gender, highest education level, living arrangement, self-selected social class, household income, ability to manage on income, and smoking status. Response options will be dichotomous (e.g., gender), continuous (e.g., age) or categorical (e.g., highest educational level), consistent with categories used in the national consensus by the ABS. Age and Gender Participants' age at last birthday and gender will be collected. Sex response options will include three categories in line with the ABS 2016 Census; male, female and other [51]. Highest Education Level Collecting data on highest educational level helps generate a single measure of an individual's overall educational attainment, whether it be a school or non-school qualification [51]. Participants will be asked to report their highest education level from eight categories in line with the ABS 2016 Census; postgraduate degree, graduate diploma and graduate certificate, bachelor degree, advanced diploma, diploma, certificate, year 12, or year 11 and

below [51]. Living Arrangement Data on participants' current living arrangement will be collected. In line with the ALSWH, response options will include; no one, partner/spouse, own children, someone else's children, parents, or other adults [29]. Self-Selected Social Class Requesting information on self-selected social class allows class designation to be meaningful to participants and is more likely to reflect their actual class identity [52]. Participants will be asked to self-select their social class from one of four response options in line with the ALWHS; 'upper class', 'middle class', 'working class', or 'don't know' [52]. Household Income and Ability to Manage on Income Gross income refers to the sum of income received from all sources before any deductions (income tax, the Medicare Levy or salary sacrificed amounts) are taken out [51]. Participants will be asked to report their average yearly gross household income from six response options in line with the ALSWH; less than $20,000, $20,001-$30,000, $30,001-$50,000, $50,001-$100,000, more than $100,000 or 'don't know/would rather not say'. Details on participants' ability to manage on their current income will also be collected. Seven response options in line with the ALSWH will include; 'impossible', 'difficult', 'always difficult', 'sometimes difficult', 'not too bad', 'easy', or 'not sure' [53]. Smoking Status Participants will be asked to report their smoking status. Wording of the question has been developed to correspond with the ABS 2016 Census and response categories will include 'yes' or 'no' [51]. Physical Factors Self-reported anthropometric data is valid and recommended for monitoring prevalence of obesity, particularly for large-scale studies because of its simplicity and low cost [54][55][56]. Physical factors will include; self-reported waist circumference, weight, and height. All response options will be continuous. Waist Circumference Waist circumference is a better indicator of central obesity than BMI or waist-to-hip ratio and is more strongly correlated with intra-abdominal fat content and cardiovascular risk factors [57]. Participants will be asked to self-report their waist circumference to the nearest centimeter. Participants will be asked to report results of two measures at each round of data collection, which will be averaged during data analysis. Measuring instructions adapted from the ALSWH will be provided to participants in the postal envelope [58]. Instructions will request participants to measure mid-central adiposity using the tape to measure at the level of the mid-point between the lower costal border and the iliac crest [58]. Weight Weight will be self-reported at each data collection point to the nearest decimal point. If the participant can only report the amount in stones and pounds, a conversion factor of 2.203 will be used to convert pounds into kilograms in line with the ALSWH [52]. Participants will be asked to describe where and how their weight was measured to assess the accuracy of the information. Height Height will be self-reported to the nearest centimeter at baseline only. If the participant can only report the information in feet or inches, a factor of 2.54 will be used to convert inches to centimeters in line with the ALSWH [52]. Physical Activity Regular physical activity is a key feature of international T2D management guidelines [9,60]. This is because it has been shown to improve glycemic control (regardless of whether weight loss has occurred), lipid levels, and blood pressure in people with T2D [61][62][63]. Participants' physical activity levels will be measured through the IPAQ-SF which is one of the most widely used physical activity assessment questionnaires and has been shown to be a valid measure of obtaining internationally comparable physical activity data [64,65]. It measures self-reported physical activity in the previous seven days and includes seven items that collect information on walking time, moderate and vigorous physical activity time and sitting time [66]. Data obtained in the IPAQ-SF will be used to estimate total metabolic equivalent (MET)-minutes per week for each participant [67]. Psychosocial Factors Healthful Eating Beliefs Healthy eating beliefs will be investigated at each of the five data collection points to better understand their beliefs, attitudes and intentions towards making positive dietary behaviors and how these impact on diet quality change over time. Participants' healthy eating beliefs will be assessed through the Healthful Eating Beliefs Scale. This scale is based on the TPB [68]. Standardized questions have been selected from previous Healthful Eating Beliefs Scales to suit the current study. Table 4 provides an outline of the rationale for investigation behind the questions and modes of responses. Participant scores will be generated for each of the seven subscales of the Healthful Eating Beliefs Scale by calculating the mean of the 5-point Likert scale items, with higher scores representing more positive beliefs, attitudes, and intentions towards improving dietary behaviors. Mental Health Mental health data will be collected at baseline, 6 and 12 months using the internationally validated K10 questionnaire [69]. This 10-item questionnaire yields a global measure of distress based on questions about anxiety and depressive symptoms experienced in the most recent four-week period [70]. It is scored using a five-level response scale based on the frequency of symptoms reported for each question. One is the minimum score for each item (none of the time) and five is the maximum score (all of the time). The maximum score is 50 indicating severe distress, the minimum score is 10 indicating no distress [70]. To better understand healthy eating beliefs among participants and determine if they change over time. Behavioral intention "I intend to eat a healthful diet each day in the next 2 months," 5-pt Likert "I will try to eat a healthful diet each day in the next 2 months," 5-pt Likert "I plan to eat a healthful diet each day in the next 2 months," 5-pt Likert [68] Perceived behavioral control "I have the self-discipline to eat a healthful diet" 5-pt Likert "I have the ability to eat a healthful diet" 5-pt Likert "Me eating a healthful diet would be easy/difficult" 5-pt Likert "Whether I do or do not follow the recommendations for my diet is entirely up to me" 5-pt Likert [71] Subjective norm "People important to me think I should not/I should eat a healthful diet" 5-pt Likert "Other people expect me to follow the daily recommendations for diet" 5-pt Likert "People important to me want me to eat a healthful diet" 5-pt Likert "Other people with diabetes follow the daily recommendations for diet" 5-pt Likert [71,72] Attitudes towards self-care "Following the recommendations for my diet would be harmful/beneficial" 5-pt Likert "It would be worthless/valuable for me to follow the daily recommendations for my diet" 5-pt Likert "Following daily recommendations for diet is unnecessary/necessary" 5-pt Likert Following daily recommendations for diet is unpleasant/pleasant" 5-pt Likert [72] Exposure to GP and Allied Healthcare Support Interactions with health professionals may help facilitate positive changes in dietary behaviors [73]. At each data collection point, participants will be asked about their concurrent and previous exposure to healthcare provider support (e.g., dietitian, diabetes educator). Participants will also be asked to report how useful they found the advice on a 5-point Likert scale (1 being 'not at all useful', 2 being 'slightly useful', 3 being 'neutral', 4 being 'somewhat useful' and 5 being 'extremely useful'). Question wording has been modified from previously conducted qualitative research that explored the experiences of dietary change in people with T2D [13]. Participant Confidentiality All study related information will be de-identified and stored securely online with password-protected access systems. Daily back-ups of all electronic data will occur to minimize any risk of lost data. Only members of the research team who need to contact study patients, enter data or perform data quality control will have access to participant information. Statistical Modeling and Sample Size The longitudinal aspect of diet quality change will be analyzed using regression models [74]. Diet quality at 12 months (measured by the DASH score) will be the primary outcome, with glycemic control, interim diet changes (primarily at 3 months), medication use, demographic measures, physical measures, psychosocial measures, and exposure to healthcare provider support as the explanatory variables. This model will determine the relative importance of diet quality change both immediately after diagnosis and in the medium term with regards to a 12-month outcome towards sustained healthy eating. Sample size calculations, such as those provided in Diggle et al. [74] are not readily computed for complex regression models and assessment using simulation studies would be more appropriate [75]. However, due to the relatively small participation rate in the feasibility study (22 participants/1000 invited) credible model parameters are currently unable to be formulated, and the effect differences over time cannot be reliably inferred. Additionally, current research of diet quality change post diabetes is lacking [15], therefore effects cannot be competently elicited. As a result, rather than determining an initial sample size for the study, a Bayesian updating procedure will be used to collect data. In this manner, sample size will be calculated during the early stages of data collection to yield an idea of how many samples should be collected. Additionally, using a Bayesian framework, the parameter estimates of the mixed model will be sequentially updated as batches of data are obtained, a process known as Bayesian learning [76,77]. Discussion The study described in this paper, the 3D Longitudinal Study, will be the first to observe changes in diet quality in people with T2D after diagnosis and the factors (demographic, physical, and psychosocial) that influence those changes. Longitudinal studies help highlight differences or changes in the values of one or more variables between different time periods, describe participants' intra-individual and inter-individual changes over time and monitor the magnitude and patterns of those changes [78]. This is important for the proposed research because it is necessary to understand the extent to which people change their diet after a T2D diagnosis and why some people are able to sustain these changes over time and others are not. Understanding this will help to develop targeted strategies and facilitate enhanced dietary behavior support important to assist all people with T2D to have long-term success in improving their diet quality and help reduce the risk of complications. The results of this study will significantly add to the body of literature on the diet quality changes of people diagnosed with T2D, which is an under-researched area. Limitations of the 3D Longitudinal Study are acknowledged. Recruitment through the NDSS is the most suitable way to access a large number of potential participants with T2D, however selection bias cannot be excluded as registration is voluntary, so participants may have greater diabetes self-management motivation. Self-reported dietary intake data and physical measurements may introduce misreporting bias and social desirability responses. Measurement errors associated with dietary assessment methods are also acknowledged. However, use of the ASA-24 h dietary recall (Australian version) which is a validated tool specifically designed for the Australian population, reduces risk of bias [43]. A feasibility study for this project has already determined that its recruitment capability, data collection and analysis procedures are achievable and appropriate. Author Contributions: E.B., L.B., H.M. and L.T.W. identified the research question. All authors developed the research protocol. All authors have been involved in drafting the manuscript and revising it critically for intellectual content. All authors read and approved the final manuscript. Funding: This research received no external funding. Conflicts of Interest: The authors declare no conflict of interest. Bilevel Positive Airway Pressure Ventilation for Improving Respiratory Reproducibility in Radiation Oncology: A Pilot Study Background Strategies for managing respiratory motion, specifically motion-encompassing methods, in radiation therapy typically assume reproducible breathing. In reality, respiratory motion variations occur and ultimately cause tumor motion variations, which can result in differences between the planned and delivered dose distributions. Therefore, breathing guidance techniques have been investigated to improve respiratory reproducibility. To our knowledge, bilevel positive airway pressure (BIPAP) ventilation assistance has not been previously investigated as a technique for improving respiratory reproducibility and is the focus of this work. Methods and Materials Ten patients undergoing radiation therapy treatment for cancers affected by respiratory motion (eg, lung and esophagus) participated in sessions in which their breathing was recorded during their course of treatment; these sessions occurred either before or after radiation treatments. Both unassisted free-breathing (FB) and BIPAP ventilation-assisted respiratory volume data were collected from each patient using spirometry. Patients used 2 different BIPAP ventilators (fixed BIPAP and flexible BIPAP), each configured to deliver the same volume of air per breath (ie, tidal volume). The

flexible BIPAP ventilator permitted patient triggering (ie, it permitted patients to initiate each breath), and the fixed BIPAP did not. Intrasession and intersession metrics quantifying tidal volume variations were calculated and compared between the specific breathing platforms (FB or BIPAP). In addition, patient tolerance of both BIPAP ventilators was qualitatively assessed through verbal feedback. Results Both BIPAP ventilators were tolerated by patients, although the fixed BIPAP was not as well tolerated as the flexible BIPAP. Both BIPAP ventilators showed significant reductions (P < .05) in intrasession tidal volume variation compared with FB. However, only the fixed BIPAP significantly reduced the intersession tidal volume variation compared with FB. Conclusions Based on the established correlation between tidal volume and tumor motion, any reduction of the tidal volume variation could result in reduced tumor motion variation. Fixed BIPAP ventilation was found to be tolerated by patients and was shown to significantly reduce intrasession and intersession tidal volume variations compared with FB. Therefore, future investigation into the potential of fixed BIPAP ventilation is warranted to define the possible clinical benefits. Introduction Respiratory motion affects all tumor sites in the thorax and abdomen and can introduce localization uncertainties that can negatively affect the image acquisition, treatment planning, and radiation delivery of a patient's radiation treatment. To reduce the effect of respiratory variations in radiation therapy, motion management strategies have been developed, such as those described in the American Association of Physicists in Medicine Task Group 76 (AAPM TG-76) report on respiratory motion management. 1 Strategies using free-breathing (eg, motion-encompassing methods) generally assume patients will reproduce the same respiratory pattern during image acquisition and each subsequent radiation delivery treatment. In reality, patients' natural freebreathing patterns can vary from breath to breath (intrafraction) and day to day (interfraction). [2][3][4] Both intrafraction and interfraction variations in the respiratory pattern cause tumor motion variations, which can result in differences between the planned and delivered dose distributions. 1 Thus, breathing feedback and guidance techniques -ranging from simple audio buzzers to interactive guiding interfaces of the respiration signal-have been developed to improve patients' respiratory reproducibility (ie, reduce respiratory pattern variations) with the goal of improving image quality and the accuracy of radiation delivery. 2,5 To this end, continuous positive airway pressure (CPAP) ventilation has recently been investigated as a potential respiratory motion management technique in radiation therapy. CPAP ventilation is a form of noninvasive ventilation that delivers a constant stream of pressurized air to the upper airways and lungs throughout the respiratory cycle. Typically used to treat respiratory complications such as obstructive sleep apnea, acute respiratory failure, and chronic obstructive pulmonary disease, CPAP ventilation increases the baseline lung volume and has been shown to reduce total pulmonary power during inspiration (ie, making it easier for patients to breathe) compared with unassisted free-breathing. 6,7 As for its potential as a respiratory motion management technique in radiation therapy, Goldstein et al found that CPAP ventilation increased total lung volume, reduced tumor motion, and reduced lung and heart dose compared with free-breathing for a cohort of 10 patients being treated with stereotactic body radiation therapy. 8 Although Di Perri et al also observed that CPAP ventilation increased lung volume, they found it had negligible effect on tumor motion and led to a small decrease in lung dose for 20 patients undergoing stereotactic ablative radiation therapy. 9 Anecdotally, CPAP ventilation has been shown to reduce the heart and lung dose in patients with respiratory complications, namely deep inspiration breath holds. [10][11][12] Although these results are mixed, they are generally encouraging for using CPAP ventilation as a technique to reduce tumor motion and dose to healthy tissues. However, the mechanism for these reductions is incidental to the imposed increase in total lung volume rather than direct control over the respiratory cycle. Therefore, the ability to consistently and robustly improve patients' respiratory reproducibility may not be accomplished with CPAP ventilation alone. Bilevel positive airway pressure (BIPAP) ventilation is another noninvasive ventilation technique that delivers alternating high and low pressures during inhalation and exhalation phases of the breathing cycle, as opposed to CPAP ventilation's single, constant pressure. Although BIPAP ventilation and CPAP ventilation are used for similar respiratory complications, the difference in positive pressures during inhalation and exhalation using BIPAP ventilation provides assistance during patients' breathing efforts, compared with both free-breathing and CPAP ventilation. 13 Most commercially available BIPAP ventilators offer volume-targeted modes, which aim to assist patients' breathing efforts by delivering the same tidal volume (ie, the volume of air inhaled and exhaled) with each breath. Based on the demonstrated strong positive correlation between tidal volume and tumor motion, improving patients' respiratory reproducibility could ultimately improve tumor motion reproducibility. 14 Given that most breathing guidance techniques, including CPAP, do not assist or augment patients' breathing to achieve consistent (ie, reproducible) tidal volume respiratory patterns, exploring the utility of BIPAP ventilation in radiation therapy is a logical progression. BIPAP ventilation assistance is designed to assist the user's breathing and can be configured to deliver the same volume of air with each breath (eg, volume-targeted modes), which may result in advantages when using respiratory-induced tumor motion management methods such as motion-encompassing, as discussed in the AAPM TG-76 report. To our knowledge, BIPAP ventilation has not been investigated as a technique to improve respiratory reproducibility in patients receiving radiation therapy. We hypothesized that BIPAP ventilation would reduce both intrafractional and interfractional variations in tidal volume compared with freebreathing. Therefore, the purpose of this work was to investigate the feasibility of using BIPAP ventilation in radiation oncology by (1) assessing whether patients with cancer can tolerate BIPAP ventilation assistance and (2) evaluating if BIPAP ventilation assistance improves respiratory reproducibility in terms of consistency in tidal volume and breathing period. The results of this pilot study are important for determining whether future studies are warranted in exploring BIPAP ventilation's potential for improving targeting accuracy, treatment plan quality, and delivery accuracy of radiation therapy. Methods and Materials We obtained institutional review board approval to collect breathing data from patients with cancer who were undergoing radiation therapy. Daily breathing sessions, which were independent from treatments, occurred in an open examination room either before or after patient treatments, depending on the patients' schedules, and involved breathing with and without BIPAP ventilation. Candidates for study enrollment were adult patients who met the following criteria: they had disease sites affected by respiratory motion; they were to be treated with normal breathing as prescribed by a physician because BIPAP ventilation is intended to assist normal breathing treatments; they were able to tolerate a nasal ventilation mask and breathe through their nose; and they were amenable to coaching for their breathing. Written informed consent was obtained for all participants meeting these criteria on their initial imaging simulation day. We used 2 different commercially available BIPAP ventilators in this study: the Philips Respironics V60 BIPAP ventilator (Philips Respironics California, LLC, Carlsbad, California) and the Lifecare Personal Lightweight Ventilator (PLV) 100 BIPAP (Respironics, Inc, Murrysville, Pennsylvania), referred to here as BIPAP 1 and BIPAP 2, respectively. BIPAP 1 is a microprocessorcontrolled, pneumatic blower ventilator equipped with a volume-targeted mode called the average volume-assured pressure support mode, which aims to maintain a target tidal volume during each breath by monitoring previous tidal volumes and continuously adjusting the delivered pressures. Patient triggering is permitted by BIPAP 1, allowing patients to initiate (ie, trigger) each breath and to also control their tidal volume (ie, how much air is inhaled and exhaled with each breath). BIPAP 2 is a microprocessor-controlled, piston-driven ventilator with a volume-targeted mode called the control mode. The control mode delivers all breaths at a preset tidal volume and breathing period, therefore prohibiting patient triggering. Ten patients were enrolled in this study and were fitted with a nasal ventilation mask and bacteria filter. The mean participant age was 58 years (range, 34-75 years) (Table 1). A smoking history was obtained from all patients, which ranged from an unknown number of pack-years to 90 pack-years (1 pack-year = 7300 cigarettes). All patients participated in sessions on more than 50% of their treatment days. Not all patients had the same number of sessions, because patients were prescribed different numbers of radiation treatment fractions. Patients were also permitted to skip sessions on treatment days when they were not feeling well, running late, or had other appointments (eg, undertreatment physician visits, chemotherapy, etc). Patients participated in sessions lasting approximately 10 minutes each, during which breathing data for each platform (free-breathing [FB], BIPAP 1, and BIPAP 2) was collected for 2 minutes-approximating the beam-on time of a typical volumetric modulated arc therapy (VMAT) beam. Patients wore their specific nasal ventilation mask and were then immobilized using the same devices used for their radiation treatments. FB data were always collected at the beginning of each session. After the completion of the FB data collection, patients were connected to either BIPAP 1 or BIPAP 2, with the order alternating with each session to mitigate any potential bias. Patient-specific BIPAP ventilator settings (eg, tidal volumes and breathing periods) were determined using verbal patient feedback during the first session and were used for subsequent sessions. After the FB data collection during the first session, patients were given an overview of the BIPAP ventilators and their functionality. Patients were then connected to a ventilator and instructed to breathe normally. Patient-specific ventilator settings were tuned using verbal feedback until each patient was comfortable with the ventilator settings of the given BIPAP. This selection of ventilator settings lasted approximately 5 to 10 minutes before BIPAP breathing data were collected. This process was then repeated for the remaining BIPAP ventilator. During subsequent sessions, after the FB data collection was complete, patients had a short warm-up period (10-90 seconds) using the BIPAP ventilator before the BIPAP data collection began. Spirometry was used to measure respiratory-volume data. A mass flow sensor was coupled to the nasal mask and used to measure FB and BIPAP 2 breathing data. Patients were also visually monitored during sessions to ensure their mouth remained closed and all breathing was only through the nasal mask. Because BIPAP 1 continuously adjusted the delivered pressures (ie, the delivered baseline volume was not constant), the mass flow sensor could not be used to measure the respiratory-volume data. Instead, breathing data for BIPAP 1 were extracted using in-house signal processing software. The anterior abdominal surface was also monitored using an in-house abdominal surface marker system designed to provide consistent measurements of breathing-pattern periods across the FB, BIPAP 1, and BIPAP 2 breathing platforms. Patients were provided visual feedback of their realtime volume waveform when using BIPAP 1 because it permitted patient triggering, although they were not required to actively watch this feedback. A projector, which displayed the real-time volume waveform from the device's display screen, was mounted to the patient couch and aimed at the ceiling directly above the patient's head. A dotted line at the target tidal volume level was superimposed on the volume waveform to help guide the patients, as shown in Figure 1. Because BIPAP 2 did not permit patient triggering, visual cues timed to inhalation and exhalation were provided when using BIPAP 2, although patients were not required to actively watch them. An in-house visual cue stand, which contained a green "inhale" light-emitting diode (LED) and a red "exhale" LED, was clamped to the couch and hung above the patient's head, as shown in Figure 2. Electronic timing from BIPAP 2 was used to synchronize the inhale and exhale LEDs with the air volume output of the ventilator. Patients were instructed to inhale when the green LED was illuminated and to exhale when the red LED was illuminated. A sample of the breathing data collected during a patient's session, specifically the tidal volumes and abdominal surface marker peak-to-peak periods, is shown in Figure 3. For each session, the coefficient of variation (CV) was calculated from the mean and standard deviation of the tidal volumes measured with each platform (FB, BIPAP 1, or BIPAP 2). Intrasession variation was defined as the mean of the CVs of all sessions for each platform. In addition, for each session, the mean tidal volume was normalized to the first session's tidal volume mean. Intersession variation was defined as the standard deviation of the relative session means for each platform. This analysis was repeated for the abdominal

peak-topeak periods for each platform. Intrasession and intersession variations were calculated for each patient. Results of the tidal volume and abdominal surface marker peakto-peak period variations for all patients were compared between platforms (FB vs BIPAP 1, FB vs BIPAP 2, and BIPAP 1 vs BIPAP 2). In addition, patient tolerance of BIPAP ventilation was qualitatively assessed by verbal feedback, and the mean data collection times were calculated and compared. Statistical significance was determined for each comparison using the nonparametric Wilcoxon signed rank test, with the significance level set at .05. Figures 4 and 5, respectively. The mean and standard deviation of the intrasession tidal volumes and abdominal surface marker periods are shown for all patients in Table 2. A summary of the intrasession and intersession variation results is shown in The mean intrasession tidal volume variations of all patients were 0.172 for FB, 0.118 for BIPAP 1, and 0.096 for BIPAP 2. The intrasession tidal volume variation of both BIPAP 1 (P = .02) and BIPAP 2 (P = .007) was significantly lower than that of FB. BIPAP 2 showed significantly lower intrasession tidal volume variation compared with BIPAP 1 (P = .047). The mean intersession tidal volume variations of all patients were 0.169 for FB, 0.126 for BIPAP 1, and 0.113 for BIPAP 2. Only the intersession tidal volume variations of BIPAP 2 were significantly different compared with those of FB. There also was no significant difference in intersession tidal volume variation between BIPAP 1 and BIPAP 2. The mean intrasession abdominal surface marker period variations of all patients were 0.140 for FB, 0.086 for BIPAP 1, and 0.055 for BIPAP 2. Intrasession abdominal surface marker period variations of both BIPAP 1 (P = .02) and BIPAP 2 (P = .005) were significantly lower than those of FB. The intrasession abdominal surface marker period variation of BIPAP 2 was significantly lower than that of BIPAP 1 (P = .007). The mean intersession abdominal surface marker period variations of all patients were 0.155 for FB, 0.136 for BIPAP 1, and 0.046 for BIPAP 2. There was no significant difference in intersession abdominal surface marker period variation between BIPAP 1 and FB, whereas BIPAP 2 showed significantly lower intersession abdominal surface marker period variations compared with FB (P = .007). In addition, the intersession abdominal surface marker period variation of BIPAP 2 was significantly lower than that of BIPAP 1 (P = .005). BIPAP 1 was well tolerated, and none of the patients mentioned any discomfort. The mean (SD) BIPAP 1 data collection time among all patients (first abdominal surface marker peak time to last abdominal surface marker peak time, 110.5 [6.8] seconds) was not significantly different than for FB (112.0 [5.0] seconds). On the other hand, BIPAP 2 was not as well tolerated. Four patients reported difficulty using BIPAP 2, especially breathing at the fixed period, and mentioned that it felt restrictive or that their breaths were "cut off." The mean (SD) BIPAP 2 data collection time of all patients (75.8 [24.3] seconds) was significantly less than for FB (112.0 [5.0] seconds) (P = .005). Discussion To our knowledge, this is the first study to evaluate the feasibility of using BIPAP ventilation to help patients undergoing radiation therapy improve their respiratory reproducibility. We hypothesized that compared with free-breathing, using BIPAP ventilation would result in reduced tidal volume variation both breath to breath (intrasession) and day to day (intersession). BIPAP ventilation was tolerated well by patients and significantly reduced both intrasession and intersession mean tidal volume variations, as well as breathing-period variations, compared with unassisted free-breathing. Based on the established positive correlation between respiratory volume (ie, tidal volume) and tumor motion, 14 we assumed tidal volume was an acceptable surrogate for tumor motion. We also used an abdominal surface marker to provide a monitoring system that was consistent across both the FB and BIPAP data collection platforms. The abdominal surface marker periods were used to provide temporal information about the respiration pattern. Patients' FB tidal volume respiratory patterns had both intrasession and intersession variations. Dosimetrically, breath-to-breath and day-to-day tumor motion variations could result in decreased tumor coverage and, consequently, increased dose to surrounding normal tissues. Tumor motion variations can be accounted for by using larger treatment margins to ensure complete coverage of the prescription dose 1,15 ; however, owing to normal-tissue tolerances, this approach may not be applicable in hypofractionated treatment regimens such as stereotactic body radiation therapy techniques. Given these potentially catastrophic consequences of tumor motion variations, reducing respiratory tidal volume variations is crucial. In this study, BIPAP ventilation significantly reduced intrasession tidal volume variations. This finding may warrant future studies into how these reductions translate to improvements both in targeting accuracy via increased image quality and in radiation treatment delivery. However, it is possible to estimate reductions in tumor motion variation with the results of the present study by assuming a mean tumor motion, as reported by Hoisak et al, of 2.5 cm and a one-to-one correlation between tidal volume and tumor motion. 1,14 This suggests that a tidal volume CV of 0.09, the median CV found for BIPAP 2, results in 2.3 mm of tumor motion variation (ie, standard deviation). Similarly, a tidal volume CV of 0.16, the median CV found for FB, results in 4 mm of tumor motion variation. This approximately 2mm improvement in tumor motion reproducibility using BIPAP ventilation could lead to more reproducible motion during radiation delivery or even a reduction of the margins added when using the motion-encompassing methods, which currently are 2 to 5 mm. This study's results also showed that BIPAP ventilation significantly reduced intersession tidal volume variations. In other words, patients using BIPAP ventilation reproduced their first-session tidal volumes significantly better during subsequent sessions, compared with free-breathing. The effect of reduced interfraction tidal volume variation on tumor motion variation still needs to be investigated in an imaging and dosimetric study. Analogous to this study's observations of tidal volume respiratory patterns, patients' FB abdominal surface marker periods showed both intrasession and intersession variations. We found that BIPAP ventilation assistance significantly reduced both intrasession and intersession variations in abdominal surface marker periods compared with FB. Neicu et al suggested that a reproducible abdominal surface marker period is required to predict tumor position and synchronize the radiation field with the tumor motion. 16,17 The significant reductions in intrasession and intersession abdominal surface marker period variations with BIPAP ventilation assistance could lead to improvements in tumor position predictions or in respiratory gating techniques in which reproducible tumor motion periods are desirable. This study had limitations beyond using a small sample size of 10 patients. Although all patients had sessions on more than 50% of their treatment days, they were permitted to skip sessions when they were not feeling well, were running late, or had other appointments. Subsequently, the overall effecy of using ventilation assistance was not fully investigated, which would have required having sessions on all treatment days. Also, 7 patients had mean BIPAP 2 data collection times shorter than 90 seconds. This was likely a consequence of BIPAP 2's control mode that prevents patient-triggering; most patients were unable to use BIPAP 2 for sustained periods before having to open their mouth to "catch their breath." This led to shorter data collection times for these patients, because BIPAP 2 data collection during the initial session -which determined the length of subsequent sessionswas terminated if patients either had to open their mouth to catch their breath or if they notified the investigator that they could not use BIPAP 2 any longer. Among the patients who had difficulty using BIPAP 2 for more than 2 minutes, there was a range in age, smoking history, and overall comfort in using the device. In addition, although breathing data were collected during 2-minute intervals to simulate the beam-on time of a typical VMAT arc, typical treatment sessions can last up to and beyond 30 minutes owing to patient setup, imaging, and multiple beams. Based on feedback from patients in this study and the data-collection-time results for BIPAP 2, requiring patients to use BIPAP ventilation assistance without patient triggering throughout the entire treatment session is most likely not feasible without additional considerations. Since this study was conducted, a relief valve has been inserted into the BIPAP patient circuit to enable free breathing during times when BIPAP use is not required (eg, between patient setup and daily imaging). Anecdotally, users of BIPAP 2 with the relief valve inserted have expressed an easier time using the device. The results of this study, which suggest that both intrasession and intersession patient respiratory reproducibility may be improved using BIPAP ventilation, warrant further investigation into the possible clinical benefits of this respiratory management technique in radiation oncology. The primary advantage of BIPAP ventilation compared with other patient monitoring systems such as surface-guided radiation therapy systems, which typically use a passive patient monitoring and positioning system, is that BIPAP ventilation is an active system that assists the patient's breathing directly to achieve consistent or reproducible tidal volume respiratory patterns. Also, in this study, BIPAP ventilation required less than 1.5 minutes of patient warmup time, after the initial use and selection of patient-specific ventilator settings, to achieve more reproducible respiratory patterns compared with free-breathing. This warmup time is comparable to established CPAP ventilation systems. Further investigations are needed to evaluate the effect of using BIPAP ventilation on tumor motion variations. In this study, BIPAP 2 yielded the largest significant reductions in tidal volume and abdominal surface marker period variations; however, it was not as well tolerated for 2 minutes as BIPAP 1. We attribute this to a reduced warm-up time compared with that in a study by Goldstein et al 8 and to the delivery characteristics of BIPAP 2-specifically, not permitting patient triggering. Because tidal volume is strongly correlated with tumor motion, a clinical imaging and dosimetric investigation is needed to assess the reduction in tumor motion variations using BIPAP ventilation. This would help elucidate the clinical benefits of using BIPAP ventilation assistance during radiation treatments. Despite the challenges of using BIPAP 2 for some patients, we recommend performing the clinical imaging and dosimetric investigation using BIPAP 2, with a relief valve inserted, based on its superior results for tidal volume and abdominal surface marker period variation compared with free-breathing and BIPAP 1. Conclusions Because modern strategies for managing respiratory motion in radiation therapy, specifically motion-encompassing methods discussed by AAPM TG-76, assume reproducible breathing, any variations in observed respiratory pattern magnitude and frequency can result in a suboptimal delivery of the prescribed dose. To improve patient respiratory reproducibility of patients undergoing radiation therapy, this study evaluated the use of BIPAP ventilation with 2 commercially available ventilators with different types of delivery settings. Compared with unassisted free-breathing, BIPAP ventilation was found to be tolerable and to significantly reduce variations in tidal volume and the period of an external surface marker. To our knowledge, this pilot study was the first to investigate and confirm the feasibility of BIPAP ventilation as a respiratory management technique in radiation therapy. Future work is warranted to further define the potential clinical advantages of using BIPAP ventilation to improve respiratory reproducibility, especially for institutions without existing motion management or surfaceguided radiation therapy systems. OUTDOOR WORK AND SOLAR RADIATION EXPOSURE: EVALUATION METHOD FOR EPIDEMIOLOGICAL STUDIES PRACA NA WOLNYM POWIETRZU A NARAŻENIE NA PROMIENIOWANIE SŁONECZNE – METODA OCENY DO STOSOWANIA W BADANIACH EPIDEMIOLOGICZNYCH Background: The health risk related to an excessive exposure to solar radiation (SR) is well known. The Sun represents the main exposure source for all the frequency bands of optical radiation, that is the part of the electromagnetic spectrum ranging between 100 nm and 1 mm, including infrared (IR), ultraviolet (UV) and visible radiation. According to recent studies, outdoor workers have a relevant exposure to SR but few studies available in scientific literature have attempted to retrace a detailed history of individual exposure. Material and Methods: We propose a new method for the evaluation of SR cumulative exposure both during work and leisure time, integrating subjective and objective data. The former is collected by means of an interviewer administrated questionnaire. The latter is available through the Internet databases for many geographical regions and through individual exposure measurements. The data is integrated into a mathematical algorithm, in order to obtain an

esteem of the individual total amount of SR the subjects have been exposed to during their lives. Results: The questionnaire has been tested for 58 voluntary subjects. Environmental exposure data through online databases has been collected for 3 different places in Italy in 2012. Individual exposure by electronic UV dosimeter has been measured in 6 fishermen. A mathematical algorithm integrating subjective and objective data has been elaborated. Conclusions: The method proposed may be used in epidemiological studies to evaluate specific correlations with biological effects of SR and to weigh the role of the personal and environmental factors that may increase or reduce SR exposure. Med Pr 2016;67(5):577–587 INTRODUCTION The interaction of solar radiation (SR) with biological tissues may induce several effects, some of which with positive consequences for human health (e.g., SR promotes vitamin D metabolism, preventing rickets and osteoporosis), but the most of that is adverse health impact [1]. The Sun represents the main exposure source for all the frequency bands of optical radiation, that is the part of the electromagnetic spectrum ranging between 100 nm and 1 mm, including infrared (IR), ultraviolet (UV) and visible radiation. It should be noted that the SR that reaches the Earth's surface has a spectral composition significantly different from that emitted by the Sun. This is due primarily to an atmospheric absorption of ultraviolet radiation (UVR) by various gaseous components, in particular the ozone, which blocks all wavelengths of less than 290 nm, and so all the UVC and a significant part of the UVB. Due to the filtering effect performed by the atmosphere, the SR to the Earth's surface is composed largely of frequencies within the IR and the visible radiation which constitute respectively the 45% and about the 50% of the SR, and only for the 5% of UVR. Although it covers only a minimal part of the spectrum reaching the Earth's surface, the UVR represents the major risk for human health because it is able to induce the most severe biological effects. Thus, SR may be responsible for acute and chronic adverse effects particularly to the skin and the eyes. It has to be noted that both UV radiation and SR have been classified by the International Agency for Research on Cancer (IARC) as human carcinogens, group I [1][2][3][4]. The quality and quantity of SR that reaches the Earth's surface varies with the elevation angle of the Sun above the horizon, so the exposure may change depending from the time of the day, the day of the year, ruption of exposure during the central hours of the day, when the SR is more intense. These aspects may be important to reduce SR exposure, both during working and leisure activities, especially during summer vacation's periods [9,10]. Finally, one of the most important factor that influences skin exposure to SR is individual characteristics. People with fair photo-types, such as Fitzpatrick's photo-types I and II, are more sensitive to the UV damage [11], and this factor is relevant also among outdoor workers [12]. As previously mentioned, solar ultraviolet radiation may cause several acute and chronic effects, mainly ocular and cutaneous, but also immunological and various others. According to a recent World Health Organization (WHO) review, acute ocular effects with a strong evidence of causality include photokeratitis, photoconjunctivitis and solar retinopathy; chronic diseases include pterygium, cortical cataract and epithelial cancers of the cornea and conjunctiva. Regarding the skin, acute effects with strong evidence of causality include sunburns and photodermatoses; chronic effects include photoaging and solar keratoses, and skin cancers: basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and malignant melanoma (MM). The only immune effect due to SR exposure with a strong evidence of causality in the WHO's review is the reactivation of latent herpes labialis infections [1]. Several studies show that outdoor workers have an increased risk of developing SR related diseases [1,[3][4][5][6] but the vast majority of the studies assess the individual sun exposure through subjective questionnaires or referring to environmental factors like the UV index of the place of usual activity or using biological parameters that estimate the UV damage or with a retrospective classification of the jobs as outdoor or indoor. Only few studies adopted quantitative or detailed semiquantitative tools to assess quantitative exposure [3][4][5][6]. On the contrary, there are many studies that provide an objective evaluation of acute SR exposure in a shortperiod of time using individual UV dosimeters [13][14][15][16][17][18][19][20][21]. Few examples of large-scale quantitative and semiquantitative monitoring of UV exposure for a long period of time were that of Germany [22], the United States [23] and Australia [24]. In the German project carried out by the Federal Institute for Occupational Safety and Health (Bundesanstalt für Arbeitsschutz und Arbeitsmedizin -BAuA), various outdoor occupations were monitored with personal UV dosimeters along the year on week days, at weekends and during holidays, considering 19 specific body parts [22]. In the American study an integration of objective and subjective data was performed by Rosenthal et al. [23], developing a model of ocular and facial skin exposure to UVB combining interviews on previous relevant outdoor work and leisure activities, use of protective equipment and laboratory measurements of UV radiant exposure in watermen. Similarly in Australia, Mc-Carty et al. [24] developed a simplified model for quantifying lifetime ocular UVB exposure considering the ambient UVB levels, the duration of outdoor exposure, the proportion of ambient UVB reaching the eye and the use of ocular protection. These studies are relevant to understand how individual and environmental factors may modify SR exposure, influencing the induction of long-term adverse effects. Objective Considering these premises, the aim of our work is to present a new method for a comprehensive evaluation of individual and environmental SR exposure, useful for an application in epidemiological studies. The assessment of cumulative SR exposure has to take into account all the relevant factors and characteristics influencing the exposure, adopting a final algorithm which integrates subjective and objective data, both related to occupation and leisure-time. An adequate esteem of the amount of solar UV radiation received by specific target organs in a period of several years should be useful to correlate chronic SR-related adverse effectsand their specific characteristics -with the cumulative working and leisure SR exposure. Collection of subjective SR exposure data To collect subjective data a new interviewer administrated questionnaire was developed, based on the individual and environmental factors influencing SR exposure considered by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) [5][6]. The items of the questionnaire, that assesses exposure modes during work and leisure activities (Table 1), have been elaborated by the authors, a team of occupational physicians and experts in optical radiation and industrial hygiene. The study was conducted in accordance with all national regulations and with principles of the Declaration of Helsinki. Complete information regarding the study was given, and subjects were informed that participation was voluntary, and that they were free to withdraw from the study at any time. Writ-ten informed consent was collected. Nobody refused to participate or withdrew during the study. A pilot administration of the questionnaire was performed by one of the authors (A. Modenese) in a sample of voluntary subjects afferent to an Italian dermatologic clinic for previously diagnosed solar-related skin lesions or for suspected lesions, from January 2014 to August 2015. The following excluding criteria were applied: an inadequate ability to understand the Italian language, an age < 40 years old and length of employment shorter than 10 years. The questionnaire takes 15-40 min and the administration was performed while patients were waiting for their turn to undergo the dermatologic examination. The questionnaire is composed of 3 sections. To answer the questions of each section, the respondent has to consider only the months of the year between March and October (except for vacations on the snow), when the exposure to SR is more intense. At the beginning of each section, the interviewer has to define the period of life, in number of years, the section refers to. In each section, the 12 items investigate the type of outdoor activity, the total time people spend outside during the activity and main personal habits that may influence SR exposure. The habits are investigated by means of a 5-point Likert type frequency scale, which ranges from 0, meaning "never adopted this habit during the activity" to 5 "always adopted this habit during the activity." The administrator has to fill in a new copy of a section -henceforth "tab" -if a change in the exposure habits is detected. Regarding the work exposure section, a new tab is administered in the following circumstances: n job change (e.g., for 10 years of employment in agriculture, then in the construction sector), n workplace change, when it is supposed that there is a significant change in the SR exposure (e.g., different UV index), n work tasks change (for the same job, we may have different tasks with different position adopted during work, different number of hours in the sunlight and different protective equipment). The second section of the questionnaire investigates leisure outdoor activities and new tabs have to be administered when there is: n residence change, when it is supposed that there is a significant change in the SR exposure (e.g., different UV index), n change in the number of days per week the activity is done by the respondent (normally 2 days per week for working people), n leisure activity change (e.g., a new outdoor activity, such as a new hobby or outdoor sport), n protective habits change (e.g., the respondent states that he has started to use sunglasses, a hat, sunscreen protections, etc.). The third section of the questionnaire investigates leisure outdoor activities during vacation periods and if the vacation is spent on the snow the respondents have to also consider the winter months. New tabs have to be administered in the following cases: n vacation place change, when it is supposed that there is a significant change in the SR exposure (e.g., different UV index) and when there is a change regarding the presence of reflecting surfaces, such as water or snow, n change in the number of days of vacation per year, n protective habits change (e.g., the respondent states that he has started to use sunglasses, a hat, sunscreen protection, etc.). Collection of objective environmental SR exposure data Meteorological climate data of the areas indicated in the questionnaire in the period of interest has to be considered and integrated in the method to assess SR exposure. We used data collected by the satellites of the European Space Agency, findable on the Tropospheric Emission Monitoring Internet Service (TEMIS) website. The first data available in TEMIS database is the UV index, valid for clear-sky conditions, that is an artificial quantity, derived from the UV irradiance at the ground level weighted by the International Commission on Illumination (Commission Internationale de l'Éclairage -CIE) action spectrum for the susceptibility of the caucasian skin to solar erythema. Clear sky UV index in TEMIS database has been available since November 1978 for many countries all over the world. Another more specific data available from TEMIS is the UV dose, derived from satellite observations, from sunrise to sunset, with a time step of 10 min. The UV dose takes into account the presence of clouds and estimates the daily amount of UV radiation absorbed by the human skin, expressed in kJ/m 2 . Ultraviolet dose in TEMIS database has been available since 1995 for many countries all over the world. Regarding the Italian environmental data, we reported in this paper the TEMIS UV doses referred to the year 2012 of Lampedusa, Rome and Venice, despite no subjects in our sample came from these 3 places. We chose these regions because they are continuously monitored by the European Space Agency for measuring the average daily environmental UV dose on a horizontal plan in cloudiness conditions and they may represent the typical theoretical environmental exposure of a person living and/or working and/or spending holidays respectively in the South of, Center of, and North Italy. Collection of objective individual SR exposure data To take into account individual factors (posture, adoption of protective habits, characteristics of the workplace, etc.), we have performed "on field" measures of personal SR exposure in outdoor workers. Following the experience of a relevant Italian regional project on the prevention of UV

exposure for outdoor workers, in which the research sector of the National Institute for Insurance against Accidents at Work (INAIL) collaborated [25], 2 INAIL experts in optical radiation and industrial hygiene (A. Militello and M. Borra) collected measures of effective radiant exposure (H eff ) in a group of fishermen working on 3 fishing boats, different for dimension and protective equipment, sailing in the Italian Mediterranean sea in a region included between latitudes 41-43'N. The measurements were performed with polysulfone and electronic dosimeters positioned on the back, on the arm (to represent eye exposure according to Coroneo [26], too), on the chest and on the cap's peak of the fishermen as well as on the boat and on the wharf to measure the environmental exposure. Subjective evaluation We collected a total of 58 questionnaires in voluntary subjects aged 43-91 years old (mean age (M) = 70.8 ± standard deviation (SD) = 11 years), 81% male. With regards to occupation, 57% of the patients reported an outdoor activity as the main profession in their life, performed for an average of 31.3 years per person. No significant differences were observed between outdoor workers (OW) and indoor workers (IW) for the main socio-demographic and anamnestic characteristics investigated: age, sex, smoke habits, alcohol consumption, diabetes. The most frequent outdoor jobs were those in agriculture -20.7% of the subjects, and the construction sector -13.8%. Subjects reported to work outside for 4.4 h/day on average, between 9 a.m. and 5 p.m., 1.2 h between 11 a.m. and 3 p.m. Only 24% of the sample reported to often stay in the shades while they were working outside and 27% reported to often work next to reflecting surfaces. Outdoor workers did not refer to any adequate use of protective equipment to repair themselves from sunlight during the occupational activities ( Table 2): 15.2% of OW never wore protective clothing, 90% never used sunscreens at work, 39% never wore a brimmed hat, 60.6% never used protective sunglasses. Regarding leisure time, not considering vacations, the subjects reported outdoor activities for 3.7 h on average between 9 a.m. -5 p.m., 0.8 h between 11 a.m. -3 p.m. Eleven percent of the subjects reported to some-times/often use tanning beds during their leisure time. Fifty-seven percent reported to perform an outdoor sport, for about 4.7 h per week on average and 18.4% reported to never/seldom stay in the shades during their outdoor leisure time. The Table 3 shows the individual protective habits reported by the subjects during their leisure time: 57.1% of the subjects wore only seldom adequately protective clothing, 60.7% never used sunscreens during their leisure time, 48.2% never wore a brimmed hat and 30.4% never used protective sunglasses. With regard to vacation periods in summer season, the subjects reported to spend on average 19.6 days/ year in vacation, staying outside on average for 5.1 h between 9 a.m. -5 p.m., and 1.4 h between 11 a.m. -3 p.m. Only 9.4% of the subjects reported to usually spend vacations in tropical or equatorial places. During the time outdoor, subjects reported to be close to reflecting water surfaces for 2.2 h on average. The 38.5% of the subjects reported often/always sunburns during their vacation periods, although the 54.3% reported to stay often in the shades. The Table 4 shows the individual protective Objective evaluation Environmental exposure data In the Figure 1 we report the average daily UV dose registered during the year 2012 in three different places in Italy, representing the typical exposure respectively of Southern, Central and Northern Italy: Lampedusa -35°30'N, Rome -41°53'N, and Venice -45°26'N. We found the most elevated exposure during June and July, with a daily UV erythemal dose ranging between 4.2 kJ/m 2 in Venice to 5.1 kJ/m 2 in Lampedusa. The lowest environmental exposure was found in January and December in Venice, with an average UV erythemal dose of 0.2 kJ/m 2 . Individual exposure data The results of the on-field measures of effective radiant exposure in a small group of 6 fishermen are showed in the Table 5. The highest exposure to solar UVR has been measured for the nose, ear and the upper part of the fishermen's shoulders with the electronic dosimeter placed on the cap's peak of the outdoor workers, reaching an effective radiant energy of 0.9 kJ/m 2 . The lowest measure of 0.04 kJ/m 2 was collected on the third boat (for further details on the measurements performed and on the characteristics of the fishermen, see also the paper published by 2 of the authors [27]). I II III IV V VI VII VIII IX X XI XII DISCUSSION The solar radiation exposure is a significant risk factor for the development of both acute and long term skin and eye diseases such as sunburns, photokeratitis, photoaging, actinic keratosis, pterygium, cataract, basal and squamous cell carcinomas and malignant melanoma. However, to date there are still some limitations in the current scientific knowledge, in particular regarding the association between specific characteristics of these diseases (histopathology, localizations, age of onset, etc.) and the cumulative occupational and non-occupational SR exposure. In addition, we still have not an adequate knowledge about the effectiveness of protective devices in preventing SR related diseases. Regarding protective habits, the pilot administration of the questionnaire developed for our research has shown a scanty adoption of protections in outdoor workers, in accordance with a previous Italian study conducted in a group of outdoor workers from Tuscany Region [25] where authors found that the clothing worn by workers was often inadequate as compared to the high level of exposure to UV. As regards to environmental SR exposure in Italy, the collection of environmental data through the online database of the European Space Agency showed a much higher daily UV exposure at the Earth's surface as compared to the limit of 30 J/m 2 -effective radiant exposure (H eff ) -set in the European Directive 2006/25/EC for non-coherent artificial optical radiation with a wavelength of 180-400 nm (UVA, UVB and UVC) [7]. The average daily UV erythemal dose in all the months of 2012 was higher than 30 J/m 2 in all the three places considered, one in the North (Venice), one in the South (Lampedusa island) and one in the center of Italy (Rome), also in the Winter months. According to another Italian study conducted in Tuscany, in Spring workers received the 53-87% of the total amount of environmental SR on the back, and about 30-60% on the arms. During summer, outdoor workers received the 36-77% of ambient exposure on the back and 19-43% on the arms [19], respectively. The exposure of the external arm is relevant because, according to the "Coroneo's effect," it represents the exposure of the external part of the face and of the eye and it is important to evaluate the UVR dose coming from the side (oblique light) [26]. The environmental data collected also showed that the weight of the UV exposure during November, December, January and February was negligible as compared to the March-October period, supporting the choice of not considering the period November-February in the interviewer-administrated questionnaire, focusing only on the period March-October, that is the most relevant in determining the cumulative SR exposure. Winter months are considered in the questionnaire only in the case of winter vacations on the snow, that last at least 1 week per year. By means of the pilot administration of the questionnaire in a group of voluntary subjects and on-field measurements in a small group of fishermen, we have collected data suggesting a high SR exposure for outdoor workers, and in particular farmers, construction and maritime workers. However, during the measurement campaign in the fishermen group, performed according to a preventive purpose [25,27], we could not be able to interview the workers with our ad hoc questionnaire: this factor is a relevant limitation for the current development of our methodology because at present we can't associate the questionnaire's answers to specific individual measurements. Despite this limit, the occupational exposures suggested by our questionnaire or measured in the group of fishermen are in accordance with recent studies that have shown an exposure in terms of Standard Erythemal Dose (SED) of 9.9 SED in Australia [13], 11.9-28.6 SED in Switzerland [14], 6.11 SED in Spain [15] for the construction sector. It has to be noted that 1 SED is equivalent to an effective radiant exposure of 100 J/m 2 [2]. Regarding farmers, high exposure to SR has been reported in New Zeland [16], Australia [17], Austria [18], and also in Italy [19], where it has been collected to measure effective radiant exposure of 1870 J/m 2 in April. With regard to maritime workers, a Spanish study has measured a personal exposure of 1143 J/m 2 [20], higher than the maximum effective radiant exposure of 900 J/m 2 that we measured with a dosimeter placed on the top of the head of a fisherman working on a small boat with inadequate protective equipment (artisan fishery). Maritime workers have been investigated also in an Australian study and their exposure ranging from 1.7 to 6.9 SED [21]. In all the above cited studies researchers measured an acute exposure to SR by means of personal dosimeters on a single day or few days. In order to retrace the history of chronic exposure to SR in groups of outdoor workers, considering also leisure activities, we developed an algorithm that allows us to integrate subjective data from the questionnaire with objective climate data, to obtain an exposure index that esteems the cumulative SR exposure of a specific tissue. The equation 1 is an estimate of the average annual effective UV dose to a specific tissue (Eh) and it takes into account: the fraction of time (xi) the tissue (i) is actually exposed to SR; the average exposure ratio (yi) of the effective irradiance measured on the tissue is compared with the effective irradiance measured on the horizontal plane; the monthly coefficient (ei) multiplied by the average annual effective radiant exposure on a horizontal plane for the specific locality (Ea) to obtain the average monthly effective radiant exposure on a horizontal plane; the coefficient (ma) which takes into account the use of protective equipment (hats, sunglasses, sunscreen, etc.); the coefficient (na) which takes into account the presence of environmental factors that influence the exposure (canopies, awnings, vegetation, etc.). (1) For the determination of the coefficient (ma) which takes into account the use of protective equipment we use specific coefficients adapted from the previously discussed models of Rosenthal et al. and McCarty et al. [23,24]. For example, for a habitual use (according to the questionnaire answers "often" or "always" adopted) of normal clothing we have a coefficient of 0.2, for no use we have a value of 1. Regarding sunscreens, we have a coefficient of 0.3 for a regular use, 1 for no use. Regarding hat, we may have a large brimmed hat with a coefficient of 0.3 in the case of habitual use both for the neck and the forehead (and cheek, ear lobe, lower lip, underside chin), and a coefficient of 0.8 for the neck and 0.5 for the forehead and the other face and head regions in the case of habitual use of a large brimmed hat. In the case of use of sunglasses, we use coefficients for eye exposure: 0.99 if the protective equipment is never used, 0.78 if it is used seldom, 0.48 if it is used sometimes, 0.34 if it is often used and 0.13 if it is always used [23,24]. For the coefficient (na) in our algorithm, which takes into account the presence of environmental factors influencing the exposure, we use a "Sky View Factor," which is the fraction of the sky visible from a given observation point on the ground, taking into account the obstacles, natural or artificial, covering a variable part of the sky view, and we use also the specific Albedo coefficients for different surfaces to evaluate the reflecting phenomena [5], making an approximation based on the Likert scale of the questionnaire's answers (never = 0% of the period, seldom < 20%, sometimes < 40%, often = 60%, always = 100%). Finally, regarding the posture, which was a major factor influencing back and chest exposure in our group of fishermen (if the worker bends down he or she shades

his chest while at the same time he or she increases the exposure on the back), in order to determine the ratios of exposure in various parts of the human body during the execution of outdoor tasks, further on-field measurements of individual exposure are needed. These measurements are useful to calculate the reduction or multiplication coefficients of the SR that reaches specific parts of the body: our aim is to carry out several on-field measurements to characterize the type of exposure for various outdoor activities. The effect of working posture in influencing SR exposure is also confirmed in a recent Swiss study on construction workers [14], in the case of which the authors have found that posture and orientation accounted for at least 38% of the total variance of relative individual exposure, accounting for more than the altitude on the total variance of effective daily exposures. In our algorithm, we use a coefficient related to the Anatomical Eh (tissue) = xi × yi × ei × Ea × ma × na ∑ 12 i = 1 Region (AR) and it is the ratio between the irradiance on the horizontal plane and the irradiance on a given anatomical region. We consider the irradiance ratio for standing position at 45° of solar elevation angle, with different coefficients weighted on azimuth angle and posture prevalence [28,29]. CONCLUSIONS Solar radiation exposure perpetrated for several years is typical of outdoor work and for an advancement in the knowledge of the epidemiology of SR related disease in the case of workers, a comprehensive evaluation of cumulative exposure is needed. We elaborated a new method to esteem the total lifelong individual exposure to SR and this tool could be useful to adequately evaluate the SR reaching specific target organs, like skin and eyes, taking into account both subjective and objective indicators of individual and environmental exposure as well as considering the influence of leisure activities. A Systematic Review of a Polyvagal Perspective on Embodied Contemplative Practices as Promoters of Cardiorespiratory Coupling and Traumatic Stress Recovery for PTSD and OCD: Research Methodologies and State of the Art Baseline respiratory sinus arrhythmia (RSA) has been proposed as a transdiagnostic biomarker of stress vulnerability across psychopathologies, and a reliable association between PTSD, OCD and lower resting RSA was found. Contemplative practices have been linked to the activation of the vagus as well as to an increased RSA that, according to the polyvagal theory, reflects the activation of the ventral vagal complex (VVC) and may promote PTSD and OCD recovery. PubMed and Scopus databases were selected to conduct a search following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) 2020 guidelines, and A MeaSurement Tool to Assess systematic Reviews-2 (AMSTAR-2) was used to appraise the methodological quality for this systematic review. Six articles met the inclusion criteria (one cross-sectional study, one study with pre-post measurements, two cohort studies and two RCT studies). Mindfulness-related interventions promoted parasympathetic activity, an increased vagal tone and improvements in PTSD and OCD symptoms. According to the polyvagal theory, mindfulness-related and compassion-related meditations would be conceptualized as neural exercises expanding the capacity of the ventral vagal complex to regulate the present state and to promote resilience. Clinical and methodological issues are discussed. Rationale The polyvagal theory [1][2][3] proposes an evolutionary and neurophysiological framework that deals with the organization of autonomic systems and has been linked to functional gastrointestinal disorders and chronic diffuse pain [4] and to psychosocial pathology [5], both connected to chronic traumatic stress during development. Considering the evidence derived from neurophysiology, behavioral observations and comparative anatomy, the polyvagal theory proposes the existence of two separate vagal pathways belonging to the parasympathetic nervous system that give rise to the emergence of a dorsal vagal complex (DVC) and a ventral vagal complex (VVC). In accordance with the polyvagal theory [1,2], the function and the structural organization of the autonomic nervous system of the human being are embedded in its phylogenetic origin through a hierarchical organization. The social engagement system (SES) originates from the myelinated VVC, whose fibers are cardioinhibitory and stem from the brainstem, in particular in the nucleus ambiguus (NA). The VVC is a threat-response system that tends to preserve homeostasis, is the most recent at the phylogenetic level and tends to act rapidly (considering its myelinated fibers). The sympathetic nervous system (SNS) is less recent than the VVC; its activation favors the frequency increase in heart rate, respiration, and mobilization for active threat responses such as escape or fight defense. The dorsal vagal complex (DVC) shows unmyelinated cardioinhibitory fibers that are rooted in the dorsal motor nucleus of the vagus (DMNX) of the brainstem. Phylogenetically, it is the less recent of the autonomic subsystems and presents a vestigial immobilization function that emerged in early vertebrates. Threat reactions and homeostasis are related to the DVC, which innervates organs below the diaphragm as well. The DVC is also responsible for the disruption of digestive mechanisms and the preservation of metabolic energies when it is recruited during reactions to threats [1,2]. Remarkably, the DVC represents the system that is mainly recruited in traumatic responses after psychological trauma [4,5]. The polyvagal theory proposes that the integration of the myelinated cardiac vagal pathways with the neural regulation of the head and face favored the advent of the SES of mammalians. The outputs of the SES include motor pathways that control striated muscles of the head and face (i.e., somatomotor) and cardiac and smooth muscles of the bronchi and heart (i.e., visceromotor). The somatomotor portion includes special visceral efferent pathways that controls the striated muscles of the head and face. The visceromotor portion includes the myelinated supradiaphragmatic vagal pathway that controls the bronchi and heart. At the functional level, the SES arises from a face-heart connection that harmonizes the heart with the muscles of the head and face. The inceptive function of the system is to orchestrate swallowing, sucking, vocalizing and breathing. A disruption of the SES during early phases of life is an index of later problems in social skills and emotional homeostasis. The neural detection of environmental risk establishes the preferential activation of the SES, or the subsequent hierarchical progressive recruitment of the SNS or the DVC. In accordance with the polyvagal theory, neuroception is a neural process different from perception that controls the neural detection of risk and does not need a conscious awareness. In addition, neuroception is carried out through a neural reflexive process that is able to immediately shift physiological state and to distinguish visceral and environmental characteristics that are safe, dangerous, or life-threatening. When environments are safe, a neuroception of safety favors the SES, and the SNS activation is adaptively dampened to preserve the central nervous system that is highly oxygen-dependent, in particular the cortex, from the activities of the DVC (e.g., fainting) that are highly metabolically conservative. In contrast, a neuroception of danger, or life threat, favors activation of the SNS or DVC, respectively [1,2,6]. The organization of these specific circuits, along with the SNS, can influence the individual experiences of body awareness by modulating information that emerges from the body through top-down post-processing, including cortical areas informed by the signals traveling through the body-integrative circuits of the brain [7,8]. The World Health Organization (WHO) defined health as a "state of complete physical, mental and social well-being and not merely the absence of disease or infirmity" [9]. Health implies rhythmicity and timing inside and among individuals [10]. Thus, health implies a state of interconnectedness [11]. Interestingly, experiencing interconnectedness and compassion has been linked to the activation of the vagus [12] as well as to an increased respiratory sinus arrhythmia (RSA) [13] that, according to the polyvagal theory, reflects the activation of the VVC. Contemplative practices, characterized by the attentive regulation of breathing, are believed to be mediated by vagal activation [14][15][16], and an increasing number of contemplative practices are being used as "health" interventions for individuals with different health conditions. Recent research has shown that contemplative practices are successful at ameliorating many different morbid situations that encompass cardiovascular disease [17], post-traumatic stress disorder (PTSD) [18], vascular disease [17], fibromyalgia [19], lower back pain [20][21][22][23][24], hypertension [25], and obsessive-compulsive disorder (OCD) [26][27][28][29][30][31][32]. In accordance with these observations, a recent meta-analysis investigating baseline RSA as a psychophysiological marker of stress vulnerability in individuals with PTSD in 55 studies revealed a small but reliable association between PTSD and lower resting RSA [33], as well as the display of lower RSA in OCD patients compared to healthy controls [33,34]. Thus, contemplative practices may be beneficial at the individual as well as the population level, and RSA has been proposed as a transdiagnostic biomarker of emotion dysregulation [35]. Common forms of contemplative practices include mindfulness, compassion and self-compassion, and Tai Chi/Qigong or yoga often practiced 20 min or more, once or twice daily, but can extend into daily life as well [11]. However, mindfulness-related and compassion-related practices are among the most common forms of meditation [36], and three kinds of meditation are considered among "mindfulness meditations" in the West: focused attention, open monitoring (attentional practices), and loving-kindness and compassion (constructive practices) [37,38]. Focused attention requires bringing the attention back, every time that is needed, to the breath or to a specific object; open monitoring (also called choiceless awareness) involves noticing what is most prominent and important, moment-to-moment, in the domain of awareness; loving-kindness meditation is related to an intentional cultivation of happiness while compassion meditation involves cultivating goodwill in the face of suffering [38]. While focused attention and open monitoring involve focusing on a specific object or on a part of the self, such as cognition, emotion, or perception, loving-kindness and compassion meditation require the self as the focus of practice [38][39][40]. In particular, Paul Gilbert and Choden, a Buddhist monk, define compassion as a sensitivity to the suffering of the self and the others with a commitment to try to alleviate and prevent it [41], while Kristin Neff defines self-compassion as 'being open to and moved by one's own suffering, experiencing feelings of caring and kindness toward oneself' [42]. Brain imaging studies confirm the idea of considering compassion as more involving, at the emotional level, than mindfulness. Practicing compassion promotes the activation of regions of the positive affect system, such as the nucleus accumbens, the ventral striatum and the medial orbitofrontal cortex [43][44][45]. In this review, we will mainly focus on the effects of mindfulness-related and compassion-related contemplative practices on traumatic stress conditions, such as PTSD and OCD (which has been associated with a significant overlap of traumatic histories) [46], from a polyvagal perspective. Objectives The aim of this systematic review was to identify common psychophysiological mechanisms underlying the beneficial effects of mindfulness and compassion contemplative practices by systematically reviewing studies in the scientific literature and their research methodologies. PICOS Only studies related to traumatic stress conditions, such as PTSD or OCD [46], and involving humans were included. We did not include research that relied on self-reporting instruments only, since the reliability of this type of research is questioned by the absence of factual measures, one of the main problems related to the contemplative sciences [47]. Our review concentrated on research studying modifications of physiological indexes relevant to central and/or autonomic nervous system activity, and their associations with behavior. In our systematic review, we included physiological parameters such as autonomic activity, investigated through respiratory sinus arrhythmia (RSA), cardio-respiratory synchronization and heart rate variability (HRV), and brain activity, investigated through fMRI and electroencephalography (EEG). We adopted the Population, Intervention, Comparison, Outcomes and Study (PICOS) design strategy (see Methods and Table 1), in order to carry out an effective search strategy. A lack of rigor in the description of the methodology (e.g., age, gender, how subjects were recruited, treatments and procedures used that are clearly stated, protocol duration, measured outcomes) and of the experimental set-up (e.g., tools and setups used to measure outcomes), so that replicability is difficult. Case reports. Search Strategy This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [48,49] and recent PRISMA 2020 updates [50]. PRISMA is a 27-item tool that serves as a checklist to improve the quality of systematic reviews [48,49]. We submitted the protocol for this review for pre-registration in the PROSPERO database, an international prospective register for systematic reviews. It has been assigned

the ID number 268353 (https://www.crd.york.ac.uk/prospero/, accessed on 1 November 2021). Using SCOPUS and PubMed databases, we conducted a systematic search: the first search was conducted in April 2021, and the final search was carried out in July 2021. The Boolean operators "AND", "OR" and "()" were used in order to combine keywords related to mindfulness, compassion, traumatic stress, OCD, and PTSD and to the physiological outcomes of mindfulness-related and compassion-related interventions in OCD and PTSD. The search for the mindfulness-related and compassion-related interventions used the combination of the following keywords: "mindfulness" OR "MBSR" OR "compassion" OR "self-compassion". The search for the physiological effects used the association of the following keywords: "Cardiorespiratory coherence" OR "Cardio respiratory coherence" OR "Cardio-respiratory coherence" OR "Cardiorespiratory coupling" OR "Cardio respiratory coupling" OR "Cardio-respiratory coupling" OR "Cardiorespiratory interaction" OR "Cardio respiratory interaction" OR "Cardio-respiratory interaction" OR "Cardiorespiratory synchronization" OR "Cardio respiratory synchronization" OR "Cardio-respiratory synchronization" OR "Electroencephalogram" OR "EEG" OR "Functional connectivity" OR "Heart rate variability" OR "HRV" OR "Magnetic resonance imaging" OR "MRI" OR "Respiratory Sinus Arrhythmia" OR "RSA". Combining the keywords "Post-traumatic stress disorder" OR "PTSD" OR "Obsessive-compulsive disorder" OR "OCD" was carried out as a search for PTSD and OCD conditions. We conducted the search both for acronyms and extended names. Study Design We established the inclusion criteria and the exclusion criteria for our review, following the PICOS strategy (Table 1). Studies found during the literature search were considered in the review if all of the following criteria were met: • They were carried out on humans diagnosed with PTSD or OCD (whether they were expert or naïve about mindfulness or compassion techniques). • Any protocol of mindfulness-related or compassion-related intervention was used. • Mindfulness-related or compassion-related interventions compared with control groups (other interventions, no intervention) were included. • Physiological parameters associated with the central nervous system or cardio-respiratory system (i.e., cardio-respiratory synchronization, RSA, fMRI, EEG, HRV) and measured through a behavioral/psychological variable (investigated through a psychometric quantitative tool). Studies found during the literature search were not considered in the review if: • Underaged (under 18 years) and/or older (over 65 years) subjects. • Slow breathing procedures not related to mindfulness or compassion interventions. • Physiological parameters that were not relevant for the review, or only a behavioral/psychological index alone was investigated. • They considered case reports. • A lack of rigor in the description of the methodological process (e.g., age, gender, how subjects were recruited, treatments and procedures used that are clearly stated, protocol duration, measured outcomes) and of the experimental tools (e.g., tools and setups used to measure outcomes), such that replicability is difficult. • They were not published in a peer-reviewed journal. • They were not available in English language and/or in full-text. The AMSTAR-2 (A MeaSurement Tool to Assess systematic Reviews-2) [51] approach was used to appraise the methodological quality of our review. A more specific evaluation of systematic reviews that comprises randomized or non-randomized studies of mindfulness-or compassion-related interventions, or both, is possible when using AMSTAR-2. Two independent raters (AP and MM) evaluated each study, and, when discrepancies were present, divergences were resolved through a meeting, referring to a third rater (AG), if necessary, until agreement was achieved. Search Results The results of the search of databases, according to the chosen queries and quantity of studies found, are presented in Table 2. The PRISMA 2020 flowchart related to the process of selecting studies that were considered in the review is shown in Figure 1. Selection and Characteristics of the Considered Studies AP and MM were the two separate reviewers that checked an early pool of 58 abstracts gathered from the outcome of the search. Abstracts and titles were reviewed, and 35 studies were discarded because they were not retrieved, duplicated, or of no interest for our systematic review. A total of 23 remaining full-text papers were evaluated for the eligibility criteria. After the analysis, six articles met the eligibility criteria and were considered in the review. One study [52] was cross-sectional and dealt with the investigation of the effects of attentional distraction in 21 unmedicated OCD patients. One study was a prepost study [53] and examined potential neural correlates of mindfulness-based exposure therapy (MBET). Two studies were cohort studies [54,55] and investigated the effects of MBSR intervention on PTSD symptoms and HRV in combat veterans [54], and the effects of transcendental meditation (TM) on 29 veterans with PTSD using EEG recordings [55]. One study was an RCT study [56] that aimed to evaluate the effect of two common components of meditation (mindfulness and slow breathing) investigating HR, HRV, awakening cortisol and PTSD measures collected through the CAPS, while Williams et al. [57] describe the protocol of an RCT to evaluate the effectiveness and mechanisms of three manualized 8-week behavioral interventions, MM, hypnosis (HYP) and education control (EDU), in 343 veterans with PTSD and chronic pain due to a broad range of etiologies. We describe the methodologies used in the considered studies and their most important results in Tables 3 and 4, respectively. Table 2. Search strategy of the study. Selection and Characteristics of the Considered Studies AP and MM were the two separate reviewers that checked an early pool of 58 abstracts gathered from the outcome of the search. Abstracts and titles were reviewed, and 35 studies were discarded because they were not retrieved, duplicated, or of no interest for our systematic review. A total of 23 remaining full-text papers were evaluated for the eligibility criteria. After the analysis, six articles met the eligibility criteria and were considered in the review. One study [52] was cross-sectional and dealt with the investigation of the effects of attentional distraction in 21 unmedicated OCD patients. One study was a pre-post study [53] and examined potential neural correlates of mindfulness-based exposure therapy (MBET). Two studies were cohort studies [54,55] and investigated the effects of MBSR intervention on PTSD symptoms and HRV in combat veterans [54], and the effects of transcendental meditation (TM) on 29 veterans with PTSD using EEG recordings [55]. One study was an RCT study [56] that aimed to evaluate the effect of two common components of meditation (mindfulness and slow breathing) investigating HR, HRV, awakening cortisol and PTSD measures collected through the CAPS, while Williams et al. [57] describe the protocol of an RCT to evaluate the effectiveness and mechanisms of three manualized 8-week behavioral interventions, MM, hypnosis (HYP) and education control (EDU), in 343 veterans with PTSD and chronic pain due to a broad range of etiologies. Cross-Sectional Studies Simon et al. [52] investigated the effects of attentional distraction [58] in 21 unmedicated OCD patients, with respect to 21 controls, while undergoing fMRI during symptom provocation with individually tailored OCD-relevant pictures. Fronto-striato-limbic circuits included the amygdala, which is relevant in OCD [59,60]. Patients showed increased blood oxygenation level-dependent (BOLD) responses during processing of OCD triggers compared with healthy controls. This result shows that amygdala hyperactivation was present across every OCD symptom dimension, indicating that it may represent a common neural correlate. Attentional distraction was able to dampen patients' amygdala hyperactivity: BOLD response of the left amygdala in relation to OCD triggers was halved only during distraction condition (p = 0.001), ameliorating OCD symptomatology. Overall, these results show that amygdala hyperactivation might constitute a shared correlate of fear expression in OCD dimensions, linking the OCD spectrum to anxiety disorders. Pre-Post Studies King et al. [53] examined potential neural correlates of mindfulness-based exposure therapy (MBET), investigating 23 veterans with PTSD. Fourteen combat veterans with PTSD were treated with MBET, while 9 combat veterans, as a control group, were treated with present-centered group therapy (PCGT). Potential neural correlates were evaluated using fMRI and examining resting-state functional connectivity (rs-FC) in the default mode network (DMN), and PTSD symptoms were evaluated with the CAPS. Results showed that patients treated with MBET showed the greatest reduction in PTSD symptoms (pre vs. post MBET, p = 0.007, average 15.6 point decrease in total CAPS, effect size Cohen's d = 0.92), even though the effect was not significantly different from PCGT. Following MBET, an increased DMN rsFC with DLPFC and dorsal ACC regions associated with executive control was shown. Eventually, posterior cingulate cortex-DLPFC connectivity was correlated with improvement in PTSD avoidant and hyper-arousal symptoms. Cohort Studies Bhatnagar et al. [54] investigated the effects of an 8-week MBSR intervention on eight veterans with PTSD (seven men from the Vietnam era and one woman from Operation Enduring Freedom/Operating Iraqi Freedom). The main outcome measures were the Clinician Administered PTSD Scale (CAPS) [61,62] and the pNN50 measure of HRV (the number of pairs of adjacent normal-to-normal (NN) intervals differing by more than 50 milliseconds divided by the total number of all NN intervals). These were collected by interview and 24-h Holter monitoring at baseline (week 0), upon completion of the course (week 8), and 1 month after completion (week 12). One month after course completion, PTSD symptoms had decreased from baseline by an overall CAPS score of 14.8 points; this reduction was clinically significant according to prior studies [63]. Parasympathetic functioning increased for all five participants that underwent HRV monitoring. Transcendental meditation (TM) represents a mental strategy that uses a mantra to promote meditation. Kang et al. [55] investigated 29 veterans with PTSD (six females) recruited from a medical center and included in the study. TM instructions were given by certified TM teachers trained at the Maharishi Foundation. TM provided 8 weeks of individual and group-based meditation practice. Outcomes of the study consisted of clinical interviews, self-report tools, and EEG recorded during resting and meditation conditions. Participants showed reductions in PTSD symptoms, experiential avoidance, and depressive and somatic symptoms, as well as increases on scores of mindfulness and quality of life, from baseline to posttreatment. Overall treatment improvement was high (mean and median rating of a 9-point scale were 6.2 and 7). With respect to baseline, low-frequency bands (1-7 Hz) of EEG spectral power increased at posttreatment and follow-up and only when meditation states were present (p = 0.01), suggesting TM-related modifications in brain state associated with the intervention. Randomized Controlled Trials (RCTs) Wahbeh et al. [56] sought to assess the effects of two well-known parts of meditation (mindfulness and slow breathing). The authors studies 102 combat veterans suffering from PTSD that were randomized to four conditions: (a) the body scan [64] mindfulness meditation (MM), (b) slow breathing (SB) with a biofeedback device, (c) MM with an intention to slow the breath (MM + SB), or (d) sitting quietly (SQ). Participants underwent six weekly one-on-one sessions followed by 20 min of daily practice at home. The most important measures obtained were HR, HRV and cortisol after awakening. PTSD scores were assessed using the CAPS. Results demonstrated that the awakening cortisol was reduced within the MM group, but there was no overt change in HR and HRV within and between groups. However, there was an improvement in relation to subjective hyperarousal symptoms within-group (but not between groups) for MM, MM plus SB, and SQ, while intrusive thoughts were reduced in MM compared with MM plus SB and SB alone. Overall, mindfulness changes, comparing before and after intervention, were significant (p = 0.04). Williams et al. [57] describe the protocol of an RCT to assess the efficacy and the functioning mechanisms of three manualized 8-week interventions: MM, hypnosis (HYP) and education control (EDU) in 343 combat veterans suffering from PTSD and chronic pain stemming from various different etiologies. The main goal of the study was to compare the efficacy of MM and HYP to EDU on average pain intensity assessed pre-and post-treatment. In addition, the study aimed to explore the efficacy of MM and HYP compared to EDU on some secondary results (i.e., sleep quality, pain interference, anxiety and depression), and the maintenance of its effects at 3 and 6 months post-treatment. EEG assessments were carried out at pre-and post-treatment to establish if the power of specific brain oscillations was able to moderate the efficacy of MM and HYP and evaluate brain oscillations as possible mediators of the effects of the treatment. Risk of Bias The methodological quality and the risk of bias of the considered studies were independently evaluated by AP and MM, using four different tools. A third reviewer (AG) resolved possible discrepancies through a discussion with the reviewers (AP and MM). The Joanna Briggs Institute (JBI)

critical appraisal checklist for cross-sectional studies, pre-post studies, cohort studies and RCTs [65,66] was used to appraise the risk of bias of cross-sectional, pre-post, cohort and RCTs studies, respectively. The four tools that were used for the assessment showed study quality that was considered varied from sufficient to good. Normality tests were lacking (e.g., Shapiro-Wilk test). Regarding cross-sectional study design, the most important concerns were related to the identification of confounding factors identified and measurement of the exposure in a valid and reliable way. When considering pre-post and cohort studies, the main concerns were related to the methods of sampling, sample sizes that may be statistically unjustified, and the lack of randomization for group assignment. Regarding cross-sectional, pre-post and cohort studies, power analysis was not reported and sample sizes were not appropriately identified. Checklists that were related to the risk of bias are shown for cross-sectional, pre-post, cohort and RCT designs in Supplementary Tables S1-S4, respectively. Discussion Conducting a revision of the studies that pertained to the psychophysiological outcomes of mindfulness-related and compassion-related interventions on traumatic stress conditions, such as PTSD and OCD, we aimed at identifying the physiological mechanisms that may be able to mediate their demonstrated beneficial psychological and behavioral efficacy. We found a paucity of evidence that highlighted a link between physiological variables and psychological and/or behavioral measures in PTSD and OCD patients. Within PTSD patients, several results suggest that mindfulness-related interventions promote parasympathetic activity, an increased vagal tone and PTSD symptom improvements. The increased pNN50 measure of HRV [54], the increased DMN rsFC with DLPFC and dorsal ACC regions following MBET [53] and the increased low-frequency bands (1-7 Hz) of EEG spectral power, at post-treatment and follow-up, and only during meditation states [55] are results that favor the parasympathetic activity-promoting interpretation. Remarkably, though no change was observed in HR and HRV within and between groups by Wahbeh et al. [56], Wahbeh et al. [56] did not use an MBSR protocol, whereas it was used by Bhatnagar et al. [54]. In addition, an observed dampening of BOLD activity in the amygdala was reported by Simon et al. [52] in OCD patients. According to the polyvagal theory, mindfulness-related and compassion-related meditations would represent neural exercises broadening the ability of the VVC to govern the current state and to favor resilience. In addition, mindfulness-related and compassion-related meditations comprise a range of practices whose aim is to accomplish a similar efficacy in improving autonomic regulation, providing greater psychological and physiological flexibility and tolerance by leveraging emotional reactivity and ameliorating the physiological reactivity threshold [67]. Hence, mindfulness-related and compassion-related meditations are believed to favor the experience of a neural training, and a way to favor the activity of the VVC whose aims are the regulation, homeostasis and resilience of the organism [12]. Through the modification of the relational awareness towards the physiological state of the neural platforms proposed by the PVT, the physiological reactivity threshold can be strengthened [68]. Mindfulness-related and compassion-related meditations may favor the availability of the VVC to support the mechanisms of physiological recovery and positive behavioral and psychological states. Mindfulness-related and compassion-related meditation practices may also be viewed as promoters of the development of the flexibility as well as of the readiness to shift in and out of the current dominance of one of these theoretical neural platforms (DVC, SNS and VVC), in order to cultivate resilience and evolutionary adaptation of the system. Learning strategies for self-regulation may help individuals to improve their relationship to suffering. Although we are not proposing that the only final goal is the cultivation of VVC, the theoretical association with the neural substrate of the VVC may be viewed as a neurophysiological platform for the advent of states such as social connection. Analogously, we do not wish to propose that the neural platforms other than VVC are "bad", as these neurophysiological states are adaptive in comprehending the complexity of human behavior and experience, and thus the potential influence of a mindfulness-related and compassion-related meditation framework for well-being. Thus, since mindfulness-related interventions promote parasympathetic activity, an increased vagal tone and symptom improvements, it can be hypothesized that many of the processes associated with contemplative practices (e.g., listening, chanting, breathing, shifting posture, and facial expressivity) may influence one's physiological state through the myelinated branch of the vagus (VVC). The passive pathway recruits the SES (including the myelinated ventral vagus) through the cues of safety, such as a quiet environment and the presentation of prosodic vocalizations (e.g., chants) in the frequency band that would overlap with the vocal signals of safety that a mother uses to signal safety to her infant [69]. Hence, mindfulness-related and compassion-related interventions optimize the effects of contemplative training, leading to a greater capacity to feel and express presence and compassion. The factors involved may be: (1) a "passive" pathway that is elicited by feeling safe in an environment that provides sensory cues that, via neuroception, down-regulate defense; (2) an "active" pathway that is implemented via voluntary behaviors (i.e., neural exercises of the vagal brake) capable of establishing a "calm" neural platform (i.e., ventral vagal state) that would functionally optimize contemplative practices; (3) extensive contemplative training; and (4) the emergent properties of contemplative practices, including the capacity to experience and express compassion [69]. From the methodological point of view and statistical analyses, several clinical research studies employed small sample sizes, which in turn lowered statistical power. A recent review reported that only 0.3% of the included studies had ≥80% power to detect a small difference and from 22% to 27% of the studies had power to detect a large difference [70]. In addition, among the studies that did not detect a statistically significant effect, 3% excluded a small difference, and 71% excluded a large difference. Hence, an important pool of clinical research studies was powered only to detect effects of large magnitude. For most studies that do not reach statistical significance, the possibility of relevant differences still exists. However, it could be highly significant for research regarding contemplative practices to evaluate and include power analysis and appropriate sample size calculations, since studies point to beneficial effects of meditation and mindfulness on cognition, affect, and social behavior [71][72][73] (for review see Dahl et al. [40]; Tang et al. [74]), but their effect often may be identified within a narrow window of small effect sizes that require appropriate samples to be detected [75]. In addition, a small effect size could correspond to a highly significant finding, depending on the sample size [76]. Limitations of our systematic review should be considered. Our study included only Scopus and PubMed databases for the identification of potentially eligible studies; addi-tional databases should be considered in future studies. The small number of studies is another limitation of this review, and the present results should be considered preliminary; future reviews may include additional studies and confirm, or revise, our findings. Another limitation concerns the fact that only one study included in the review assessed the effects of TM at follow-up, and this prevented the evaluation of the effects long-term. Furthermore, four out of six studies did not report power analysis, raising the possibility of underpowered study designs. Finally, pharmacotherapy for psychiatric disorders has been shown to have an influence on HRV [77]. In fact, treatment of major depression (selective serotonin reuptake inhibitors (SSRIs) and serotonin and norepinephrine reuptake inhibitors (SNRIs)) was able to influence autonomic function far more than the disease itself [78]. In addition, though SSRIs have been shown to have less impact on HRV than other antidepressants, results suggest that reductions in HRV observed among depressed older adults are driven by the effects of antidepressant medications [79]. Thus, future research regarding contemplative practices and HRV monitoring should control for the effects of psychoactive medications. Despite these limitations, our review has several strengths. We provided a detailed search strategy for literature search and study identification, and appraised the methodological quality of this systematic review and of the included studies. In addition, we considered methodological aspects such as power analysis, which is rarely reported or considered in study designs or reviews but could be a crucial step to generate reliable data and conclusions. Conclusions Our results suggest that mindfulness-related interventions promote the dampening of BOLD activity in the amygdala in OCD patients [52] and parasympathetic activity, increased vagal tone and PTSD symptom improvements [53][54][55]. However, very limited research was highlighted by our systematic review, and peculiar methodological limitations of the existing studies should be taken into account. Even the results from underpowered and poorly designed RCTs may be overrated because their design granted them unfounded credibility. In addition, inaccurate conclusions derived from these trials may guide clinical practice as clinicians' decisions may be conditioned by the fact that an RCT design was used [80]. Thus, for contemplative practices research, it is highly recommended to include, and report, an a-priori power analysis with appropriate sample size identification (see, for example, Schmidt et al. [81]). The results of our systematic review and the documented positive effects of meditation on mental and physical health [82,83] promote contemplative practices as health-related interventions. Science is now interfacing with insights derived from historical and often ancient contemplative practices. The accumulated knowledge suggests that meditative practices not only lead to a different perspective of reality that fosters a connectedness with others expressed through feelings of compassion, but also may have positive influences on health. Supplementary Materials: The following are available online at https://www.mdpi.com/article/10 .3390/ijerph182211778/s1, Table S1: JBI critical appraisal checklist for cross-sectional studies; Table S2: JBI critical appraisal checklist for pre-post studies, Table S3: JBI critical appraisal checklist for cohort studies; Table S4: JBI critical appraisal checklist for RCT studies. Institutional Review Board Statement: Ethical review and approval were waived for this study because it was a systematic review, and no new data were collected. Distribution of sulfamethoxazole trimethoprim constin in Vibrio cholerae isolated from patients and environment in Iran The occurrence of drug-resistant Vibrio cholerae is being reported with increasing frequency worldwide. Spread of resistant strains has been attributed, in part, sulfamethoxazole trimethoprimconstin (SXT-C). Sixty V. cholerae isolates obtained from cholera patients from different provinces in Iran during 2004 to 2006 and thirty-seven V. cholerae strains from surface water sources at 5 different locations in Tehran, Iran during 2006 were subjected to antibiotic susceptibility testing and polymerase chain reaction amplification of SXT-C. In clinical isolates the highest and the least levels of antibiotic resistance were seen to SXT, streptomycin and chloramphenicol (95, 95 and 92%, respectively) and doxycycline, gentamicin and oxytetracycline (0, 3 and 3%, respectively). PCR for SXT element of clinical and environmental isolates was positive for 95 and 19% of isolates, respectively. The results of this study showed that among the clinical and environmental V. cholerae resistance to SXT, streptomycin and chloramphenicol could be, in part, due to wide distribution of SXT-C isolates. INTRODUCTION Vibrio includes a wide spectrum of species causing pandemics to free-living aquatic strains. Besides morbidity and mortality associated with cholera, multiple drug-resistant Vibrio cholerae O1 has been shown as a major public health problem in Iran (Bakhshi et al., 2008a). The reports of strains resistant to commonly used antibiotics are also appearing with increasing frequency globally (Garg et al., 2000;2001). Spread of antibiotic resistance among V. cholerae occurs through mobilization of a variety of genetic elements. Antibiotic resistance determinants have been detected on sulfamethoxazole trimethoprim-constin (SXT-C), a novel conjugative transposable element, which encodes resistance to SXT, chloramphenicol and streptomycin (Glass et al., 1980). In this study we determined antibiotic susceptibility testing and distribution SXT-C among the clinical strains of V. cholerae isolates *Corresponding author. E-mail: [email protected]. collected from cholera patients from different provinces in Iran during 2004 to 2006, and environmental isolates collected from surface water sources at 5 different locations in Tehran, Iran during 2006, where several cholera epidemics have occurred in the last several years (Bakhshi et al., 2008b;Pourshafie et al., 2007). Presence of SXT-C as an important antibiotic resistance genetic determinant among these clinical and environmental isolates was studied to understand the role of this element in emergence of drug-resistant V. cholerae isolates. (95) SXT, sulfamethoxazole trimethoprim. Clinical samples Zahedan, Golestan and Qom (Table 1). V. cholerae ATCC 14035 type strain was used as a positive control throughout the study. Collection and processing of environmental samples Five hundred milliliters of surface water samples were

collected from 5 different geographical locations in Tehran, Iran during a period of 3 months between June and August 2006. The samples were taken from local surface water at different locations in the west (labeled as sources 1 and 2), east (4 and 5) and center (3) of Tehran where there were no outlets from waste water treatment plants. Sampling from each surface water source was performed 3 times with the interval of 30 days. The transportation of each sample to the laboratory was performed in the sterile 500cc glass container on ice. Vacuum pressure of 15 to 20 lb/in2 was used to filter water samples through 0.45 mm pore size membrane after a pre-filtration through filter paper (Wattman No.1; Maidston, UK).The membranes were then cut into 8 pieces after which they were vortexed in 2 ml of 10 mM phosphate buffered saline (PBS, pH 7.4) for 3 min, followed by addition of 20 ml of alkaline peptone water (APW) containing peptone (1% wt/vol) and NaCl (1%wt/vol,pH 8.5). The tubes were then shaken (100 rpm) for 16 h at 37°C. Each sample was streaked on thiosulfate-citrate-bile-sucrose agar (TCBS) plates and incubated overnight at 37°C. All the yellow colonies on TCBS plates which were suspected of being V. cholerae were further examined by 10 biochemical assays including oxidase, motility, sucrose and lactose fermentation, growth in 0% NaCl, arginine dehydrolase, ornithine decarboxylase, methyl red, Voges-Proskauer and indole test .Confirmation of identity of isolates was performed by PCR using species-specific primers (prVC-F/ prVCM-R). A total of 37 V. cholerae strains were then isolated and subjected to further analysis. Antimicrobial susceptibility testing of environmental samples A total of 12 antimicrobial resistance profiles were observed among the total isolates (Table 4). Profile 1 was the predominant pattern (51%) and showed sensitivity to all 10 antimicrobials tested. The profile 2 constituted 11% of the isolates and represented resistance to only SXT. Among the isolates, the highest level of resistance was observed with ampicillin (27%), followed by SXT (22%) and streptomycin (16%). No resistance to gentamicin or ciprofloxacin was observed. Five isolates (13.5%) showed resistance to more than 3 antimicrobials tested. Distribution of SXT-C among clinical and environmental samples The majority of 60 clinical strains showed significant DISCUSSION In this study, we analyzed one important genetic determinant responsible for drug susceptibility pattern of clinical V. cholerae strains isolated from four different provinces in Iran over a 3 year period between 2004 and 2006 and environmental V. cholerae strains from surface water sources at 5 different locations in Tehran, Iran during 2006. The pattern of antibiotic resistance among clinical isolates was similar throughout the 3 years period, observing that the time of sample collection had no effect on the drug susceptibility. During the 3 years period only a few isolates, obtained during 2005, were resistant to ciprofloxacin, gentamicin, oxytetracycline and tetracycline. This trend of antibiotic sensitivity, however, was changed, and clinical isolates become sensitive during 2006. The results showed that the trend of ampicillin resistance had significantly increased from 2004 to 2006, whereas erythromycin resistance was decreased. Such change could be an indication of the antibiotic usage by the public in Iran, which further signifies the need to further investigate the genetic mechanisms involved. PCR assay for SXTint revealed that 95% of our total clinical isolates in 3 years contained SXT-C responsible for resistance to cotrimoxazole (95%), streptomycin (95%) and chloramphenicol (92%). The appearance of SXT-C has been reported by Iwanaga et al. (2004) to have occurred in El TorO1 strains isolated in Laos after 1997, which has replaced the class I integron with an aadA1 gene cassette in pre-1997 V. cholerae isolates. Similarly, Amita et al. (2003) have reported that class I integron with an aadA1 gene cassette was widely distributed among clinical O1 strains before emergence of pre-O139 in India, which eventually disappeared and replaced with SXT-C. The results may suggest that the SXT-C has turn into the dominant antibiotic-resistant element among clinical V. cholerae O1 isolates in Iran. Increasing V. cholerae antibiotic resistant strains of clinical origin poses the need for assessing mobile nature of resistance gene content of the environmental isolates (Sack et al., 2003). Among the antibiotic resistance profiles, significant resistance to SXT and streptomycin was seen in comparison to other antibiotics among our clinical isolates. We previously found resistance to same antibiotics in the clinical isolates obtained in Iran (Pourshafie et al., 2007), which suggests the presence of the resistant genetic determinants in the environmental isolates even during non-endemic cholera periods. Presence of the SXT element (19%) among our environmental isolates supports this supposition. Two of our isolates (5.4%) were found to be resistant to 8 antibiotics. Among the SXTint environmental isolates (19% of the total isolates), 57 and 71% were resistant to cotrimoxazole and streptomycin, respectively. The resistant genes for these two antibiotics are known to be encoded by SXT element. The reason that not all SXTint isolates were resistant to SXT and streptomycin could be the finding that the SXT element may acquire the resistance genes through horizontal transfer . Therefore, the presence of SXT element should be monitored even in drug susceptible V. cholerae isolates. Miyazato et al. (2004) have indicated that no mobile genetic elements such as plasmid, class I integron or SXT element was detected in 22 environmental non-O1, non-O139 strains which were isolated from 13 distant sampling sites in Vietnam. In conclusion, the data presented in this study showed that the SXT-C element intrinsically harboring several different antibiotic resistance gene cassettes is widely distributed among different clinical and in acceptable number, in environmental V. cholerae in Iran. Although the resistance element found in this study may be responsible for the antibiotic resistance seen in this study, further global investigations are needed to determine the importance of SXT element in particular in the horizontal acquisition and dissemination of antibiotic resistance genes among V. cholerae and other microbes. Also the limited information on the epidemiological linkage between the clinical and environmental isolates of V. cholerae pose the need to further monitor the environmental isolates. The Anti-inflammatory Immune Regulation Induced by Butyrate Is Impaired in Inflamed Intestinal Mucosa from Patients with Ulcerative Colitis Altered gut microbiota composition and reduced levels of short-chain fatty acids, such as butyrate, have been identified as key components of ulcerative colitis (UC). We aimed to determine and compare effects of butyrate on the intestinal immune profile of UC patients with active disease and non-inflamed controls. Biopsies were cultivated during 6 h with or without butyrate. Cytokines were measured in supernatants and mRNA gene expression was analyzed in biopsies using Qiagen RT2 Profiler PCR Arrays. The intestinal immune profile of cultured biopsies, as determined by mRNA gene expression and secreted cytokines, differed between inflamed UC samples and controls. Principal component analysis revealed that addition of butyrate differently regulated mRNA expression in inflamed biopsies from UC and non-inflamed biopsies from controls. Highly discriminant and predictive orthogonal partial least squares discriminant analyses identified 29 genes for UC (R2 = 0.94, Q2 = 0.86) and 23 genes for controls (R2 = 0.90, Q2 = 0.71) that were most regulated by butyrate. UC displayed more up-regulation of genes as compared with controls, and controls displayed the most prominent down-regulations. Ingenuity Pathway Analysis identified a down regulation of the Neuroinflammation Signaling pathway and predicted inhibition of the categories Inflammatory response, cellular movement, and cellular development as top diseases and functions, respectively, for controls but not for UC. In conclusion, butyrate has a different effect on gene regulation and more potently down-regulates gene expression of inflammatory pathways in non-inflamed controls than in inflamed tissue of UC patients. These discrepancies may at least partly explain why anticipated anti-inflammatory effects of local butyrate induction or supplementation are not always obtained. INTRODUCTION Inflammatory bowel disease (IBD) is a chronic disease of the gut thought to involve an altered immune response to unknown microbial related threats of genetically susceptible individuals. The composition of the gut microbiota in IBD patients differs from that of healthy individuals, with reports of lower abundance of butyrateproducing bacteria of the Firmicutes phylum such as Roseburia hominis and Faecalibacterium prausnitzii [1,2]. Further, reduced colonic levels of butyrate, possibly related to disease activity, have been demonstrated in IBD patients [3,4]. Butyrate, a short-chain fatty acid and the main endproduct of intestinal microbial fermentation of dietary fiber in the colon, is a histone deacetylase inhibitor [5] and has been suggested to have anti-inflammatory effects, as shown by the ability to ameliorate disease in animal models of colitis [6][7][8]. Hence, results primarily obtained from mouse models and in vitro systems suggest that butyrate improve intestinal barrier integrity [9], increase secretion of antimicrobial peptides [10,11], down-regulate Toll-like receptor (TLR) expression and secretion of proinflammatory cytokines [12], and inhibit the activity of granulocytes [8] and lymphocytes [13]. Moreover, butyrate may promote T regulatory cell generation [14,15] and inhibit inflammatory signaling including the AKT [16] and NF-κB pathways [17]. Given its potential anti-inflammatory properties, butyrate has been proposed as a therapeutic option for IBD patients, although results so far have been indecisive. Several clinical trials investigating efficacy of butyrate supplementation suggested the compound to be beneficial for IBD patients [18][19][20][21], whereas other studies were not able to show any effect on intestinal inflammation [22,23]. More recently, attempts to restore the gut microbiota balance by fecal microbiota transplantation (FMT), which may result in increased abundance of butyrate-producing bacterial taxa, have been implemented. A meta-analysis based on randomized controlled trials for patients with UC, including 4 studies with 277 participants, demonstrated that significantly more patients receiving donor FMT achieved clinical remission (42.1%) compared with those receiving control interventions (22.6%), and therefore concluded that FMT appears promising as treatment to induce remission, although long-term durability still remains unclear [24]. Recently, a randomized controlled trial using anaerobically prepared pooled donor FMT or autologous FMT in UC patients reached the primary outcome with a higher likelihood of remission at week 8 in donor compared with autologous FMT [25]. The somewhat diverging results of butyrate induction or supplementation may result from design of studies, and could also be due to that butyrate has different effects on the immune system of the host during inflamed and noninflamed conditions. Hence, we aimed to determine and compare effects of butyrate on the intestinal immune profile of UC patients with active disease and non-inflamed controls, to potentially identify factors explaining the lack of convincing therapeutic effects on intestinal inflammation of butyrate. Study Subjects and Sample Collection Study subjects were recruited among patients at the outpatient clinic at the Sahlgrenska University Hospital, Gothenburg, Sweden. Inflamed (sigmoid colon) and noninflamed (ascending colon) biopsies were obtained from the same UC patients. Non-inflamed biopsies (sigmoid and ascending colon) were obtained from the same control subjects undergoing colonoscopy for other indications (polyps, weight loss). All biopsies were taken according to a clinical routine using the same diameter endoscopic forceps. Disease activity was determined by Mayo score [26]. The study was performed after receiving informed written consent from all subjects, and the protocol was approved by the Regional Ethical Review Board at the University of Gothenburg. Cell Cultivation Assay Six biopsies were obtained from each site and the four most even-sized were used for cultivation. The same laboratory technician performed the handling of all samples to ensure conformity and all samples were cultivated in duplicates. Biopsies were cultivated in 0.2 mL Iscove's medium supplemented with 10% human FBS, 100 μg/ml gentamicin (Sigma-Aldrich, St Louis, USA), and 3 μg/ml L-glutamine (Sigma-Aldrich) without or with 1.6 mM butyrate (B5887, Sigma Aldrich), at 37°C and 5% CO 2 . After 6 h, the duplicate biopsies were collected and pooled for RNA purification and supernatants were pooled and frozen for cytokine analysis. Butyrate concentration was chosen by titration from 0.1 to 6.4 mM on biopsies from healthy controls with reduction of IL-6 expression in the supernatant as readout, lowest concentration exhibiting IL-6 suppression was selected. Messenger RNA Extraction from Biopsies Total mRNA from biopsies was extracted using Nucleospin® DNA, RNA, and protein purification kit (Macherey-Nagel, Düren, Germany) according to the manufacturer's protocol. Concentration and purity of the RNA was measured using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, Delaware, USA) with 260/280 and 260/230 ratios of 2 and 2.1-2.2, respectively. Mucosal Gene Expression Array Analysis Gene expression array analysis was performed as previously described [27].

Briefly, cDNA was prepared using the RT 2 First Strand Kit (Qiagen, Hilden, Germany) according to the manufacturer's protocol. The RT 2 Profiler PCR arrays for "antibacterial response" (PHAS-148Z, Qiagen) and "innate and adaptive immune responses" (PAHS-052Z, Qiagen) were analyzed in a Quantstudio 12K Flex Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) by the use of RT 2 qPCR SYBR Green ROX MasterMix (Qiagen). Data was analyzed in the RT 2 Profiler PCR Array Data Analysis version 3.5 (Qiagen). All samples passed the quality checks for PCR array reproducibility, RT efficiency, and genomic DNA contamination. ACTB, B2M, and RPLP0 were used as housekeeping genes and normalized values are expressed as 2 −(Target-Housekeeping) . For genes present in both arrays (n = 34), mean values from the two arrays were used. A complete list of the genes from the arrays, including annotation of duplicates and undetected genes (n = 14), is shown in Supplementary table 1. Data Analyses Principle component analysis (PCA) was conducted on logarithm-transformed gene expression data using the prcomp-algorithm and visualized using the pca3d-package in R (version 3.3.2) [28]. To examine the relationship between gene expression without and with butyrate (Y-variable) and mRNA levels (X-variables), multivariate factor analysis (SIMCA-P+ software; Umetrics, Umeå, Sweden) was used. Orthogonal Projections to Latent Structures Discriminant Analyses (OPLS-DA) were implemented to correlate selected Y-variables and X-variables with each other in linear multivariate models. The quality of the OPLS-DA was based on the parameters R2, that is, the goodness of the fit of the model (values of ≥ 0.5 defines good discrimination, best possible fit, R2 = 1) and Q2, that is, the goodness of prediction of the model (values of ≥ 0.4 defines high predictive ability, best possible predictive ability Q2 = 1). [29] A variable influence on projection (VIP) cut-off of > 1.2 was used as a variable selection based on discriminatory power, since VIP > 1 is most influential for the model and most relevant for explaining the Y observations [29]. Significance of the separation between the groups in the OPLS-DA was calculated using CV-ANOVA. Parameters identified by OPLS-DA as VIP > 1.2 were logarithm transformed and subject to univariate analysis using Student's T test. Mean values were back transformed and fold changes (FC) were calculated between butyrate 1.6 mM and none for each gene and evaluated using Ingenuity Pathway Analysis (IPA, version 2.3) (Qiagen). Cut-off used for IPA was p < 0.05. Gene expression data are presented as FC on a log 2 scale where log 2 FC = 1 and − 1 define a 2-fold increase and decrease, respectively. Activation z-scores are calculated by the IPA software and predict whether a specific pathway, disease or function is increased (z-score > 2.0) or decreased (z-score < − 2.0) based on the experimental dataset. For cytokine expression, the Mann-Whitney U test was used to determine differences between two independent groups and Wilcoxon signed-rank test was used for comparison of related samples. Data are shown as median (range) unless otherwise stated. All statistical analyses were performed using IBM SPSS Statistics 23; p values < 0.05 were considered as statistically significant. Boxplots and the heatmap were generated using the ggplot2-package in R. Patient Demographics The study included 8 controls (4 males, age 54 (24-84), median (range)) and 8 patients with UC (6 males, age 38 (32-74)) with a disease duration of UC of 7 (< 1-47) years. All UC patients had active disease with sigmoidal endoscopic Mayo score 2 (n = 7) or 1 (n = 1) and Mayo score 0 in ascending colon. All controls had endoscopic Mayo score 0 throughout the colon. Current treatment for UC patients was 5ASA (n = 5), 5ASA and thiopurines (n = 1), corticosteroids (n = 1), and no treatment (n = 1). None of the controls was taking any anti-inflammatory drugs and The Anti-inflammatory Immune Regulation Induced by Butyrate none of the participants had used antibiotics the past 3 months. UC Patients Show Increased Biopsy Cytokine Secretion and Innate/Adaptive Gene Expression at the Site of Inflammation Cytokine analysis of the sigmoidal biopsy supernatants showed increased secretion of all cytokines except IL-2 and IL-5 for UC patients as compared with controls (Fig. 1a), and a similar pattern was apparent when compared with non-inflamed biopsies from the same UC patients (Supplementary Figure 1). The mRNA expression in sigmoidal biopsies cultured without butyrate revealed higher expression of genes mainly present in the array "innate and adaptive immune response" for UC patients compared with controls, with only NLRP1 and ZBP1 related exclusively to the "antibacterial response" array ( Fig. 1b, c). Butyrate Modifies Cytokine Secretion Differently at the Site of Inflammation Compared with Non-inflamed Sites Addition of butyrate for 6 h decreased the levels of IL-6 for controls and non-inflamed samples from UC patients but no changes were detected for inflamed UC samples (Fig. 2a). The opposite pattern was identified for TNF and IL-10 where butyrate only induced a decrease for inflamed UC samples and not at non-inflamed sites or for controls (Fig. 2b, c). In addition, GM-CSF was reduced by butyrate for controls (0.94 pg/ml (0.15-4.73) to 0.22 pg/ml (0.06-0.42), p = 0.02), while no other changes for any of the cytokines could be detected at any site (data not shown). Fig. 1. Cytokine protein expression and gene expression from in vitro cultivated biopsies. Sigmoidal biopsies were taken from control subjects (n = 8, shown in white) and UC patients (n = 8, shown in gray) and cultivated in vitro for 6 h. Cytokine levels in the supernatants were analyzed by MSD® Multi-Spot Assay system and gene expression was analyzed using PCR arrays for genes involved in antibacterial response and innate and adaptive immune responses. a Levels of GMCSF, IFN-γ, IL-10, IL-12p70, IL-13, IL-17A, IL-1β, IL-2, IL-4, IL-5, IL6, IL-8, and TNF in the supernatants. b Score scatter plot and c loading column plot from an Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) for the expressed genes using a variable influence on projection (VIP) cut-off of > 1.2. Genes in c are shown in light gray, genes present in both arrays ("antibacterial response" and "innate and adaptive immune responses") are marked with ¤, genes present exclusively in "antibacterial response" are marked with #, and genes present exclusively in "innate and adaptive immune responses" are unmarked. Significance was assessed by Mann-Whitney U test (cytokine data) or Student's T test (logarithm-transformed gene data); *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001. Butyrate Alters the Sigmoidal Gene Expression Profile of Both UC Patients and Controls The mRNA expression of inflamed sigmoidal biopsies from UC patients and non-inflamed sigmoidal biopsies from controls cultured with or without butyrate revealed differential clustering in a PCA, reflecting different regulation of gene expression by the addition of butyrate at inflammation (Fig. 3). Highly discriminant and predictive OPLS-DA plots identified 23 genes for controls (R2 = 0.90, Q2 = 0.71, p = 0.006) and 29 genes for UC (R2 = 0.94, Q2 = 0.86, p = 0.0001) that were most regulated by butyrate (Fig. 4). Of the genes identified to be regulated by butyrate in the OPLS-DA analysis, 11 were overlapping and one (CCR4) showed no significant change within any of the groups resulting in a combination of 40 genes used for further analysis (Fig. 4b, d). Ingenuity Pathway Analysis Indicates More Potent Down-regulation of Inflammatory Pathways for Controls than for UC Patients at the Site of Inflammation Fold changes in gene expression caused by butyrate in sigmoidal biopsies were analyzed in a heatmap. Common for both groups were down-regulation of IL2, IL1A, CSF2, CD40LG, and NFKB1 and up-regulation of BIRC3, TLR9, MAP2K3, IRF3, and IL18, while regulation of the other genes differed (Fig. 5a). Overall, UC displayed more up-regulation of genes as compared with controls, as shown by genes indicated in red, and controls displayed the most prominent down-regulations, as shown by genes indicated in blue (Fig. 5a). Next, the regulated genes were evaluated by IPA. The top canonical pathway identified by IPA was Neuroinflammation Signaling pathway (-log(p value) 39, 27 associated genes), and z-scores of − 2.117 and − 0.962 for controls and UC patients, respectively, indicated a down-regulation in the presence of butyrate for controls but not for UC patients. Data were further analyzed with the IPA software to identify the most significantly enriched diseases and functions related to gene regulation by butyrate. Among the top eight most enriched diseases and functions for controls and UC, controls showed a decrease in predicted activation states for 5 diseases/ functions (defined by a z-score < − 2.0) while no changes were detected for patients with UC (Table 1). Since inflammatory response and leucocyte movement/interaction were enriched for both groups, the changes induced by butyrate were further visualized in relation to the biological functions of Inflammatory response and Binding of leucocytes. IPA predicted strong inhibition of both functions for controls as shown by the dark blue color of the nodes connecting the analyzed genes (Fig. 5b, left). For UC patients at inflammation, only modest and weak inhibition were predicted for Inflammatory response and Binding of leucocytes, respectively, as shown by the medium and light blue colors of the connecting nodes (Fig. 5b, right). DISCUSSION In this study, we have demonstrated that butyrate alters the intestinal gene expression profile of both UC patients and non-inflamed controls. Nevertheless, butyrate had a different effect on intestinal gene expression during inflamed and non-inflamed conditions. Hence, butyrate more potently down-regulated expression of inflammatory pathways in intestinal biopsies from non-inflamed controls than in inflamed biopsies from UC patients. In the absence of butyrate, the cytokine secretion and gene expression of cultured sigmoidal biopsies differed substantially between the two study groups. The higher cytokine secretion as well as expression of genes encoding proinflammatory cytokines, chemokines, and receptors for recognition of microbial products in inflamed UC patients than non-inflamed controls reflected the inflammatory status of Fig. 3. Overview of mucosal gene expression in controls and patients with UC, with and without butyrate. Sigmoidal biopsies were taken from control subjects (n = 8) and UC patients (n = 8) and cultivated in vitro for 6 h without and with 1.6 mM butyrate. Gene expression was analyzed using PCR arrays for genes involved in antibacterial response and innate and adaptive immune responses. The data is presented by a principle component analysis including all detectable genes (n = 120). Controls without butyrate (control none, gray triangles), controls with butyrate (control butyrate, black circles), UC without butyrate (UC none, white diamonds), and UC with butyrate (UC butyrate, gray squares) are shown. Groups are connected by lines to their centroids and the confidence intervals (0.95%) are shown by the ellipses. UC patients with active disease. Few changes were detected in cytokine expression due to butyrate, which was not surprising given the short incubation time. However, paired samples from inflamed and non-inflamed tissue of the UC patients as well as paired samples from sigmoid and ascending colon from controls revealed that the few butyrateinduced differences in cytokine secretion were inherent to the inflammation, not to the disease. Undeniably, butyrate had similar effects on the regulation of the expression of a smaller share of genes in UC patients and non-inflammatory controls. Similarities of gene regulation in the presence of butyrate in the two groups included down-regulated expression of NFKB1, along with reduced secretion of the NF-κB-induced pro-inflammatory cytokines TNFα and IL6. Indeed, in CD patients, butyrate has been demonstrated to inhibit NF-κB activation and IκBα degradation [30] and control ROSmediated NF-kB activation [31]. Also, genes expressed by T regulatory cells, i.e., RORC and FOXP3, were downregulated by butyrate in UC patients and non-inflammatory controls, respectively. While butyrate has been reported to support induction of FOXP3 + T regulatory cells in animal models [14,15], data from the human setting are so far lacking, and our results do not support butyrate-induced expression of genes related to this admittedly antiinflammatory cell population. Furthermore, the gene expression of a few cytokines and growth factors was regulated Fig. 4. Butyrate induces differential mucosal regulation of gene expression in controls and patients with UC. Sigmoidal biopsies were taken from control subjects (n = 8) and UC patients (n = 8) and cultivated in vitro for 6 h without and with 1.6 mM butyrate. Gene expression was analyzed using

PCR arrays for genes involved in antibacterial response and innate and adaptive immune responses. Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) with gene expression as X-variables (shown in white) and patient groups as Y-variables (without butyrate shown in black and with butyrate shown in gray) are depicted. a Score scatter plot and b loading scatter plot from an OPLS-DA for controls. c Score scatter plot and d loading scatter plot from an OPLS-DA for patients with UC. Variable influence on projection (VIP) cutoffs of 1.2 were used. R2Y defines the goodness of fit and Q2 the goodness of prediction. Significance of regulated genes in c and d was assessed by Student's T test, *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001. ns, not significant. The Anti-inflammatory Immune Regulation Induced by Butyrate similarly in both groups. Hence, the effect of butyrate on the expression of a limited numbers of genes is shared during inflamed and non-inflamed conditions. The most prominent finding of our study was that butyrate had different effects on regulation of gene expression with only minor overlaps between the non-inflamed controls and UC patients. Based on the intestinal gene expression, IPA identified Neuroinflammation Signaling pathway to be inhibited in non-inflamed controls, but not in UC patients with active disease. IPA also predicted different regulation of the biological diseases and functions Inflammatory response and Binding of leucocytes for the two groups with a stronger decrease for controls. Hence, our data suggest that butyrate more prominently down-regulate genes alluring to inflammatory pathways during the healthy state, but not during chronic inflammatory conditions. There are few previous studies of the individual genes that were differently regulated by the presence of butyrate in health and disease. Nevertheless, XIAP expression, found to be down-regulated by butyrate in UC patients but not in non-inflamed controls, has been reported to be reduced by butyrate addition to Caco-2 cells [32]. Additionally, similar to our finding, butyrate has been reported to substantially down-regulate the expression of CD80 on human dendritic cells [33]. Opposite to reports of butyrate having effects on epithelial function expression of antimicrobial peptides such as cathelecidin [11], RegIIIγ, and βdefensins [10,34], we found no evidence for regulation of genes encoding for antimicrobial peptides. Potentially, the conflicting results may reflect that previous studies have made use of epithelial cell lines, whereas our data were based on cultured biopsies, where the epithelial barrier only constitutes a smaller part of the whole tissue. Still, the effect of butyrate on the human intestinal immune profile, irrespective of presence of inflammation, is under-investigated and needs further attention. The altered regulation of genes of several inflammatory pathways in UC patients with active inflammation as described in our study may be due to impaired butyrate metabolism. Possibly, inflammatory conditions can result in downregulated expression of genes encoding enzymes involved in butyrate metabolism and oxidation, as demonstrated in inflamed mucosa of UC patients [35]. This is supported by the fact that in UC patients responding to anti-TNF therapy the mucosal expression of butyrate metabolism/oxidation genes are increased [35]. Another study, promoting that butyrate has different effects on intestinal cells during health and disease, demonstrated that addition of butyrate alone to intestinal primary epithelial cultures increased the epithelial resistance, whereas butyrate in the presence of pro-inflammatory cytokines led to a drop in resistance [36]. In line with this, a recent study showed that TNFα reduces the ability of the intestinal epithelium to take up and metabolize butyrate [37]. Hence, others and our data imply that butyrate effects on the host are altered by inflammation and butyrate supplementation alone may be insufficient to resolve inflammation and regain gut homeostasis. Recently, manipulation of the gut microbiota by fecal transplantation, potentially increasing the abundance of butyrate-producing taxa, has been proposed as a target for IBD therapy [38]. So far, the treatment efficacy seems highly variable and may be related to microbiota composition of the donor and/or recipient. Interestingly, sustained remission in UC patients undergoing fecal transplantation has been associated with increased abundance of butyrateproducing bacteria and overall increased butyrate production capacity, while relapse was associated with persisting high relative abundance of Proteobacteria and Bacteroidetes [39]. Our data, along with the reports of impaired butyrate metabolism during inflammatory conditions described above, imply that improved long-term effects of butyrate induction, or local supplementation, may be best achieved while distributing butyrate during noninflamed conditions. Hence, butyrate may be more potent to maintain rather than induce remission. The fact that we only determined the effects of butyrate on intestinal gene expression, not including analyses of certain cell populations or protein expression, is a potential weakness of this study. Further, the number of study subjects included is limited and addition of consecutive time-points or several concentrations of butyrate for our analyses might have revealed another pattern of gene regulation and cytokine secretion by the addition of butyrate. Indeed, underdosing may be a reason for the differences detected in our study and in clinical studies of butyrate supplementation. However, our approach, analyzing pathway-focused gene expression a Activation z-score is calculated by the IPA software and predicts whether a specific disease or bio-function is increased (positive z-score) or decreased (negative z-score) based on the experimental dataset. Z-scores < − 2 or > 2 indicates decrease and increase, respectively b Z-scores of < − 2 or > 2 are shown in italic IPA, Ingenuity Pathway Analysis; UC, ulcerative colitis using verified PCR assays, allows for a broad and still relatively detailed analysis including a wide range of targets in specific pathways. Also, coherent analysis methods, including multivariate tools and Ingenuity Pathway Analysis, admit for better understanding of the overall picture, rather than isolated findings. To the best of our knowledge, this study is the first of its kind, comparing effects of butyrate on human gene expression ex vivo, making use of intestinal biopsy cultures during inflammatory conditions in ulcerative colitis patients and non-inflammatory controls. To conclude, although butyrate altered the intestinal gene expression profile of both UC patients and noninflamed controls, butyrate regulated a different set of genes during inflamed and non-inflamed conditions. Inflammatory pathways were more potently down-regulated by butyrate in non-inflamed controls than UC patients at active inflammation. These discrepancies may at least partly explain why anticipated anti-inflammatory effects of local butyrate induction or supplementation in UC patients are not always obtained. ACKNOWLEDGMENTS Open access funding provided by University of Gothenburg. The authors would like to thank Maria Wenåker for including the patients into the study. Magnetic Resonance Imaging Assessment of Pre- and Post-Surgery Myocardial Changes in Hypertrophic Cardiomyopathy: Correlation with Echocardiography Hypertrophic cardiomyopathy (HCM) is a common form of cardiomyopathy and a leading cause of sudden death in the young. Magnetic resonance imaging (MRI) is an established pre-operative tool for the evaluating of patients suspected with HCM for morphological assessment and identifying patients at risk of sudden death. Echocardiography and MRI are equally used in the post-treatment assessment of cardiac function and morphology. In this report, we present the comparative role of these two modalities in pre- and post-operative imaging assessment in our patients, treated surgically with the left ventricular myomectomy. Relative merits of MRI and echocardiography are presented and discussed. INTRODUCTION Hypertrophic cardiomyopathy (HCM) is a genetic disorder involving the cardiac sarcomere characterized by the left ventricular (LV) hypertrophy without obvious etiology. [1] It is the most common inheritable cardiac disorder with autosomal dominant inheritance (50-60%). [2] Morphologically, it is classified as asymmetrical, symmetrical, apical, mass-like (tumefactive), and end-stage form (burned-out phase). [2] e most common variety is asymmetrical type, which frequently involves the anteroseptal myocardium. Echocardiography and magnetic resonance imaging (MRI) provide clinically useful parameters for the evaluation of HCM. Some observations are common in both modalities, others specific to the modality. Commonly assessed parameters are ejection fraction (EF), interventricular septal (IVS) thickness, wall motion, and assessment of chamber lumen. Echocardiography provides quick, reliable assessment of gradients at different parts of the left ventricle. MRI, although capable of assessing gradients, has technical limitations to obtain consistently accurate gradient measurements. Echocardiography is a clinically established technique for the assessment of HCM. However, the technique is limited by operator dependency, poor acoustic window, incomplete visualization of the left ventricular wall, and inaccurate evaluation of the LV mass. MRI is useful in quantitative evaluation of wall thickness and documenting the extent and distribution of disease better than echo, especially in the anterolateral wall of the LV myocardium. MRI also has the ability to accurately evaluate the LV mass, chamber volume, global/regional wall motion abnormalities, and detection of aneurysms. Myocardial fibrosis, detected as foci of delayed myocardial enhancement (DME), also described as late gadolinium enhancement (LGE), is the information unique to the modality. [2] MRI evaluation also has a very effective role in the post-interventional evaluation. Post-interventional changes following alcohol injection are widely reported in patients with HCM. [3]. On the other hand, there are few reports of postmyomectomy changes evaluated by MRI. [2] CASE REPORT Clinical, MRI, and echo observations of three patients of HCM treated with LV myomectomy are presented. Pre-and post-operative MRI imaging parameters and echo results are presented in Table 1. Case 1 A 55-year-old male patient with clinical suspicion of HCM was investigated with echo and MRI. Asymmetrical LV hypertrophy involving the basal (22 mm) and mid-septum was demonstrated [ Figure 1]. ere was associated systolic anterior motion (SAM) of the mitral valve (MV) with severe LV outflow tract (LVOT) narrowing and flow acceleration. Mild obliteration of the apical LV cavity was seen. ere were moderate mitral regurgitation (MR) and mild tricuspid regurgitation (TR). On contrast MRI, mild patchy DME was noted in the basal septum and right ventricular insertion points. He had low-normal indexed LVEDV and LVESV with hyperdynamic LV systolic function. Post-operative echo and MRI at 6 months, after myomectomy of the basal septum, showed minimal residual concentric LV hypertrophy with reduced LVOT narrowing. No regional wall motion abnormality was noted. ere were moderate MR and mild TR. On DME, there was a thin rim of mild subendocardial enhancement from basal septum to apex [ Figure 1]. Case 2 A 27-year-old female suspected of HCM was investigated. Asymmetrical hypertrophy of basal, mid-septum, and anterior segments was seen with hypokinesis of the segments and SAM of mitral leaflet with LVOT obstruction. Mild patchy DME was noted. e patient following transaortic extended myomectomy showed impaired LV systolic function with asymmetrical LV hypertrophy (LVH) [ Figure 2]. ere was persistent hypokinesis of the apex and apical anterior segment. On DME, there was near transmural enhancement [ Figure 2]. Case 3 A 57-year-old male was a known case of triple-vessel disease with worsening of angina. Echocardiography showed LVOT turbulence, concentric LVH, and hyperechoic septum. MRI confirmed LV asymmetrical septal hypertrophy at mid-cavity, anteroseptal segment, and obliteration of the LV apical cavity during systole [ Figure 3]. ere was LVOT narrowing with SAM. Hypokinesis of the basal and mid-septum was noted. ere were mild MR and TR. ere were patchy areas of subendocardial enhancement at LV apex. FU after transaortic septal myomectomy revealed no significant gradient across LVOT or wall motion abnormality. ere was asymmetrical LVH with severe hypokinesia of the apical, basal, and midsegments of the septum. ere was a lamellated, adherent LV thrombus at apex [ Figure 3]. On gadolinium-enhanced images, there was near transmural enhancement of the LV apex with subendocardial septal enhancement. DISCUSSION Established MRI abnormalities in patients with HCM are asymmetrical thickening of septum and narrowing of LVOT (20-30%). [4] e extent of narrowing varies at rest, may be latent or labile. A gradient of 30 mmHg or more is now generally considered significant for prognostic importance. [2] LVOT narrowing and outflow gradients are best assessed with echocardiography. On MRI contrast-enhanced examination, patchy DME of mid-septum occurs in up to 80% of patients. [5] Abnormalities of the MV movement, such as SAM, occur at the portion of the anterior mitral leaflet distal to the coaptation point as the valve being displaced into the LVOT by Venturi (drag) forces. [2] Other findings are diastolic dysfunction and LA enlargement. Apical form of HCM is a rare presentation, wherein absolute apical wall thickness of >15 mm is noted or a ratio of apical LV and basal LV wall thicknesses of ≥1.3-1.5 is seen. [3] HCM with mid-ventricular obstruction presents as mass-like thickening

of the LV. "Burned-out phase" is noted in up to 10% of patients, often presents with LV dilatation, loss of myocardial thickness, and replacement fibrosis. Detailed evaluation of myocardial interstitial changes and altered flow kinetics is well shown with presently available MR techniques. [6] e risk of sudden death in HCM patients increases with the following MR criteria: 1. LV maximal wall thickness of 30 mm or more. 2. LVOT gradient of 30 mmHg or more at rest or 50 mmHg or more with provocation. 3. LV dilatation with depressed EF. 4. e presence of fibrosis, perfusion defect, and reduced functional reserve flow. [7,8] Septal myomectomy is considered the gold standard among septal reduction techniques currently in use. [4,9] Techniques for septal myomectomy are LV and transaortic routes. e transaortic approach is indicated in patients with LVOT obstruction. In our first patient, both echo and MRI showed interval resolution of LVOT narrowing and flow acceleration. No regional wall motion abnormality was detected in both modalities. MRI showed better EF (67% -MRI and 55%echo) accurate measurement of residual septal thickness (18 mm -MR and 15 mm -echo). e DME on MRI showed the extent of post-operative scar tissue. In the second patient, MRI detected residual septal thickening in midseptum which was not detected by echo. Both examinations showed interval resolution of LVOT narrowing and flow acceleration. EF was comparable. MRI additionally showed hypokinesis of the basal and mid anteroseptal segments and the apex with near transmural DME. In the third patient, there was LV thrombus at the apex, post-operative scar with akinesia of the apical segment, and hypokinesia of basal and mid-septum only shown on MRI. Assessment of EF, interval resolution of LVOT narrowing, and residual septal thickness was comparable in both modalities. In all patients, MRI provided additional, more accurate information compared to echo with better understanding of post-operative state and some valuable information for immediate patient care. MRI was superior in measurement of residual thickness and detection of regional wall motion abnormalities. T1 mapping techniques appear to have a potential role in identifying and quantifying diffuse myocardial disease. [10] LGE is sensitive in detecting focal myocardial fibrosis, which is an end-stage feature of the disease. However, LGE is less sensitive to diffuse inflammation and myocardial remodeling, hence underestimates the overall disease burden. Patients with HCM show high T1 indices in overt disease as well in subclinical disease state. us, T1 mapping may find an important role which is identifying subclinical disease in genetically susceptible population and monitoring the course of the disease. Evolving MR techniques and ease of affordability certainly will drive this advantage further by shorter examination time and more accurate assessment of structural and functional parameters. Clinical impact of observed "MRI advantage" on the overall patient management needs to be evaluated further in larger data sets. Echocardiography certainly has the great advantage in ease of use and clinician comfort. Availability, cost factor of MRI examination, and gadolinium contrast-related issues are important factors which will play a significant role in selection of the examination. CONCLUSION Cardiac MRI is an extremely valuable non-invasive tool to assess pre-and post-operative state of HCM. At present, echo assessment remains a comprehensive, practical tool for post-operative assessment. However, our study demonstrates superiority of MRI inputs in the assessment of patients following septal myomectomy. Clinically, relevant observations not evident on echocardiography were noted in our patients. Emerging T1 mapping techniques appear to have a role in assessing focal and diffuse myocardial changes in overt as well as subclinical disease. We see a definite role for a post-operative MRI in certain patients such as the one with incomplete clinical relief, in those with suboptimal echocardiography information, and in patients with post-operative complications. Considering availability, cost factor, and contrast-related issues with MRI, we defer recommending routine MRI post-myomectomy in all patients. In view of greater availability and rapid developments in MRI technology, it is worth exploring the role of MRI in these groups of patients for more accurate results. Spanish Legal Reproscape: The Making of a Bio- Industry Europe accounts for the largest number of assisted reproduction treatments (ARTs) in the world, with 56 percent of the global reproductive market quota, followed by Asia (23 percent) and North America (15 percent). However, Europe’s legal landscape of reproductive bio-commodities is a patchwork of permissive and restrictive countries, one of the main reasons for the transnational movement to access ARTs. Spain is the main destination for European middle- and upper-class couples seeking egg donation. The use of legislation has been a significant feature in making Spain a leading country in the global reproscape. This paper aims to understand the specific role of several undetermined legal concepts used by the Spanish regulation, such as “compensation” or “best interest of the child” in making global reproductive bio-commodities. Introduction Europe accounts for the largest number of assisted reproduction treatments (ARTs) in the world, with 56 percent of the global reproductive market quota, followed by Asia (23 percent) and North America (15 percent). 1 However, Europe's legal landscape of reproductive bio-commodities is a patchwork of permissive and restrictive countries, one of the main reasons for the transnational movement to access ARTs. 2 Spain is one of the priority destinations for couples and women in Europe demanding eggs. Over half the donated ova used in in vitro fertilization (IVF) cycles across Europe come from Spain. 3 Within the global bioeconomy, Spain counts as a safe hub for fertility treatments since they are offered in a formally well-regulated and publicly insured health system. However, the result is that the demographic profile of "altruistic" donors intersects with the lowest echelons of informal service labor, recruited from young, marginalized segments of the population. The Spanish reproscape has been shaped following the first Act on assisted reproduction 30 years ago. The law's role in legitimizing new reproductive bio-commodities, such as human eggs, has significantly influenced the rise of Spain's popularity as a destination country for fertility treatments. The Spanish case highlights the arguments made by Cooper and Waldby that the use of bioethical guiding principles (e.g., "donation" and "compensation"). It has proved remarkably useful to the task of governing a precarious reproductive market of immigrants and young women that justifies exemptions from the standard protection offered by statutory labor contracts. 4 In this article, I re-examine the history of the ART regulation in Spain (the first extensive law of reproduction in Europe). Following this, I will address the criticism of egg donation regulation, focusing specifically on the anonymity, compensation, and filiation concepts. I will also discuss the recent proposal to legalize surrogacy in Spain and draw some parallels between ova donation and surrogacy regulation. Finally, some provisional conclusions about the impact of these concepts on the female body's legal status will be proposed. Europe accounts for the largest number of assisted reproduction treatments (ARTs) in the world, with 56 percent of the global reproductive market quota, followed by Asia (23 percent) and North America (15 percent). However, Europe's legal landscape of reproductive bio-commodities is a patchwork of permissive and restrictive countries, one of the main reasons for the transnational movement to access ARTs. Spain is the main destination for European middle-and upper-class couples seeking egg donation. The use of legislation has been a significant feature in making Spain a leading country in the global reproscape. This paper aims to understand the specific role of several undetermined legal concepts used by the Spanish regulation, such as "compensation" or "best interest of the child" in making global reproductive bio-commodities. Thirty Years of the Act of Assisted Reproduction in Spain Despite its discreet approval, the Spanish law 35/1988 of November 22, 1988, on assisted human reproduction techniques (LTRHA) was the third Act in the world concerning the date of enactment after Victoria (Australia) 5 and Sweden (which only referred to artificial insemination). 6 The LTRHA was preceded by a Parliamentary Report on ART, 7 which formed the Act of 1988. The Spanish Act surprised the world by its "liberality." It has been considered one of the most liberal pieces of ART regulation in the world. 8 In 1988, it declared the right of single women to become a mother through sperm or embryo donation (art. 6.1 LTRHA) and the access of widowed women to the sperm of her deceased partner. A complex and integrated anonymous gamete donation system was meant to be put in place by latter development decrees. Embryo cryopreservation was authorized, and no prohibition was settled on research on it. The sole, relevant limit settled by the Act was the prohibition of surrogacy (in all forms). The law considers that surrogacy contracts are void and reinforces the presumption that the child's mother gives birth to her (art.10 LTRHA). The LTRHA came ahead of society's needs of the moment in 1988. 9 However, it also fits in with the need to modernize the country, which yearned to leave behind a long dictatorship and open channels to society's changes.The regulation of biomedical treatments in Spain had opened with the 1979 Transplants Act, considered in its day as one of the most advanced in the world (it established the principle of donation by default and an integrated system of waiting lists). 10 In the 1980s, there was also the major reform of the family law, the decriminalization of abortion, the General Statute of Health's approval, etc. As such, the LTRHA was not such an exotic piece of regulation as it may seem, but rather it was fully inscribed in the legislative trend of the period. The LTRHA was hailed by the medical profession internationally. It was observed as a progressive law that would allow the proper development of procreation technologies in Europe. 11 Conversely, it provoked great disappointment and rejection by jurists. They branded it technically deficient ("as it has been written by a doctor instead of a lawyer"), 12 and it was not sufficiently discussed in the Parliament. 13 The jurists also denounced the excessive delegation of the applicable standards on health authorities. The law had provided for making regulations implementing several fundamental issues, such as accreditation requirements for the fertility treatment centers; information protocols for donors; creating a national registry of donors; centers' activity registry; creating the National Commission for Assisted Human Reproduction (CNRHA); and a list of hereditary diseases that could be screened on the embryo. Only four out of the six regulations were finally made. The first two were enacted seven and a half years after the Act's commencement. The fourth took another six months to appear, ordering the creation of the National Commission for Assisted Human Reproduction. The Donor Registry has been enforced only recently, forcing fertility centers to provide data to the Assisted Human Reproduction Information System (SIRHA). 14 The LTRHA has been revised twice since its introduction. The first turned out to be an ephemeral reform, passed in 2003 15 and overturned in 2006. The reform responded to the case made by the Catholic Church about spare embryos from IVF treatments. The reform settled that only three oocytes could be fertilized in each cycle. The clinics protested the reform vigorously, asking for the limitation to be removed, which happened in 2006 (Act 14/2006 It also allowed pre-implantation genetic diagnosis for therapeutic purposes and "designer babies." Researchers congratulated the government and considered it "research-friendly." 17 Over thirty years after the enactment of the LTRHA, Spain holds the record for the highest number of private clinics in Europe. 18 Spain has become one of the prominent global hubs for assisted reproduction. The clinics treat women from all over Europe, and there is an increasing number of local couples and single women demanding fertility treatments. The average age of local female patients in 2018 was 39 years, along with the ever-increasing maternity age of Spanish women. 19 More recently, new demands on assisted reproduction are being made by intending parents asking for equal access to parenthood through surrogacy. Egg Donation in Spain More than half of the oocytes implanted in European fertility clinics come from Spain. 20 Of this large number of gametes, 80% have been provided by national women and the rest by non-national residents. 21 Spanish fertility clinics have become the preferred destination of German and Norwegian women seeking treatments prohibited in their homeland. French and British women who have difficulties accessing ova

donation locally due to the lack of available eggs in their countries also come to Spain. Additionally, most couples who wish to keep their infertility treatment a secret arrive at Spanish hospitals in summertime pretending to be on a holiday trip to the Mediterranean. 22 Another attraction of the Spanish ova market lies in the donors responsible for one of the highest rates of efficiency concerning pregnancies achieved by cycle. 23 Leftover eggs from IVF treatments (i.e., women who use their eggs in autologous IVF cycles) are rarely used in Spain. Spanish hospitals' egg supply and competitive prices occur because donors are compensated with 1000€ each cycle under a very strict regime of anonymity covering the donors' and beneficiaries' identities. Anonymity of the Donor The LTRHA mandated absolute confidentiality on treatment data and the identity of the donor and recipient. On many occasions, couples have tried to thank their donor, but the physicians would answer that they cannot give any contact information (not even through the center). Even donors who wanted to learn about the donation's result have not obtained any response. The doctors and health professionals will not even tell them if the donation resulted in birth or proved fruitless. Any breach of this rule makes the biomedical and administrative team responsible for a severe crime. 24 Notably, the origin gamete donation rules (anonymity and compensation) comes from the regulations of the first semen banks that emerged in Europe in the 1970s. 25 These rules, devised by doctors and the health authorities of the time, were automatically applied to egg donation regulation in the LTRHA following IVF's introduction. The early acceptance of anonymity comes as no surprise, given the medical profession's strong influence on the provisions of the 1988 Act. In contrast, most lawyers of the time made numerous objections to the requirement for anonymity. 26 These objections followed from reform in 1981 to the Civil Code, whereby the principle of biological truth was adopted following the mandate of the 1978 Constitution (art. 39.2 CE). The jurists' doubts were reflected in the Palacios Report, 27 but the Parliament finally settled the issue by adopting the rules of anonymity of semen banks defended by doctors. Once this milestone was settled, fertility centers have very narrowly interpreted the anonymity ruling. Data about the donor are recorded at the fertility center. In adoption, the adopted child could access the civil registry data when she is 18. 28 In contrast, the information the donor child can get about her conception is completely left to the parents' will since there is no record or register on the issue outside the clinical record. 17 Comparable jurisdictions, such as the British 29 and Swedish 30 in Europe, or Victoria in Australia, 31 have reviewed this rule of anonymity and recognized the child's right to know her origin. They also stated that this right refers exclusively to access the donor identity data, while in no case does such knowledge allow any claim of parenthood. Therefore, it is not a rule of parentage law but a personal right to know a relevant piece of identity information. The right to know the biological origin as a fundamental right has been recognized by many more European countries in the last decade (Finland, Netherlands, and Belgium). Furthermore, the European General Data Protection Regulation (EU) 2016/679 (GDPR) could oblige European fertility clinics to inform donor-conceived people about the existence of clinical files that contain very sensitive information about them. Under the new regulation, the right of access (Article 15) is a personal right. It gives citizens the right to access their personal data and gain information about how this data is being processed, such as the purposes of the processing, with whom the data is shared, and how the data is acquired. A data controller must provide, upon request, an overview of the data categories that are being processed and a copy of the actual data. Hiding sensitive information about the biological origin and preventing offspring access to donor information files "for her own sake" could breach the general principle of accessing sensitive data. Ultimately, it must be discussed if the conflict between the donor's privacy and the legal parents against the child's interest in knowing their origin should be resolved in favour of the latter. It has been said that the right to know the genetic origin can be interpreted as an aspect of the ever-evolving right to health since genetic testing is gaining more momentum. 32 It is also very relevant information for donor-conceived people when they decide to have children themselves. The genetic origin will be routine information that is difficult to keep secretive shortly since genetic screening combined with the gene matching platforms and Internet web sites continue to expand. So far, the arguments used to defend the child's right involve informing her of their biological origin. Still, there is also another consequence of the anonymity rule that is rarely cited. I am referring to the donor's invisibility from the obligation of anonymity that is imposed upon her. As we have observed, donors who request information from the clinics in Spain find that the clinics refuse to provide information on the donation results. All the donor's involvement with the child is radically cut after the donation, except where the newborn needs some health assessment that requires the donor's intervention. However, doctors will do their best not to disclose the donor's identity even in this case (art. 5.5 LTRHA). This institutional effacement also has an important implication from the perspective of donor rights and bio-value transference. Physicians and the law have conceptually framed assisted reproduction to imitate biological reproduction. Gametes are exchanged as if it could consist of a simple exchange of tissue. In reducing the meaning of donating to "giving tissue," as the clinics claim, the nature of the transmission is denied. As Sara Lafuente has put it, we should frame it as a transference of reproductive capacity instead of talking about egg donation. 33 Compensation: Quid Prodest? The medical practice of compensating donors with a fixed price, pre-agreed between clinics, was initially tolerated by authorities and later sanctioned by the law. 34 In 1998, one year after its establishment, the Spanish National Commission on Assisted Reproduction was consulted on donor compensation. At the time, young women donating their oocytes were being compensated 600€. The Commission first examined the issue in 1998 and decided that: The financial compensation of 100,000 pesetas (600€) per donation for the donation of oocytes (equivalent to twenty times the usual compensation by sperm donation) is proportionally acceptable for compensating a greater discomfort and damage caused by oocyte extraction, thus it should be considered that this emolument does not break nor undermine the principle of gratuity or disrepute of the purely altruistic motivation of the donor. 35 At this point, differences between public and private clinics were made evident since, in public hospitals, compensating donors with any amount is not allowed. The 2006 Act revisited the issue and ordered the Health Ministry to fix the criteria and the limits for this compensation, "so that compensation is not the sole incentive for donation." 36 Yet, this even more diluted and weak limit was never implemented. Clinics have held their ways, and they keep adding the Consumer Price Index (CPI) to calculate the annual "fee," which was around 1000 € in 2020. This amount is enough incentive for young women who are not well off in Spain. The case illustrates how clinics have profited from the gray zone of the term compensation to make an expansive interpretation accepted by the public authorities that has never been challenged in a court to date. Therefore, it is necessary to review the whole concept of "compensation" to return to the path of the prohibition of trade in human gametes. The rule of property is not an adequate frame for regulating gamete transfer, as long as they are both elements of human reproduction and elements of human reproduction. This pretension is regressive since it goes back to atavistic ownership models on human body parts wiped out by the modern legal systems. Human gametes must remain extra commertium; they are not suitable for appropriation and transfer by price as elements of the human body and because no person can claim to own the human genome of another, not even her own. Some time ago, Europe established the rule that human DNA is not appropriable concerning patenting the genome. 37 This same rule should apply when it comes to establishing parenthood relationships. Crossing the Rubicon: The Debate on Surrogacy in Spain From its commencement, the LTRHA stated that surrogacy contracts are void, and the woman who gestates and gives birth is the legal mother of the child born. This applies the rule mater semper cert est, combined with the legal prohibition to challenge her motherhood. 38 Balancing Eggs and Gestation The Palacios Report refused surrogacy, arguing that "this kind of contract is unacceptable in a fair and democratic society, as there is an increased risk of abuse and commercialization of vulnerable women." 39 Notably, these same risks of abuse and commercialization were not appreciated concerning egg donation at that time. Perhaps the explanation lies in the conflict between genetic maternity and pregnancy maternity raised a little further in the same report. Regarding this conflict, the Commission concludes: The gestational component is more important than the genetic one, as the gestating mother bears the child within her for nine months and protects the child physiologically and psychologically, this being an element that will give priority to the childbearing woman, and opposes surrogacy. In this sense, we recommend that the biological preponderance of gestational maternity over the genetic one is admitted and that the legal mother is always the gestating mother, even if originally there was an intervention of donors. 40 Thus, according to the Spanish legal order, egg donation, even challenging the principle of biological truth, will be an acceptable practice if the cause of the transfer of gametes is altruistic. Conversely, surrogacy, no matter if the cause is commercial or altruistic, would be unacceptable because contracting pregnancy services undermines the woman and child's dignity. 41 In Spain, as in other legal systems that allow egg donation but reject surrogacy, pregnancy enjoys a different legal consideration or value compared to gametes. In all cases, the kinship is determined by labor and childbirth, regardless of whether there is a genetic link between mother and child. This prohibition accounts for a strong public order principle. Reproductive Tourism and Fait Accompli Politics Given the prohibition to contract surrogacy services at home, couples seeking surrogate mothers flocked to California guided by Spanish fertility clinics that held commercial agreements with local Californian surrogacy agencies since the mid-eighties. 42 More recently, as new hubs began to emerge in countries such as Tabasco (Mexico), India, Thailand, and Europe (Ukraine and Russia), for-profit intermediary agencies began to arise. These agencies can freely move to Spain, offering brokerage services to couples and individuals wishing to have children through surrogates abroad. 43 Stimulated by lower prices, surrogacy figures soared; informal data show that surrogacy has surpassed the number of international adoptions in Spain. 44 In the beginning, there were no problems with Spanish citizens returning home with the newborn. For over a decade, Spanish authorities at the Consular Registry tolerated the practice of considering intended parents as the natural parents of the offspring born abroad. 45 It was not until the recognition of same-sex parentage that case law on the issue began to emerge. child in the Consular Registry made visible an issue that was previously covered up conveniently by the façade of heterosexual couples giving birth abroad. In this case, the intended parents, two Spanish men, sought to register the official birth certificates of surrogate-born twins in conformity with a pre-birth judgment issued by a California court, with no reference to the genetic or gestational parentage of the twins. The consulate refused to register them as legal parents, and the children were denied visas to travel to Spain. A court hearing the matter declared that it was a violation of Spanish law not to include the gestational mother as a parent in the registry since the primary and most important fact for this purpose was who gave birth. 46 At

the same time, the Spanish Parliament had been sized to address surrogacy, among other issues concerning the revision of the LTRHA. However, the Parliament refused to tackle the problem since there was no minimum consensus on the matter. 47 The new law of reproductive technologies of 2006 kept the exact same wording for the surrogacy regulation as the original 1988 Act. At this point, the Spanish Ministry of Justice intervened to establish guidelines for entry into the civil registry of children born to surrogate mothers abroad. 48 The Ministry found it necessary to balance the children's interests with the Spanish government's interests in prohibiting surrogacy. It concluded that his balance could be achieved by obtaining a judgment in a host country court, recognizing the birth certificate's legal validity, and making factual findings that the surrogacy contract was entered into without fraud, overreaching, or exploitation of the surrogate mother. 49 The General Public Prosecutor challenged this instruction before the Supreme Court. The resolution of the court (STS 247/2014, April 6, 2014) ruled against the instruction, condemning surrogacy contracts as incompatible with Spanish public order: […] Surrogacy is a means for commodifying gestation and legal parenthood, also meaning "reification" of the pregnant woman and the child, allowing certain intermediaries to conduct business by exploiting young vulnerable women and creating a kind of "selective-citizenship" in which only those with high financial resources can reach parenthood, in ways that the majority of the population cannot afford. 50 Still, the Court also suggested that nothing prevented the genetic father from registering as the child's legal father. After that, the resolution said, the spouse could adopt the child also to become a legal parent. 51 At this point, Spain's Civil Registry Law has been amended to deal more directly with birth certificates issued by other countries in international surrogacy cases, strengthening the requirements for the intended parents to get access to the registry. 52 As is the case in other European countries, these decisions show that Spain deploys a fait accompli politics in surrogacy. Commercial surrogacy is prohibited at home but is tolerated when done abroad, as long as Spanish citizens may get a desired result from the domestic courts of becoming the child's legal parents, invoking the child's best interest overrules the public policy prohibition. The Jurisprudence of the European Court of Human Rights The jurisprudence of the European Court of Human Rights on recognizing legal parenthood in surrogacy cases is quite consistent with the Spanish Supreme Court´s position. In fact, the European Court has condemned France for preventing the genetic father of the offspring to register as the child's legal parent in several partial surrogacy cases (Mennesson v. France 53 , Labasse v. France 54 ). This jurisprudence invokes the right to respect the private life (within the meaning of Article 8 of the European Convention of Human Rights) of a child born abroad through a gestational surrogacy arrangement. This requires the legal relationship between the child and the intended father, where he is the biological father, to be recognized in domestic law. However, the court has approved the Italian Government's decision to consider adoption and deny the legal parenthood of intended parents where there was no genetic tie among the offspring and the intended parents (Paradiso & Campanelli v. Italy). 55 recently, the court has given an Advisory Opinion, stating that respect for private life within the meaning of Article 8 of the Convention also requires that domestic law provide a possibility of recognizing a legal parent-child relationship in certain instances. This applies if there is an intended mother (who is designated in the birth certificate legally established abroad as the "legal mother"), the child was conceived using the eggs of a third-party donor, and the legal parent-child relationship with the intended father has been recognized in domestic law. 57 The domestic proceedings do not concern a child born through a gestational surrogacy arrangement abroad and conceived using the intended mother's eggs. However, the Court considers it important to emphasize that, where the situation is otherwise similar to that in issue in the proceedings, the need to recognize the legal relationship between the child and the intended mother applies with even greater force. 58 A resolution similar to that of the European Court of Human Rights has been provided by other European countries where surrogacy arrangements are prohibited. In several states where surrogacy contracts are forbidden, it is, nonetheless, possible for an intended father who is the biological father to establish paternity concerning a child born through surrogacy. Further, some of these countries permit an intended mother to establish maternity of a child born through a surrogacy arrangement to whom she is not genetically related. The procedure for establishing or recognizing a legal parent-child relationship between children born through a surrogacy arrangement and the intended parents varies from one state to another. Several different procedures may be available within a single state. The avenues available include registering the foreign birth certificate, adoption, or court proceedings not involving adoption. 59 This regulation shows that the appropriate role of states' public policies against surrogacy in applying the current law remains contested. The concern about these minors' situation has prompted the European Court pronouncements, where the best interest of the child and the decisions in concreto have resulted in enforcing the effects of surrogacy contracts by the back door. The Terms of the Debate in Spain: Defusing Altruism The Spanish Supreme Court's decision condemning commercial surrogacy 60 incited parents' associations, especially ones belonging to the gay community, to ask for the legalization of altruistic at-home surrogacy. Intending heterosexual parents coalesced with other progressive campaigns to widen the scope of what constitutes "a family," to include gay couples and single parents. 61 Gay men are heavily represented in this campaign and have pressed for the legalization of surrogacy contracts as a logical consequence of the Same-Sex Marriage Act 13/2005. In 2018, the Spanish Fertility Society (SEF) and the liberal party Ciudadanos supported the pro-surrogacy camp and proposed a Bill to legalize altruistic surrogacy. 62 Its main premise consisted of stating the fundamental right of every citizen "to start a family by means of surrogacy" in the name of "the evolution of liberty, the enrichment of the personality and the multiplicity of ways of understanding the personal and social life." 63 The Bill proposed "compensating" the surrogate for the expenses and economic losses that pregnancy and labor should carry. 64 However, surrogate compensation would follow the same path as egg donor compensation. It would also become an incentive for the candidates. Once again, the construction of the term "compensation" could be used to disguise the practice of exploiting young, vulnerable women. Conclusions Many European countries decided to close the doors to donor-assisted ART in the 1980s. This was not the case for Spain, which decided to take the flag of progress, enacting a permissive ART statute allowing all techniques and forms of donation, except for surrogacy contracts. In 1988, the LTRHA considered surrogacy as the Rubicon of the Spanish reproscape. Thirty years later, Spain has become a privileged destination for patients seeking donated ova and other treatments, while Spaniards travel to foreign destinations searching for surrogate mothers. As evidenced by the previous examination, the law played a central role in this process, both by default and excess. The principles of altruism and anonymity of the donation were first adopted by the regulation of ART in 1988, resulting in desultory 57 ECHR, Advisory Opinion concerning the recognition in domestic law of a legal parent-child relationship between a child born through a gestational surrogacy arrangement abroad and the intended mother. 58 ECHR, Advisory Opinion concerning the recognition in domestic law of a legal parent-child relationship between a child born through a gestational surrogacy arrangement abroad and the intended mother. 59 ECHR, Advisory Opinion concerning the recognition in domestic law of a legal parent-child relationship between a child born through a gestational surrogacy arrangement abroad and the intended mother. 60 Sentencia del Tribunal Supremo, 2014. 61 "Son Nuestros Hijos", 2020. 62 Surrogacy Bill, 2017. 63 Surrogacy Bill, 2017, Preamble 64 Surrogacy Bill, 2017, art. 5. ways of institutional effacement of the donors. The prohibition of disclosing information about the donor is mainly used to provide an appearance of "naturalness" to the assisted procreation. However, it is at the price of ignoring the child's right to know her biological origin and that of the donor to recognize her contribution. The Spanish case also illustrates how clinics have profited from the gray zone of the term "compensation" to make an expansive interpretation, accepted by the public authorities and so far never challenged in a court, to attract donors with a fixed price of 1000€ per cycle of hormonal stimulation. This way, under a guise of compliance with the universally admitted bioethical principle of donor compensation, a precarious and informal donor market of immigrants and young women has been established. Under the cover of a safe and legal offer, a contingent of young women, mostly students, 65 serves as an unregulated workforce to provide ova for a pittance. At the same time, Spanish citizens easily circumvent the insufficient regulation about surrogacy by seeking the services abroad, as is the case in many European countries. The fait accompli fulfils the legal vacuum. . Commercial surrogacy is prohibited at home but tolerated when done abroad. This is true as long as Spanish citizens may actually achieve the desired result from the courts of becoming the child's legal parents, invoking the child's best interest, which overrules the public policy prohibition. . The undetermined legal concept "best interest of the child" is used to legalize this contract's effects, recognizing parenthood to the intended biological parent through the civil registry. Reframing ART in Spain could consist of correcting the excess and vacuum. The new donor-assisted reproduction model requires disclosing the donor's identity and recognizing donor-assisted reproduction as a third form of parenthood determination. We should avoid the simulation that operates in the present law and recognize openly, with all its implications, that there is another way of becoming a legal parent with the intervention of a gamete donor. The new regulation of this form of childbearing with donor intervention could be attempted at the Civil Code, adding a third typology to the existing biological and adoptive forms. Conversely, it is necessary to review the rhetoric of "compensation" to return to the path of the prohibition of marketing human gametes. Regarding surrogacy, sufficient regulation explicitly prohibiting commercial contracting and condemning intermediaries should be in place. Further decisions on the legal parenthood of children born in foreign countries based on the child's interest should not substitute the responsibility of international bodies (The Hague Group, the European Council, and the United Nations) to finally condemn commercial surrogacy as a form of gendered human exploitation. Coronavirus 2019 (COVID-19) Detection Based on Deep Learning Accepted: 21st Nov. 2020 Abstract Deep learning modeling could provide to detected Corona Virus 2019 (COVID-19) which is a critical task these days to make a treatment decision according to the diagnostic results. On the other hand, advances in the areas of artificial intelligence, machine learning, deep learning, and medical imaging techniques allow demonstrating impressive performance, especially in problems of detection, classification, and segmentation. These innovations enabled physicians to see the human body with high accuracy, which led to an increase in the accuracy of diagnosis and nonsurgical examination of patients. There are many imaging models used to detect COVID-19, but we use computerized tomography (CT) because is commonly used. Moreover, we use for detection a deep learning model based on convolutional neural network (CNN) for COVID-19 detection. The dataset has been used is 544 slice of CT scan which is not sufficient for high accuracy, but we can say that it is acceptable because of the few datasets available in these days. The proposed model achieves validation and test accuracy 84.4% and 90.09%, respectively. The proposed model has been compared with other models to prove superiority of our model over the other models. Introduction New coronavirus (COVID-19) formerly known as (2019-nCoV) [1]- [2], has been reported in Wuhan, China [2]- [6], since late December 2019. The personto-person transmission has affected 212 countries around the world [6,7]. Overall, COVID-19 is considered an acute disease but can also be

fatal, with a 2% mortality rate. Severe illness may result in death from massive alveolar progressive respiratory damage and failure [2,8]. Until this writing moment, there has NJES 23(4)408-415, 2020 Sadoon & Ali 409 been a rapid increase in the number of corona disease cases as well as the number of deaths. From the situation report in Word Health Organization-209, 16-August-2020, there are globally 21,294,854 confirmed and 761,779 deaths [9]. Computed tomography (CT) is the preferred imaging method for diagnosing the new COVID19 [10]. However, CT is a well-known medical imaging method used to produce cross-sectional slides (slices) of specific areas of a scanned body. Therefore, the user will be able to see the objects scanned from the inside without cutting. To do this, they use many computerprocessed combinations of X-ray measurements from different angles to photograph the slice [11,12]. Machine learning algorithms such as deep learning play a vital role in the diagnosis of the disease [13]. There are three categories of machine learning, supervised learning, unsupervised learning, and reinforcement learning. In supervised learning, the training data set must consist of the correct input and output together. For example, regression, and classification. While, the training data in unsupervised learning contain inputs only without valid outputs. It is used for clustering. Reinforcement learning uses input, output, and grade in the training data. Such as control and game plays [14]. Deep learning is one types of machine learning algorisms based on used many layers to extract the feature. In contrast, the others machine learning algorithms the feature extraction is independent of the algorithms [15]. Convolutional Neural Network (CNN) or ConvNet, is common deep learning algorithms used for medical image processing, and were largely revived in 2012 when Krizhevky and others proposed a CNN model called Alex-net [16]. Since there is no much research in this felid, we are building a CNN-based deep learning model for classifying a lung CT image to COVID-19 and NonCOVID-19. Then we compare our results with a pre-trained ResNet-50 and Alex-net model. Moreover, we can ignore the accurate classification due to the small input data set. In the future, an accurate model can be built on the available materials, and the accuracy increase about 10% and reach to 95% depended on the number of data set. In [17], Shuai Wang1, et al. proposed a deep learning model to classify CT scan of COVID-19. The model based on extract the Region of Interest from the CT slice and the applied transfer learning neural network based on Inception network. After that, they use Decision tree and Adaboost to improve the classification accuracy. The validation accuracy and testing are 82.9% and 73.1% respectively. While Xiaowei Xu1, et al. in [18] used a pre-trained ResNet-18 model to classify CT slice of lungs into COVID-19, Influenza-A viral pneumonia, and healthy cases. The author firstly candidate the segmentation region as preprocessing step. Then, they use a calculation method to distinguish the structure of the infection as a feature. After that, a pre-trained model was used for classification. The overall accuracy was 86.7%. Currently, the strength of deep learning frameworks and the power of the graphics processing unit (GPU) that helped design, train and validate deep neural networks, in addition to that, helped to develop many models in these years. These models can be run through a high-level programming interface that relies on NVIDIA GPUs accelerated libraries. Common deep learning frameworks are: PyTorch, MXNet, TensorFlow, MATLAB, NVIDA Caffe, Chainer, PaddlePaddle [19]. In this study, we use MATLAB 2018 frameworks, and the powerful of GPU and CUDA from NAVIDA Geforce 920M. This paper is structured in form; in section 2, the pre-processing and augmentation of data is discussed, then in section 3 the proposed model is discussed with all the details. After that, the experiment and outcome were discussed in Section 4 followed by a conclusion in section 5. Data pre-processing and augmentation Due to the novelty of the disease, we relied on this data that available in [20] to carry out the research process. These data set contains 349 CT slices of COVID-19, and 195 CT slices of NonCOVID-19. Pre-processing is very important step before the images fed into the models, to correct, adjust, and obtain non-contaminated medical image and this is led to improve the performance, and also decrease the complicity of the models [21]. In this study, we downscale the image into 128x128 and then applied the Gaussian filter to remove the noise that generate during diagnose from patients moving. Moreover, the data has been shuffled during the training every epoch. The data set is divided into 79% for training, 20% for validation, and the remainder for model testing. After that, to reduce the overfitting as well as increase the data set, we augment the data using many methods, such as add salt and paper noise, flipping, rotation with 45, 135, 180, and 360 angles, and mirror. The data set became 4352 after data augmentation. Fig.1 and Table 1 show an example of CT slice from the data set and the number of data before and after augmentation. CNN model for covid-19 detection CNN is a deep neural network that has many hidden layers, these layers are used to extract the feature from the input image. The more hidden layers, the more feature extraction [22]. ConvNet include 20 layers began with the input layer that take the input image and at last classification layer which make the last decision for classification, and in between the hidden layers. We should note that, the numbers of layers, and each parameter were selected by trial and error. Convolutional layer In this layer, the input image has been convolved with convolutional filters (also called kernel) to extract the feature, and the output is called feature map, which is equal to the number of kernels [13]. In this work, the number of filters is 48, 64, 96, and 128 with kernel size 5x5, 7x7, 9x9, and 11x11 respectively. The stride (which is mean by moving the kernel by one step size or more through convolutional operation) size is 1,1,1, and 2. While the padding (which is mean adding more row and column around the image matrix) size is 0, 1, 2, and 2 respectively for each convolutional layer. Figure (2) show an example of convolutional layer with kernel size 3x3, stride size 1, and padding size 0. Rectifier Linear Unit (ReLU) Each convolutional layer followed by ReLU activation function, used to solve vanishing gradient problem through back-propagation algorithm [23]. Figure 3 show the behaviour of ReLU function. Pooling layer To reduce the dimension of the feature map, and as a result, the complexity of CNN, we can use pooling layer. In this study, we use max pooling layer with size of 2x2, and stride size of 2x2 in all max pooling layers. Figure 4 show the basic work of max pooling layer. Figure (4) show an example of max pooling layer. Batch Normalization Used to normalize the data set during training processing instead of normalizing all the data set in the pre-processing step, it can be decreasing the training time [25]. Dropout Layer Dropout layer selected some nodes randomly depended on percentage value. This layer is a common method to prevent overfitting. The dropout ration used in this model was 0.1, 0.2, and 0.3 respectively. Figure 5 show the neural network before and after applied dropout layer. Fully-Connected layer Finally, the two-dimensional image has been turned into 1D by using fully connected layer, and connect each neuron to the previous neuron before performs the final result of the classification. In Fig.6, we see the basic neural network represent fully connected layer. Softmax Layer In this study, softmax layer were used to calculate the probabilities of each categories, and the biggest value of probability represented the correct class. The following equation show the behavior of this function Where, f(x) is the activation function output, and is the input [24]. Classification Layer In this layer the loss function used to calculate the validation error is cross entropy, which tell us the value of prediction from the actual output, used two parameters; output through learning process and the label in the case of supervised learning algorithms. After that, the weight is update using an optimization method. In our research, we find that the best result obtained when used stochastic gradient descent with momentum (sgdm). Fig. 7 show the block diagram of the proposed model. 4 Experiments and result In the process of training for deep learning, momentum is set to 0.9, the initial learning rate is 0.0001, the maximum iteration 10700, epoch is 100, and the mini-batch size is 32. The training process graph is shown in Fig.8. Looking at the result, we can see that the accuracy of the training shows an increase in curve with respect to the number of iterations. The validation accuracy obtained is 84.4%. In contrast, there is a decrease in the curve of loss function with respect to the number of iterations, which is about 0.352. This means that the proposed CNN structure does well despite the insufficient data set, and there is no overfitting in the training process. In the case of test step, we use 44 slices for testing and just 4 slices for COVID mislabel as NonCOVID. Figure 9 show some of the predict labels in command window compared with test labels. The testing accuracy is 90.09%. Number of Layer and Hyper Parameters In this subsection, parameters for different structures are included in the training process. Table 2 shows the various previously tested parameters until reaching the structure got a better view performance. Time and Tool The proposed model for COVID-19 detection is trained on Intel (R) Core(TM) i3-4005U CPU @1.7GHz, RAM (4 GB), NVIDIA GeForce 920M GPU, NVIDIA CUDA 10.1.236 , and Matlab 2018b . The training time was 253 minutes and 55 sec for training 4,308 images. Confusion Matrix The confusion matrices has been used to measure the model's performance for our study. Precision, Sensitivity, Specificity, and Accuracy have been determined using the following equations: Looking at the dataset and test model, TP is a positive percentage (COVID-19) that has been correctly classified as COVID-19 by the model, FP is a negative percentage (NonCOVID-19) that is labeled as positive (COVID-19), TN is the negative percentage (NonCOVID-19) that is correctly categorized as NonCOVID-19, and FN is the positive percentage (COVID-19) that is categorized as false (NonCOVID-19) negatively by the model. Table 3 shows the accuracy metrics that are extracted from the confusion matrices show in Fig.10. The precision, sensitivity, specificity and accuracy are 88.5%, 87.27%, 78.9%, and 84.36% respectively. Table 4 show compression among our model and the other models. Two pre-trained models ResNet-50, and AlexNet were used in the comparison in addition to [17], and [18]. We should note that, the proposed model has the higher test accuracy in compare with the other models. Moreover, the simplicity of the proposed model is better than the complexity of the models in [17,18]. This gives possibility to obtain better results using the existing data as is without any complications. This type of model can also be applied to other forms of medical images. Conclusion In this paper, a CNN model was established to detect COVID-19 by applying the CNN model to CT slides, and it proved to be a promising complementary diagnostic method for frontline clinicians. Several parameters of CNN models are used to adapt the system before the last architecture is achieved, and the different architecture and excessive parameters are summarized in Table 2. The system shows a validation accuracy about 84.4%, and the testing accuracy is 90.09%. However, in this study the proposed system needs to be tested on larger data sets Includes different ages and genders to increase their accuracy. In addition, the classification system architecture cannot be reused in few images because it is one of deep learning determinants. Administration of ferrous sulfate drops has significant effects on the gut microbiota of iron-sufficient infants: a randomised controlled study their efforts. Despite differences in iron concentration, infants’ age and sequencing techniques, both studies demonstrate unfa-vourable iron effects on gut microbiota with decreased abundance of bifidobacteria and lactobacillus, and increased abundance of pathogenic bacteria in iron-deficient/ anaemic Kenyan infants. We have investigated changes in gut microbial composition

due to iron fortification or supplementation in healthy, Swedish infants. Iron-sufficient infants at 6 months of age were randomly allocated to receive low-iron-fortified formula (1.2 mg Fe/day; n=24), high-iron-fortified formula (6.6 mg Fe/day; n=24) or no-added-iron formula with liquid ferrous sulfate supplementation (iron drops; 6.6 mg Fe/day; n=24) for 45 days. All participants gave their informed consent before inclusion through parents or legal guardians. Total iron intake was 1.2, 6.4 and 5.7 mg/day (all differences p<0.01) in the low-iron, high-iron and iron-drops group, respectively. Stool samples were collected before and after the intervention. We applied 16S rRNA gene amplicon sequencing of the V3–V4 region to profile Administration of ferrous sulfate drops has significant effects on the gut microbiota of iron-sufficient infants: a randomised controlled study We read with interest the work by Jaeggi et al 1 and Paganinni et al 2 and commend their efforts. Despite differences in iron concentration, infants' age and sequencing techniques, both studies demonstrate unfavourable iron effects on gut microbiota with decreased abundance of bifidobacteria and lactobacillus, and increased abundance of pathogenic bacteria in iron-deficient/anaemic Kenyan infants. Gut November 2019 Vol 68 No 11 PostScript Table 1 Baseline characteristics of the study participants and anthropometric and biochemical values at the 45-day follow-up. We have investigated changes in gut microbial composition due to iron fortification or supplementation in healthy, Swedish infants. Iron-sufficient infants at 6 months of age were randomly allocated to receive low-iron-fortified formula (1.2 mg Fe/day; n=24), high-iron-fortified formula (6.6 mg Fe/day; n=24) or no-added-iron formula with liquid ferrous sulfate supplementation (iron drops; 6.6 mg Fe/day; n=24) for 45 days. All participants gave their informed consent before inclusion through parents or legal guardians. Total iron intake was 1.2, 6.4 and 5.7 mg/day (all differences p<0.01) in the low-iron, high-iron and iron-drops group, respectively. Stool samples were collected before and after the intervention. We applied 16S rRNA gene amplicon sequencing of the V3-V4 region to profile the gut microbiome using Illumina MiSeq. We used QIIME 3 to assess composition and diversity of gut microbiota and the DESeq2 package 4 to investigate differences in relative abundance of gut bacteria among the groups. PICRUSt was used to predict metagenome functional content. 5 Vaginally delivered infants (n=53) with paired stool samples were included in the analyses. There were no significant differences in anthropometrics or iron-related biomarkers among the randomisation groups; no adverse effects were reported (diarrhoea, increased rates of infections, other illnesses, etc), and growth was not affected (table 1). 6 In this study, we confirm findings that consumption of high-iron formula is associated with decreased relative abundance of Bifidobacterium (p<0.001, 60% vs 78%) after only 45 days of intervention, but we did not detect enhanced growth of pathogenic bacteria. However, we were able to partly confirm previous findings regarding abundance of lactobacilli due to iron consumption. We found lower relative abundance of Lactobacillus sp (p<0.007, 8% vs 42%) in infants who received iron drops versus highiron-formula group. Unexpectedly, we also found higher relative abundance of Lactobacillus sp (p<0.0002, 42% vs 32%) in high-iron compared with low-iron formula group; this result challenges the hypothesis that the mode of iron administration has a direct effect on lactobacilli colonisation in the gut. Furthermore, the iron-drops group had lower abundance of Streptococcus (p<0.0003, 0.2% vs 0.9%) but higher abundance of Clostridium (p<0.05, 25% vs 9%) and Bacteroides (p<0.02, 1.2% vs 0.9%) compared with the high-iron formula group (figure 1). In the present study, all groups received formula with added galacto-oligosaccharides (GOS) at 3.3 g/L. This prebiotic may mitigate adverse effects of iron fortification on gut microbiota, 2 but in the irondrops group, iron was administered apart from the formula meals. Thus, we cannot exclude a possible protective effect of GOS on the gut microbiota of infants in our study. As in the study by Paganinni et al, 2 faecal calprotectin did not differ between the groups (table 1), but in our study, it correlated positively with Clostridium difficile in high-iron-formula (r Spearman =0.4, p<0.01) and iron-drops intervention groups (r Spearman =0.48, p<0.004). The bacterial function pathway related to Staphylococcus aureus infection (KEGG module 05150) 5 was significantly lower in the iron-drops group compared with the low-iron-formula group (p=0.027). This is a novel finding which suggests that changes in bacterial composition due to administration of iron drops may reduce the protective response of the gut microbiota to bacterial infections. Nevertheless, no effects on the health of the participants were seen due to this. To summarise, in healthy, non-anaemic Swedish infants, consumption of highiron formula is associated with significantly lower abundance of bifidobacteria compared with low-iron formula, and administration of iron as drops, even in a dose comparable with the daily iron requirement and for a short time, leads to decreased relative abundance of lactobacilli and potentially increases susceptibility to bacterial infection. Figure 1 Differences in gut bacterial composition depend on the concentration and administration mode of the consumed iron. In the cladogram, showing the results of the microbiome analysis over time, taxa are grouped on the basis of synapomorphy. The outermost small, white circles represent the 561 OTUs (operational taxonomic units). Differences in gut microbial composition between the high-Fe-formula group versus the low-Fe-formula group over time are presented in the yellow component around the cladogram, where blue bars represent lower relative abundance of bacteria in the high-Fe-formula group compared with the low-Feformula group and the red bars represent higher relative abundance in the high-Fe-formula group compared with the low-Fe-formula group, respectively. Differences in gut microbial composition between the high-Fe-formula group versus the Fe-drops group over time are presented in the red component around the cladogram, where the blue bars represent lower relative abundance of bacteria in the high-Fe-formula group and the red bars represent higher relative abundance in the high-Fe-formula group compared with the Fe-drops group, respectively. OTU, operational taxonomic unit. Contributors eAs-G, MD, OH, BL and tL designed the original study and eAs-G, MD, OH and tL conducted the study. tL was involved in planning of the study, analyses and interpretation of the data. Kss planned and performed laboratory work, analysed and interpreted data, and wrote the first draft of the manuscript. CL performed laboratory work and wrote the section on subjects and methods for the manuscript. As assisted with bioinformatics, interpretation and visualisation of the data. CeW contributed to the discussion and provided intellectual input. All authors have read, provided critical comments and approved the final version of the letter. Funding this project was supported by the Umeå University Foundation for Medical research and the regional agreement between Umeå University and Västerbotten County Council on cooperation in the fields of medicine, odontology and health (ALF). semper AB, sweden, generously provided the study formulae and the fruit-based and vegetable-based infant foods. Disclaimer the funding bodies had no role in designing or conducting the study, in the collection, management, analysis or interpretation of the data and had no input into the preparation, review or approval of the manuscript. Mutual Cross Talk between the Regulators Hac1 of the Unfolded Protein Response and Gcn4 of the General Amino Acid Control of Saccharomyces cerevisiae ABSTRACT Hac1 is the activator of the cellular response to the accumulation of unfolded proteins in the endoplasmic reticulum. Hac1 function requires the activity of Gcn4, which mainly acts as a regulator of the general amino acid control network providing Saccharomyces cerevisiae cells with amino acids. Here, we demonstrate novel functions of Hac1 and describe a mutual connection between Hac1 and Gcn4. Hac1 is required for induction of Gcn4-responsive promoter elements in haploid as well as diploid cells and therefore participates in the cellular amino acid supply. Furthermore, Hac1 and Gcn4 mutually influence their mRNA expression levels. Hac1 is also involved in FLO11 expression and adhesion upon amino acid starvation. Hac1 and Gcn4 act through the same promoter regions of the FLO11 flocculin. The results indicate an indirect effect of both transcription factors on FLO11 expression. Our data suggest a complex mutual cross talk between the Hac1- and Gcn4-controlled networks. T he baker's yeast Saccharomyces cerevisiae executes two wellestablished pathways, the general amino acid control (GAAC) and the unfolded protein response (UPR). The GAAC regulatory network is induced not only by amino acid starvation or imbalances but also by other environmental stimuli, including supply of glucose (1), purines (2), and tRNA synthetases (3). A variety of physiological or environmental stress conditions such as calcium depletion, glucose deprivation, hypoxia, or misfolded proteins lead to an accumulation of misfolded or unfolded proteins in the endoplasmic reticulum (ER) lumen, which results in the induction of the UPR (4-7). These pathways are conserved in mammals, where they are essential. The bZIP transcription factor Gcn4 represents the global key activator of the GAAC (8) and regulates transcription of numerous metabolic genes of amino acid or purine biosynthesis in response to amino acid starvation (9)(10)(11)(12). In contrast to its mammalian homologues, yeast Gcn4 can bind only as a homodimer to a specific 9-bp palindromic nucleotide sequence (5=-ATGA[C/G] TCAT-3=) (termed Gcn4 protein recognition element [GCRE]) (13,14). These GCREs are located upstream of many genes induced by amino acid starvation. Gcn4 can also bind to naturally occurring variants of this sequence (TGATTCA, TGACTCT, TG ACTGA, TGACTAT, and ATGACTCT), and therefore, using a computer algorithm, this consensus site was generalized to RRR WGASTCA (R ϭ purine, W ϭ T or A, and S ϭ G or C) (9). Gcn4 also binds to GCRE half-sites with high affinity in vitro (15,16). Gcn4 not only acts as a metabolic regulator but also has a developmental function. In response to nutrient starvation, Gcn4 is involved in the regulation of FLO11 expression (17,18). The cell surface flocculin Flo11, also named Muc1, is required for diploid pseudohypha formation and for adhesion upon nutrient starvation (19)(20)(21)(22). Hac1 plays a central role in the yeast UPR system and represents a bZIP transcription factor, like Gcn4 (23,24). Conserved from yeast to mammals is the sensing and response pathway that is transduced by Ire1, leading to an upregulation of transcription levels of approximately 400 genes, i.e., 7% to 8% of the yeast ge-nome (25)(26)(27)(28)(29)(30). In S. cerevisiae, Ire1 senses the stress and mediates a signaling cascade to upregulate responsive genes through unconventional splicing of HAC1 mRNA. Ire1 encodes a bifunctional transmembrane kinase/endoribonuclease consisting of an unfolded protein sensor domain in the ER lumen, a transmembrane domain, and a cytosolic effector domain, which contains an intrinsic serine/threonine kinase as well as an endoribonuclease in its C terminus (26,27,(31)(32)(33). An accumulation of misfolded proteins in response to ER stress leads to oligomerization and trans-autophosphorylation of Ire1 (34,35). This in turn results in an activated cytosolic endonuclease effector domain (33,36). Ire1 recognizes two "loop" structures in the HAC1 mRNA. The transcript is constitutively synthesized as a precursor bearing a 252nucleotide intron that blocks translation, and the endonuclease effector domain of Ire1 splices the HAC1 mRNA (37)(38)(39). Subsequently, the tRNA ligase Rlg1 religates, causing exons to produce the mature, efficiently translated HAC1 mRNA (33,38). As the level of Hac1 rises in the cell, the genes that harbor unfolded protein response elements (UPREs) within their promoters are induced at the transcriptional level (40). The synthesis of Hac1 in response to ER stress is regulated not only at its translational level but also by mechanisms that regulate the rate of turnover of Hac1. A similar mechanism had been described previously for the bZIP transcription factor Gcn4 (41)(42)(43). Like Gcn4, Hac1 is ubiquitinated by the SCF Cdc4 E3 ligase complex, resulting in degradation by the 26S proteasome. Furthermore, phosphorylation by the cyclin-dependent kinase (CDK) Srb10 marks Hac1 for ubiquitination, similarly to Gcn4, whereas phosphorylation by the CDK Pho85 was not observed so far. Hac1 also contains a PEST region, which is typical for rapid turnover of transcription factors (44). At least 381 UPR target genes were identified in yeast and encode functions ranging from protein folding, protein translocation, and protein transport to protein degradation within the secretory pathway. Whereas the predicted UPRE-1 consensus sequence (CAGNGTG) was absent in most of them (25), Patil and coworkers identified two further UPREs, which are recognized by Hac1 (UPRE-2, consensus sequence TACGTG; UPRE-3, consensus sequence AGGAACAAC) (45). Apart from its role as a transcriptional activator of the GAAC, Gcn4 and its activator Gcn2 are required for induction of a majority of UPR target genes upon ER stress. A direct

binding of Gcn4 could be demonstrated for UPRE-1 and UPRE-2, while binding to UPRE-1 was Hac1 dependent. In contrast, Gcn4 is not necessary for the regulation of genes without a recognizable UPRE, which represent half of all UPR targets. Both Hac1 and Gcn4 are bZIP transcription factors. Heterodimer formation of Gcn4/Hac1 or its mammalian counterparts ATF4/XBP1 is an attractive hypothesis to explain the mechanism (45) but could not be verified yet. Recently, Fordyce and coworkers discovered that Hac1 binds only to UPRE-2 but not to the 7-bp UPRE-1 sequence, hereafter termed core UPRE-1 (cUPRE-1) (46). However, they could demonstrate that an extended core UPRE-1 (xcUPRE-1) containing flanking sequences is important for Hac1 binding. Therefore, the 7-bp cUPRE-1 consensus sequence can be extended to a 12-bp UPRE-1-like motif (GGACAGCGTGTC). In this study, we identified novel functions of Hac1 in metabolic and developmental processes regulated by Gcn4. We demonstrate not only that Gcn4 is able to activate Hac1-specific target genes but also that Hac1 is involved in Gcn4-specific target gene regulation and FLO11 expression in response to amino acid starvation. MATERIALS AND METHODS Yeast strains and growth conditions. All yeast strains used in this study are listed in Table 1. They are derivates of the S. cerevisiae strain background ⌺1278b unless otherwise stated. Transformations were carried out using the lithium acetate method (47). For ␤-galactosidase assays, strains were cultivated in liquid synthetic minimal medium (YNB) overnight at 30°C, diluted into fresh medium, and cultivated for 6 h before assaying enzymatic activities. For amino acid starvation, 3-amino-1,2,4-triazole (3AT) (Sigma-Aldrich, Steinheim, Germany) was added to fresh diluted cultures to a final concentration of 10 mM, and cells were incubated for 8 h before further assays. For nitrogen starvation, cells grown to logarithmic phase were washed twice with 2% glucose and incubated for 24 h in liquid YNB medium containing only 50 M ammonium sulfate (instead of 50 mM) as the sole nitrogen source. Tunicamycin (Tm) (Calbiochem/Merck KGaA, Darmstadt, Germany) was added to fresh diluted cultures to a final concentration of 1 g/ml and incubated for 6 h to induce UPR stress. Additionally, cultures grown to log phase (4 h or instead 6 h in YNB) were treated with 1 g/ml Tm for 15, 30, 60, 90, and 120 min. To compare strains under different conditions in Western hybridization experiments, strains were cultivated in 250 ml liquid synthetic minimal medium (YNB) to an optical density at 600 nm (OD 600 ) of 0.6 to 0.8 at 30°C, subsequently divided into 50-ml cultures, and cultivated for a further 90 min under different conditions each. Plasmids. All plasmids used in this study are listed in Table 2. Plasmid pME3498 expressing the HAC1 inclusive intron under the MET25 promoter was constructed by amplifying HAC1 with PfuUltra HF DNA polymerase (Promega, Mannheim, Germany) from genomic DNA and introducing it as a XbaI/ClaI fragment into SpeI/ClaI-restricted p426MET25. Protein analysis. Whole-cell extracts of S. cerevisiae were prepared from yeast cultures grown to exponential phase. Cells were washed in 2.5 ml ice-cold buffer B (100 mM Tris-HCl, pH 7.5, 200 mM NaCl, 5 mM EDTA, 20% glycerin), lysed with glass beads (diameter, 0.25 to 0.5 mm; Carl Roth GmbH, Karlsruhe, Germany) in 500 l of B-buffer-containing protease inhibitors (Complete, EDTA-free; Roche Diagnostics GmbH, Mannheim, Germany) and 14.3 mM ␤-mercaptoethanol at 4°C, and centrifuged at 13,000 rpm for 12 min to remove glass beads and large pieces of cell debris. Extracts (10 l) were removed to determine total protein concentration using the Bradford protein assay (50), and proteins were denatured in SDS loading dye by heating at 65°C for 15 min. Equal amounts of protein were subjected to SDS-PAGE and transferred to nitrocellulose membranes. Hac1, the ␣ subunit of eukaryotic initiation factor 2 (eIF2␣), and eIF2␣-P were detected using ECL technology (Amersham, United Kingdom). For the first incubation, polyclonal rabbit anti-Hac1 (gift from Kazutoshi Mori, Kyoto University, Japan), polyclonal rabbit anti-eIF2␣ (pS52) (catalog no. 44728G; Invitrogen, Darmstadt, Germany), or rabbit anti-eIF2␣ (gift from Thomas Dever, NIH, Bethesda, MD, USA) antibodies were used. Peroxidase-coupled goat anti-rabbit IgG was used as a secondary antibody (catalog no. G21234; MoBiTec, Göttingen, Germany). Adhesive growth tests. Amino acid starvation-induced adhesive growth tests on solid YNB medium were performed as described previously (18,51). For visualization of biofilms in wells of polystyrene plates, assays were performed as described in reference 19. Growth tests. Yeast strains were precultured to the same optical densities (OD 600 ϭ 0.6) and then diluted 10-fold, starting with 3 ϫ 10 4 cells per 20 l. For each dilution, 20 l was spotted onto solid YNB medium with or without 0.5 g/ml tunicamycin for ER stress survival assays and on selective YNB medium with or without 5 mM 3AT for resistance upon amino acid starvation. After incubation for 3 to 4 days at 30°C, plates were photographed under white light. ␤-Galactosidase assay in S. cerevisiae. Starting from one overnight culture, strains carrying either a UPRE-, a FLO11-, a GCRE6-, or a GCN4:: lacZ reporter were diluted into fresh medium and further cultivated for 6 to 24 h before they were harvested. The incubation term was based on the medium (for details, see "Yeast strains and growth conditions"). Extracts were prepared and assayed for specific ␤-galactosidase activity as de-scribed previously (52) and normalized to the total protein (50), resulting in the specific enzyme activity (OD 420 ϫ 0.35)/(0.0045 ϫ protein concentration ϫ extract volume ϫ time). Assays were performed for at least three independent cultures. Analysis of FLO11 promoter elements. Rupp et al. (53) constructed a set of 14 reporter constructs containing individual 400-bp FLO11 promoter fragments that overlap by 200 bp and were cloned in front of a CYC1::lacZ fusion gene. Thus, after transformation of these constructs in the diploid wild-type strain as well as in ⌬hac1/⌬hac1 and ⌬gcn4/⌬gcn4 This study mutant strains, the influence of the transcription factors on specific regions in the FLO11 promoter can be determined by ␤-galactosidase assays. A construct without an insert served for background measurements. RNA isolation and quantitative real-time PCR (qRT-PCR). Total RNA was isolated from yeast cells that were grown in YNB in the presence (8 h) or absence (6 h) of 10 mM 3AT using the High Pure RNA isolation kit (Roche Diagnostics GmbH, Mannheim, Germany) to determine FLO11 transcript levels. For analyzing GCN4 or HAC1 mRNA expression levels, yeast cells were grown to an OD 600 of ϳ0.6 at 30°C before division into independent cultures and further cultivation for 90 min under indicated conditions. cDNA synthesis was performed in duplicate for each sample using 0.8 g RNA and the QuantiTect reverse transcription kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions. Twenty nanograms of cDNA was used as the template for quantitative real-time PCR (qRT-PCR) experiments, and amplification was performed in a LightCycler 2.0 (Roche Diagnostics GmbH, Mannheim, Germany) using the RealMaster SYBR Rox kit (5Prime GmbH, Hamburg, Germany). Independent PCRs were performed using the same cDNA for both genes of interest (FLO11, GCN4, and HAC1) and CDC28 or H2A as reference. The following temperature profile was applied after an initial denaturation at 95°C for 2 min 20 s: 20-s denaturation at 95°C, 22-s hybridization at 64°C, and 22-s elongation at 70°C. The 40 cycles were followed by construction of a melting curve to determine PCR specificity, contamination, and the absence of primer dimers. Gene expression was quantified using the threshold cycle (⌬C T ) method with efficiency. qRT-PCR experiments were performed from three independent cultures for each strain and condition. RESULTS The high-copy-number suppressor Hac1 supports Gcn4 activity during amino acid starvation. In S. cerevisiae, amino acid starvation triggers the activation of the general amino acid control (GAAC) network and the cell surface flocculin gene FLO11 by the transcriptional activator Gcn4 (9,18,54). The Gcn4 L267S variant carrying an amino acid substitution in the third of the four conserved leucines of the zipper dimerization domain results in a transcription factor which is less active than wild-type Gcn4. Indeed, Gcn4 L267S has a reduced activation of metabolic genes in comparison to that of wild-type Gcn4, which is, however, sufficient to fulfill metabolic processes and to permit growth under amino acid starvation. In contrast, the developmental function of Gcn4 L267S is diminished. Gcn4 L253G carrying a helix breaker substitution at Leu253 results in a highly stable but transcriptionally inactive protein (17). We searched for a high-copy-number suppressor of Gcn4 L267S that improves the transcriptional activity and growth during amino acid starvation. Patil et al. (45) described interplay between Gcn4 and the UPR bZIP transcription factor Hac1. We analyzed whether an overexpression of the native unspliced HAC1 influences growth of the gcn4 deletion strain expressing different GCN4 variants. Amino acid starvation was induced by addition of the histidine analogue 3-amino-1,2,4-triazole (3AT) to the growth medium, which acts as a false feedback inhibitor and inhibits the histidine biosynthetic enzyme His3 (55). Due to the fact that most natural yeasts are dimorphic and diploid and that the reduction in transcriptional activation capacity of Gcn4 L267S is less severe in haploids, we used diploid yeast cells (17,56). Growth of the diploid gcn4 deletion strain expressing GCN4 L267S was enhanced during amino acid starvation when the bZIP transcription factor Hac1 was overexpressed (Fig. 1). Furthermore, growth of yeast cells expressing wild-type GCN4 in the presence of 3AT could be strengthened while overexpressing HAC1. In contrast, overexpression of HAC1 could not complement the growth defect of ⌬gcn4 cells expressing the stable but inactive GCN4 L253G upon amino acid starvation. This suppressor analysis supports a cross talk where the transcription factor Hac1 can support Gcn4 activity in amino acid biosynthesis. Hac1 controls the unfolded protein response (UPR), which is activated due to accumulation of misfolded proteins in the endoplasmic reticulum (23). The involvement of Hac1 in the Gcn4-mediated supply of amino acids (general amino acid control [GAAC]) has not been described yet, whereas it is known vice versa that Gcn4 is involved in the unfolded protein response (UPR) (45). Hac1 is required for inducing GCREs in haploid and diploid yeast cells. Subsequently, we examined whether Hac1 is required for activating the canonical Gcn4 promoter elements (GCREs). The influence of the hac1 deletion in comparison to the wild type was analyzed with a Gcn4-specific reporter which contains six GCRE binding sites upstream of the CYC1::lacZ minimal promoter. This construct was chromosomally integrated into the URA3 locus (57). Basal expression of the GCRE6::lacZ reporter was almost identical in wild-type and ⌬hac1 cells under nonstarvation conditions. However, ⌬hac1 cells were unable to induce the GCREs in response to amino acid starvation (3AT) and remained at the basal level as in sated wild-type cells without amino acid limitation ( Fig. 2A). As expected, strains containing a gcn4 deletion were unable to activate GCRE6::lacZ expression in response to amino acid starvation. We compared the effect of Hac1 on the Gcn4 element GCRE with the effect of Gcn4 on the Hac1-dependent unfolded protein response element (UPRE). The reported UPRE::CYC1::lacZ, which is induced by tunicamycin-mediated ER stress, was tested (23). The strong induction of the UPRE:: CYC1::lacZ reporter in the wild type is abolished when the transcription factor Hac1 is absent (⌬hac1). A defective GCN4 gene (⌬gcn4) results in partial induction. The double mutation ⌬gcn4 . Units of specific ␤-galactosidase activities are shown in nanomoles per minutes per milligram. The bars represent the mean values of at least three independent measurements. As additional control, the haploid ⌺1278b wild-type strain (WT) (RH2816), as well as ⌬hac1 (RH3351), ⌬gcn4 (RH2676), and ⌬gcn4 ⌬hac1 (RH3402) mutant strains, was transformed with the UPRE-CYC1-lacZ reporter gene carried on a multicopy vector (pMCZ-Y). Starting from one overnight culture, strains were diluted into fresh medium and further cultivated for 6 h in the respective media before specific ␤-galactosidase activities were assayed. Either cultures were grown to log phase in YNB medium [light gray bars, YNB (6 h)], or ER stress conditions were induced by the addition of 1 g/ml tunicamycin for 2 h [black bars, YNB (4 h) ϩ Tm (2 h)]. Units of specific ␤-galactosidase activities are shown in nanomoles per minutes per milligram. The bars represent the mean values based on quadruplicate determinations of at least three independent transformants. (B) The diploid wild-type yeast strain (WT) (RH3421), as well as homo-and heterozygous ⌬hac1/⌬hac1 (RH3422), ⌬hac1/HAC1 (RH3423), ⌬gcn4/⌬gcn4 (RH2398), ⌬gcn4/GCN4 (RH3424), ⌬gcn4/⌬gcn4 ⌬hac1/⌬hac1 (RH3350), and ⌬gcn4/GCN4

⌬hac1/HAC1 (RH3425) mutant strains each carrying a chromosomally integrated GCRE6::lacZ reporter, was grown to log phase in YNB in the absence (light gray bars, YNB) or presence (dark gray bars, ϩ3AT) of 10 mM 3AT before specific ␤-galactosidase activities were assayed. As a further control, the diploid yeast strains indicated on the abscissa were transformed with the UPRE-CYC1-lacZ reporter gene (pMCZ-Y) and transformants were grown in the presence or absence of tunicamycin before being used for ␤-galactosidase assays. ⌬hac1 provides a phenotype similar to that of the ⌬hac1 mutation, further supporting the conclusion that UPRE transcription is primarily mediated by Hac1 ( Fig. 2A). For analyzing the impact of Hac1 on Gcn4 target gene expression in diploids, haploid MATa strains containing the GCRE6:: lacZ reporter gene were crossed with respective MAT␣ strains to obtain homo-or heterozygous diploid strains deleted for HAC1, GCN4, or both. Heterozygous yeast strains revealed that a single intact copy of either GCN4 or HAC1 is sufficient to provide induction of the GCRE6::lacZ reporter upon amino acid starvation. A strain carrying only one intact GCN4 and one intact HAC1 copy was hardly able to induce the GCRE reporter. Induction of the GCRE reporter by 3AT was abolished when diploid homozygous strains deleted for HAC1 or GCN4 were analyzed (Fig. 2B). Therefore, neither haploid nor diploid ⌬hac1 cells showed intrinsic activation of GCRE upon amino acid starvation. In accordance with the data with haploids, the analysis of the corresponding activation of the UPRE-mediated unfolded protein response in diploids revealed that the homozygous ⌬gcn4 cells showed a reduced response to ER stress, whereas homozygous ⌬hac1 cells failed to activate UPRE-lacZ expression after tunicamycin treatment (Fig. 2B). These data suggest that there is a cross talk in both directions between Hac1 and Gcn4. Besides the known requirement of Gcn4 for UPRE activation, there is also a Hac1 influence on the activation of Gcn4-specific target genes in response to amino acid starvation in haploids, as well as in diploids. One copy of either GCN4 or HAC1 is sufficient to fulfill the activation of Gcn4-specific target gene expression in diploids. The noncomplementation of the double heterozygous mutants could be a consequence of direct Gcn4 and Hac1 interactions. ER stress inhibits GCN4 mRNA by a Hac1-independent mechanism. Since the ER stress regulator Hac1 is required for the GCRE response during amino acid starvation, we analyzed the effect of tunicamycin-mediated ER stress on GCRE activity. ER stress represses GCRE activity independently of the presence or absence of Gcn4 or Hac1, suggesting an additional molecular mechanism ( Fig. 2A). Nitrogen starvation was used as a control and was achieved by decreasing the ammonium sulfate concentration in the culture medium (from 50 mM to 50 M). GCRE- (p180) was measured in a haploid ⌺1278b wild-type strain (WT) (RH2816) as well as in ⌬hac1 (RH3351), ⌬gcn4 (RH2676), and ⌬gcn4 ⌬hac1 (RH3402) mutant strains under different nutritional conditions. Bars depict means of at least three independent measurements of ␤-galactosidase activities. (B) Crude protein extracts were prepared from haploid ⌺1278b wild-type cells (WT) (RH2816) as well as from ⌬gcn4 (RH2676) and ⌬hac1 (RH3351) mutant strains, respectively. Cells were grown either under normal conditions (untreated) or in the presence of ER stress conditions induced by 1 g/ml tunicamycin (Tm). Additional amino acid starvation was obtained by adding 10 mM 3AT. Starting from one main culture with an OD 600 of ϳ0.8 at 30°C, cultures were quartered and cultivated for a further 90 min under the indicated conditions. Protein levels of Hac1 and eIF2␣-P were analyzed by immunoblotting using specific antibodies. eIF2␣ was used as a loading control. driven gene expression was drastically reduced by ER stress, and the effect was similar to, and even more pronounced than, the described repressive effect of nitrogen starvation on GCREs (58). The kinetics of the observed repression of GCREs by ER stress suggests that it starts after about 60 min. A transient upregulation of Gcn4 protein levels 15 and 30 min after tunicamycin treatment had been described previously (45). However, it did not result in increased GCRE activation in the corresponding period (see Fig. S1 in the supplemental material). We analyzed how the repressive effect of ER stress on GCREs correlates with the translational control of the GCN4 mRNA, which was monitored by a GCN4::lacZ reporter containing the wild-type leader with all four intact upstream open reading frames (uORFs) (59). Translational efficiency of GCN4 mRNA decreased in response to tunicamycin-mediated ER stress in haploid wildtype and ⌬hac1 and ⌬gcn4 single and double mutant strains (Fig. 3A). The increased activity in the ⌬gcn4 strain corresponds to permanent limitation caused by the lack of the Gcn4 regulator, resulting in an induced translation of the GCN4 reporter. This further suggests that ER stress activates an additional mechanism, which controls gene expression independently of Hac1. The repression of GCN4::lacZ by tunicamycin, which was measured as the control, is similar to the described effect of nitrogen repression (58) (Fig. 3A). There is no hint of a translational control of GCN4 by Hac1 in haploids since Hac1 influenced neither GCN4::lacZ Amino acid starvation activates the general control system primarily on the level of translation. The eukaryotic initiation factor of translation eIF2␣ is phosphorylated (eIF2␣-P) resulting in two effects: (i) the overall translation rate is reduced to save precursors of translation during amino acid limitation and (ii) GCN4 mRNA translation is increased to produce larger amounts of this transcription factor, which then activates numerous genes for amino acid biosynthesis (11). We monitored phosphorylation of eIF2␣ to analyze how ER stress (tunicamycin) in addition to simultaneous amino acid limitation (3AT) affects the levels of eIF2␣-P (Fig. 3B). Phosphorylation of eIF2␣ upon amino acid starvation is unaffected by additional ER stress. Accordingly, ER stress without amino acid starvation does not result in phosphorylation of eIF2␣. We also analyzed whether Hac1 is required for phosphorylation of eIF2␣. Hac1 protein levels are significantly increased as a result of ER stress. Additional amino acid limitation still shows elevated Hac1 protein levels, but due to the generally reduced translation rate as a result of the increased levels of eIF2␣-P, the amounts of Hac1 are decreased (Fig. 3B). In the absence of Hac1, eIF2␣ phosphorylation is still functional during simultaneous amino acid starvation and ER stress. In contrast, upon additional amino acid starvation Hac1 protein levels are reduced in ⌬gcn4 and RH2656) and a haploid or diploid HAC1 deletion strain (RH3351 and RH3412) were determined by qRT-PCR and normalized against H2A. Starting from one main culture with an OD 600 of ϳ0.6 at 30°C, cultures were divided and cultivated for a further 90 min under the indicated conditions. Amino acid starvation was induced by 10 mM 3AT (dark gray bars, ϩ3AT), ER stress conditions were achieved by 1 g/ml tunicamycin (black bars, ϩTm). Experiments were performed from three independent cultures for each strain and condition. The mRNA levels were normalized to the respective untreated (YNB) wild type. Standard deviations are indicated as error bars. (B) HAC1 mRNA levels were analyzed similarly in either a haploid or a diploid wild-type strain (RH2816 and RH2656) and a haploid or a diploid GCN4 deletion strain (RH2676 and RH2658). (WT) (RH3406) as well as in ⌬hac1 (RH3360), ⌬gcn4 (RH3407), and ⌬gcn4 ⌬hac1 (RH3408) mutant strains each carrying a chromosomally integrated FLO11::lacZ reporter. Cultures were grown to log phase in YNB in the absence (light gray bars, YNB) or presence of 10 mM 3AT (dark gray bars, ϩ3AT) before specific ␤-galactosidase activities were measured. Relative FLO11 mRNA abundances determined by qRT-PCR were measured in haploid ⌺1278b wild-type (WT) (RH2816), ⌬hac1 (RH3351), ⌬gcn4 (RH2676), and ⌬gcn4 ⌬hac1 (RH3402) yeast strains and normalized against CDC28. Experiments were performed from three independent cultures for each strain and condition, and cultivation was accomplished as described for FLO11::lacZ expression. The ⌬C T method including efficiencies was used for quantification. Standard deviations are indicated as error bars. (B) The untransformed yeast strains described in panel A as well as a ⌬flo11 (RH2681) mutant strain were streaked out on solid YNB medium (nonstarved cells) and with 10 mM 3AT (histidine-starved cells), respectively. After incubation for 3 days at 30°C, adhesive growth was determined. Plates were photographed before (before wash) and after washing under a stream of water (after wash) to document remaining cells on the agar surface. The same yeast strains were grown in liquid YNB medium until reaching an optical density of 0.6 before 300 l of each culture was transferred in a microtiter well. Cells were grown in the absence or presence of 5 or 10 mM 3AT to induce starvation-dependent adhesive growth. After incubation for 24 h at 30°C, sedimented cells were dyed with crystal violet and carefully washed. Finally, plates were photographed to cells. In conclusion, these data suggest that ER stress inhibits translation of GCN4 mRNA in a molecular mechanism, which does not affect eIF2␣ phosphorylation caused by amino acid starvation. This novel ER stress-induced process on GCN4 and subsequently GCRE expression is independent of Hac1. In contrast, Gcn4 appears to influence Hac1 upon amino acid starvation, which further supports a cross talk between the two transcription factors. Hac1 and Gcn4 mutually influence their mRNA expression levels. We further analyzed the impact of Hac1 on the mRNA expression level of GCN4 and vice versa. Therefore, we performed quantitative real-time PCR (qRT-PCR) experiments under amino acid starvation as well as under ER stress conditions. The levels of GCN4 and HAC1 mRNA were upregulated by induction of amino acid starvation (3AT) in both haploid and diploid wild-type strains (Fig. 4). Deletion of HAC1 slightly reduced GCN4 mRNA expression levels upon 3AT treatment in haploids, whereas this effect was very prominent in diploid deletion strains. In contrast to amino acid starvation, 90-min tunicamycin-mediated ER stress did not result in enhanced GCN4 mRNA expression levels (Fig. 4A). The data are consistent with our results obtained from the GCN4::lacZ experiments (Fig. 3A). As expected, HAC1 mRNA expression levels increased under ER stress conditions in both haploid and diploid wild-type cells. Deletion of GCN4 impaired HAC1 mRNA expression levels in response to amino acid starvation as well as under ER stress conditions. The data are consistent with our results where Hac1 protein levels were reduced in ⌬gcn4 cells when they were treated with 3AT (Fig. 3B). In contrast to GCN4 mRNA levels, HAC1 mRNA expression levels were similar in haploid and diploid ⌬gcn4 cells (Fig. 4B). These findings further support our assumption that there is a cross talk between Hac1 and Gcn4. Gcn4 appears to be involved in HAC1 transcription in both haploid and diploid cells, whereas Hac1 appears to be absolutely required for GCN4 transcription in diploids. Hac1 supports FLO11 expression and adhesive growth in haploid or diploid cells during amino acid starvation. Besides the activation of target genes by binding to specific Gcn4 recognition elements in their promoter regions, Gcn4 evokes a strong adhesion of yeast cells on surfaces or on each other upon amino acid starvation. This adhesion is mediated by the flocculin Flo11. The FLO11 promoter lacks a typical GCRE and therefore is not a typical Gcn4-dependent promoter (18). Since Hac1 is required for activation of Gcn4 promoter elements (GCREs), we analyzed Hac1-dependent FLO11 expression in more detail in haploid and diploid cells. We investigated how Hac1 influences expression of a FLO11::lacZ reporter construct that contains 3,500 bp of the FLO11 promoter in front of a CYC1::lacZ minimal promoter integrated into the URA3 locus. Amino acid starvation (3AT) led to only a partial induction of ␤-galactosidase activity in ⌬hac1 cells in comparison to haploid wild-type cells. Haploid cells containing a gcn4 deletion showed no induction upon amino acid starvation. These findings were confirmed by quantitative real-time PCR (qRT-PCR) (Fig. 5A). Subsequently, the consequences of the reduced FLO11 expression of ⌬hac1 cells on the adherence phenotype were analyzed. We investigated to what extent ⌬hac1 cells can still grow adhesively when starved for amino acids on either agar or plastic surfaces. Cells deleted for GCN4 were not able to grow adhesively and were comparable to the ⌬flo11 strain deficient in the structural gene for the adhesin. Haploid wild-type and ⌬hac1 cells became adhesive on agar when starved for amino acids (3AT), but ⌬hac1 cells showed only a constricted adhesive growth on plastic, which reflected the halved FLO11 expression (Fig. 5B). We also explored Hac1-dependent FLO11 expression in

diploids and found a much more pronounced phenotype. Haploid MATa strains containing the FLO11::lacZ reporter gene were crossed with respective MAT␣ strains to obtain homo-and heterozygous diploid strains deleted for HAC1, GCN4, or both. Starvation-dependent FLO11::lacZ expression was strongly decreased in diploid homozygous ⌬hac1 and ⌬gcn4 strains, and the cells were not able to grow adhesively (Fig. 5C). A single copy of HAC1 was sufficient in heterozygous ⌬hac1/HAC1 cells to restore FLO11::lacZ expression and adhesive growth, whereas heterozygous ⌬gcn4/GCN4 resulted only in a partial FLO11 induction and reduced adherence. These data support an auxiliary role of Hac1 for FLO11 expression during amino acid starvation in haploid and even more in diploid yeasts. Hac1 and Gcn4 act on similar promoter elements in the FLO11 promoter. Both Hac1 and Gcn4 affect FLO11 expression during amino acid starvation. Gcn4 action on the presumably longest promoter of S. cerevisiae, spanning approximately 3.5 kb, might be indirect, because no promoter binding had been detected. Gcn4 action is also complex because it includes several promoter regions, including also basal promoter elements (18). We compared the effects of the presence or absence of Hac1 and Gcn4 on a set of 14 described reporter constructs containing individual 400-bp FLO11 promoter fragments that overlap by 200 bp in front of a CYC1::lacZ fusion gene (53). Homozygous diploid yeast cells were analyzed, because they show the most pronounced effect of Hac1 on FLO11 expression (Fig. 5). The comparison between diploid wild-type, ⌬gcn4, and ⌬hac1 cells shows two promoter regions, which are significantly affected by both Gcn4 and Hac1. These regions are located approximately 2 or 1 kb upstream of the AUG of the FLO11 open reading frame, respectively ( Fig. 6; see also Table S1 in the supplemental material). Already in the absence of amino acid limitation, the 1-kb upstream region requires not only Gcn4 but also Hac1 for basal expression. Activation by amino acid limitation (3AT) is reduced when Hac1 is missing and is abolished in the absence of Gcn4. This regulatory region corresponds to the major regulatory region of the FLO11 promoter (18,21,60). The second upstream region at Ϫ2 kb is also affected by Hac1 and Gcn4. There are differences between the document adhesive growth. (C) FLO11::lacZ expression was also determined in the diploid ⌺1278b wild-type yeast strain (WT) (RH3417) as well as in diploid homo-and heterozygous ⌬hac1/⌬hac1 (RH3362), ⌬hac1/HAC1 (RH3418), ⌬gcn4/⌬gcn4 (RH2695), ⌬gcn4/GCN4 (RH3419), ⌬gcn4/⌬gcn4 ⌬hac1/⌬hac1 (RH3349), and ⌬gcn4/GCN4 ⌬hac1/HAC1 (RH3420) mutant yeast strains each carrying a chromosomally integrated FLO11::lacZ reporter. For testing amino acid starvation-induced adhesive growth, the diploid wild-type yeast strain (WT) (RH2656) as well as ⌬flo11/⌬flo11 (RH2661), ⌬hac1/⌬hac1 (RH3412), ⌬hac1/HAC1 (RH3413), ⌬gcn4/⌬gcn4 (RH2658), ⌬gcn4/GCN4 (RH3414), ⌬gcn4/⌬gcn4 ⌬hac1/⌬hac1 (RH3415), and ⌬gcn4/GCN4 ⌬hac1/HAC1 (RH3416) mutant strains was used, and the assay was performed as described for panel B. two transcription factors, because only Hac1 seems to participate in repression of this promoter region in the absence of amino acid limitation. The effect of Hac1 and Gcn4 on the same FLO11 promoter elements further corroborates the interplay between the two transcription factors. DISCUSSION XBP1 and ATF4, the mammalian homologues of Hac1 and Gcn4, represent essential genes, which are involved in a multiplicity of metabolic and developmental processes ensuring the survival of the organism. The general amino acid control (GAAC) and the unfolded protein response (UPR) of baker's yeast are, in contrast to those of mammals, not essential. Yeast has been used here to study the interplay between the two networks. Patil et al. (45) discovered a linkage between the two pathways where Gcn4 is required for induction of a majority of UPR target genes during ER stress. We demonstrate here that this is a mutual interplay, which also applies vice versa. The initial finding was that the survival of diploid cells expressing either wild-type GCN4 or the partially active GCN4 L267S (17) could be increased upon amino acid starvation when native HAC1 was overexpressed. Hac1 can only improve Gcn4 function but is unable to complement a gcn4 deletion strain or a strain with an inactive Gcn4 variant. Hac1 and the general amino acid control. Gcn4 target gene expression and GCN4 mRNA expression itself are influenced by Hac1 in both haploid and diploid cells, but effects are stronger and more prominent in diploids. In haploids, Hac1 is not involved in basal expression of Gcn4 target genes but is required for the Gcn4mediated response to amino acid starvation. Diploid cells show the same lack of induction during starvation, but in addition, Hac1 is required for the basal expression levels. This could be a direct effect where Hac1 itself or in combination with Gcn4 activates Gcn4 targets, or an indirect effect like Hac1-dependent stabilization of Gcn4 as earlier proposed (45). Several findings indicate that the effects of Hac1 on Gcn4 are indirect: (i) Hac1 itself does not influence eIF2␣ phosphorylation, (ii) Hac1 does not affect GCN4 mRNA translation in haploids, (iii) ER stress inhibits GCN4 mRNA translation in a Hac1-independent mechanism, (iv) ER stress represses Gcn4 target gene expression, and (v) Hac1 is hardly detectable in ⌬gcn4 cells upon ER stress conditions and additional amino acid starvation. A regulation of the HAC1 gene by Gcn4 is supported by the fact that in the absence of GCN4 and ER stress constitutive expression of HAC1 does not activate transcription of Hac1 target genes (45). Furthermore, Hac1 contains two Gcn4-specific consensus sequences in its promoter, which is not the case vice versa. Furthermore, Gcn4 has a weak but distinct RNase activity, and therefore, it might be possible that Gcn4 regulates HAC1 mRNA stability (61). The situation is more complicated because Hac1 is responsible for full activation of Gcn4 target gene expression upon amino acid starvation. Vice versa, it is described that Gcn4 directly interacts with two of the three Hac1-specific promoter elements, which share half-site similarity: three bases (GTG) are identical. Gcn4 is able to bind to half-sites (15), and the shared half-site is present in the consensus sequence which is found in the promoters of Gcn4 target genes (RRRWGASTCA, with R ϭ purine, W ϭ T or A, and S ϭ G or C) (9). An attractive explanation is that both Gcn4 and Hac1 regulate the activation of the other target genes by binding to half-sites in their promoter regions. Hac1 and Gcn4 could also act together at target promoters, but we could not copurify a Gcn4/ Hac1 heterodimer in our experiments. Nevertheless, a collaboration between the two factors which might depend on a stable physical interaction is supported by the findings that (i) overexpression of HAC1 increased survival of diploid cells expressing either wild type or the partially active GCN4 L267S during amino acid starvation and (ii) Hac1-and Gcn4-specific target gene expression is strongly decreased when the responsible main transcription factor is deleted. Hac1 function in dimorphism. CaHac1 and HacA, the Hac1 Table S1 in the supplemental material). The activity was determined under nonstarvation conditions (YNB, upper graphs) or in the presence of amino acid starvation (3AT, lower graphs) induced by the addition of 10 mM 3AT. Each breakpoint represents the measured reporter construct expression less the measured expression of the construct without insert (pME2212) in the indicated genetic background. ␤-Galactosidase activities measured in the wild type are shown by diamonds, ⌬hac1/⌬hac1 breakpoints are shown by squares, and ⌬gcn4/⌬gcn4 breakpoints are shown by triangles. homologues of Candida albicans and Aspergillus fumigatus, respectively, play important roles in regulating morphology, which in turn is important for virulence of these pathogenic fungi (62,63). Furthermore, both CaGcn4 and CpcA, the Gcn4 homologue proteins, are also involved in pathogenicity (64)(65)(66). The mammalian Hac1-like XBP1 and the unfolded protein response (UPR) play important roles in tumorigenesis, and UPR suppressors are proposed as therapeutic agents (67)(68)(69). In S. cerevisiae, Gcn4 is required for adhesion and pseudohyphal development upon nutrient starvation (18). In this study, we identified Hac1 as an auxiliary regulator of FLO11 expression and therefore dimorphism of S. cerevisiae. Gcn4 and Hac1 influence an identical FLO11 promoter element and presumably act indirectly in combination with other transcriptional regulators because there is neither a Gcn4 nor a Hac1 predicted recognition element in the FLO11 promoter. It is yet unclear why both Hac1 and Gcn4 are specifically required in diploids to induce FLO11 expression. The overlapping elements, which are influenced by the transcription factors Tec1, Ste12, and Flo8, support this hypothesis (53,70). STE12 and TEC1 represent potential target genes of Gcn4, since both carry at least one Gcn4 recognition element in their promoters. Furthermore, the promoter of TEC1 actually contains five independent UPREs, whereas three of them are arranged on the complementary strand. These findings enforce our hypothesis that both Gcn4 and Hac1 are involved in Flo11 regulation per se, however, presumably by binding to another transcription factor, e.g., the TEA protein Tec1 as one of the major regulators of the FLO11 promoter. However, Tec1 protein levels did not depend on the absence or presence of Gcn4 or Hac1 (data not shown). Our data suggest that the impact of Gcn4 and Hac1 on FLO11 is complex. It includes the same regions of the FLO11 promoter and is at least partially mediated by changes of the amount of another transcription factor, which in turn is able to bind to the FLO11 promoter. In summary, Hac1 not only affects the UPR to reduce misfolded or unfolded proteins but also is involved in metabolic and developmental processes generally regulated by Gcn4 in response to amino acid starvation. At least 13 bZIP transcription factors exist in S. cerevisiae, whereas the increasing complexity during evolution is reflected by a minimum of 51 bZIP factors in humans (71). Understanding the complex regulation of dimorphism, stability control, nuclear trafficking, and cell death pathways in fungal models might be relevant for tumor therapy in humans. The mutual cross talk between the UPR and the GAAC in yeast is much broader than supposed, and it will be interesting to analyze if such a cross talk also exists in higher eukaryotes. The role of magnetic resonance imaging in Ménière disease: the current state of endolymphatic hydrops evaluation ABSTRACT Technical advances in magnetic resonance imaging have allowed to accurately detect and grade endolymphatic space distension in Ménière disease; this was only possible in post-mortem histological studies until a few years ago. Magnetic resonance imaging rules out other causes of vertigo and hearing loss, and is able to evaluate the cochlear and vestibular compartments of the endolymphatic space using a dedicated protocol. ❚ INTRODUCTION Ménière disease (MD) is a clinical syndrome of unknown etiology, and consists of intermittent episodes of vertigo, often associated with fluctuating sensorineural hearing loss, tinnitus and aural fullness. (1) The pathogenesis of MD is attributed to endolymphatic hydrops (EH), characterized by distension of the labyrinthine structures that contain endolymph: cochlear duct, saccule, utricle, ampullae and semicircular ducts, corroborated by post-mortem studies. (2) However, the relation between MD and EH is complex and not yet fully established. Only recently has magnetic resonance imaging (MRI) been able to detect EH in MD, allowing its confirmation in vivo. Nakashima et al., (3) demonstrated endolymphatic space distension in patients with MD using a three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) sequence, in a 3-Tesla field device, 24 hours after intratympanic administration of gadolinium. As gadolinium accumulates in the perilymph and does not reach the endolymph, it is possible to differentiate these two compartments and to demonstrate EH. Since then, new protocols and sequences have been developed to differentiate the endolymphatic and perilymphatic compartments in clinical practice, and many of them use intravenous gadolinium administration. Although the intratympanic route results in a higher concentration of gadolinium in perilymph, it consists of an off-label use, is less practical and requires a 24-hour wait before image acquisition. On the other hand, the intravenous route has the following advantages: it is less invasive, evaluates both ears at the same time, does not depend on the permeability of the oval and round windows, allows to evaluate the blood-labyrinth barrier and requires a shorter waiting time before image acquisition (4 hours). (4) Three-dimensional fluidattenuated inversion recovery and inversion recovery turbo spin echo with real reconstruction (3D real-IR) are among the most used MRI sequences to characterize the signal differences between perilymph (with contrast) and endolymph (without contrast). Regarding EH grading, one of the first methods used was the one proposed by Nakashima et al., (5) which classified

EH as none, mild and significant according to the ratio between the endolymphatic space and the labyrinthine fluid space (sum of endolymphatic and perilymphatic spaces). Vestibular hydrops would be considered mild if the endolymphatic space occupied between 33.3% and 50% of the vestibular fluid space, or significant if it occupied more than 50% (Figure 1). Cochlear hydrops would be considered mild if the dilated cochlear duct was smaller than the vestibular scale, or significant if the cochlear duct was larger than the vestibular scale ( Figure 1). However, some authors have questioned this method by demonstrating that the area of endolymphatic space can be altered according to the inversion time used in image acquisition. (6,7) Other semiquantitative graduation methods were described using different values of cut-off and evaluation criteria, but there is still no consensus in the literature about the method to be used. (4) A recent meta-analysis demonstrated an order of EH progression in MD, which begins in the cochlea and then involves the saccule, utricle, ampullae and finally the semicircular ducts. (2) In addition, the degree of distension of the membranous labyrinth structures appears to be related to its mechanical complacency, which is high in the saccule and lower in the utricle and semicircular ducts. (8) In this context, Attyé et al., (7) described a new criterion for EH evaluation called SURI (inversion of the saccule to utricle area ratio), which was only observed in patients with MD (sensitivity: 50% and specificity: 100%). Several studies have shown the relation between EH detection and grading in MRI with the clinical findings in patients with MD. (1,9,10) In one of them, (9) 90% of patients with MD had endolymphatic hydrops in MRI, similar frequency found in histopathological studies. In addition, the progression of EH over time and the correlation with loss of cochlear and vestibular function in patients with MD have been demonstrated. (1,10) These studies also revealed the presence of variable EH in the asymptomatic ear of patients with unilateral clinical presentation, indicating that MD can be a systemic disease with bilateral evolution over time. The MRI advances have shown that this imaging method is a robust tool in the evaluation of EH, with results similar to those found in post-mortem temporal bone studies. Magnetic resonance imaging allows to rule out other causes of vertigo and hearing loss, such as vestibular schwannomas, and also to evaluate separately the cochlear and vestibular compartments of the endolymphatic space with a dedicated protocol. The imaging acquisition and evaluation techniques of EH are still under development, but it is possible that new large-scale studies validate MRI as an accurate tool in the diagnostic criteria of MD in a near future. Pulmonary renal syndrome in a patient with vasculitis: Case report and review of literature Granulomatosis with polyangiitis (GPA) previously known as Wegner’s granulomatosis, is a small vessel vasculitis that preferentially involves capillaries, arterioles and venules, presenting as multisystemic disease classically with alveolar haemorrhage and renal insufficiency. We report a case of GPA diagnosed on history, clinical findings and supported by imaging and very high levels of C-ANCA. Renal biopsy confirmed the typical histopathological findings. We discuss herein the management of the case and review of literature. INTRODUCTION Granulomatosis with polyangiitis (GPA), previously known as Wegner's granulomatosis, is a small vessel vasculitis due to antineutrophil cytoplasmic antibodies(ANCA). 1 It presents as a multisystem disorder resulting in significant morbidity and mortality. 1 We describe herein a case of GPA presenting with hemoptysis and severe renal insufficiency that showed remarkable improvement with timely management. CASE REPORT A 40 year-old female referred from a local hospital, presented in emergency with complaints of shortness of breath at rest and haemoptysis for the previous five days. The patient was in her usual state of health twenty days ago when she developed generalized swelling of body, headache and subconjunctival hemorrhage. She was treated for new onset hypertension and ten days later, after an episode of hemoptysis, presented to a local hospital. She received antibiotics for pneumonia and then referred to our hospital due to worsening hypoxia and acute kidney injury (AKI). On presentation she was an obese lady with a BMI of 34 and marked dyspnea. On examination, she was conscious, blood pressure of 130/80mmHg and regular pulse of 120beats/minutes. She was afebrile, respiratory rate of 36/minutes and finger pulse oximetry saturation of 74% on room air. She also had pallor, periorbital puffiness and lower limb dependent edema. Chest examination revealed bi basilar end inspiratory crepitations. Her anti hypertensive medications included Amlodipine 5mg daily. Initial investigations were as follows: haemoglobin (Hb) 11.2g/dL; white blood cells (WBC) 24×10 3 / dL Neutrophils 86%; serum creatinine 6.7mg/dL; blood urea 210mg/dL; serum sodium 130mmol/L; serum potassium 3.7meq/L. Urine examination showed presence of many RBCs/HPF and proteins +3 and RBC casts. Chest x ray revealed bilateral middle and lower zone infiltrates ( Fig.1-A) Initial differential diagnosis was acute glomerulonephritis either post infectious related to pneumonia versus rapidly progressive glomerulonephritis (RPGN) due to vasculitis. Broad spectrum antibiotics were initiated and autoimmune serology were sent. Sputum for gram staining and cultures were also sent. Arterial blood gas was suggestive of combined metabolic acidosis (high anion gap) and respiratory alkalosis. Ultrasonographic scan of the abdomen revealed normal sized kidneys with grade two renal parenchymal changes. High resolution computed tomography (HRCT) chest done on the day of admission revealed patchy ground glass haziness in a geographic distribution confirming crazy paving, most likely alveolar hemorrhage ( Fig.1-B). Empirically methylprednisolone 750mg/day for three days followed by oral 60 mg per day of prednisolone; and plasmapheresis was initiated on second admission day due to RPGN and Pulmonary vasculitis. HRCT chest was repeated on third admission day which revealed remarkable improvement ( Fig.1-C). On fifth admission day, we received the results of ANCA titers which came out to be very high,(C ANCA:265.5 IU). A third session of plasmapheresis was done after an interval of one day and cyclophosphamide given on the sixth day (Table-I). She had both clinical improvements in terms of her oxygen requirement, urine output and falling serum creatinine. Further plasmapheresis was not done due to the cost and rapid clinical recovery of the patient. Renal biopsy was done on eleventh admission day which revealed total of nine glomeruli, six glomeruli showed fibro-epithelial crescents with collapsed tufts. Immunofluorescence (IF) was negative confirming pauci immune crescentic RPGN (Fig.2). She was discharged on fifteenth day of admission on prednisolone 60mg/day and monthly scheduled doses of cyclophoshamide. Follow up after six months and six doses of cyclophoshamide, revealed cushingoid face, maintained oxygen saturation on room air and serum creatinine had improved to 1.1mg/dL. Urine examination showed few RBCs and spot urine for protein to creatinine ratio 0.8 gram. At twelve months follow up and a total 8 doses of cyclophosphamide monthly, currently, she was stable on Azathioprine and 5 mg of prednisolone, follow up ANCA were in normal range. She however presented at fourteenth months with severe community acquired pneumonia (CAP) and rapidly deteriorated requiring mechanical ventilation and died. DISCUSSION GPA is classified as small vessel vasculitis preferentially involving capillaries, arterioles and venules. Clinically it can involve multiple systems, commonly pulmonary in 78%, upper respiratory tract in 86% and kidney in 61% of cases. 1 Most of the patients (90%) seek medical attention for nasal and sinus symptoms with or without involvement of lower respiratory tract. 2 Lower respiratory tract presents as hemorrhagic infiltrates and cavitating lesions leading to haemoptysis and respiratory failure in 45% of cases. 1 Renal manifestations are haematuria, proteinuria and RPGN in 50% of cases while 25% of cases may reach end stage renal disease (ESRD) in 3-4 years. 3 Our patient presented predominantly with pulmonary renal syndrome as lower respiratory tract involvement and RPGN. Other systemic presentation of GPA as Cardiovascular system (CVS), Gastrointestinal (G.I), Central Nervous system (CNS) is as prescribed in a recent review by Langford C. 1 The mainstay of GPA diagnosis is serologic evaluation. Definitive diagnosis is made on a cytoplasmic pattern of two antineutrophil cytoplasmic antibodies (ANCA). ProteinS3 ANCA, which is reactive toward proteinase-3 (PR3) or myeloperoxidase (MPO), called as c ANCA and p ANCA respectively. 4 C ANCA has sensitivity of 91% and specificity of 99% for GPA, still p ANCA is positive in 25% of cases of GPA and about 5% of cases of GPA are negative for both c ANCA and p ANCA and diagnosis in these cases is made on strong clinical interpretation. 4 Renal biopsy usually shows segmental or globular glomeuralr necrosis with crescent formation, immunofluroscent studies are negative for immune deposits and complements, and hence called as pauci immune. 1 Papillary necrosis due to fibrinoid necrosis of vasa recta, focal segmental glomerular sclerosis (FSGS) or renal limited vasculitis may be other presentations of GPA. 5 Lung biopsy is more invasive and usually not helpful due to patchy involvement of respiratory tract. 1 Invariably the diagnosis is based on clinical presentation, ANCA serology and renal biopsy. In our patient, the clinical presentation and very high serology was enough to guide our management and RPGN on renal biopsy further consolidated the diagnosis. Significant improvement in morbidity and mortality has been observed recently with the use of Immunosuppressive medications and plasmapheresis. Plasmapheresis increased the chances of renal recovery when used along with induction regimen as recently shown by Pepper RJ, et al. 6 Patients who receive cyclophoshamide and corticosteroid for induction, the remission is seen in 75% by three months, similar to our patient and 90% by six months. Unfortunately nearly half (49%) of these patients attaining remission will have at least one relapse. In maintenance phase Azathioprine or methotrexate use is well established. 7 Greater risk of relapse has been observed in patients with C-ANCA positive or pulmonary involvement. Increasing interest is developing in early detection of relapse for timely management with the help of biomarkers such as CXCL13 (BCA-1), matrix metalloproteinase-3 (MMP-3) and tissue inhibitor of metalloproteinases-1(TIMP-1). 8 Increasing level of ANCA titers may also help in predicting the early relapse though may not be sensitive 4 Rituximab (monoclonal antibody CD20) is a new addition in the armamentarium of immunosuppressive medications for GPA. 5 Recent trials have shown its efficacy as induction therapy alone and also in patients with relapse. 7,9 Due to the high cost of rituximab, cyclophoshamide still preferred as induction therapy, where as in resistant cases Rituximab is the drug of choice. Anti TNF alpha biologics (Infliximab and etanercept) and mycophenolate mofetil have also been used in resistant cases. 9 A search through PubMed and Pak Medinet revealed four articles of ANCA associated vasculitis from Pakistan; by two centers, representing only twenty five patients. 2,3,10 This does not mean that prevalence of ANCA associated vasculitis is much less, we and our other colleagues have managed several cases of ANCA associated vasculitis,(verbal communication). It is necessary that one of the tertiary care centre from Pakistan take the responsibility of maintaining a registry of all the ANCA associated vasculitis cases to document its clinical presentation and response to current treatment regimen in our population. In conclusion, early detection of GPA is essential since it may rapidly deteriorate as in our patient. High level of index of suspicion and early initiation of management significantly improves morbidity and mortality. Plasmapheresis should be considered early on if AKI due to vasculitis is diagnosed. Grant support and Financial disclosures: None. Nurses' professional values scale‒three: Validation and psychometric appraisal among Saudi undergraduate student nurses Objectives Since the nursing professional values have garnered attention as a principal criterion for safe‒quality nursing practice, it was measured using the Nurses Professional Values Scale‒three. We aimed to validate and ascertain the psychometric indicators of the Arabic version of the Nurses Professional Values Scale–three among Saudi student nurses. Method This methodological study recruited student nurses using convenience sampling from two nursing colleges at KSA. About 438 valid questionnaires were returned out of 500 questionnaires which were distributed over students in a formal day class time; representing a response rate of 87.6%. A 2‒fold cross‒validation process was adopted. A transcultural process was conducted. Face, content, and construct validity using exploratory and confirmatory factor analyses were used. Convergent and discriminant validity were also assessed. The reliability of the scale was assessed using Cronbach's alpha. Results Face validity was achieved. The content validity of items ranged from .83

to 1.00, while it was .96 for the overall scale. The exploratory factor analysis yielded a scale containing 28 items with a three‒factor model, explaining 74.5% of the total variance. Confirmatory factor analysis confirmed that three‒factor solution had an adequate model fit (CMIN/df = 1.98; RMSEA = .065; SRMR = .039, CFI = .972, and GFI = .968). Convergent validity and discriminant validity were achieved. Cronbach's alpha values were .89, .90, .90, and .96 for activism, caring, professionalism, and the overall scale, respectively. Conclusion Adequate levels of reliability and validity of the Arabic version of the Nurses Professional Values Scale–three were established, indicating the appropriateness of using this version to assess the professional values among Saudi and other Arabic‒speaking nurses. Method: This methodological study recruited student nurses using convenience sampling from two nursing colleges at KSA. About 438 valid questionnaires were returned out of 500 questionnaires which were distributed over students in a formal day class time; representing a response rate of 87.6%. A 2-fold cross-validation process was adopted. A transcultural process was conducted. Face, content, and construct validity using exploratory and confirmatory factor analyses were used. Convergent and discriminant validity were also assessed. The reliability of the scale was assessed using Cronbach's alpha. Results: Face validity was achieved. The content validity of items ranged from .83 to 1.00, while it was .96 for the overall scale. The exploratory factor analysis yielded a scale containing 28 items with a three-factor model, explaining 74.5% of the total variance. Confirmatory factor analysis confirmed that three-factor solution had Introduction Values are the objectives and beliefs that determine which decision can be established in order to provide actions. Professionals are usually guided by values that serve as a standard of action to evaluate their behaviors. 1 In health care setting, there are innumerable ethical challenges, 2 which make the development of professional values among healthcare professionals as a crucial concept to impart quality healthcare services. Professional values in healthcare settings are code of ethics and conduct norms that serves as basis for judging practice and actions. Currently, nurses form the largest share of manpower in healthcare organizations 3 and their ever-increasing professional decisions and practices could lead to difficult dilemmas 4 and ethical concerns. 1 Primarily, the nursing profession is grounded in ethics and professional values that shape its performance. 5 Furthermore, professional nursing practice is provided by nurses who are equipped with professional values. 6 According to Aktas¸and Karabulut, 7 values in nursing encompass not only what is considered important for the care recipients, but also provides an appreciation for what is considered important for professional nurse. Additionally, nursing professional values (NPVs) are associated with patient safety and positive patient experiences. 8 Consequently, these values have arisen as criteria for nurses' recruitment in many Western countries and KSA. Since the NPVs have garnered attention as a principal criterion for safe-quality nursing practice, it was measured primarily using the Nurses Professional Values Scale (NPVS) developed by Weis and Schank. 9 The NPVS was conceptualized based on a critical review of the nursing codes of ethics and professional value development among nurses. 9 Later, the NPVS was amended and anchored to the 2001 American Nursing Association's 10 code of ethics and developed into the Nurses Professional Values Scale-Revised 11 (NPVS-R). However, the NPVS-R has been culturally validated in several languages and is popularly used. 12 Although the NPVS-R showed excellent psychometric indicators, Weis and Schank 1 declared that it is not a robust measure. Hence, in accordance to the adjustments made for the 2015 Code of Ethics for Nurses, 13 Weis and Schank 1 updated the NPVS-R and developed the Nurses Professional Values Scale-Three (NPVS-3). Currently, the NPVS-3 is the only tool used to investigate the NPVs of nurses in education and practice contexts. It assesses three domains of NPVs: caring, activism, and professionalism. Caring refers to the commitment of nurses to provide holistic care and protection for all types of patients without discrimination. Activism focuses on nurses' activities to support the profession and improve public and global health. Professionalism reflects nurses' professional development through continuous self-evaluation and life-long learning. However, the implementation of these NPVs into the nursing practice continues to be challenging. 2 Empirical evidence has reported that many nurses are unaware of these NPVs. 5,14 Despite the registered nurses' clinical expertise, there was no significant increase in their NPV mean scores compared to the nursing students. 4 However, these studies argued that the reason behind this gap is the paucity of a valid and reliable tool that is linguistically and culturally adapted. 2,4 Alabdulaziz et al., 2 justified that nursing students' NPVs in KSA and other Arab countries are seldom studied due to the lack of validated and culturally adapted Arabic versions that measure NPVs among nurses. Although Weis & Schank 1 recommended further validation of the NPVS-3 in different cultures to ensure its applicability and reliable results, it has not been validated in Italy 15 and Indonesia. 4 Additionally, the NPVS-3 was validated in KSA using limited techniques. 2 This study published only the factor structure of the NPVS-3 and recommended confirmatory factor analysis (CFA) for future studies to confirm the latent variable structure of the NPVS-3. However, since its factor structure is not robust and is usually affected by sample bias, further validation studies are required to ensure the robustness of the crossvalidated measure. 16,17 Therefore, this study aimed to bridge this gap by evaluating the psychometric indicators and confirming the latent variable structure of the Arabic version of the NPVS-3 among Saudi student nurses. Design and sample This methodological study conducted throughout the cross-sectional period of March 2020 to April 2020. Nursing students were recruited using convenience sampling from two academic institutions. Students were included if they were enrolled in the second (third level) to fifth academic year (tenth level). We excluded students who were in the introductory year. Although there has been a protracted debate about the appropriate sample size for factor analysis (FA), some evidence exists based on the subject-to-variable (STV) ratio, ranging from 5:1 18,19 to 30:1. 17,20 Others have argued that 150 participants are an absolute minimum for FA. 21 However, for an instrument with 28 items, 150 participants were determined as the absolute minimum sample size. Consistent with the best practice for a psychometric appraisal, we adopted a 2-fold cross-validation process through random splitting of the sample into two equal halves to conduct exploratory factor analysis (EFA) on the first half and validate the model on the second half to confirm the model rather than the data. 22 Therefore, we aimed to collect a sample of more than 300 participants. However, the study protocol was approved by institutional review board of King Saud University [KSU-HE-20-71], dated (10/3/2020). Written informed consents were obtained from the respondents prior to their participation. Measures The original NPVS-3 was used along with a socio-demographic sheet that inquired the participants᾽ backgrounds and asked their informed consent. Items on the socio-demographic sheet included age, gender, academic year, and a closed-ended (Yes/No) question on whether the nursing specialty was the first academic choice or not. Initially, the NPVS-3 was developed by Weis and Shank 1 and was designed to measure NPVs among nursing students. Typically, the NPVS-3 is a self-administered questionnaire that comprises 28 items rated on a 5-point Likert scale and requires participants to indicate their responses over five categories for each item, ranging from A (not important) to E (most important). The NPVS-3 encompasses three factors: caring (10 items), activism (10 items), and professionalism (8 items), resulting in a total score ranging from 28 to 140, with high scores indicating a high level of professional values. Concerning the construct, the three-factor structure of the NPVS-3 is frequently supported. 1,2,4,15 A written permission to validate this scale into Arabic language was obtained through an email on 14/10/2019. Translation and cultural adaptation process The transcultural adaptation process of the NPVS-3 was guided by the proposed guidelines for the transcultural adaptation process of self-report measures. 23 In stage I, we recruited two bilingual translators, whose native language was Arabic, to create individual Arabic translations of the NPVS-3. One of the forward translators was a Saudi academic professor in nursing who lived and graduated from the United States of America (USA) with a distinct background in instrument construction. The other was naı¨ve to the instrument content and concepts. The forward translators had in-depth knowledge of colloquial phrases and jargon in both languages. This stage generated two Arabic versions: NPVS-3 AR1 and NPVS-3 AR2 . In Stage II, we compared NPVS-3 AR1 and NPVS-3 AR2 using a third bilingual translator whose native language was Arabic. The suggested modifications were discussed, and a common Arabic translation was obtained. This stage synthesized a common Arabic version of the NPVS-3, named NPVS-3 AR12 . In Stage III, we executed a blind backward translation of the NPVS-3 AR12 using only one bilingual translator, as shown adequate in this stage. 23 The native language of the backward translator was English, and he was neither aware nor informed of the instrument's intent. This stage aimed to ensure conceptual equivalence and clarity. This stage generated an English-translated version of the NPVS-3 named NPVS-3 BA . However, NPVR-3 BA was found to be highly similar to the original NPVS-3. In Stage IV, we invited a panel comprising of four bilingual translators (forward and backward), two students, and a statistician in addition to the principal investigator of this study in a ZOOM session to compare the NPVS-3 AR12 and NPVR-3 BA with the original NPVS-3 and then develop a valid pre-final NPVS-3 AR that is understandable by the equivalent of a 12-years old individual. Additionally, semantic, idiomatic, experiential, and conceptual equivalences were ascertained between the original and pre-final versions. 23 In this stage, a pre-final NPVS-3 AR was synthesized. In Stage V, once a valid prefinal version was generated, it was evaluated using 20 nursing students. The students were asked to identify their perceptions of the scale's items in terms of suitability, relatedness, and clarity. No further modifications were required based on respondents' feedbacks. Thus, the final NPVS-3 AR was prepared and subjected to further validity and reliability tests to ensure its robustness. Statistical analysis IBM Ò SPSS Ò Statistics 24 for Windows v.25 was used for data processing and statistical interpretation. Descriptive and inferential statistics were used to describe the frequency, mean, standard deviation (SD), and significant correlations among the variables. Significant results were inferred at p .05. Cases were screened for missing data and treated according to the data management that proposed by Mertler et al., 25 and Newman. 26 These criteria suggested that if cases with missing data were less than 5% of the whole sample, listwise deletion was appropriate. 25,26 Multivariate normality and outliers Since a univariate normal distribution does not necessarily reflect a multivariate normal distribution, 27 we evaluated the multivariate normal distribution using Royston's H test and Mardia's test considering Mardia's coefficient >8 as an indicator of kurtosis violation. 27 Multivariate outliers were assessed using the Mahalanobis distance. 28 The Mahalanobis distance indicates that cases with probability >.001 would be a cause for concern. 29 Validity assessment The validity of the NPVS-3 AR was assessed and confirmed through face validity, content validity, and construct validity. Additionally, researchers have argued that when a plausible measurement model fit is assumed, convergent and discriminant validity assessments are necessary to conclude about the construct validity. 16,17 Hence, we evaluated convergent and discriminant validity to support the construct validity assessment of the NPVS-3 AR . Face and content validity. To ensure the face validity of the NPVS-3 AR , we asked a panel of six academicians in the field of nursing education to confirm that the NPVS-3 AR measures NPVs. Those experts have in-depth knowledge and contributions in instrument construction in addition to their expertise in nursing profession. The expert panelists also evaluated the content validity of the NPVS-3 AR using the Content Validity Index (CVI) for both items (I-CVI) and the overall scale (S-CVI). The panelists were asked to rate each item of the NPVS-3 AR according to its relevance to the NPVs on a 4-point Likert scale (1 ¼ not relevant, 2 ¼ somewhat relevant, 3 ¼ quit relevant, 4 ¼ very relevant) to prevent neutral or ambivalent responses.

30 Then, the I-CVI was obtained by dichotomizing the results of the 4point relevance scale into two values: ῾1᾽ for relevant (including scores 3 & 4) and ῾0᾽ for irrelevant (including scores 1 & 2). Then, each item score was divided by six, i.e., the number of experts in the panel, resulting in the I-CVI. The S-CVI was calculated using the average method (S-CVI/Ave), in which the sum of the I-CVI was divided by six, i.e., the number of experts. For a panel of six raters, the minimum acceptable indices for the I-CVI and S-CVI/Ave were as .78 and .90, respectively. 30 Construct validity. The construct validity of the NPVS-3 AR was established through EFA, followed by confirmatory factor analysis (CFA). For EFA, assessments of sample size adequacy and data factorability were checked using the Kaiser-Meyer-Olkin (KMO) and Bartlett's test of sphericity. A significant Bartlett's test with KMO value ranging from .60 to 1.00 indicates that EFA would yield reliable factors. 31 In EFA, the data of the first half of the sample (n ¼ 219) were subjected to extraction and rotation methods to identify a plausible pattern underlying our dataset. For extraction purposes, we decided to use the Kaiser-Guttman rule and a scree plot. To extract factors with 100% accuracy, we incorporated parallel analysis (PA) with the Kaiser-Guttman rule and scree plot to extract factors. 32 For the rotation procedure, we employed an oblique rotation using the Promax technique with Kappa power (k ¼ 4) to obtain theoretically meaningful factors. 16,17 Furthermore, we used a criterion of factor loadings value > .40 for retaining items. 16,17 However, after the theoretical framework of the NPVS-3 AR became understandable, we utilized CFA on the second half of the sample (n ¼ 219) to assess how well dataset fit the hypothesized model. IBMÒ SPSSÒ AMOS 33 for Windows v.26 was used to perform the CFA. We evaluated our model using the difference chi-square test (c 2 ) and its associated p value. Additionally, we evaluated several other descriptive indices, including c 2 goodness-of-fit index per degree of freedom 34 (CMIN/df; <3), root mean square error of approximation (RMSEA; < .08), and standardized root mean square residual 35 The convergent validity of the NPVS-3 AR was evaluated using the Fornell & Larcker᾽s criterion 38 which requires that average variance extracted (AVE) for each construct must be greater than .50. For discriminant validity, we used the average variance extracted versus shared variance 38 (AVE-SV) and heterotrait-monotrait (HTMT) ratio correlations. 39 To achieve discriminant validity, each construct's squared AVE must be greater than the correlation involving the construct. 38 Whereas to use HTMT as a criterion, we compare the value of HTMT to a predefined threshold, and when the value is below the threshold, the discriminant validity of the measurement model is considered as achieved. In this study, we decided to use the value of .85 as the threshold (HTMT .85 ). Reliability assessment Since the assumptions of Cronbach's a are rarely met, 40,41 we utilized an alternative coefficient, omega coefficient 42 (u) (McDonald, 1999), to support the conclusion about the test's reliability. 41 McDonald 42 argued that even if the scale yields tau-equivalent items and follows a unidimensional model, u yields the same coefficient value as coefficient a. 42 Concomitantly, composite reliability (CR) has been found appropriate when the items composing the scale are unitweighted creating the total test score, 43 the same as the NPVS-3 AR . Therefore, the u coefficient and CR of the factors were assessed using the bare minimum value of .707 for good reliability. 16,44 Results Sample description About 444 questionnaires returned out of 500 distributed questionnaires. Cases were screened for missing data and yielded 6 cases with partial responses. Since the cases with partial responses (1.35%) constituted less than 5% of the whole sample, listwise deletion function was adopted and resulted in 438 valid cases; representing a response rate of 87.6%. Table 1 presents the frequencies and percentages of the sample᾽s background characteristics. Females comprised more than half of the sample (n ¼ 246; 56.2%). The majority of the students (39.5%; n ¼ 173) were aged 22e24 years, followed by those aged 20e22 years (25.1%). Most of the students (29.1%) were enrolled in the 4th academic year, followed by the 2nd, 5th, and 3rd academic years. Of the total sample, 266 students (60.7%) reported that nursing specialty was their first academic choice, and 172 students reported it as an alternative academic choice. Multivariate normality and outliers Multivariate normality was violated as the result of Royston's H test, which was significant (H 438 ¼ 534.421, p ¼ .006). An evaluation of the Mahalanobis distance indicated no outliers. Face and content validity The panelist looked at the NPVS-3 AR and attested its ability to measure the attributes of NPVs. All items of the NPVS-3 AR were retained as their I-CVI values ranged from .83 to 1.00. The S-CVI/Ave was calculated and yielded a good content validity value of .96. Construct validity Assessments of the data's factorability showed convincing results. The correlation matrix was subjectively scanned and showed no weak coefficients. The KMO statistic was .96, which falls within the range of "Marvelous". 45 Bartlett's test was significant (c 2 ¼ 6685.47, df ¼ 378, p < .001), suggesting that the dataset was factorable. 46 Initial EFA using principal axis factoring (PAF) was performed due to the violation of multivariate normality. 47 Oblique rotation was utilized using the Promax technique on the 28 items. Table 2 presents three factors with eigenvalues well above the Kaiser's criterion of one. The scree plot (Figure 1) showed leveling out at the 4th factor, suggesting a three-factor solution. Additionally, PAF was utilized using a specialized syntax 48 for SPSS Ò . Consequently, the eigenvalues of the first three factors in the actual data were greater than those in the simulative data, while the 4th factor's eigenvalue shifted to be greater, verifying the three-factor solution. The 1st factor explained the highest variance in data and included 10 items that theoretically represented the Activism construct (factor loadings ranged between .72 and .93). The 2nd factor represents caring and comprised 10 items with factor loadings ranging between .55 and .83. Furthermore, eight items with factor loadings ranging between .74 and .95 were clustered on the 3rd factor which reflects the professionalism construct (see Table 3). Collectively, the three factors explained 74.5% of the variance in NPVs among nursing students, suggesting excellent construct validity. 31 Next, CFA was used on the second half of the sample (n ¼ 219) to cross-validate the factor structure of the NPVS-3 AR obtained from EFA. Based on the proposed model information, the number of estimating parameters was less than the number of covariances and variances, suggesting that our model was overidentified. 49 Considering the non-normal property of our dataset, we utilized maximum-likelihood estimation with robust standard errors (MLR) as an estimator. 31,49 The initial three-factor CFA indicated that the empirical data did not fit our 20 However, a revised model was created after the modifications (see Figure 2). Consequently, the model fit indices of the revised model improved considerably, as After the model fit, we investigated convergent validity by assessing the constructs' AVE and CR values. As shown in Table 3, the AVE values of the activism, caring, and professionalism constructs were .70, .69, and .69, respectively, indicating that the model's variance is overwhelmingly explained by its constructs. In addition, all values of CR ranged from .92 to .95, implying that the individual items are adequately representative of their particular constructs. Overall, the convergent validity of the NPVS-3 AR model was well achieved. For discriminant validity, the HTMT .85 criterion and AVE-SV were used. Table 3 shows that all values of HTMT .85 analysis were below the value of .85, indicating that the constructs in the model are empirically distinct. Additionally, in Table 3, squared AVE measures for the three constructs are much larger than the correlation involving the particular construct, indicating further evidence of discriminant validity. Reliability assessment Standard deviations were considerably different from one to another, suggesting that items had different true scores and error variances 50 ; thus, the assumption of a tauequivalent model was violated. Hence, we utilized the u coefficient to support the a coefficient. The coefficient a values, as shown in Table 3 Discussion This study established the psychometric properties of the Arabic version of the NPVS-3, which assesses NPVs among nursing students. The most common guidelines of the transcultural validation process for the self-report test proposed by Beaton et al. 23 were followed to establish the NPVS-3 AR . The NPVS-3 AR was rigorously subjected to validity and reliability evaluations to provide a robust version. Its validity was ascertained through various evaluation techniques, including face validity, content validity, and construct validity with convergent and discriminant assessments. In the content validity assessment, a panel of six experts evaluated I-CVI for the scale's items and the S-CVI for the whole scale based on its relevance to NPVs. The CVIs of the NPVS-3 AR showed favorable content validity when compared to the cutoff values 26 and was also congruent with the results of other NPV studies. 2,4,15 Our data were factorable and followed a non-normal distribution; hence, we subjected it to the PAF extraction method. 47 Therefore, it yielded a three-factor solution, which is consistent with the original 1 NPVS-3, the Italian version 15 of the NPVS-3, and the Indonesian version 4 of Figure 2: CFA result of a three-factor solution with standardized estimates. the NPVS-3. Additionally, rotation of 28 items on the threefactor solution showed fair factor loadings without crossloaded items, similar to the Indonesian study's results 4 and contrary to the findings of the Saudi study, which showed several cross-loaded items on two factors. 2 Compared to the original NPVS-3, the rotated items clustered on three factors: activism, caring, and professionalism. 1 Although the number of clustered items on activism and caring constructs were equal, the activism construct explained the highest share of the variance in NPVs among nurses, followed by the caring and professionalism constructs. These results are congruent with the validation study 2 of the NPVS-3. In the Indonesian and Italian validation studies of the NPVS-3, the caring factor explained the highest share of the variance in NPVs. 4,15 Notably, this study accounted for the highest shared variance of NPVs compared to other NPVS-3 validation studies. 2,4,15 On the other hand, the activism construct reflects the last three provisions of the 2015 code of ethics for nurses. 1,13 It reflects the activist position of professional nurses in political and health policies, global and community health, and leadership positions in the healthcare systems. The second extracted construct was the caring factor, which explained 7.54% of the variance in NPVs. It reflects the first three provisions of the 2015 code of ethics for nurses. 1,13 The last extracted factor was the professionalism, which explained 5.15% of the variance in nurses' NPVs. This factor represents the fourth through sixth code provisions and focuses on nursing boundaries and standards. 13 However, the strongest correlation was found between the professionalism and caring constructs. This supports the evidence that professionalism is fundamental to Saudi nurses' care practices. 51 However, EFA is known as a data-driven technique that has the ability to extract the latent variables from the observed data, while CFA is a theory-driven technique that requires a prior hypothesis to be tested to determine whether the observed data fits the proposed model. Therefore, we utilized CFA after the EFA was conducted to confirm the latent variable model and assess the validity and reliability of the NPVS-3 AR . The CFA indices assume that our revised model is adequate. The same latent variable structure was confirmed in the original, Indonesian, and Italian studies 1,4,15 of the NPVS-3. To the best of our knowledge, this study is the only study that assessed convergent validity and discriminant validity through rigorous procedures to support the construct validity of the NPVS-3 AR . For convergent validity, the constructs' AVE and CR values were assessed, and implied that a large share of the model's variance was explained by its factors. We used the criterion HTMT .85 , as it provides a relatively high violation detection rate and a low false positive rate. 52 Additionally,

we used the AVE-SV procedure to ascertain discriminant validity. However, the results supported the discriminant validity of the NPVS-3 AR . Concerning reliability, the NPVS-3 AR showed high internal consistency coefficients for both, whole scale and constructs. These results have been yielded in other NPVs᾽ studies. 2,4,15 This study had several limitations. First, the sample of this study was recruited from only two academic institutions and consequently underrepresented nursing students enrolled in other Saudi academic institutions, thus; limiting the generalizability of the findings. Second, since we recruited students with different academic levels, some of whom may or may not have been exposed to clinical experience and may, therefore, have heterogeneous experiences in professional values that might have affected the validity of the results. Third, we were unable to conduct a test-retest reliability procedure due to chronological and logistical challenges. Future studies should ascertain test-retest reliability, including a large sample, to strengthen the present findings. The study's findings have several implications for nursing education. The NPVS-3 AR allows nursing educators to investigate NPVs and the associated situations among nursing students to ascertain how those students perceive and develop NPVs. Additionally, it can be used to equip nursing graduates with effective professional values that help fulfill organizational and patient needs. Concomitantly, in nursing practice, it can be used as a post-intervention evaluation tool to assess the impact of related programs on the reinforcement of NPVs among registered nurses. Conclusion The development of NPVs among undergraduate nursing students is crucial for ensuring safe and high-quality patient care. These values have arisen as criteria for nurses' recruitment in KSA. In this study, adequate levels of reliability and validity of the NPVS-3 AR were established, indicating the appropriateness of using this version to assess the NPVs among Saudi and other Arabic-speaking nursing students and registered nurses. Source of funding This study received funding from the Deanship of Scientific Research, College of Nursing Research Centre at King Saud University, Saudi Arbia FAA and AMA; writingdreview and editing: AMA, AEA, FAA, and YMA; funding acquisition: AEA; project administrator: AMA. All authors have critically reviewed and approved the final draft and are responsible for the content and similarity index of the manuscript. Antibacterial Studies of Penicillin G Loaded Carboxylic Cellulose Acetate Nanoparticles Cellulose acetate nanoparticles (CCA NPs) with mean particles sizes of 97 nm were synthesized via the nanoprecipitation process. The antibacterial properties of these CCA NPs were evaluated against Gram (+) and Gram (-) bacteria, respectively. The CCA NPs exhibited good antibacterial activity against Methicillin-resistant Staphylococcus aureus (MRSA) (+), Staphylococcus epidermis (+), Escherichia coli (-), Bacillus cereus (+), and Salmonella typhimurium (-) in range of MIC of 2.5×102 to 5.0×102 μg.mL-1 and MBC of 5.0×102 to 1.0×103 μg.mL-1. Penicillin G (PenG)loaded CCA NPs demonstrated synergistic antibacterial activities against Gram (+) and Gram (-) bacteria. PenG-loaded CCA NPs also exhibited promising antimicrobial activity against the Methicillinresistant staphylococcus aureus (MRSA) superbug, which is resistant to penicillin G. These promising antibacterial properties suggested that CCA NPs could potentially serve as an alternative potent antimicrobial agent for both Gram (+) and Gram (-) bacteria as well as the superbug MRSA. Introduction Even though there are many types of antibiotics available in the market for the treatment of bacterial infections, however, most of the bacteria tend to evolve into mutated antibacterialresistant bacteria. For instance, Staphylococcus aureus evolved and mutated into MRSA superbugs. Furthermore, misuse and overdosage of antibiotics may lead to bacteria resistance towards antibiotics, reduce the effectiveness, and ultimately lead to the emergence of new infections. Therefore, the search for a potential cure for MRSA infection is still a big challenge, and the development of new antibacterial agents has become an urgent need to treat infectious diseases. Recently, polysaccharide-based nanoparticles have been studied extensively for biological applications due to their non-toxic, low cost, good biocompatibility, renewable and biodegradable [1,2]. Also, antimicrobial studies of polysaccharide-based nanoparticles were widely reported. For instance, Ismail and Gopinath [3] reported that starch nanoparticles loaded with penicillin and streptomycin were fabricated via the microemulsion method and evaluated for their antimicrobial activity against Streptococcus pyogenes and Escherichia coli. The result displayed an inhibition zone of 17 mm at the concentration of 1 mg/mL. Another similar study was also reported by Gopinath et al. [4] on the preparation of ampicillin-loaded cellulose nanoparticles and applied for antimicrobial activity against Escherichia coli. The result showed a good inhibition zone of 20 mm. In addition, cellulose can also absorb toxins produced by bacteria and enhance the drugs' effectiveness [5]. However, unmodified cellulose has its limitations due to its weakness of hydration, structural organization, and lack of antimicrobial activity [6,7]. Therefore, modification of cellulose is of vital importance to impart functionality and antimicrobial properties for various biomedical applications [8]. Based on previous studies, several antibacterials studies of antibiotics-loaded cellulose derivatives nanoparticles have been reported. For instance, Panin et al. [9] reported on the preparation of clarithromycin-loaded ethyl cellulose nanoparticles, which exhibited excellent antibacterial activity against H.pyrori by binding to the HEp-2 cell. Besides that, another study related to antibiotic-loaded polymeric nanoparticles was also reported. Farrukh et al. [10] prepared ciprofloxacin (CIP)-loaded diethylaminoethyl cellulose nanoparticles and evaluated them for their antimicrobial activity against E.coli and pathogenic staphylococci with an inhibition zone of 27 mm and 14 mm, respectively. In this study, the antimicrobial activity of the PenG-loaded CCA NPs against grampositive and gram-negative bacteria was studied and evaluated. Therefore, this investigation also aimed to evaluate new possible PenG-loaded CCA NPs to act as promising candidate nanoparticles-based antibacterial against superbugs Methicillin-resistant staphylococcus aureus (MRSA). Preparation of CCA NPs: the dried powdered CCA was dispersed in 10 mL of ultrapure water and added dropwise into 30 mL ethanol via the nanoprecipitation process. The resulting mixtures were centrifuged at 1250 rpm, and the supernatant was removed to obtain CCA NPs. The CCA NPs, were rinsed three times with absolute ethanol and dried in a conventional oven at 60 ˚C overnight. A measured expanse of nanoparticles was dispersed in absolute ethanol, and a drop of the dispersed sample was drop coated onto formvar-coated copper grids. The morphology of samples was characterized and observed under a transmission electron microscope (TEM) (JEOL Model1230). Penicillin G loading: CCA NPs (100 mg) were immersed in phosphate buffer saline (PBS, pH 7.4), which contained PenG (1 mg/mL), and incubated at 37 ˚C for 72 h until equilibrium absorption was achieved. Loading capacity (mg.mg -1 ) = where, PenGini (mg) is the initial amount of penicillin G used, and PenGfree (mg) is the amount of penicillin G remaining in the supernatant. PenGini−PenGfree weight of CCA NPs After a specific time interval, the absorbance of the solution containing the residual drug was measured spectrophotometrically using a UV/Vis spectrophotometer at 212 nm. The molar concentration of penicillin G was calculated from the absorbance values, according to a standard calibration curve in PBS solution. The loading capacity of PenG for CCA NPs was calculated using the following equation (1) [12]. Antibacterial activities: the antibacterial activities of samples were evaluated against Gram (-) pathogenic bacteria (Escherichia coli (-), and Salmonella typhimurium (-)) and Gram (+) pathogenic bacteria (Methicillin-resistant staphylococcus aureus (MRSA) (+), Staphylococcus epidermis (+), Bacillus cereus (+)). Each bacteria strain was cultured in Mueller Hinton broth (MHB) medium and incubated at 37 °C for 24 h to be used as inoculums before being applied to the antibacterial assay of good diffusion, minimum inhibition concentration (MIC), and minimum bactericidal concentration (MBC) analyses. All the methods applied to evaluate the antibacterial activity were according to the Clinical and Laboratory Standards Institute (CLSI) protocol [13]. PenG-loaded CCA NPs were tested for antibacterial activity via well diffusion assay against the Gram (+) and Gram (-) pathogenic bacteria. The pure cultures of bacteria (1×10 6 CFU.mL -1 ) were sub-cultured on MHA and were swabbed uniformly onto the individual plates using sterile cotton swabs. Subsequently, wells were punched into the agar medium by a sterile straw and filled with 75 μL of samples (1.0×10 3 µg.mL -1 ). PenG is used as a positive control. Bacterial-cultured (Gram-negative) plates and bacterial-cultured (Gram-positive) plates were incubated in the upright position at 37 o C for 24 h and 18 h, respectively. The diameter of the inhibition zone was measured with a ruler. Minimum inhibitory concentration (MIC) assay was performed via the microdilution method with slight modifications. Each 100 µL of samples of known concentration prepared was added into 96 well round-bottomed microtiter plates containing 100 µL of Muller Hinton broth (MHB) medium. Dilutions were carried out by a two-fold serial dilution approach. Then, 100 µL of tested microorganisms bacteria (1×10 6 CFU.mL -1 ) were inoculated to all wells, and the microtitre plates were incubated at 37 o C for 24 h. After the incubation of 24 h, 3-(4,5dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) was subsequently added to 96 wells and incubated again at 37 °C for an hour. The optical densities of cultures are read at 540 nm using a microplate reader (Biorad Model 680). From the absorbance of optical densities (OD), the minimum inhibitory concentration was determined as the lowest concentration of samples that inhibits the growth of bacteria [14]. The reduction of bacteria was calculated in percentage according to equation (2) shown below: where, OD test is the optical density of microorganisms treated with sample and ODcontrol is the optical density of microorganisms untreated with sample. Minimum bactericidal concentration (MBC) was determined from minimum inhibitory concentration (MIC) that did not reveal any visible growth of bacteria colonies from the microtitre wells after 24 h of incubation [15]. The inhibition of bacterial growth was assessed by comparing the optical density of samples to normal growth of culture (untreated with prepared samples) in the control wells. Briefly, exactly 5 µL of the mixture from serial dilution of microtitre wells with no sign of turbidity was pipetted onto the MHA agar plates and incubated at 37 o C for 24 h. The bacteria growth on the plate was then observed. All experiments and analyses were carried out in triplicate. Statistical analysis was accomplished using Microsoft Excel, and results are expressed as mean ± standard error (SE). Preparation of PenG-loaded CCA NPs route for antibacterial assay. As shown in Figure 1, prepared CCA NPs were loaded with antibiotics (PenG) via immersion process under incubation at 37 °C for 72 h. The highest PenG loading capacity was evaluated for antibacterial activity against Gram (+) and Gram (-) bacteria, respectively, and provides a release of the PenG to inhibit and deactivate bacteria strains. Also, CCA NPs contribute towards enhancing antibacterial efficiency. Surface morphology of CCA NPs and PenG-loaded CCA NPs As shown in Figure 2 (a), the TEM image showed that the nanoparticles were spherical particles with a mean particles size of 91 nm, while loading of penicillin G onto CCANPs, PenG-loaded CCA NPs were observed to have a spherical shape with a mean particles size of 200 nm based on the TEM micrograph shown in Figure 2 (b). It is because most PenG was absorbed into CCA NPs could lead to the particles size enlarged. This showed that the loading of the antibiotic onto nanoparticles could lead to the increased particles size of the nanoparticles. Loading capacity. As shown in Figure 3, the loading of PenG was observed to increase very rapidly initially between the loading duration of 0 and 8 h. This could be attributed to the initial migration of the drug solution into the CCA NPs until the CCA NPs were wet enough, after which the PenG could be loaded quickly until saturation. However, the loading slowed down gradually between 8 h and 16 h, eventually maintaining the loading capacity after incubation for 32 h or longer. It is because CCA NPs almost being fully occupied by drug molecules. Hence, the maximum loading capacity of PenG was observed at 0.66 mg.mg -1 after 72 h. Subsequently, PenG-loaded CCA NPs were evaluated for antibacterial activity against Gram (+) and Gram (-) bacteria. Antibacterial activities of CCA NPs, and PenG-loaded CCA NPs. Pathogenic bacterial infection is one of the major infectious diseases that lead to globally severe illness and plague to healthcare [16]. Especially, methicillin-resistant Staphylococcus aureus (MRSA) was listed as important pathogens causing severe community in the World Health Organization's priority pathogens list for investigation and development of new antibacterial agents [17,18]. MRSA is a bacterium

that causes infections in different body parts and is hard to treat with antibiotics [19,20]. Based on a previous study, MRSA produced an enzyme that could hydrolyze the β-lactam ring in antibiotic molecules, thus deactivating the function of antibiotics [21]. MRSA is also called a "superbug" due to its resistance to the most commonly used antibiotics [22]. Due to MRSA's medical importance, MRSA is still investigated in many surveillance initiatives [23][24][25][26]. Therefore, the enhancement or development of new antibacterial agents has become urgently needed for the treatment of bacterial infectious diseases. Interestingly, CCA NPs were found to be a good antibacterial agent against MRSA and also other bacteria such as Gram (+) bacteria (Staphylococcus epidermis, and Bacillus cereus) and Gram (-) bacteria (Salmonella typhimurium, and Escherichia coli), respectively. According to the results of antibacterial activities presented in Table 1 and Figure 4 (b and c), PenG-loaded CCA NPs exhibited a more superior antibacterial effect against Salmonella typhimurium, and Escherichia coli with an inhibition zone of 12 and 13 mm, respectively compared to CCA NPs. Further determination of MIC and MBC values which recorded in Table 2, PenGloaded CCA NPs revealed MIC values of 2.5×10 2 µg/mL against both Salmonella typhimurium , and Escherichia coli, while MBC of PenG-loaded CCA NPs against Salmonella typhimurium, and Escherichia coli with the values of 1.0×10 3 and 5.0×10 2 µg/mL, respectively which shown in Figure 5 (a and e). Based on the previous studies, Gram (-) bacteria have peptidoglycan between membranes, which results in an antibacterial agent that is difficult to pass through compared to Gram (+) bacteria, consisting of a peptidoglycan layer on the outside of the cell wall [27,28]. However, it is composed of a protein channel on the outer membrane of the cell wall [29,30]. Several protein channels could be affected by negatively charged ions from a carboxylic acid (COOH), which could increase the membrane permeability on bacteria's cell wall. The carboxylic of CCA NPs could produce proton (H + ). This H + could diffuse into the bacteria's cytoplasm to lower internal pH, disrupting bacteria cellular adenosine triphosphate (ATP) which, produced energy and resulted in the depletion of energy in bacteria [31,32]. Therefore, the bacteria cells are inhibited and damaged. Also, this allows the diffusion of H + ions from COOH into the plasma membrane, which results in the leakage of protein from the membrane bacteria [33,34]. At this point, PenG molecules released from PenG-loaded CCA NPs could easily pass through the outer cell wall and inhibit the peptidoglycan layer of the bacteria from stopping the growth of bacteria cells [33,35,36]. Furthermore, acetate from CCA NPs could penetrate through the cell membrane into the cytoplasm. Roe et al. [37] concluded that acetate anions treated bacteria cells may inhibit the activity of a protein and led to the accumulation of homocysteine which is the last intermediate on the methionine biosynthetic pathway. Thus homocysteine was found to inhibit the growth of Escherichia coli. Therefore, this has shown that PenG loaded onto CCA NPs could enhance its antibacterial activity. On the other hand, Gram (+) bacteria consisted of a peptidoglycan layer outside of the cell wall but lacked an outer membrane compared to Gram (-) bacteria [29]. Because of this, PenG molecules could penetrate through the outer cell wall easily to reach the peptidoglycan layer of the bacteria [38]. PenG molecules consist of β-lactam, which could interact with peptidoglycan targeted sites and inhibit peptidoglycan biosynthesis. As a result, the formation of a new cell wall of microorganisms could be avoided [39,40]. From Table 1 and Figure 4 (a), the PenG and CCA NPs against S. epidermis have shown the value of inhibition zone with a diameter of 15 and 13 mm, respectively. This had shown that PenG could produce a good antibacterial effect against S. epidermis. Therefore, the S. epidermis strain was able to be inhibited by PenG well compared to CCA NPs. In addition, PenG-loaded CCA NPs could produce a better antibacterial effect against Staphylococcus epidermis with a diameter inhibition zone of 14 mm compared to CCA NPs. This has proven that CCA NPs loaded with penicillin G have the potential to enhance antibacterial activity. Table 2 also showed that PenGloaded CCA NPs had produced a lower value of MIC with 1.25×10 2 µg/mL against Staphylococcus epidermis compared to CCA NPs with MIC of 2.5×10 2 µg/mL. Therefore, the PenG-loaded CCA NPs against Staphylococcus epidermis with a reduced growth rate of 97.53%. Similarly, PenG-loaded CCA NPs also showed good antibacterial activity against Bacillus cereus with an inhibition zone of 12 mm compared to both PenG and CCA NPs with an inhibition zone of 9 mm. Further evaluated by MIC and MBC analysis which is shown in Table 2 and Figure 5 (c), PenG-loaded CCA NPs had shown the lower value of MIC and MBC value of 1.25×10 2 and 5.0 ×10 2 µg/mL, respectively, against Bacillus cereus. This has proved that loading of PenG onto CCA NPs could exhibit better antibacterial effects which are necessary to inhibit those bacteria cells. However, antibiotics such as PenG are less effective against MRSA due to MRSA has mutated Staphylococcus aureus, which is highly resistant to antibiotics containing methicillin molecule [22]. PenG against MRSA with an only exhibited inhibition zone of 8 mm which is revealed in Table 1 and Figure 4 (d). This smaller inhibition zone of PenG against MRSA is due to MRSA being able to produce a penicillin-binding protein (PBP2a) which is resistant to β-lactam ring in PenG, and stop the inhibitory effect of the PenG [41,42]. Therefore, MRSA can be resistant to all antibiotics that contain β-lactam ring structure and deactivate the functions of the antibiotic [43,44,45,46]. In contrast, CCA NPs against MRSA has a better inhibition zone of 17 mm than PenG alone. Since CCA NPs had exhibited good antibacterial activity against MRSA. Notably, PenG loaded onto CCA NPs had exhibited an excellent antibacterial effect against MRSA with larger values of inhibition zone diameter, which was 20 mm compared to both PenG and CCA NPs and further determined by MIC and MBC of PenG-loaded CCA NPs against MRSA which recorded in Table 2 and Figure 5 It was shown that PenG-loaded CCA NPs could enhance antibacterial effect against MRSA with lower values of MIC and MBC which were 1.25×10 2 and 5.0 ×10 2 µg/mL, respectively, compared to both CCA NPs and PenG alone. In addition, the reduction growth of MRSA (98.63%) with PenG-loaded CCA NPs had shown a great enhancement in antibacterial effect compared to PenG alone (94.83%). Figure 6 (a) and (b) compared the morphology of bacteria before and after being treated with PenG-loaded CCA NPs. The shape of MRSA bacteria cells was disrupted and damaged after being treated with PenG-loaded CCA NPs compared to untreated MRSA. The antibacterial mechanism of this phenomenon could be due to the proton (H + ) produced from COOH, which could diffuse into the bacteria's cytoplasm to lower internal pH, disrupted bacteria cellular adenosine triphosphate (ATP) which, produced energy and resulted in depletion of energy in bacteria [31]. Furthermore, acetate anion produced from CCA NPs also diffused into the cell membrane and led to the inhibition of enzyme activity by the accumulating acetate anions. Wei et al. [47] reported that acetate ion could inhibit Staphylococcus aureus by inhibiting protein transcription factor called nuclear factor kappa B (NF-kB), and deactivating it. PenG released from CCA NPs could pass through the outer cell wall and inhibit peptidoglycan synthesis, which could terminate the growth of bacteria cells [39]. Conclusions In this study, the antibacterial property of CCA NPs has been evaluated. CCA NPs showed great potential as a promising antibacterial agent, and PenG-loaded CCA NPs displayed synergistic antibacterial effect against Gram (-) and Gram (+) bacteria strains and the Methicillin-resistant Staphylococcus aureus (MRSA) superbug. The mechanism underlying the antibacterial activity was due to the dissociation of H + from CCA NPs, which decreased the pH of bacteria cells and disrupted the cells membrane. Furthermore, acetate ions could inhibit the growth of bacteria cells by deactivating the protein of bacteria. Given the various unique properties of cellulose-based nanoparticles such as low toxicity, biodegradability, abundance, high surface to volume ratio, and excellent antibacterial properties, CCA NPs and PenG loaded CCA NPs were envisaged to be the potential nanoparticles-based antibacterial agents for the effective treatment of bacterial infections. Analgesia Nociception Index-Guided Remifentanil versus Standard Care during Propofol Anesthesia: A Randomized Controlled Trial The clinical benefits to be expected from intraoperative nociception monitors are currently under investigation. Among these devices, the Analgesia Nociception-Index (ANI) has shown promising results under sevoflurane anesthesia. Our study investigated ANI-guided remifentanil administration under propofol anesthesia. We hypothesized that ANI guidance would result in reduced remifentanil consumption compared with standard management. This prospective, randomized, controlled, single-blinded, bi-centric study included women undergoing elective gynecologic surgery under target-controlled infusion of propofol and remifentanil. Patients were randomly assigned to an ANI or Standard group. In the ANI group, remifentanil target concentration was adjusted by 0.5 ng mL−1 steps every 5 min according to the ANI value. In the Standard group, remifentanil was managed according to standard practice. Our primary objective was to compare remifentanil consumption between the groups. Our secondary objectives were to compare the quality of anesthesia, postoperative analgesia and the incidence of chronic pain. Eighty patients were included. Remifentanil consumption was lower in the ANI group: 4.4 (3.3; 5.7) vs. 5.8 (4.9; 7.1) µg kg−1 h−1 (difference = −1.4 (95% CI, −2.6 to −0.2), p = 0.0026). Propofol consumption was not different between the groups. Postoperative pain scores were low in both groups. There was no difference in morphine consumption 24 h after surgery. The proportion of patients reporting pain 3 months after surgery was 18.8% in the ANI group and 30.8% in the Standard group (difference = −12.0 (95% CI, −32.2 to 9.2)). ANI guidance resulted in lower remifentanil consumption compared with standard practice under propofol anesthesia. There was no difference in short- or long-term postoperative analgesia. Introduction The monitoring of nociception has made substantial progress in the last decade. Several devices have been validated as monitoring tools for intraoperative nociception. Among these devices, the Analgesia Nociception Index (ANI, Mdoloris Medical Systems, Loos, France) has the particularity of assessing more specifically the parasympathetic 2 of 11 component of the autonomic response. Using the electrocardiogram signal as an input, it provides a continuous, normalized and automated index, comprised between 0 and 100, derived from the high-frequency component of heart rate variability. In anesthetized patients, the ANI decreases when the level of analgesia does not compensate the intensity of the nociceptive stimulation [1][2][3]. The amplitude of this ANI decrease is positively related to the intensity of the stimulation, and inversely correlated to the amount of opioids [4][5][6][7]. Based on the first published studies, the manufacturer suggests that an ANI of between 50 and 70 may correspond to adequate antinociception. The final goal of the ANI, as for all nociception monitors, is to improve patients' outcomes. Individually adjusting opioid administration according to this pharmacodynamic biofeedback throughout the surgical procedure is expected to limit opioid underdosage and overdosage. This might improve hemodynamic stability, prevent opioid tolerance and hyperalgesia, and also decrease the incidence of opioid-related side effects. Two studies, performed under sevoflurane anesthesia, have shown encouraging results regarding ANI-guided intraoperative opioid administration, with either intraoperative [8] or early postoperative [9] benefits. Conversely, another study failed to demonstrate any advantage of ANI guidance over standard practice [10]. These studies were included in a recent meta-analysis, concluding that under sevoflurane anesthesia, the difference between ANI-guided analgesia and standard care was not significant [11]. This meta-analysis, along with recent literature reviews [12,13], considered the available data insufficient to draw definitive conclusions, and called for additional trials. In particular, there were no published data about ANI guidance of intraoperative opioids under propofol anesthesia. Propofol and sevoflurane both depress global autonomic nervous activity, but their specific effects on the sympathetic and parasympathetic components of the autonomous nervous system are different [14,15]. The ANI data obtained under sevoflurane cannot be directly extrapolated to propofol anesthesia. We designed this prospective randomized controlled trial to assess the potential benefits of ANI-guided remifentanil administration in patients under propofol anesthesia. We hypothesized that ANI guidance would result in lower intraoperative remifentanil consumption, which was our main outcome measure.

We also studied postoperative morphine requirements, pain and opioid-related side-effects. Materials and Methods This was a prospective, randomized, controlled, single-blinded study conducted in two centers: Armand Trousseau Academic Hospital (Paris, France) and Tenon Academic Hospital (Paris, France). The trial was approved by the Ethics Committee for the Protection of Persons (CPP Sud-Ouest et Outre-Mer, Number 1-18-38, 9 July 2018), and registered at clinicaltrials.gov (NCT03498820) before the first inclusion. Written informed consent was obtained from each patient prior to enrollment. Population We included 18-60 year-old women, ASA status I-II, scheduled for a gynecologic surgery under general anesthesia, with an expected procedural duration of at least 60 min. We did not include obese patients, patients with chronic pain, patients with a history of substance abuse or psychiatric disease, patients with cardiac arrhythmia or a pacemaker or patients with a neurologic or metabolic disease. Randomization After inclusion, patients were randomly assigned to ANI group or Standard group, using a secure web-response system (CleanWEB Telemedicine Technologies SAS, Boulogne-Billancourt, France). Randomization (1:1 ratio) was stratified on center and block balanced (different widths of blocks, not communicated to investigators). Randomization was prepared by an independent statistician. The patients were blinded to their group allocation. Anesthesia Upon arrival in the operating room, standard monitoring was initiated: electrocardiogram, non-invasive blood pressure, oxygen saturation, bispectral index (BIS; Covidien, Dublin, Ireland), and temperature. In addition, ANI monitoring was used for all patients, with the thoracic cutaneous electrode placed according to the manufacturer's recommendation. For this study, we only considered "instantaneous ANI", averaged over one minute, with a new value displayed every second. Induction: Anesthesia was induced by effect-site target-controlled infusion (Base Primea; Fresenius-Kabi, Bad Homburg, Germany) of propofol and remifentanil. The initial effect-site estimated target concentrations (Ce) were set at 6 mg mL −1 for propofol (Schnider model), and 4 ng mL −1 for remifentanil (Minto model). Patients received atracurium 0.5 mg kg −1 for intubation. Then, remifentanil Ce was set at 2 ng mL −1 . Ventilation was adjusted to maintain end-tidal carbon dioxide between 35 and 45 mmHg. Maintenance: Propofol was adjusted to target a BIS of (40-60). If the train-of-four induced more than one response before the beginning of wound closure, patients received atracurium 0.25 mg kg −1 . Remifentanil management depended on the group: - In the Standard group, intraoperative remifentanil management was left to the discretion of the anesthesiologist in charge of the patient, according to their usual practice. In both institutions, ANI monitoring was not part of standard practice, so in this group, the anesthesiologist was blinded to the ANI. - In the ANI group, intraoperative remifentanil was guided by the ANI value, and could be modified every 5 min. If ANI was <50, remifentanil Ce was increased by 0.5 ng mL −1 . If ANI was >70, remifentanil Ce was decreased by 0.5 ng mL −1 . If ANI was between 50 and 70, no changes were made. The minimal remifentanil Ce allowed in the protocol was 1 ng mL −1 . Several safety items regarding the management of hemodynamic changes were added to our algorithm: if SBP was >130 mmHg on two consecutive measurements, nicardipine 1 mg kg −1 was administered. Conversely, if SBP was <80 mmHg, patients received 500 mL of crystalloids. If SBP remained low, ephedrine was administered (3 mg boluses) until blood pressure was restored. Finally, if heart rate (HR) decreased below 45 bpm, patients received atropine (1 mg). Atropine or ephedrine administration resulted in the discontinuation of the ANI-guidance algorithm: patients were managed as in standard practice for the rest of the procedure. Emergence: Patients received 15 mg kg −1 of paracetamol (maximum 1 g) and 0.05 mg kg −1 of morphine 30 min before the end of the procedure. Remifentanil was discontinued at the completion of wound closure. After wound closure, a Transversus Abdominis Plane block (laparotomy) or port-site local anesthetic infiltration (laparoscopy) was performed with ropivacaine (2 mg ml −1 ). Patients were then extubated and transferred to the post-anesthesia care unit (PACU). Postoperative Period In PACU, morphine was titrated with 1 mg boluses every 3 min until the visual analog scale (VAS) score was <4/10. Then, morphine was managed by a standardized patientcontrolled analgesia device (1 mg boluses, 6 min refractory period). Patients received 15 mg kg −1 of scheduled intravenous paracetamol (maximum 1 g) every 6 h. If VAS score was >3/10 despite morphine and paracetamol, patients received nefopam 20 mg IV every 6 h as necessary. If VAS score remained >4/10, patients received ketoprofen 50 mg IV every 8 h as needed. Data Collection Intraoperative data: Baseline HR and SBP were obtained just before skin incision. Then, HR, SBP, BIS, propofol Ce, remifentanil Ce and ANI were collected every five min from skin incision until wound closure. For example, during a 3-h procedure, 36 sets of data were obtained. At the end of the procedure, total doses of remifentanil and propofol were recorded, as well as the number of atropine, ephedrine and nicardipine boluses. Surgeons were also asked to rate their overall satisfaction on a 4-points scale (0 = not satisfied at all, 3 = very satisfied). All intraoperative data were collected by an investigator dedicated to the protocol. This investigator could not be blinded to the patient's group. Postoperative data: HR, SBP, SpO 2 and pain score (Visual Analogue Scale, VAS) were collected every 15 min in PACU. Then, HR, SBP, VAS, morphine consumption as well as opioids-related side effects were collected 2, 4, 6, 12 and 24 h after the end of surgery by nurses, blinded to the group allocation. On postoperative day 1, an investigator, unaware of the group, interviewed the patients using a standard set of questions to detect possible intraoperative awareness. Patients were also asked to rate their overall satisfaction on a 4-points scale. Finally, a phone interview was scheduled with each patient 3 months after the procedure. The patients were asked if they still felt pain on the surgical site, and they could answer "yes" or "no". The interviews were conducted by an investigator unaware of the group allocation. Aims and Outcome Measures Our primary objective was to compare intraoperative remifentanil consumption between ANI and Standard groups. The main outcome measure was the total dose of remifentanil (µg kg −1 h −1 ). Our secondary objectives were to compare between the groups: • The quality of anesthesia: the related outcome measures were the total dose of propofol, the number of changes in remifentanil Ce, duration of anesthesia, time to emergence (between remifentanil discontinuation and extubation), potential awareness and surgeon's satisfaction. • Postoperative analgesia: the related outcome measures were postoperative cumulated morphine consumption 12 and 24 h after surgery, the proportion of patients requiring nefopam or ketoprofen, VAS scores, incidence of nausea, vomiting, urinary retention, respiratory depression requiring oxygen administration and patient's satisfaction. • Chronic pain: presence of pain 3 months after the procedure. Statistical Analysis Assuming a mean intraoperative remifentanil consumption of 7.8 ± 1.9 µg kg −1 h −1 in the Standard group [16], 80 randomized patients were needed to achieve 90% power to detect a relative decrease of 20% in remifentanil consumption in the ANI group, considering a non-parametric test with a two-sided alpha of 5% and an expected dropout rate of 10%. Baseline characteristics, preoperative postoperative data were reported using frequency (%) for categorical variables and mean ± standard deviation (SD) or median (interquartile range (IQR)) for quantitative variables, depending on their distribution. The analysis was performed according to intent-to-treat (ITT) principle, among the asrandomized patients who underwent the surgical procedure. Total dose of remifentanil was compared using Wilcoxon Mann-Whitney test. Missing data were replaced by the maximum value observed (worst-case scenario). Sensitivity analyses were performed among the as-randomized population with available data and on the per-protocol population. Per-protocol population was defined as as-randomized population excluding patients with a missing primary outcome value, non-respected eligibility criteria, patients receiving ephedrine or atropine or with a procedure duration shorter than 1 h. To avoid multiple testing, secondary outcomes were compared using a confidence interval approach. Differences (ANI minus Standard group) of means or medians or proportions were calculated with their 95% CIs evaluated using normal approximation, Mood method and Exact method, respectively. In each group, 95% CIs were estimated by normal approximation for means, by distribution-free method for medians and by Exact method for proportions. Post hoc analyses included the number of patients requiring ephedrine, atropine and nicardipine and descriptive plots of remifentanil consumption over surgical time. Analyses were performed with SAS software version 9·4 (SAS Institute Inc., Cary, NC, USA), except for 95% CI differences estimated with R Studio version 1.2.5019 (R: A Language and Environment for Statistical Computing, R Core Team, R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org). All tests were two-sided and a p value of less than 0.05 indicated statistical significance. Results This section may be divided by subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn. Population Eighty patients were included between November 2018 and December 2019. Among them, 78 underwent the surgical procedure (hysterectomy, n = 35; myomectomy, n = 23; adnexectomy, n = 7, other, n = 13; two procedures were cancelled) and were included in the ITT analysis. ANI guidance was interrupted in three patients of the ANI group because they received ephedrine or atropine. The flowchart is provided in Figure 1; patients' characteristics are provided in Table 1. In the 78 patients who underwent surgery, a total of 1864 intraoperative datasets were analyzed between skin incision and wound closure. Mood method and Exact method, respectively. In each group, 95% CIs were estimated by normal approximation for means, by distribution-free method for medians and by Exact method for proportions. Post hoc analyses included the number of patients requiring ephedrine, atropine and nicardipine and descriptive plots of remifentanil consumption over surgical time. Analyses were performed with SAS software version 9·4 (SAS Institute Inc., Cary, NC, USA), except for 95% CI differences estimated with R Studio version 1.2.5019 (R: A Language and Environment for Statistical Computing, R Core Team, R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org). All tests were two-sided and a p value of less than 0.05 indicated statistical significance. Results This section may be divided by subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn. Population Eighty patients were included between November 2018 and December 2019. Among them, 78 underwent the surgical procedure (hysterectomy, n = 35; myomectomy, n = 23; adnexectomy, n = 7, other, n = 13; two procedures were cancelled) and were included in the ITT analysis. ANI guidance was interrupted in three patients of the ANI group because they received ephedrine or atropine. The flowchart is provided in Figure 1; patients' characteristics are provided in Table 1. In the 78 patients who underwent surgery, a total of 1864 intraoperative datasets were analyzed between skin incision and wound closure. Quality of Anesthesia Propofol consumption and time to emergence were not different betwe groups ( Table 2). Duration of anesthesia was shorter in the ANI group. Overall, fo tients received atropine, three received ephedrine, and one received nicardipine. Individual evolution of heart rate and systolic blood pressure are provided in 3. Surgeons were more frequently "very satisfied" in the ANI group: 89.5% vs. 69 the Standard group (difference = 20.2% (95% CI, 1.7% to 39.2%)). No awarene suspected. Quality of Anesthesia Propofol consumption and time to emergence were not different between the groups ( Table 2). Duration of anesthesia was shorter in the ANI group. Overall, four patients received atropine, three received ephedrine, and one received nicardipine. Individual evolution of heart rate and systolic blood pressure are provided in Figure 3. Surgeons were more frequently "very satisfied" in the ANI group: 89.5% vs. 69.2% in the Standard group (difference = 20.2% (95% CI, 1.7% to 39.2%)). No awareness was suspected. Postoperative Analgesia There was no difference between the groups in cumulated morphine consumption 12 or 24 h after surgery ( Table 2). The incidence of opioids-related side effects was comparable between the groups. The proportion of patients requiring nefopam or ketoprofen for rescue analgesia was similar between the groups. Postoperative

VAS scores were low in both groups (Figure 4). The proportion of patients who were "very satisfied" was higher in the ANI group: 83.3% vs. 38.5% in the Standard group (difference = 44.9% (95% CI, 20.8% to 63.8%)). There was no difference between the groups in cumulated morphine consumption 12 or 24 h after surgery ( Table 2). The incidence of opioids-related side effects was comparable between the groups. The proportion of patients requiring nefopam or ketoprofen for rescue analgesia was similar between the groups. Postoperative VAS scores were low in both groups (Figure 4). The proportion of patients who were "very satisfied" was higher in the ANI group: 83.3% vs. 38.5% in the Standard group (difference = 44.9% (95% CI, 20.8% to 63.8%)). Chronic Pain Five patients were lost to follow-up after hospital discharge (did not answer our phone calls after five attempts) and data were unavailable for two other patients. Thus, 71 answers were analyzed (Figure 4). The proportion of patients reporting pain 3 months after surgery was 18.8% in the ANI group versus 30.8% in the Standard group (difference = −12.0 (95% CI, −32.2% to 9.2%)). Discussion Under propofol anesthesia, ANI guidance of intraoperative remifentanil resulted in a significant decrease in total remifentanil consumption, while maintaining a stable anesthesia. This decrease was not associated with modifications in postoperative morphine requirements, or opioids-related side-effects. Fewer patients in the ANI group reported chronic pain 3 months after surgery, but this difference was not significant. Under volatile anesthetic agents, the ANI has been used to guide intraoperative opioids in different settings, and with various results. In bariatric and breast surgery, ANI guidance resulted in a decrease in intraoperative opioid consumption [8,17]. No postoperative benefits were evidenced in these studies. Conversely, in spine surgery, Chronic Pain Five patients were lost to follow-up after hospital discharge (did not answer our phone calls after five attempts) and data were unavailable for two other patients. Thus, 71 answers were analyzed (Figure 4). The proportion of patients reporting pain 3 months after surgery was 18.8% in the ANI group versus 30.8% in the Standard group (difference = −12.0 (95% CI, −32.2% to 9.2%)). Discussion Under propofol anesthesia, ANI guidance of intraoperative remifentanil resulted in a significant decrease in total remifentanil consumption, while maintaining a stable anesthesia. This decrease was not associated with modifications in postoperative morphine requirements, or opioids-related side-effects. Fewer patients in the ANI group reported chronic pain 3 months after surgery, but this difference was not significant. Under volatile anesthetic agents, the ANI has been used to guide intraoperative opioids in different settings, and with various results. In bariatric and breast surgery, ANI guidance resulted in a decrease in intraoperative opioid consumption [8,17]. No postoperative benefits were evidenced in these studies. Conversely, in spine surgery, ANI guidance did not result in a difference in intraoperative opioid consumption [9,18], but could be associated with benefits in the first 90 min after emergence: lower pain scores, less postoperative morphine, less nausea. Finally, during laparoscopic cholecystectomy, intraoperative opioid dosage was not reduced by ANI guidance, and no postoperative benefits were evidenced. These results, although indisputably conflicting, should be interpreted with caution because of the heterogeneity in the anesthetic agents, surgical procedures and populations. Several devices have been validated as quantitative nociception monitors [7,19]. Pupillometry [16], Surgical Pleth index [20] and Nociception Level [21] have demonstrated an intraoperative opioid-sparing effect under propofol-remifentanil anesthesia: our study demonstrates that ANI has the same ability in our experimental conditions. However, as is the case with the ANI, there are also negative reports with each of these monitors used in different anesthetic conditions [22][23][24]. The potential benefits of nociception mon-itoring do not only depend on the choice of the monitoring device; they also depend on the global anesthetic strategy and surgical context, the thresholds of intervention and the target population. The current issue may now be to determine the best way to use each of the validated nociception monitors, in order to assess "if" and "how" they can be useful for the patients [12]. Our results, along with the other published data, suggest that ANI monitoring could prove more useful under propofol than under volatile agents, with short-acting opioids such as remifentanil, during long rather than brief surgical procedures. The size of the opioid-sparing effect we reported was consistent, with a difference of approximately 30% between the groups. In a previous study, our team investigated the benefits associated with pupillometry-guided remifentanil in a very similar context: the same population, surgical procedures, anesthetic agents, and frequency and amplitude of remifentanil steps [16]. We had evidenced a decrease in remifentanil consumption of approximately 50% in the pupillometry-guided group. However, interestingly, median remifentanil consumption in the former pupillometry group (3.8 µg kg −1 h −1 ) was of the same order as the dose received in our ANI group. Propofol consumptions in both studies were also comparable. Thus, using either the ANI or pupillometry in similar populations and similar surgical contexts led to relatively close remifentanil consumptions. In contrast, median remifentanil consumption in the Standard group of our current study was well below the one reported in the Standard group of the pupillometry study (7.9 µg kg −1 h −1 ). Our relatively low standard remifentanil consumption might reflect the fact that, at least in our center, standard practice has changed since we published the pupillometry study. ANI guidance did not result in more frequent adaptations of remifentanil Ce. The decrease in remifentanil consumption might be explained by differences in the timing, amplitude and direction of the Ce changes ( Figure 2). There were no substantial intraoperative hemodynamic differences between the groups. Only one patient in the ANI group received nicardipine (single bolus), and very few patients received atropine or ephedrine in both groups. In our setting, ANI guidance allowed for us to maintain a stable anesthesia while reducing opioid consumption. Remifentanil has been associated with postoperative hyperalgesia. In our former study [16], pupillometry led to a moderate decrease in postoperative morphine. In contrast, in this study, we failed to demonstrate any association between the lower remifentanil consumption in the ANI group and postoperative morphine consumption. This result might have several explanations. The monitor-related remifentanil decrease was less marked in this study: the amplitude of the difference might not have been sufficient to induce a significant postoperative opioid-sparing effect. In addition, the amount of remifentanil administered in the Standard group might have been too low to induce hyperalgesia. Hyperalgesia has been associated with the development of chronic pain. The proportion of patients who reported persistent pain 3 months after surgery was lower in the ANI group. However, the width and overlap of the confidence intervals did not allow for us to conclude a difference between the groups. Our study was not designed to answer this question, and might have lacked the necessary power to detect a difference in chronic pain incidence. In addition, we did not use a validated chronic pain questionnaire during the telephone interview. Our study has several other limitations. Our anesthetic protocol did not include antihyperalgesic medications such as ketamine, or other adjuvants such as alpha-2 agonists or lidocaine. We discontinued ANI guidance when atropine or ephedrine was administered. These agents are expected to modify the ANI, but the amplitude and duration of their effect on the index have not yet been precisely described. Whether ANI guidance still makes a difference when these agents are used remains to be demonstrated. In addition, our study was performed in a very specific population: we did not include elderly, diabetic or obese patients or patients with chronic pain or arrhythmias. Thus, our patients do not represent the usual population managed by anesthesiologists on a daily basis. Whether our results can be extrapolated to a wider population also remains to be demonstrated. Finally, because it is our institutional standard practice, we used two different regional anesthesia techniques, depending on the surgery (TAP-block for laparotomies, wound infiltration for laparoscopies); although these techniques are described as equivalent in gynecological surgery [25], this might have affected the amount of analgesia required in the early postoperative period. However, as the proportion of laparoscopies/laparotomies was equivalent in both groups (Table 1), it is unlikely that our results were influenced by the techniques of regional anesthesia. In conclusion, ANI-guided remifentanil administration resulted in lower remifentanil consumption compared with standard practice, while maintaining a stable anesthesia in healthy women undergoing major gynecological surgery under propofol-remifentanil TCI. This technique was not associated with peri-operative complications, and there was no difference in postoperative outcomes. ANI, along with other nociception monitors, should be further investigated under different experimental conditions to optimize the potential clinical benefits they may bring to patients. Prevalence of tick-borne pathogens in questing Ixodes ricinus ticks in urban and suburban areas of Switzerland Background Throughout Europe, Ixodes ricinus transmits numerous pathogens. Its widespread distribution is not limited to rural but also includes urbanized areas. To date, comprehensive data on pathogen carrier rates of I. ricinus ticks in urban areas of Switzerland is lacking. Results Ixodes ricinus ticks sampled at 18 (sub-) urban collection sites throughout Switzerland showed carrier rates of 0% for tick-borne encephalitis virus, 18.0% for Borrelia burgdorferi (sensu lato), 2.5% for Borrelia miyamotoi, 13.5% for Rickettsia spp., 1.4% for Anaplasma phagocytophilum, 6.2% for "Candidatus Neoehrlichia mikurensis", and 0.8% for Babesia venatorum (Babesia sp., EU1). Site-specific prevalence at collection sites with n > 45 ticks (n = 9) significantly differed for B. burgdorferi (s.l.), Rickettsia spp., and "Ca. N. mikurensis", but were not related to the habitat type. Three hundred fifty eight out of 1078 I. ricinus ticks (33.2%) tested positive for at least one pathogen. Thereof, about 20% (71/358) were carrying two or three different potentially disease-causing agents. Using next generation sequencing, we could detect true pathogens, tick symbionts and organisms of environmental or human origin in ten selected samples. Conclusions Our data document the presence of pathogens in the (sub-) urban I. ricinus tick population in Switzerland, with carrier rates as high as those in rural regions. Carriage of multiple pathogens was repeatedly observed, demonstrating the risk of acquiring multiple infections as a consequence of a tick bite. Electronic supplementary material The online version of this article (10.1186/s13071-017-2500-2) contains supplementary material, which is available to authorized users. Background Ixodes ricinus is the most frequent tick species throughout Europe. Its life-cycle proceeds through three developmental stages, larvae hatching from eggs, nymphs, and adult males or females. Ixodes ricinus may act as a parasite on more than 200 different species, including humans. It serves as a vector for numerous human and animal pathogens of bacterial, viral, or protozoic origin [1,2]. Tick-borne encephalitis virus (TBEV) causes disease of variable severity, ranging from subclinical infections to severe disease with neurological involvement and potentially fatal outcome. TBEV is taxonomically classified into European, Siberian and Far Eastern subtypes; I. ricinus is the principal vector for the European subtype of the virus [3,4]. Multiple species of rodents, insectivores and carnivores serve as reservoir hosts of TBEV [5,6]. Although the virus is transmitted transovarially in I. ricinus ticks, this transmission is not effective enough in sustaining viral circulation in nature [7]. Co-feeding is essential for TBEV maintenance in natural foci [8]. Mean prevalence in endemic regions ranges from < 0.1 to 5% in Europe and 4 to 39% in Asia [9]. In Switzerland, 38/165 rural sites screened for the presence of TBEV in I. ricinus ticks were shown to harbor natural foci, with a mean virus prevalence of 0.46% [10]. Lyme borreliosis is a multisystemic disease that causes local infections in the skin or disseminates to various tissues, including joints, the central nervous system and the heart [11]. It is prevalent in North America, Europe, parts of North Africa, and northern Asia. Within the B. burgdorferi (sensu lato) complex, B. afzelii, B. burgdorferi and B. garinii are confirmed agents of localized, disseminated and chronic manifestations of Lyme borreliosis, whereas B. spielmanii, B. bissettii and B. valaisiana have only been associated with few cases of Lyme borreliosis [11]. Ixodes ricinus is the predominant vector of B. burgdorferi (s.l.) in Europe and small mammals and ground-foraging birds serve as reservoir hosts [2,12]. Transovarial transmission of B. burgdorferi (s.l.) in I. ricinus is limited [13]. Mean carrier rates are higher in adults (18.6%) than in nymphs (10.1%), and

highest carrier rates are found in central Europe [14]. In questing I. ricinus ticks in (sub-) urban areas of Europe, carrier rates range between 2 and 40.8% [2]. In rural areas of Switzerland, prevalence ranges between 9 and 40% for nymphs and from 22 to 47% in adults [15]. Borrelia miyamotoi may cause a febrile illness possibly presenting as relapsing fever. In immunocompromised patients, it may cause severe disease including meningoencephalitis. The prevalence of B. miyamotoi in I. ricinus ticks in Europe ranges between 0 and 4%. In urban areas of France, a prevalence of 4% was found, whereas the carrier rate was much lower (2/428) in a study conducted in peri-urban and urban areas in southern England [16][17][18][19][20]. Potential reservoir hosts include species of rodents and birds. Different tick species such as Ixodes scapularis and I. ricinus transmit B. miyamotoi transovarially [13,18,[21][22][23]. Babesia spp. are best known to cause animal illness. Three species are currently recognized to be involved in human disease in Europe: B. divergens, B. venatorum (Babesia sp., EU1), and B. microti, with the bovine parasite B. divergens being thought to be responsible for most cases. Clinical signs of babesiosis such as flu-like symptoms or hemolytic anemia are usually but not exclusively limited to immunocompromised patients [2,58,59]. Carrier rates of I. ricinus ticks in Europe range around 0.2 to 3.0% for B. divergens and 0.4 to 1.3% for B. venatorum [2,[60][61][62]. There is evidence for circulation of B. divergens and B. venatorum in urban areas, given that the respective host species (cattle, ungulates) are present [2,30,63]. In Germany, Poland and Slovakia, prevalence in urban habitats ranges from 0.4 to 4.5% [33,64,65]. In rural areas of Switzerland, a prevalence of 1.9% has been documented [27]. Babesia spp. are generally known to be transmitted both transstadially and transovarially in ticks [66]. However, transovarial transmission could so far not be experimentally demonstrated for B. microti [67]. In Switzerland, several studies on the prevalence of all of the above-described tick-borne pathogens in questing ticks have been performed [10,27,[68][69][70][71][72][73]. However, data on the carrier rate of ticks in suburban areas of Switzerland are scarce [60,74], and data on tick-borne pathogens in questing ticks in urban areas were not available to date. In this study, we analyzed 1078 questing I. ricinus ticks sampled at (sub-) urban collection sites throughout Switzerland for the presence of TBEV, B. burgdorferi (s.l.), B. miyamotoi, Rickettsia spp., A. phagocytophilum, "Ca. N. mikurensis" and Babesia spp. Additionally, we analyzed ten tick DNA samples using next generation sequencing (NGS), including two positive samples as well as eight randomly selected samples negative for the investigated pathogens. In these latter eight samples, we searched for pathogens potentially missed using specific screening PCRs as well as for members of the tick microbiota. Tick sampling A total of 45 (sub-) urban study areas were defined in collaboration with the respective authorities. Within the areas, similar collection sites of at least 100 square meters were chosen. Collection sites in urban parks, river sides, cemeteries or open air swimming pool areas were characterized by the presence of bushes or trees and some kind of litter layer. Within urban forests surrounded by built-up areas and within suburban forests located at the border of the city, collection sites were situated at the edge of deciduous forest with high recreational frequentation. Sampling was performed between 10:00 am and 16:00 pm but not on rainy days. Most collection sites were visited only once in June 2016, with a monthly average temperature of about 16°C. At 11 collection sites in the city of Zürich, ticks were collected throughout the year at 6 different time points (June, July, September and November 2015, April and May 2016). These sites were selected to be visited several times in the framework of another study, where the presence of ticks was related to the number of registered tick bites (unpublished data). Temperature at the collection days for these sites ranged between 13-30°C, with a relative humidity ranging between 50-85%. Ticks were collected by flagging low vegetation using a terry towel of 1 m of width and length fixed to a wooden stick. Time invested for tick collection at one collection site ranged between 3 and 5 h. Tick collection was not standardized, since this study did not focus on the tick density in the investigated sites, but rather on the pathogen prevalence found within the analyzed ticks. Collected ticks were kept alive at 4°C. Following identification based on morphological characteristics [75,76], ticks were individually sorted into collection microtubes (Qiagen, Hilden, Germany) and stored at -20°C. Sample preparation Tick samples were homogenized in 600 μl of pre-cooled PBS using the TissueLyser system (Qiagen, Hilden, Germany). After a short centrifugation step, 400 μl of the supernatant were transferred to a Deepwell plate (Eppendorf, Hamburg, Germany), 60 μl of glycerin were added per well and the plates stored at -80°C for further use. 100 μl of the supernatant were used for nucleic acid extraction. Nucleic acid (NA) extraction 100 μl of tick homogenate supernatant were lysed in 400 μl of AVL buffer supplemented with InhibitEX Tablets (Qiagen, Hilden, Germany) in a 96-well MagNA Pure processing cartridge (Roche, Penzberg, Germany). NA extraction was performed with the MagNA Pure 96 instrument and the MagNA Pure 96 DNA and Viral NA Large Volume kit, using the Pathogen Universal LV 2.0 protocol, a sample volume of 500 μl and an elution volume of 100 μl. NA quality was randomly controlled using the Agilent 2100 Bioanalyzer system with the Agilent High Sensitivity DNA Kit (Agilent Technologies Inc., Santa Clara, California, USA). Real-time (reverse transcription-) PCR The real-time (RT-PCR) systems used for screening the tick samples on the presence of TBEV, Borrelia spp., B. miyamotoi, Rickettsia spp., A. phagocytophilum, "Ca. N. mikurensis" and Babesia spp. are summarized in Table 1. For Rickettsia spp. and Babesia spp., two screening systems were used. Sanger (capillary electrophoresis) sequencing Samples positive for Borrelia spp., Rickettsia spp. and Babesia spp. were further examined by sequence analyses to identify the respective species. A subset of samples, where tick species identification based on morphological characteristics was unclear (mainly larvae, n = 75), were analyzed by Sanger sequencing as well. Nested PCR amplifications and sequence analyses were done by Microsynth (Balgach, Switzerland) using the primers and annealing temperatures summarized in Table 2. First-step PCR reactions were run with 2.5 μl of template DNA in a total volume of 12.5 μl including 0.5 μM of each primer, 200 μM dNTPs, 1.5 mM MgCl 2 and 0.02 U/μl KAPA2G Robust polymerase (Axon Lab, Baden, Switzerland). Fourty cycles were run for each PCR (denaturation: 20 s, 95°C; annealing: locusspecific temperatures, 20 s; elongation: 100 s, 72°C; final elongation step: 45 s, 72°C). First-step PCR products were diluted 1:100 for the second-step PCRs, which were run under the same PCR conditions as described for the first-step PCR using the nested primers described in Table 2. Successful amplification was verified on a 1.5% agarose gel. PCR products were purified and uni-directionally Sanger sequenced. Sequences were quality-trimmed and manually edited, then locus-wise subjected to alignment and phylogenetic analysis using the Phylogeny.fr website [77]. Species identification was done using BLASTn comparison (NCBI nucleotide database) [78,79]. The sequences obtained from this study have been deposited in the GenBank database (MF121944-MF121977). Reverse line blot (RLB) Samples positive for Borrelia spp. yielding mixed sequences in Sanger sequencing, indicating the presence of multiple Borrelia species, were additionally analyzed using RLB as described before [80][81][82][83]. The variable spacer region between 2 repeated copies of the 23S and 5S ribosomal genes was amplified by PCR with primers 23S-Bor and B-5S-Bor [80]. For species identification, PCR products were hybridized to 15 oligonucleotide probes [81][82][83] and blotted on an active Biodyne C membrane using a Miniblotter 45 (Immunetics, Boston, Massachusetts, USA). Hybridization was visualized by incubating the membrane with enhanced chemiluminescence detection liquid and by exposing the membrane to an X-ray film. NGS and bioinformatics pipeline Eight randomly chosen samples negative in all pathogen screening PCRs (samples 3-8), 1 sample positive in Borrelia spp., R. helvetica and A. phagocytophilum screening PCRs (sample 1), and 1 sample positive for R. helvetica (sample 2) were subjected to NGS. With these analyses, we aimed to (i) demonstrate the congruency of detecting known pathogens using NGS and real-time screening PCR, (ii) investigate whether some pathogens may potentially be missed using specific screening PCR, and (iii) analyze the microbiota of our I. ricinus tick samples. The NGS workflow as well as the bioinformatics pipeline used for data evaluation are described in Additional file 1. Pathogen prevalence Individual carrier rates were assessed for collection sites with more than 45 collected ticks (n = 9). Furthermore, since the carrier rates did not significantly differ between habitat types (see statistical analysis), overall prevalence was calculated. Larvae were only included for calculation when the respective pathogen is transmitted transovarially (B. miyamotoi, Rickettsia spp., Babesia spp.). As the samples size for the different dates and collection sites was small, a statistical evaluation of pathogen prevalence in dependence of collection dates was not possible. Statistical analysis The stats package of the R software (version 3.3.2) [84] was used to assess differences in pathogen prevalence between collection sites, habitats (cemetery, urban park, urban forest, suburban forest), developmental stages (larvae, nymphs, adults) and gender (male, female). A generalized linear model (GLM) using the logit link function under the binomial distribution was applied. Tick sampling and species identification A total of 1,079 ixodid ticks (66 larvae, 740 nymphs, 138 adult males and 135 adult females) were collected at 18 collection sites (Fig. 1, Table 3); at 27 sites, no ticks were found. Tick collection was not standardized with respect to collection time and area, with exception of the sites where flagging was done at multiple time points. Therefore, the collection success in this study must not be equated to questing tick density in the sampling regions. At the collection sites where flagging was done at six different time points, collection was significantly more successful in spring (June 2015, April and May 2016) than in summer or fall (July, September, November 2015) (Chi-square test with Bonferroni correction, χ 2 = 52.62, df = 2, P < 0.0001) ( Table 4). Except one female Ixodes hexagonus, all ticks were identified as I. ricinus based on morphological criteria or Sanger sequencing results of the cytochrome c oxidase locus. Pathogen prevalence prevalence, we calculated individual carrier rates for collection sites where more than 45 I. ricinus ticks had been collected ( RLB for samples with suspected carriage of multiple B. burgdorferi (s.l.) species Carriage of multiple B. burgdorferi (s.l.) species, indicated by mixed sequences in Sanger sequencing analyses, was found in 23 I. ricinus ticks (13 nymphs, four males, six females). Using RLB, however, only five of these samples were found to be positive for B. garinii and one sample was found to be positive for B. afzelii. The remaining 17 samples were negative in RLB analysis. Carriage of multiple Borrelia spp. could not be confirmed in any of the samples using RLB. NGS NGS was done with a total of ten samples. Although most of the taxonomically classified reads (Kraken output) were assigned to ixodid ticks (96.5-99.9%), which is expected in untreated metagenomics samples of eukaryotes, the read numbers of the pathogens previously identified by screening PCRs were clearly distinguishable from the background noise in sample 1 and 2. The reads assigned to R. helvetica denoted 76.3 and 82.6%. The reads of sample 1 classified to A. phagocytophilum and B. afzelii represented 1.7 and 0.1%, respectively (Fig. 4a). In the remaining eight samples (3)(4)(5)(6)(7)(8), no known pathogens could be detected using NGS, which is in agreement with the negative screening PCRs. However, a total of 8 samples (2 adult female, 1 adult male and 5 nymphal ticks) were positive for the tick endosymbiont "Candidatus Midichloria mitochondrii" [85] (Fig. 4a, b). In the adult female ticks, the reads classified to "Ca. M. mitochondrii" represented 74 and 92% of all bacterial reads. For the male and nymphal ticks, the percentages of bacterial reads classified to this endosymbiont were 0.1% or 0.5-25%, respectively. In addition, every sample contained variable proportions of organisms known to be residents of soil and water, plant associated bacteria, or normal human microbiota (Fig. 4b) Discussion Throughout Europe, I. ricinus transmits numerous

human and animal pathogens. Its widespread distribution includes urbanized areas. Most wildlife species found in urbanized areas in Europe act as maintenance hosts for I. ricinus, but may also serve as reservoirs of tick-borne pathogens. In urban sites, these hosts may be rodents, hedgehogs, shrews, birds, lizards, dogs and cats. In periurban areas, larger animals such as foxes, roe deer, and wild boars may act as tick-maintenance and pathogen reservoir hosts. As a consequence of increasing urbanization and the behavior of humans increasingly encroaching on their peri-urban surroundings, the exposition of humans to vector ticks and tick-transmitted pathogens is increasing [2,86]. Whereas several studies on the prevalence of various tick-borne pathogens in questing I. ricinus ticks have been done in Switzerland so far [10,27,[68][69][70][71][72][73], only limited research has focused on ticks collected in suburban areas [60,74]. Here, we analyzed questing I. ricinus ticks collected at (sub-) urban sites for the presence of various pathogens. Furthermore, we analyzed ten DNA samples using NGS, thereby detecting true pathogens, tick symbionts, as well as organisms of environmental or human origin. Tick collection was successful in about 40% (18/45) of the areas flagged during this study. As the focus of our study was the investigation of pathogen prevalence rather than tick density, our tick collection method was not highly standardized. Therefore, the number of collected ticks at the different collection sites does not necessarily reflect the tick density in these areas. As an exception, tick collection effort was approximately standardized at eleven collection sites in the city of (Table 4). When comparing collection success between collections done in spring (April, May, June) to collections done in summer or fall (July, September, November), we found that collection was significantly more successful in spring than in summer or fall (P < 0.0001). These findings are in agreement with the results of a study focusing on seasonality of I. ricinus ticks on the vegetation in two regions in Switzerland, where a significant decline of questing activity in June was observed [87]. Also, they are explained by the conditions for tick activity (temperature and humidity), which are more likely fulfilled in spring than in summer or fall. TBEV-infected ticks are distributed in a patchy manner in so-called natural foci. In Europe, within these foci, carriage rates of I. ricinus ticks range between < 0.1% and 5% [9] (Switzerland: 0.46% [10]). In the present study focusing on urban areas, we could not detect any TBEV-positive I. ricinus ticks. However, given the low expected carrier rates, the sample sizes per collection site are too small to allow for a reliable estimation of TBEV prevalence. Accordingly, the prevalence of 0% has to be interpreted with caution, and more extensive studies are needed to precisely estimate the carrier rate of (sub-) urban I. ricinus ticks with TBEV in Switzerland. In studies focussing on urban or peri-urban regions of other European countries (Germany, Poland), TBEV has been detected with carrier rates of 0.31% or 0.1%, respectively [88,89]. On the other hand, other authors estimate the risk for contracting TBE in urban areas to be low [4]. Four different species belonging to the B. burgdorferi (s.l.) complex were detected in questing I. ricinus ticks in our study: B. afzelii (8.2% of ticks), B. garinii (2.8%), B. burgdorferi (s.s.) (1.3%) and B. valaisiana (0.9%). All of them are confirmed agents of Lyme borreliosis [11] and have already been detected in I. ricinus ticks in other studies in Switzerland [15,27]. In agreement with previous observations, we found that B. afzelii and B. garinii are the most prominent species, and that adult ticks are more often infected with B. burgdorferi (s.l.) than nymphs. The latter observation is explained by the fact that adult ticks had two blood meals with the possibility of acquiring B. burgdorferi (s.l.), whereas nymphs only had one [14]. The overall prevalence of B. burgdorferi (s.l.) in the present study was 18.0% (11.7% for nymphs, 25% for adults), with site-specific prevalence being significantly variable (7.2-35.8%, P < 0.0001). These observations are in agreement with a study realized in rural areas of Switzerland, where carriage rates ranged between 9-40% for nymphs and from 22 to 47% in adults [15]. The overall prevalence of B. burgdorferi , two (or more) different B. burgdorferi (sensu lato) species. R. helvetica was significantly more often detected alone than in association with another pathogen (GLM with developmental stage as a dependent variable; Chi-square test with Bonferroni correction, P = 0.023) (s.l.) in questing I. ricinus ticks in our study is highly comparable to carriage rates found in urban areas of neighboring countries, ranging from 2.4 to 26.6% in Germany, 10 to 30% in France, and 10.4% in Italy [2,20,[90][91][92]. In Sanger sequence analyses of the 5S-23S intergenic spacer region, mixed sequences indicating the presence of multiple B. burgdorferi (s.l.) species were obtained for 23 samples (13 nymphs, four males, six females). In confirmatory analyses using RLB, however, only 6 of these samples gave positive results (five B. garinii, one B. afzelii), and carriage of multiple Borrelia spp. could not be confirmed in any of the samples. Since many of these samples contained only very small amounts of Borrelia DNA with cycle threshold values in screening PCR ranging between 36-40 (data not shown), false-negative results in RLB cannot be excluded. In Sanger sequencing, we were able to raise the sensitivity of the test by adding a second-step PCR using nested primers. Since this was not possible in RLB, we expect this test to have a slightly lower sensitivity, accounting for the discrepancy between RLB and Sanger sequencing results. Therefore, the 23 samples, representing 14.9% of ticks positive for B. burgdorferi (s.l.), are regarded as being infected with more than one B. burgdorferi (s.l.) species despite the negative RLB results. This proportion is in agreement with the percentage of carriage of multiple B. burgdorferi (s.l.) found previously [14]. Human disease cases caused by B. miyamotoi, usually presenting as febrile illness have been reported in Russia, USA, the Netherlands and Japan [18]. In I. ricinus, the pathogen is found at a prevalence ranging between 0-3.5% in Europe [17][18][19]. Borrelia miyamotoi has been shown to be present in I. ricinus ticks in Switzerland in rural areas at a prevalence of about 1% [27]. In our study 2.5% of I. ricinus ticks (2.7% of nymphs, 2.6% of adult ticks) were infected with B. miyamotoi, which is slightly less than the prevalence described for urban I. ricinus ticks in France (4%) [20], but higher than the number of B. miyamotoi positive ticks (2/428) reported in a study focusing on urban and peri-urban areas in southern England [16]. Thus, although no disease cases have been reported so far, there is a potential of acquiring such an infection, in urban as well as in rural regions in Switzerland. Studies investigating I. ricinus ticks collected from vegetation or animals in Switzerland revealed Rickettsia spp. carriage rates of 7.3 to 14% [21,26,93]. In accordance with these results and with the detection of Rickettsia spp. in urban areas in other studies in Germany and Slovakia at carrier rates ranging between 2.2-30.1% [30,31,33,34], we found R. helvetica-positive I. ricinus ticks at a prevalence of 13.2% in urban areas of Switzerland. We observed significant differences in site-specific carrier rates (2.6-24.5%, P < 0.0001), which is in agreement with a study in Germany, where prevalence of Rickettsia spp. in I. ricinus ticks ranged between 0-50% [31]. Unlike the frequent detection of R. helvetica in I. ricinus, the documentation of human infection with this agent in different countries, including Switzerland, remains rare [25]. In addition to R. helvetica, three samples were found to be positive for R. monacensis, which has been detected for the first time in Switzerland in 2009 [26] and is known to be present in I. ricinus ticks in at least 18 European countries [25]. R. monacensis has already been discovered in I. ricinus ticks in some urban and peri-urban sites in different European countries [2], which is in accordance with our findings. Anaplasma phagocytophilum has been detected in I. ricinus ticks in Europe at a prevalence between < 1% and about 20%. In Switzerland, carrier rates between 1.2-2% have been found [27,36,[93][94][95][96][97]. Corresponding to these findings we found a carrier rate of 1.4% in urban I. ricinus ticks. This rate is in agreement with carrier rates found in urban areas of Austria and France (1.0 and 0.7%, respectively) [20,41], but is rather low compared to the prevalence found in Slovakia or Hungary (4.5-5.5% and 8.8%, respectively) [42][43][44]. In Switzerland, human granulocytic anaplasmosis (HGA) is a rarely diagnosed disease so far. However, considering the repeated detection of the causative agents in ticks and knowing that the seroprevalence in humans bitten by I. ricinus ticks is 17.1% [98], HGA may increasingly be included in the diagnostic workup of patients with a history of a tick bite. In our study, we merely focused on the detection of A. phagocytophilum, without considering the four different ecotypes. So far, all human cases clustered in ecotype I. The different ecotypes are known to have significantly different host ranges, with ecotype I hosts including numerous urban species [2,50]. We would therefore expect many of the A. phagocytophilum isolates detected by real-time PCR in our study to belong to ecotype I. However, the respective analyses have not been done so far. Neoehrlichiosis is a rare human disease. In Switzerland, a close geographic association of disease cases with I. ricinus populations carrying "Ca. N. mikurensis" has been shown for the region of Zürich, where pool carrier rates of 0-8% were found [99]. In our study we could confirm the presence of "Ca. N. mikurensis" in I. ricinus ticks in the region of Zürich, focusing on (sub-) urban areas. In addition, we could show the pathogen to be present in the cities of Basel, Bern, Geneva, and Neuchâtel, with an overall prevalence of 6.2%. This is a higher rate of carriage compared to findings from urban habitats in Slovakia, where prevalence ranged between 1-2.4% [44,53]. Sitespecific carrier rates for "Ca. N. mikurensis significantly differed in our study, ranging from 0 to 10.6% (P < 0.006). This is in agreement with the variation found in the Swiss study in the rural region of Zürich (pool carrier prevalence between 0-8%) [99]; variable carriage rates ranging between 1.1-4.5% were also found in (sub-) urban habitats in a study conducted in Slovakia, the Czech Republic and Austria [42]. Three Babesia species, B. divergens, B. venatorum and B. microti are currently known to cause human disease, and all of them have been found to circulate in urban areas [2,30,63]. In 2012 other authors found Babesia spp. to be present in 1.9% of I. ricinus ticks collected in deciduous forests in Western Switzerland. Thereof, 64.3% were identified as B. venatorum and 17.9% as B. divergens [27]. Here, we found a carriage rate of questing urban I. ricinus ticks of 0.83%. All positive samples were classified as B. venatorum using Sanger sequencing. The prevalence of 0.8% is in accordance with I. ricinus carrier rates with this parasite in different urban regions in European countries (Germany, Poland and Slovakia), ranging from 0.4% to 4.5% [33,64,65]. Since B. divergens is a bovine parasite, it would only be expected in areas where cattle are found concurrently with I. ricinus ticks [2]. To our knowledge, none of the collection sites of our study represent areas where cattle are present, wherefore the absence of B. divergens is plausible. Human babesiosis is a rare but possibly emerging disease in Europe, with about 50 disease cases reported so far [2,100]. Site-specific pathogen prevalence significantly differed for B. burgdorferi (s.l.), Rickettsia spp., and "Ca. N. mikurensis" (P < 0.0001 for B. burgdorferi (s.l.) and Rickettsia spp., < 0.006 for "Ca. N. mikurensis"). However, these differences were not attributable to the habitat type (i.e. cemetery, urban park, urban forest, suburban forest) (P > 0.1 for B. burgdorferi (s.l.), B. miyamotoi, A. phagocytophilum, and B. venatorum, > 0.05 for "Ca. N. mikurensis"). When comparing the carrier rates from our study focusing on (sub-) urban areas to carrier rates found in rural areas of Switzerland, no obvious differences were found for most pathogens (prevalence in urban vs rural regions for B. burgdorferi (s.l.) 18.0 vs 9.0-47.0% [15], for Rickettsia spp. 13.5 vs 7.3-14.0% [21,26,93], for A. phagocytophilum

1.4 vs 1.2-2.0% [27,36,[93][94][95][96][97], and for "Ca. N. mikurensis" 6.2 vs 0-8.0% [99]). For B. miyamotoi, the overall prevalence was 2.5%, which is higher than the prevalence of about 1% assessed in a study focusing on rural areas of Switzerland. For Babesia spp., the overall prevalence assessed in our study focusing on (sub-) urban areas was lower than the prevalence found in the rural area (0.8 vs 1.9%) [21]. This latter finding is in agreement with a study comparing the carrier rates between urban and natural habitats in Slovakia [64] and might be in association with the presence of competent reservoir hosts. Altogether, the potential of pathogen transmission as a consequence of a tick bite is highly comparable between urban and rural areas. In a study investigating about 270 female I. ricinus ticks in the French Ardennes, 45% of infected ticks were carrying multiple pathogens [101]. In our study involving I. ricinus ticks of all developmental stages, about 80% of infected ticks were positive for only one pathogen, giving a lower proportion of multiple carriage rates. Nevertheless, carriage of multiple pathogens by ticks and therewith co-transmission of pathogens to humans might have important consequences with respect to disease severity and treatment [101][102][103][104]. The most frequent pathogen combinations in our study were B. afzelii + R. helvetica (n = 11) and B. afzelii + "Ca. N. mikurensis" (n = 8). Interestingly, the same pathogens have been found to be predominantly involved in coinfections in a study focusing on mixed deciduous forests in the western part of Switzerland. In both, the present and the previous study, B. afzelii and R. helvetica were the pathogens with the highest prevalence, possibly accounting for the frequent combination of these two bacteria within ticks. B. afzelii and "Ca. N. mikurensis" share common reservoir hosts, which might account for their concurrent detection in individual I. ricinus ticks [27,105,106]. Using NGS, we could confirm the presence of all pathogens previously detected by screening PCRs in 2 samples (Fig. 4a, b). In the eight samples negative in all pathogen screening PCRs (samples 3-8), we did not identify any known pathogen using NGS. However, in six of these samples as well as in samples 1 and 2, we could detect the tick endosymbiont "Ca. M. mitochondrii", a member of the order Rickettsiales (Fig. 4a, b). This bacterium is localized in the mitochondria of ovarian cells in I. ricinus female ticks and is transmitted to all offspring. It has been shown to be highly prevalent in I. ricinus ticks, with a mean carrier rate of females of 95%, but a lower prevalence in other developmental stages [85,107]. Our results agree with these findings with both female, but only five out of seven nymphal I. ricinus ticks being positive for "Ca. M. mitochondrii". Also, the number of reads was much higher in female ticks than in male or nymphal ticks, which is in agreement with the described lower bacterial load in male than in female I. ricinus ticks [107]. Besides known pathogens (R. helvetica, A. phagocytophilum, B. afzelii) and tick endosymbionts, we detected various organisms known to be residents of soil and water, plant associated organisms or members of the normal human microbiota in NGS analyses of ten tick samples (Fig. 4a, b). Since we did not wash the surface of the collected ticks prior to sample preparation and nucleic acid extraction, these findings are easily explainable by the presence of these organisms on the exterior of the ticks. While plant, soil and water organisms originate from the collection sites, members of the human microbiota were transmitted to the tick surface during the collection and sorting procedure. Conclusions In this study we documented the presence of B. burgdorferi (s.l.), B. miyamotoi, R. helvetica, R. monacensis, A. phagocytophilum, "Ca. N. mikurensis" and B. venatorum in the (sub-) urban I. ricinus tick population in Switzerland. The pathogen prevalence was as high as the one in rural regions and thus there is a risk of contracting tick-transmitted diseases in urban areas of Switzerland. Carriage of multiple pathogens was observed in about 20% of infected I. ricinus ticks, and therefore there is a true risk of acquiring multiple infections as a consequence of a tick bite. Acute Pancreatitis in a Pregnant Women at 30 - 31 Weeks of Gestational Age with Complete Cure Introduction: Acute pancreatitis is an acute inflammatory disease of the pancreas characterized clinically by upper quadrant pain and elevated levels of enzymes in the blood. Although The pathogenesis of pancreatitis is not fully understood, gallstone and chronic alcohol abuse is considered for two-thirds or more cases in the united stated. Case Presentation: In this case report, the researchers present a 29-year-old pregnant female G3P2 with 31 w, 2 d of gestational age, who was referring to maternity ward with upper quadrant pain, nausea, and vomiting. Her ultrasound, examination, and blood analysis showed acute pancreatitis due to hyperlipidemia. The patient underwent six plasmapheresis and medical treatment and was discharged with complete cure at 34 weeks of gestational age. Conclusions: Accurate assessment of the incidence and mortality of acute pancreatitis is difficult as mild pancreatitis may be subclinical and deaths may occur before the diagnosis of sever and fulminant attacks. Mortality rate is three percent in patients with interstitial pancreatitis and 17% in patients with pancreatic necrosis. Introduction Pancreatitis is inflammation in the pancreas. The pancreas is a long flat gland that is located in the upper abdomen. It produces enzymes and hormones that help digestion and regulate the glucose processes. Acute pancreatitis can be divided to two broad categories based on Atlanta classification (1). -Interstitial edematous acute pancreatitis is characterized by acute inflammation of the pancreatic parenchyma and per pancreatic tissues without recognizable tissue necrosis. Acute pancreatitis according to severity is divided to the following: -Mild acute pancreatitis, which is characterized by the absence of organ failure or transient organ failure (lesser than 48 hours) and/or local complications. -Sever acute pancreatitis, which is characterized by persistent organ failure (greater than 48 hours) that may involve one or multiple organs. At initial evaluation, the severity of acute pancreatitis should be assessed by clinical examination to assess for early fluid losses, organ failure (particularly cardiovascular, respiratory or renal compromise) measurement of the APACHE2 score, and systematic inflammatory response syndrome (SIRS) score (1,2). Physical findings vary depending upon the severity of acute pancreatitis. In patients with mild acute pancreatitis, the epigastrium may be minimally painful in palpation. In contrast, in patients with severe pancreatitis, there may be significant tenderness to palpation in the epigastrium. Patients may have abdominal distention and hypoactive bowel sounds (BS) due to an ileus secondary to inflammation. Patients with severe pancreatitis may have hypoxemia, fever, tachypnea, and hypotension. In three percent of patients with acute pancreatitis, ecchymosis may be in the periumbilicus (Cullen sign) or the flank (grey turner sign). Patients with severe acute pancreatitis may have dyspnea due to diaphragmatic inflammation secondary to pancreatitis, pleural effusions, or adult respiratory distress syndrome. Approximately five to ten percent of patients with acute severe pancreatitis may have painless disease and have unexplained hypotension (e.g. dialysis and organophosphate poisoning). Although measurement of lipase and amylase is useful for diagnosis of pancreatitis, serial measurements in patients with acute pancreatic are not useful to predict disease prognosis and severity or for changing the management. Serum amylase rises within 6 to 12 hours of the onset of acute pancreatitis. Amylase has a short half-life of approximately 10 hours and in uncomplicated attacks returns to normal within three to five days. Serum amylase elevation of greater than three times the upper limit of normal has a sensitivity for the diagnosis of acute pancreatitis of 67 to 83 percent and a specificity of 85 to 98 percent. Serum lipase has a sensitivity and specificity for acute pancreatitis ranging from 82 to 100 percent. Serum lipase rises within four to eight hours of the onset of symptoms, peaks at 24 hours, and returns to normal within 8 to 14 days. Lipase elevations occur earlier and last longer as compared with elevations in amylase and are therefore especially useful in patients, who present greater than 24 hours after the onset of pain. Serum lipase is also more sensitive as compared with amylase in patients with pancreatic secondary to alcohol, after the onset of acute pancreatitis (3). Overall acute pancreatitis is rare in pregnancy, occurring most commonly in the third trimester, and gallstones are the most common cause. When laparoscopic cholecystectomy is not feasible and a common bile duct stone is highly suspected on imaging, endoscopic sphincterotomy or stenting may help prevent recurrence and postpone cholecystectomy until after delivery (Table 1). Case Presentation In this case report, a 29-year-old pregnant female G3P2 (Gravida 3, Para 2) with gestational age of 31 weeks and three days referred to the maternal ward. Symptoms of this patient were epigastrium pain, RUQ pain, nausea, and vomiting without any delivery (labor pain, PROM, vaginal bleeding) or others sever signs. The vital signs were normal, fetal heart rate was 155 beat per minute and fundal height was normal. The patient did not utilize alcohol or cigarette. Past medical history (PMH) of the patient showed hyper-lipidemia and gestational diabetic mellitus; she was on a diet for GDM. In her drug history, cholestyramine was prescribed from three days before admission due to rising TG. After admission, the author ordered NPO, N/serum, NGtube, echocardiography, and surgery consultation. Blood Analysis (LFT, Amylase, Lipase, Bun, Cr, CBC, CRP, lipid profile, BS, Na, K, U/A) and abdominal-pregnancy ultrasound was requested The The ultrasound showed multi-locolar collection in pancreas with normal gall bladder and liver. Her pregnancy was 31 -32 weeks of gestational age, posterior placenta, BPP = 6/8 (Activity = 0). For this patient, jugular catheter (shaldon) was prepared on the next day and she was undergone plasmapheresis (40 cc/kg) as well as gemfibrozil 600 mg BID, Insulin, and Heparin 5000 IU TDS. After her first plasmapheresis, TG and total cholesterol showed 2626 and 500, respectively, and, then plasmapheresis was done for the patient six times in total and TG and total cholesterol were decreasing. During this time, pregnancy ultrasound, BPP, and AFI were normal and the fetus was monitored closely many times. The patient was discharged after 21 days at 34 weeks of gestational age and with normal blood analysis (Hb = 11.1, HCT = 33.7, MCV = 94.3, MCH = 29.6, PLT = 27000, PT = 10.5, Cr = 0.6, Na = 136, K = 4.4, total cholesterol = 191, TG < 500, BS = 89, TSH = 1.41, Amylase and lipase = NL). The patient moved to her city in Kerman province (Bam city) and finally delivered at 37 weeks after 21 days of hospitalization. She is completely healthy at present. Discussion Acute gestational pancreatitis is rarely associated, yet can be caused by important factors, such as maternal mortality and fetal loss. It is generally believed that APIP is associated with several factors (1); gallstone disease or hypertriglyceridemia are the most frequent, and gallstones are amongst top reasons (2). Other reasons, such as Hyperthyroidism (Hyper parathyroidism), connective tissue diseases, infections, and trauma are not the most common causes of acute gestational pancreatitis (3). Acute pancreatitis is explained after medical abortion (4). Although gallstones are more common causes than hypertriglyceridemia in acute pancreatitis in pregnancy, yet it tends to the severe type in the third trimester (5). Physiological changes in pregnancy, such as overweightness, raised triglycerides, and elevated level of estrogen can increase the incidence of acute pancreatitis in pregnancy (6). Diagnosis of acute gestational pancreatitis is very difficult, particularly in the first trimester towards the third trimester (6). Ruptured corpus luteal cyst and ectopic pregnancy are part of differential diagnoses (6). Associations of APIP with HELLP syndrome, preeclampsia, and diabetes mellitus type 2 are important points and can lead to preterm delivery and increase fetal mortality and mobility (7). 2 Zahedan J Res Med Sci. 2019; 21(3):e91408. Finally, some clinical presentations, namely pain and tenderness in the epigastrium, nausea, vomiting, and abdominal distention led the researchers to characterize pancreatitis; serum amylase and/or lipase were the blood marker for diagnosis. Amylase has severe rise in the first 24 hours and falls down to baseline in three to five days. Instead, serum lipase remained in the upper normal limit steadily for two weeks.

However, there are no differences in both of them for diagnosis (8,9). However, amylase level is not associated with severity (7). The second step is imaging for discovery of the etiology. Abdominal ultrasound and endoscopic ultrasound are useful for diagnosis of APIP with no more additive rise because of Xray radiation (9). Computed tomography, magnetic resonance cholangiopancreatography (MRCP), and endoscopic retrograde cholangiopancreatography (ERCP) are not routine, and should carefully be used case by case (9). Ultimately, the type of pancreatitis should be determined in mild acute pancreatitis (MAP) does not have organ failure and systemic complications recover before long yet in severe acute pancreatitis (SAP), it is presented by permanent organ failure (10). For APIP, collective bargaining is an expected therapy except in pancreatic abscess or infected effusion or gastrointestinal perforation or the condition deteriorates after active treatment. The best time for surgical intervention is the second trimester that is associated with the least complications (10). Another indication of surgery during pregnancy is the presence of cholangitis (11) that has been identified cholecystectomy during the second trimester, which has no additive risk for the mother and the fetus. For the current patient after primary study, the researchers understood that amylase = 131, cholesterol = 1078, TG = 6036 and the ultrasound showed normal gallbladder and liver. As a consequence, the researchers decided to try conservative treatment. Therefore, plasmapheresis (40 cc/kg) was done six times in total and then TG and cholesterol were decreased. Meanwhile, gemfibrozil 600 mg BID, insulin, and Heparin 5000 IU TDS were ordered. With sever acute pancreatitis diagnosis, the researchers started Total Parental Nutrition (TPN) and hospitalized the patient NPO for 21 days. Many studies have shown that in mild acute pancreatitis (MAP), nutritional support is not recommenced and low fat diet can be used in the first week (12). Advising antibiotics in sever acute pancreatitis is controversial and the researchers did not use it in this case. There is no more evidence for using antibiotics in mild acute pancreatitis (13). For the current patient, two other similar cases were reported before by hypertriglyceridemia-induced AP. It is recommended to treat her by plasmapheresis and she was discharged after 21 days from hospitalization in 34 weeks of gestational age and ultimately she delivered at 37 weeks. Ex vivo expansion of dysfunctional regulatory T lymphocytes restores suppressive function in Parkinson’s disease Inflammation is a pathological hallmark of Parkinson’s disease (PD). Chronic pro-inflammatory responses contribute to the loss of neurons in the neurodegenerative process. The present study was undertaken to define the peripheral innate and adaptive immune contributions to inflammation in patients with PD. Immunophenotyping revealed a shift of peripheral myeloid and lymphoid cells towards a pro-inflammatory phenotype. Regulatory T cells (Tregs) were reduced in number, and their suppression of T responder proliferation decreased. The PD Tregs did not suppress activated pro-inflammatory myeloid cells. Ex vivo expansion of Tregs from patients with PD restored and enhanced their suppressive functions while expanded Tregs displayed increased expression of foxp3, il2ra (CD25), nt5e (CD73), il10, il13, ctla4, pdcd1 (PD1), and gzmb. Collectively, these findings documented a shift towards a pro-inflammatory peripheral immune response in patients with PD; the loss of Treg suppressive functions may contribute significantly to this response, supporting PD as a disorder with extensive systemic pro-inflammatory responses. The restoration and enhancement of Treg suppressive functions following ex vivo expansion may provide a potential cell therapeutic approach for patients with PD. INTRODUCTION Parkinson's disease (PD) is a progressive, age-associated neurodegenerative disease characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc). The presence of alpha-synuclein (a-syn) inclusions, pathology in the basal ganglia, and multiple adversely affected systems throughout the body lead to a multitude of physical, sensory, and cognitive complications. 1,2 Current studies and clinical trials focus on clearance of a-syn protein aggregates and disrupting cell-cell pathogenic protein transmission dynamics as hopeful avenues for therapeutic efficacy; however, successful results have been limited. [3][4][5] Pathological findings and disease associations suggest that the immune system is intimately involved with PD, and an extensive study of the dysfunctional immune cells and their destructive mechanisms is warranted to generate novel, impactful therapeutic options with disease-modifying capabilities. Clinical evidence points to inflammation and the immune response as an important mediator in PD pathogenesis and progression. [6][7][8][9] Increased microgliosis and peripheral immune cell infiltration are noted in post mortem brain and in neuroimaging of patients with PD. [10][11][12][13] Furthermore, pro-inflammatory cytokines (IL-6, TNF, IL-1β, IFN-γ etc.) are increased in the CNS as well as in the periphery. [14][15][16][17][18][19] The genetics also point to the injurious effects of inflammation in PD as polymorphisms in a gene coding for HLA-DR (MHC class II surface receptor) increase the risk of late onset PD. 20 Furthermore, other mutant genes linked to PD provide additional compelling evidence for the involvement of inflammation in disease pathogenesis such as PINK1, Parkin, and LRRK2. [21][22][23][24][25] Epidemiologically, there is a decrease in risk of PD in people regularly using non-steroidal anti-inflammatories and in patients previously treated with anti-TNF therapies. [26][27][28] Animal models of PD recapitulate these inflammatory findings and immunemodulating therapies are effective in ameliorating neuroinflammation, disease pathology, and subsequent neurodegeneration in these models. [29][30][31][32][33][34] Due to these inflammatory associations in PD, peripheral immune cell dysfunction is a topic of interest and investigation over the years while also positioning PD as a prime candidate that would benefit from immune-modulating therapies. [35][36][37] With regard to the myeloid compartment, previous studies show shifting of peripheral monocyte populations in PD patients as well as increased expression of chemokine receptor CCR2 on PD monocytes, suggesting enhanced migration of peripheral monocytes to the CNS. [38][39][40] Rodent models of PD confirmed that activated, peripheral monocytes migrating and entering the CNS led to neurodegenerative outcomes. 31,41 Analyses of the peripheral lymphoid compartment in PD demonstrate alterations in lymphocyte populations including CD4 + helper T cell, helper T-cell subsets, and CD8 + cytotoxic T cells. [42][43][44][45][46] Additional studies describe a complex phenotype of the CD4 + compartment in PD patients with decreased anti-inflammatory subsets along with increased pro-inflammatory subsets. 47 Multiple studies point to the direct involvement of T cells in response to pathogenic, aggregated species of a-syn. The abnormal protein causes a loss of peripheral immune tolerance with activation of multiple proinflammatory subsets of T cells. 17,18 Evidence for pro-inflammatory T cells reactive to a-syn in mid to late stages of disease has been reported as has evidence that T-cell involvement is persistent in early, prodromal phases of disease. 16,19 The immune system is a complex and tightly regulated network of innate and adaptive processes known to be compromised in aging and disease. Regulatory T cells (Tregs), an immunosuppressive T-cell subset, are critical regulators of immune cell tolerance and sustain immune homeostatic balance in health and disease. Treg dysfunction has been reported in multiple systemic and neurological disorders resulting in chronic and hyper activation of pro-inflammatory immune mechanisms. 35,48 In neurodegenerative disease such as ALS and Alzheimer's, dysfunction of Tregs is associated with significantly increased pro-inflammatory innate immune myeloid cells. [49][50][51][52] In PD patients, Tregs are decreased in number and display impaired suppression of T-cell proliferation. In animal models of PD, restoring Tregs and their suppressive function reduces disease associated inflammation and provides neuroprotection. 17,53 There is increasing evidence that substantial blood-brain barrier dysfunction, extensive neuro-immune cross talk, and infiltration of peripheral components contribute to the pathogenesis of PD. [54][55][56][57] The present study adds to the evidence for alterations of the peripheral immune system. Peripheral myeloid and lymphoid cell populations become more pro-inflammatory as disease progresses. We document that PD Treg suppression of T-cell proliferation is significantly reduced. Most critically, we document that baseline Tregs do not suppress pro-inflammatory myeloid cells. Following ex vivo expansion, Treg suppression of T-cell proliferation in vitro is significantly enhanced, and suppression of pro-inflammatory myeloid cells is restored. Additionally, transcripts of foxp3, il2ra (CD25), nt5e (CD73), il10, il13, ctla4, pdcd1 (PD1), and gzmb are increased in expanded Tregs, and each of these individually and in varying combinations have been implicated as contributing to the mechanisms whereby Tregs suppress proliferating T cells and activated pro-inflammatory myeloid cells. 58,59 The overall evidence suggests that ex vivo expanded PD Tregs may provide a meaningful therapeutic option for ameliorating the immune dysfunction driving PD disease and progression. RESULTS Activation-mediated shifts in PD peripheral monocyte populations Peripherally derived myeloid cells are of increasing interest in PD disease and progression. An examination into peripheral myeloid cells was done via flow cytometric analysis following staining of whole blood from PD patients and controls ( Supplementary Fig. 1). Classical monocyte populations (CD14 + CD16-) in PD were decreased along with an increase in the intermediate population (CD14 + CD16 + ) (Fig. 1a). There were no changes in the nonclassical monocyte populations (CD14lowCD16 + ). However, in more advanced stages of disease, there was a shift from the classical monocyte population to the intermediate population (Fig. 1b). The total number of monocytes did not change in PD compared with controls but total monocytes decreased with later stages of disease (Fig. 1c). Myeloid-derived suppressor cells (MDSCs) are typically activated and increase their population numbers during chronic, systemic pro-inflammatory activation states. Flow cytometric analysis of monocytic MDSCs (CD14 + HLADR-CD11b + CD33 + ) revealed a slight increase in PD patients compared to controls with a trending increase in the later stages of disease (Fig. 1d). Next, we examined the HLA-DR inflammatory surface signature of these peripheral monocyte subsets in PD and control as surface expression of HLA-DR is upregulated during myeloid activation to promote proinflammatory signaling and communicate to T cells. HLA-DR mean fluorescent intensity (MFI) was increased in the PD intermediate monocyte population (Fig. 1e) but with no apparent deviation as PD patients progressed through disease. Monocyte inflammatory transcript analysis revealed trending increases of pro-inflammatory RNA transcripts from PD monocytes accompanied by decreasing signatures in known anti-inflammatory transcripts but did not reach significance (Fig. 1g). Specifically, we observed trending increases in il6, tnf, and il8 along with decreases in il10 and il13. Together these data suggest a disease-associated, pro-inflammatory shifting of the peripheral monocyte compartment in PD. Pro-inflammatory T-cell changes in PD The interconnected and disease-associated compartment of T-cell populations in the periphery warrants increased investigation. Tcell populations from patients with PD and controls were examined by flow cytometry and RNA gene expression analysis following isolation from peripheral blood. There were no changes in the numbers of CD3 + , CD4 + , and CD8 + T cells from patients with PD compared with controls (Fig. 2a). Phenotypes and functions of T cells for patients with PD and controls were analyzed. A reduction was observed in the T effector (Teff) cell population (CD4 + CD25-) in PD samples (Fig. 2b). Following RNA isolation and RT-PCR analysis, the Teff population from patients with PD was polarized to a pro-inflammatory state as indicated by increased levels of pro-inflammatory transcripts tnf, ifnγ, and il2 (Fig. 2c). tbx21 and rorc, master transcription factors for T helper type 1 (Th1) and T helper 17 (Th17), respectively, were increased in patients with PD compared to controls (Fig. 2d). Our analysis of Tcell populations shows significant alterations consistent with a pro-inflammatory shift in PD patients. Treg numbers and function are impaired in PD patients Immunosuppressive Tregs organize and orchestrate peripheral immune tolerance necessary to maintain inflammatory homeostasis while dysregulation in Treg numbers and/or function can lead to inflammation and disease. We analyzed the PD and control Treg populations, defined as CD4 + CD25 + FOXP3 + T cells, via flow cytometric analysis using peripheral whole blood samples. The analysis showed a significant decline in the number of Treg cells (% CD4 + T-cell population) in PD patients (2.67%) compared to controls (3.42%) (Fig. 3a). Corroborating this, a significant reduction in PD Tregs compared to controls was observed following Treg isolations from the blood (Fig. 3b). Additionally, the MFI analysis demonstrated that Tregs from patients with PD have reduced protein expression of CD25 and FOXP3 protein per cell (Fig. 3c, d). The lower levels of CD25 and FOXP3 suggest an alteration of the suppressive functions of PD Tregs, and prompted a direct assay of their suppressive functions. Isolated PD Tregs demonstrated profound dysfunction as they presented with severely reduced suppressive capacity compared to control Tregs (Fig. 3e). Control Tregs

showed suppression of 59.6% (1:1 Tresp: Treg), 51% (1:1/2), and 34.4% (1:1/4) with corresponding patient Tresp proliferation assays while the PD Tregs could only suppress by 40% (1:1), 25.6% (1:1/2), and 11.6% (1:1/4). These data display an overall reduction in suppressive capacity of PD Tregs by approximately 22.5%. Additionally, PD Treg suppression seemed to worsen with increasing burden of disease (Fig. 3f). Heterogeneity was seen in both control and PD Tresp proliferation while no significance between the two or through disease progression was observed ( Supplementary Fig. 5a). No correlation was seen between control or PD Treg suppression and Tresp proliferation capacity ( Supplementary Fig. 5b). In our study, the PD patients demonstrated reduced circulating Tregs, aberrant markers of signaling, and reduced suppressive capacity on Tresp proliferation. Declining PD Treg function correlates with increasing proinflammatory T-cell activation The loss of immune tolerance by Tregs can directly result in the subsequent increase in pro-inflammatory signaling by other immune cell populations and we examined this relationship in our PD patients. Treg suppression of T-cell proliferation significantly correlated with peripheral pro-inflammatory immune cell phenotypes. A decrease in PD Treg suppressive function at the 1:1/2 (Tresp:Treg) ratio correlated (r = 0.4480 p = 0.04) with an A.D. Thome et al. increase in tnf transcripts from corresponding PD isolated Teffs. Additionally, this decrease in PD Treg suppression also correlated (r = 0.4759, p = 0.03; r = 0.5038, p = 0.04) with an increase in PD Teff ifnγ transcripts (Fig. 4a). These correlations were not significant between control Treg suppression and their corresponding Teff pro-inflammatory transcripts (Fig. 4b). Treg ex vivo expansion restores Treg suppressive functions Although PD Tregs show reduced number and extensive dysfunction, we investigated their ability to respond to protocols designed to increase their immunosuppressive function and tested them in co-culture with proliferating T cells and pro-inflammatory myeloid cells. Following ex vivo culture, Tregs from patients with PD and controls expanded to a similar variable extent (Fig. 5a). Tregs from patients and controls were co-cultured with responder T cells (Tresps) or pro-inflammatory iPSC-derived myeloid cells (Fig. 5b). Co-culture of control Tregs/Tresps had a 59% suppressive capacity at baseline that increased to 79% suppression following expansion. For PD Tregs, baseline suppression levels of Tresps were 42% and were increased to 84% following expansion (Fig. 5c). Baseline Tregs from neither PD patients nor controls suppressed RNA transcription of proinflammatory cytokines il6 or il1β, from iPSC-derived proinflammatory myeloid cells (Fig. 5d, e). Following ex-vivo expansion, both PD and control Tregs were clearly able to suppress iPSC-derived pro-inflammatory myeloid cells. Expanded PD and control Tregs suppressed il6 transcription by 85 and 89%, respectively (Fig. 5d), and suppressed il1β by 59 and 58%, respectively (Fig. 5e). Supernatants from the co-culture assays were collected and examined for levels of IL-6 protein. As with the RNA transcript data, baseline IL-6 protein suppression of PD and control Tregs was minimal with no suppressive capacity (Fig. 5f). However, following expansion, PD and control Tregs suppressed IL-6 protein production and release by 46 and 52%, respectively. These data document that PD and control Tregs respond robustly to the ex vivo expansion protocols in both number and suppressive function, and exceed baseline suppression levels. Fig. 1 Peripheral monocyte populations are shifting and activating in PD. Analysis into the peripheral myeloid cells isolated from PD and controls was done to detect population and polarization changes due to disease and progression. a Flow cytometry analysis of shifting monocyte populations in control (n = 25) vs PD (n = 29). b Monocyte population shifts as a function of disease progression using the H&Y PD scale (C n = 25, H&Y1 n = 4, H&Y2 n = 16, H&Y3 n = 5, H&Y4 n = 4). c No change in overall monocyte counts in control vs PD analyzed samples but d decreasing monocyte numbers through disease progression using H&Y PD scale. e Trending increase in myeloid-derived suppressor cells in PD patients compared to controls (p = 0.09). e Flow cytometric analysis of pro-inflammatory, HLADR MFI signatures on cells in shifting monocyte populations (C n = 25, PD n = 29). f RNA analysis of pan monocytes isolated via negative, bead/column-based methods show increased trends in increased pro-inflammatory transcripts in monocytes from PD patients (il6, il1β, tnf, and il8) and decreased antiinflammatory transcripts (il10, tgfβ, and il13) (C n = 12, PD n = 12). Numbers shown as averages ± SEM with Student's t test or one-way ANOVA with appropriate post hoc testing for multiple comparisons as appropriate. P-values are *p < 0.05, **p < 0.01, and ***p < 0.001. Fig. 2 Peripheral T-cell changes in PD. An investigation into the complementary T-cell compartment of PD patients and controls to find proinflammatory changes was done. a Analysis of lymphocyte populations in blood samples from control and PD patients show no discernable difference in the numbers of CD3, CD4, or CD8 cell populations following flow cytometry (C n = 24, PD n = 30). b After bead/column-based isolation methods from peripheral blood, the number of T effector cells (CD4 + CD25-) is decreased in PD patients compared with controls (C n = 28, PD n = 35). Functional analysis of T effector polarization was done following isolation using RNA transcript analysis of c proinflammatory cytokine transcripts, tnf, ifnγ, and il2, and d RNA of transcription factors for T-cell polarization, tbx21, rorc, and gata3 (C n = 16, PD n = 17). Numbers shown as averages ± SEM with Student's t test or one-way ANOVA with appropriate post hoc testing for multiple comparisons as appropriate. P-values are *p < 0.05, **p < 0.01, and ***p < 0.001. A.D. Thome et al. Gene expression profiles of PD and control Tregs at baseline and following expansion The mechanisms of enhanced Treg suppression following expansion are of interest for therapeutic opportunity and diseasemodifying means. We performed transcript analysis from RNA isolated from both PD and control Tregs at baseline and after ex vivo expansion (Fig. 6). foxp3 and il2ra (CD25) transcripts were both increased in PD and control Tregs. The expression of p2rx7 was increased in PD baseline Tregs compared with control Tregs, possibly suggesting a mechanism of dysfunction and inactivation in this population of Tregs during PD. Interestingly, PD Tregs had reduced expression of p2rx7 following expansion. Although no differences were observed in Treg expression profiles of nt5e (CD73), il10, and il13 between PD and control Tregs at baseline, expression of both nt5e and il13 was increased following expansion. It is important to note that the levels of il13 were increased by 94 and 134 fold in the expanded PD and control Tregs, respectively. Endogenous levels of tgfβ were decreased in baseline PD Tregs compared to baseline controls. Interestingly, both PD and control Tregs reduced their tgfβ expression following expansion. Examination of transcripts involved in other cited mechanisms for Treg suppression such as ctla4, pdcd1 (PD1), cd274 (PDL1), and gzma were analyzed. After ex vivo expansion, we noted a trend toward increased levels of ctla4 and pdcd1 along with decreased trends in cd274 and gzma. Similar to the remarkable increase in levels of il13 following expansion, we noted a similar pattern with gzmb whereby the expanded control Tregs were increased 101 fold compared to baseline and expanded PD Tregs were increased 75 fold. Collectively, these data suggest that ex vivo expansion of Tregs, whether from diseased or control, generates Treg cells enriched with antiinflammatory and immunosuppressive transcripts. DISCUSSION Central nervous system (CNS) inflammation is known to play a prominent role in the pathobiology of PD. However, peripheral inflammation has not been well studied in patients with PD. The current study found that subsets of immune cells in the periphery were pro-inflammatory in patients with PD; there were also increases in many cytokine transcripts that trended in the proinflammatory direction in these patients. Furthermore, and most significantly, PD Tregs were dysfunctional and their numbers decreased in patients with PD which may compound these proinflammatory responses. Finally, this study demonstrates that Fig. 3 Investigation into PD Treg populations shows reduced numbers and impaired function. The number of Tregs in PD patients are decreased via a flow cytometric analysis of CD4 + CD25 + FOXP3 + cells as a percent of total CD4 + population and b counting of viable CD4 + CD25 + immune cells following bead/column-based isolation methods from peripheral blood (C n = 28, PD n = 34). Treg health and function markers were deceased in PD patients compared to controls when examining c CD25 protein MFI and d FOXP3 protein MFI from CD4 + CD25 + FOXP3 + cells during flow cytometry (C n = 28, PD n = 34). e Treg suppression of Tresp proliferation is impaired in PD patients compared to controls at ratios (Tresp:Treg) of 1:1, 1:1/2, and 1:1/4 (C n = 25, PD n = 30). f The suppressive capacity of PD Tregs on Tresp proliferation decreases with increasing PD disease burden using the H&Y disease scale (C n = 25, H&Y1 n = 4, H&Y2 n = 17, H&Y3 n = 5, H&Y4 n = 4). Numbers shown as averages ± SEM with Student's t test or one-way ANOVA with appropriate post hoc testing for multiple comparisons as appropriate. P-values are *p < 0.05, **p < 0.01, and ***p < 0.001. dysfunctional PD Tregs were reversed following ex vivo expansion; the expanded Tregs were immunosuppressive on T-cell proliferation assays and suppressed myeloid cell pro-inflammatory signaling. Phenotyping the expanded Tregs via RNA transcript analysis documented the altered Treg profiles following expansion. Thus, this study demonstrates that in addition to the wellknown CNS pro-inflammatory responses in patients with PD, there are novel concurrent peripheral pro-inflammatory responses in PD that reflect burden of disease. The peripheral immune compartment is of increasing interest in neurodegenerative diseases. Neuro-immune crosstalk results from extensive blood-brain barrier breakdown and infiltration of peripheral cells into the CNS. Many studies have shown that collateral damage from neuronal cell death as well as pathogenic species of a-syn promote pro-inflammatory activation of myeloid cells such as microglia and monocytes/macrophages, and also cause dysfunction of a wide array of central and peripheral immune constituents. 29,31,60,61 The current study demonstrated that monocytes in the blood of patients with PD shifted from the classical monocyte subset into the intermediate subset, and this shift increased with escalating disease burden. The intermediate monocyte subset represents monocyte maturation and a shift to a more pro-inflammatory subset. [62][63][64] A similar study of monocyte populations from patients with PD reported an enrichment in the classical monocyte subset, although a different regrouping of the three monocyte populations combining the classical and intermediate groups allows limited comparisons between both studies. 40 The flow cytometric analysis of monocyte HLA-DR surface expression, a MHC-class II receptor upregulated in monocyte maturation and activation, revealed increased HLA-DR in PD intermediate monocytes. Disease progression was not associated with increased intermediate monocyte HLADR cell expression. Although they did not reach significance, there was a trend for increased pro-inflammatory gene expression in these cells; il6, tnf, and il8 levels were up, whereas il10 and il13 levels were down. Another group showed that PD monocytes were altered in vitro along with a higher proliferative capacity. 65 The current study demonstrated that the total number of monocytes were unchanged in patients with PD which is in accordance with other reports. 40,66 There were increased MDSCs in the periphery of patients with PD. Increases in MDSCs are prevalent in cancer, chronic inflammatory disorders, and reported recently in early stages of neurodegenerative diseases such as Alzheimer's and Parkinson's disease. 51,67 While not significant, this increase in suppressive MDSC populations in PD patients can dilute the proinflammatory phenotype analysis of the isolated, total monocyte population that we analyzed. This MDSC population increased incrementally as disease progressed in PD patients-possibly as an effort to counterbalance the loss of suppressive Tregs, or alternatively due to an increase of a dysfunctional or proinflammatory MDSC population. More advanced, extended analyses of the peripheral myeloid compartment and their phenotypes in patients with PD will allow us to understand their respective contribution to PD while also being a potential proxy for the microglial activation states during disease progression. Early post-mortem analysis of CNS tissue from patients with PD showed diffuse infiltration of activated T cells in areas with microglial activation and alpha-synuclein accumulation. Previous

studies examining peripheral blood-derived T-cell changes were inconsistent and less than definitive. 42,43,46,68,69 The current study documented no changes in the CD3 + and CD8 + T-cell populations in patients with PD; there was a trend for less CD4 + cells in these patients. Peripheral populations of Teffs were significantly decreased in PD, possibly due to trafficking to the CNS. 11,13,70 Interestingly, the decreased population of Teffs express increased pro-inflammatory transcripts such as tnf, ifnγ, rorc, and tbx21. These signatures are indicative of a Th1 and Th17 proinflammatory polarization of T cells. The observation that there was a Th1 bias in patients with PD was previously reported. 47 Th17 cells, another pro-inflammatory T-cell subset that produces IL-17, has been reported to be increased in the periphery of PD patients and can directly induce IL-17R-mediated midbrain neuronal cell death in an in vitro co-culture model of PD. 67,71 Of significance, it is documented that PD T cells recognize and respond to alpha- synuclein epitopes which can drive T-cell responses. 16,19 The correlations of PD Teff pro-inflammatory tnf and ifnγ RNA against Treg produced anti-inflammatory tgfβ and il10 transcripts proved non-significant (data not shown). Previous reports of increased Th17 cells in the periphery of PD patients prompted us to examine associations of Th17 cells and Treg cells in the balance of peripheral immune tolerance. We did not find a correlation between Treg cells and the expression of Teff rorc, the precursor transcript for the Th17-polarizing transcription factor (Supplementary Fig. 4). Future experiments analyzing these sub-populations of CD4 + Teff and Treg cells are warranted to answer these questions. The associations between Teff inflammatory output and Treg function could lead to significant targets for preventing or ameliorating Treg dysfunction in disease. Together, these data support the finding that pro-inflammatory polarization is occurring in T cells of PD patients. Tregs are immunosuppressive cells that regulate the immune response and maintain homeostasis in the inflammatory microenvironment. Extensive studies of Tregs and their functional involvement in health and disease have led to the development of therapies that ameliorate disease. 49,[72][73][74] Tregs are found to be decreased and/or dysfunctional in a number of diseases such as systemic lupus erythematosus, type 1 diabetes, multiple sclerosis, amyotrophic lateral sclerosis, and Alzheimer's disease. 49,50,72,[75][76][77][78][79][80][81][82] The current study demonstrates decreased numbers of Tregs in patients with PD. More importantly, this study demonstrates impaired Treg suppressive function starting early in disease and worsening as disease progresses. CD25 and FOXP3 proteins were Tregs respond robustly to ex vivo expansion protocols generating increased Treg suppression of Tresp proliferation and proinflammatory myeloid cells. a Tregs from both control and PD patients expand their numbers following ex vivo expansion protocols. b Coculture assays utilized to assess baseline and expanded Treg suppressive function. Baseline Tregs from control and PD patients are co-cultured with Tresp cells at 1:1 ratio for 5 days and proliferation assessed via tritium incorporation (C n = 9, PD n = 10). Independently and concurrently, baseline Tregs are co-cultured at 1:1 ratio with iPSC-derived pro-inflammatory myeloid cells overnight for 18 h following stimulation with LPS and IFN-γ. Suppression of pro-inflammatory myeloid effector function measured by il6 and il1β RNA transcripts and IL-6 protein from coculture media. Control and PD Tregs will be ex vivo expanded and subjected to the same battery of co-culture suppression tests to examine increases in suppressive function following expansion protocols. c Increased suppression of Tresp proliferation following ex vivo expansion protocols of both control and PD Tregs. d-f Robust increase in suppression of il6 transcript, il1β transcript, and IL-6 protein following 18 h coculture of expanded Tregs with iPSC-derived pro-inflammatory myeloid cells (C n = 6-7, PD n = 10-12). Numbers shown as averages ± SEM with Student's t test or one-way ANOVA with appropriate post hoc testing for multiple comparisons as appropriate. P-values are *p < 0.05, **p < 0.01, and ***p < 0.001. A.D. Thome et al. also shown to be decreased on PD Tregs which could suggest increased cell dysfunction or disruption of necessary developmental or maintenance signaling for Tregs. Future investigations into diseased Tregs are planned to analyze these aberrant baseline signaling pathways that could lead to deleterious Treg issues, increased peripheral inflammation, and subsequent initiation of neurodegenerative processes. Previous studies reported mixed results concerning Treg numbers and their suppressive functions in patients with PD. 42,69,83,84 In animal models of PD, Tregs were found to be dysregulated 85 ; Treg depletion results in exacerbation of inflammation and neurodegeneration. 86 Therapies harnessing Tregs by reconstitution or functional restoration attenuated neuroinflammation and subsequently slowed neurodegeneration. 17,87,88 Dopamine has been hypothesized to suppress Treg function in vitro, and dopamine replacement therapy has been thereby proposed to be a potential confounding variable in Treg dysfunction in PD. 89 However, another study examining Tregs in dopamine-naïve and dopamine-treated PD patients demonstrated no change in Treg numbers and suppressive function. 47 We found that addition of dopamine at both 1 and 0.1 uM concentrations had no effect on control or PD Treg suppressive function on Tresp proliferation in vitro (Supplementary Fig. 6). The correlations in this study found that the increasing PD Treg dysfunction resulted in an increase in pro-inflammatory activation of PD Teff cells. It is possible that a pro-inflammatory milieu of specific signaling components such as IL-6, IFNγ, TNF, etc. could be driving Treg dysfunction. Investigations into causative peripheral factors causing Treg dysfunction is ongoing, but our preliminary data suggest that these cytokines, per se, do not cause Treg dysfunction in vitro, and direct contact may be a relevant factor. Additionally, targeting dysfunctional Tregs directly may provide a promising route to suppress the inflammatory cascades in PD. Several therapeutic paradigms currently exist that target Tregs to improve their numbers and function. Stimulating IL-2 receptor along with inhibiting the mTOR pathway present promising avenues for correcting dysfunctional Tregs in vivo. 90 This strategy works in a neutral setting but disease complicates the viability of this strategy as the pro-inflammatory milieu provides large thresholds to overcome while cells may be unresponsive to the therapy due to dysfunction caused by chronic inflammation. Previous preliminary clinical studies in ALS patients demonstrated that Tregs appeared unresponsive to in vivo-targeted therapies to restore suppressive function; however, a phase 2a clinical trial from a European consortium suggests that Fig. 6 Transcript analysis of expanded Tregs demonstrate enhancements of Treg anti-inflammatory and immunosuppressive mechanisms. RNA transcript analysis of markers of Treg health, suppressive function, and other mechanisms of Treg anti-inflammatory and immunomodulatory function. Increased levels of Treg health markers following expansion of foxp3 and il2ra (CD25). p2rx7, a marker increased with Treg dysfunction, is increased in PD patients compared to controls at baseline and is reduced following expansion protocols. Markers of anti-inflammatory function, nt5e (CD73) il10, and il13 are significantly increased in control and PD expanded Tregs. There is a decrease in tgfβ in PD Tregs compared to control at baseline and those transcripts are further reduced following expansion protocols. Additional transcript markers of Treg function are increased post expansion in Tregs such as ctla4, pdcd1 (PD1), and gzmb while other markers are trending toward decreasing levels following expansion such as cd274 (PDL1) and gzma (C n = 6-8, PD n = 6-8). Numbers shown as averages ± SEM with one-way ANOVA with appropriate post hoc testing for multiple comparisons as appropriate. P-values are *p < 0.05, **p < 0.01, and ***p < 0.001. subcutaneously administered IL-2 may enhance Tregs in vivo in ALS, and potentially provide clinical benefit. 73 With relevance to PD, Treg targeted therapy utilizing recombinant GMCSF to stimulate Tregs in vivo proved efficacious in inducing Treg responses and protecting against nigrostriatal degeneration in pre-clinical models of disease. 88,[91][92][93] Subsequently, a phase 1 clinical trial using this therapy in a small PD population demonstrated that the therapy was safe and well tolerated and warrants further investigation. 94 An alternative approach to enhancing Tregs is to isolate and purify Tregs from peripheral blood, expand them in vitro, and administer autologous infusions of expanded Tregs as a cell-based therapeutic. 74 This is a promising strategy currently underway in ALS. Our present data in PD demonstrate that ex vivo expansion not only restores suppressive function but also significantly enhances the suppressive function beyond typical baseline levels. The expanded Tregs potently suppress multiple pro-inflammatory pathways in myeloid cells and inhibit Tresp proliferation. This study provides evidence that these expanded Tregs would be effective in targeting and suppressing both innate and adaptive immune processes that are altered and pro-inflammatory in PD. The mechanisms by which expanded Tregs induce significant suppression are not fully understood. Following expansion of control and PD Tregs, we noted increased expression of Treg health and function markers, foxp3 and il2ra (CD25). These gene signatures demonstrate a traditional Treg gene signature that is enhanced following the expansion process. We have found, previously and in this study, that the Treg expansion procedures produce a consistent flow signature of cells enriched with the Treg markers CD4 + CD25 + FOXP3 + (Supplementary Fig. 3). We also observed increased anti-inflammatory cytokine transcripts, il10 and il13, and increased CD73 transcript, nt5e, which can mediate inflammatory cell suppression by converting AMP to adenosine. Additionally, gzmb was increased following expansion in both control and PD Tregs, and gzmb provides an alternative mechanism of suppression i.e., inducing cell death. Collectively, these results, together with those that did not reach statistical significance, such as CTLA4 and PD1, suggest that expanded Tregs could use multiple mechanisms to mediate suppression, and such mechanisms could differ under different circumstances. There is increasing importance in understanding the mechanisms by which expanded Tregs are able to suppress both T cell and proinflammatory myeloid cells. Our data suggest that there are multiple mechanisms working synergistically, as suggested and outlined by Sakaguchi et al. and others. 58,59 Overall, this study documents the shift of PD peripheral immune cells to pro-inflammatory phenotypes that increase with increasing burden of disease. PD Treg numbers and immunosuppressive functions are decreased, and correlate with the increased proinflammatory phenotypes. Furthermore, ex vivo expansion of dysfunctional PD Tregs restores their suppressive functions and enhances their ability to reduce Tresp proliferation and decrease pro-inflammatory myeloid cell responses. Expanded Tregs provide a potentially meaningful therapeutic strategy for cell-based immunomodulatory therapies for diseases with acute or chronic pro-inflammatory insults such as PD. Patient recruitment for PD patients and controls PD patients (n = 39, M/F: 27/12, age: 70.6 ± 8.4) and age-matched healthy controls (n = 31, M/F: 11/20, age: 69.5 ± 8.9) were recruited to the study by the Houston Methodist Neurological Institute under the direction and evaluation of Dr. Eugene C. Lai and his Neurodegenerative Disease Clinic. Patient assessment and diagnosis were evaluated using the Movement Disorder Society clinical diagnostic criteria for PD. 95 Written informed consent was obtained from PD patients and controls according to approved protocols evaluated by the Houston Methodist Institutional Review Board (IRB). Motor phenotypes of PD patients were evaluated using the Hoehn and Yahr (H&Y) scale which describes the motor manifestations of the disease according to stages (H&Y 1→H&Y 5). Additional cross analyses of variables such as age and gender revealed no significant confounding effects in the data representing PD vs controls in this study (data not shown). Immune cell isolations Immune cells were isolated from peripheral blood of PD patients and controls using a Lymphoprep (Stemcell) density gradient followed by positive or negative bead-based, magnetic column (Miltenyi Biotec) isolations. For peripheral monocytes, negative isolation of desired population was obtained using Human Pan Monocyte Isolation Kit (Miltenyi Biotec). Treg and Tresp populations were obtained from PBMC pool using the CD4 + CD25 + Regulatory T Cell Isolation Kit (Miltenyi Biotec) whereby Tresps were negatively isolated in the flow through while the Tregs were positively isolated and run through the column twice for purity. RNA purification and RT-PCR analysis RNA was isolated from blood-isolated immune cells, in vitro experiments, and ex vivo expansions using Trizol reagent followed by Direct-zol RNA MiniPrep Plus Kit (Zymo Research). RNA concentration/quality were assessed using Nanodrop spectrophotometer and Quantitative RT-PCR (qRT-PCR) experiments were performed using a One-Step RT-PCR kit with SYBR Green and a Bio-Rad iQ5 Multicolor Real-Time PCR Detection System. Primers for the study were acquired from BioRad and the relative expression of each mRNA was calculated using the ΔΔCt method with normalization to β-actin and relative to

control samples. Primer information can be found in Supplementary Table 2. Treg suppression of Tresp proliferation assays Patient Tresp and corresponding patient Tregs were isolated and cultured in 96-well, round-bottom plates at a density of 5 × 10 4 cells per well (in triplicate) at ratios of 1:1, 1:1/2, and 1:1/4 (Tresp:Tregs). A CD3/ CD28 stimualtion reagent, Human Treg Suppression Inspector (Miltenyi Biotec), was added to the co-culture for five days followed by the addition of tritiated thymidine (Amersham Life Sciences) for 18 h. Proliferation is measured via tritium incorporation. Treg suppression of iPSC-derived, pro-inflammatory myeloid cells magnetic columns. CD14 cells are then cultured for 7 days in 10% FBS 1640 media supplemented with GMCSF (50 ng/mL; Miltenyi Biotec) to generate resting myeloid cells (M0). We harvest M0 cells with enzyme-free/PBSbased cell dissociation buffer (Gibco) and plated at 5 × 10 4 cells per well in a 24-well plate. M0 cells are allowed to settle for an hour followed by a stimulation using lipopolysaccharide (LPS) (0.1 ng/mL; Sigma) and gamma interferon (IFN-γ) (0.2 ng/mL; eBioscience) to create activated, proinflammatory myeloid cells (M1). Tregs are co-cultured at 1:1 ratio with M1's overnight (~20 h) to assess suppression of myeloid-specific proinflammatory markers. Cultured Tregs and M1 cells are individually isolated for RNA transcript analysis and cultured media collected to assess cytokine protein levels via ELISA (Sigma). Treg ex vivo expansion protocols Tregs are isolated via bead-based negative selection as described previously. Tregs are suspended at a concentration of 1 × 10 5 cells per well in 100 uL tissue culture media supplemented with 100 nM rapamycin (Miltenyi Biotec), 500 IU/mL IL-2, and Dynabeads Human Treg Expander (Gibco) according to the manufacturer's protocol. Fresh media mix with rapamycin and IL-2 were added to the cells every 2-3 days. After 10-14 days of culture, the Tregs were harvested, washed, and utilized in their respective suppressive function assay. Statistical analysis Statistics were generated using Graphpad Prism software. Analysis of two groups was performed with Student's t test while analyzing more than two groups utilized one-way ANOVA with appropriate multiple comparisons testing. Data are expressed as mean ± SEM and p values reported according to the New England Journal of Medicine suggested output and guidelines. Reporting summary Further information on research design is available in the Nature Research Reporting Summary linked to this article. DATA AVAILABILITY The data collected during this study are available from the corresponding author upon reasonable request from qualified individuals. REFERENCES. of time and participation to contribute to clinical studies that have the opportunity to advance disease understanding and develop disease-modifying therapies. We would also like to thank the Stanley H. Appel Department of Neurology, Dr. Eugene Lai and his Neurodegenerative Disease Clinic, and the Houston Methodist Hospital for their contributions to the study. This study was made possible through philanthropic funding from the Parkinson's Cell Therapy Research Fund. FDG-PET in Creutzfeldt-Jakob disease: Analysis of clinical-PET correlation ABSTRACT Objective: To assess the relationship between clinical pattern and cerebral glucose metabolism on [18F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) in Creutzfeldt-Jakob disease (CJD). Methods: Predefined clinical signs (ataxia, visual, pyramidal, myoclonus, limb apraxia, limb dystonia, sensory, parkinsonism, and corticobasal syndrome [CBS]) and FDG-PET data were assessed in consecutive CJD patients. Two types of statistical parametric mapping (SPM) analyses, using stringent level of significance p < 0.001 and extent threshold of 100 voxels, were performed: one comparing CJD patients presenting specific sign against CJD patients without this specific sign (inter-CJD analysis), and one comparing CJD patients with specific sign against 18 healthy controls (CJD-control analysis). Results: Fifteen CJD patients (11 probable and two histologically proven sporadic and two genetic CJD) were analyzed. CJD-control analysis of the entire CJD group showed lateralized frontal and parietal hypometabolism. When analyzing clinical CJD subgroups, inter-CJD analyses showed hypometabolism in more restricted areas than on CJD-control analyses. For CJD patients presenting with ataxia, visual signs and CBS (and CBS-associated signs), additional hypometabolic areas probably related to the specific signs were identified: pons and middle cerebellar peduncles in patients with ataxia; occipital cortex in patients with visual signs; and prerolandic and lateral parietal cortex in patients with CBS. For pyramidal signs, sensory loss, and parkinsonism, no abnormalities in brain areas typically involved in these signs were observed. Conclusion: In addition to lateralized frontal and parietal hypometabolism previously reported in CJD and observed here, hypometabolism in brain areas related to some specific signs (i.e. ataxia, visual signs, and CBS) is also seen. INTRODUCTION Our group previously reported a series of Creutzfeldt-Jakob disease (CJD) patients studied by [18F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET), analyzing nine CJD patients by statistical parametric mapping (SPM), showing lateralized FDG-PET hypometabolism in the medial and lateral parts of the frontal and parietal cortex (confirming earlier PET data in CJD patients). 1,2 In that study, FDG-PET proved more sensitive than MRI for detecting cortical abnormalities. 1 However, due to the high sensitivity and specificity of electroencephalogram abnormalities, MRI changes (typically showing high signal in the basal ganglia and/or the cortex on diffusion-weighted imaging and/or fluid-attenuated inversion recovery sequences), and 14-3-3 protein detection in the cerebrospinal fluid, the additional diagnostic value of FDG-PET for CJD diagnosis is probably limited. In our earlier CJD FDG-PET study, however, one of the most striking observations was the asymmetry of FDG-PET hypometabolism observed in each of the patients. 1 Signs frequently encountered in CJD include dementia, cerebellar ataxia, visual signs, pyramidal signs, extrapyramidal signs (rigidity, bradykinesia, and limb dystonia), akinetic mutism, myoclonus, ocular movement disorders, limb apraxia, sensory loss, and alien limb. 3 Sometimes, one or more of these clinical symptoms are predominant and considered as clinical CJD subtypes (e.g. the Heidenhain variant when prominent visual signs are present; or the corticobasal syndrome [CBS] subtype in the presence of higher cortical dysfunction [alien limb, apraxia, or cortical sensory loss] and movement disorder [rigid/ akinetic syndrome, limb dystonia, and myoclonus]). 4,5 In these clinical CJD subtypes, case reports often show FDG-PET hypometabolism involving cortical areas related to the clinical signs. To the best of our knowledge, a systematical analysis of the relationship between clinical presentation and FDG-PET metabolism in CJD patients has never been reported. Our aim was to assess this relationship. METHODS Between December 2007 and February 2017, the diagnosis of CJD was established in 17 patients in our centre. Fifteen CJD patients were analyzed by FDG-PET, performed a median of 66 days after symptom onset. The remaining two patients (or their family) refused FDG-PET. All probable sporadic CJD patients had diagnosis based on the WHO criteria and the in 2009 updated clinical diagnostic criteria for CJD. 3 We predefined the following signs as present or absent in each patient based on standardized clinical examination: cerebellar ataxia, visual signs (impaired visual acuity, visual field loss, or visual hallucinations), pyramidal signs (muscle weakness, spasticity, or Babinski sign), myoclonus (spontaneous or reflex), limb apraxia, limb dystonia, sensory loss, parkinsonism (rigidity or hypokinesia), and corticobasal syndrome (alien limb, apraxia, or cortical sensory loss associated with rigid/akinetic syndrome, limb dystonia, or myoclonus). Patients' demographic and clinical characteristics, codon 129 polymorphisms, disease duration at time of FDG-PET, and lateralization of PET hypometabolism were analyzed. FDG-PET analyses were performed using the same methods and techniques as earlier described. 1 All brain FDG-PET scans were performed with a PET-CT GEMINI GXL (Philips Medical Systems). After fasting for at least 6 h, blood glucose level was check and less than 160 mg/dl. Patients were positioned comfortably in a quiet, dimly lit room before FDG administration and during the uptake phase of FDG (at least 20 minutes). They received intravenous injection of 185 to 250 MBq (5 to 6.7 mCi: according to the weight) of 18 F-FDG by a canula inserted 10 minutes before. Patients were instructed not to speak, read or be otherwise active. For imaging, patients were in supine position, and the head immobilized in a masthead. Imaging began by CT surview (view angle 90, 120 kV, 30 mAs), then transmission CT scan for attenuation correction was done (120 kV, Mas/slice 200, Pitch 0.563, Rotation 1.5, thickness 3 mm, filter UB, collimation 16 £ 1.5, FOV 600); static emission scan started 30 minutes after injection, in 3-D mode for 20 minutes, axial field of view 180 mm, 256 £ 256 matrix, voxel size 2 mm 3 , and reconstruction was done with a three dimensional row-action maximum likehood algorithm LOR-RAMLA resulted in 90 transaxial slices. Data were analyzed using statistical parametric mapping (SPM8, Wellcome Department of Cognitive Neurology, London, UK) implemented in Matlab R2012b (Mathworks, Natick, Massachusset, USA). Images have been globally normalized to 50 using proportional scaling to remove confounding effects to global cerebral glucose consumption changes, with a masking threshold of 0.8. The resulting statistical parametric maps, SPM[t], have been transformed into normal distribution (SPM[z]) unit. SPM t-maps have been set at p < 0.001, corrected for multiple comparisons with the False Discovery Rate option at voxel level. Only those clusters containing more than 100 contiguous voxels have been accepted as significant. For SPM analysis, we used 18 healthy controls age-matched against the CJD patient group. We performed SPM analyses (false discovery rate, FDR) for each of the different clinical signs assessing brain areas showing decreased FDG-PET uptake using a stringent level of significance of p < 0.001 and an extent threshold of 100 voxels. On SPM analysis, to better assess the brain areas involved in patients with specific clinical signs, we first compared the entire CJD group with controls. After this general analysis, we looked for hypometabolic brain areas for each of the clinical CJD subgroups presenting with a specific clinical sign. Two types of SPM analyses were performed: one comparing CJD patients presenting the specific sign against CJD patients without this specific clinical sign (inter-CJD analysis), and one comparing the CJD patients with the specific sign with the 18 healthy controls (CJD-control analysis). Twosample t test design model were used for these analysis For visualization, the significant voxels were projected onto the 3D rendered brain or a standard MRI template allowing anatomic identification. Anatomical loci were also determined by converting cluster maxima to Talairach space (Talairach & Tournox, 1988; http:// imaging.mrc-cbu.cam.ac.uk/imaging/MniTalair ach). This output was cross-checked using the atlases of Talairach and Tournox (1988). Patient Characteristics Fifteen patients (10 women and five men; median age 69, range 52-86; including 11 patients with probable sporadic CJD, two with histologically proven sporadic CDJ, and two with genetic CJD [one with a E200K and one with a V210I missense PRNP mutation]) were studied. Codon 129 polymorphism was Met/Met in nine patients, Val/Val in three patients, and Met/Val in 1 patient, and was not performed in two patients. On MRI, basal ganglia and/or cortical MRI hyperintensities on DWI/FLAIR were observed in all patients. Periodic sharp wave complexes on electroencephalopgram were present in 11 out of 15 CJD patients, and CSF 14-3-3 protein present in all patients. Median time between symptom onset and FDG-PET was 66 days (range 18-247). Patient data is shown in Table 1. None of our patients experienced alien limb syndrome. Twelve CJD patients had left predominant and three right predominant brain hypometabolism. Eighteen healthy individuals, median age 69 (range 55-86), were included as controls. FDG-PET data for the entire CJD group and the different clinical CJD subgroups are shown in Table 2. Decreased FDG-PET metabolism was observed in the left lateral frontal cortex and the left mesial parietal cortex, and to a lesser degree the right mesial parietal cortex and the left lateral posterior temporal cortex in CJD patients in comparison to controls (Fig. 1). Cerebellar Ataxia On inter-CJD analysis, in patients with cerebellar ataxia (n D 9), FDG-PET hypometabolism was observed in the pons, the bilateral (left-predominant) middle cerebellar peduncles, the right frontal subcortical lobe, and the left mesial temporal cortex (Fig. 2). On CJD-control analysis, hypometabolism was seen in the left lateral frontal cortex, the bilateral (left-predominant) mesial parietal cortex, and the left lateral posterior temporal cortex in the CJD group. Visual Signs On inter-CJD analysis, decreased metabolism was seen in the bilateral (right-predominant) occipital cortex and the right frontal subcortical lobe in CJD patients with visual signs (n D 6) (Fig. 3). On CJD-control analysis, hypometabolism was observed in the left occipital cortex, the left lateral frontal cortex, the left mesial parietal cortex, the right lateral posterior temporal cortex, and the left anterior deep grey

matter in comparison to the controls. Pyramidal Signs On inter-CJD analysis, hypometabolism was observed in the left subcortical occipital lobe in patients with pyramidal signs (n D 5). On CJD-control analysis, decreased metabolism was observed in the left lateral frontal cortex and the left mesial parietal cortex in comparison to the controls. On CJD-control analysis, hypometabolism was seen in the left lateral parietal cortex, the bilateral (left-predominant) mesial parietal cortex, the left lateral frontal cortex, and the left lateral posterior temporal cortex in the CJD group. Limb Apraxia On inter-CJD analysis, hypometabolism was seen in the bilateral mesial parietal cortex, the bilateral mesial and left lateral frontal cortex, and the left mesial occipital cortex in CJD patients with limb apraxia (n D 8). On CJD-control analysis, hypometabolism was seen in the left lateral parietal cortex, the left lateral frontal cortex, and the left occipital cortex in the CJD group. Limb Dystonia On inter-CJD analysis, in the CJD patients with limb dystonia (n D 7), the left lateral parietal cortex and the left lateral prerolandic frontal cortex showed hypometabolism (Fig. 5). On CJD-control analysis, hypometabolism was seen in the left lateral and mesial parietal cortex, the left lateral frontal cortex, and the left lateral temporal-occipital cortex in the CJD group. Sensory loss In the patients with sensory loss (n D 2), no specific areas of hypometabolism were observed on inter-CJD analysis or CJD-control analysis. Parkinsonism On inter-CJD analysis, no areas of specific hypometabolism were observed in the patients with parkinsonism (n D 4). On CJD-control analysis, hypometabolism was seen in the left lateral frontal cortex, the bilateral (left-predominant) orbitofrontal cortex, the bilateral (left predominant) mesial parietal cortex, and the left lateral posterior temporal cortex in the CJD group. Corticobasal syndrome On inter-CJD analysis, hypometabolism was seen in the left lateral prerolandic frontal cortex, the left -lateral more than mesialparietal cortex, and the left lateral posterior temporal cortex in patients with CBS (n D 7) (Fig. 6). On CJD-control analysis, hypometabolism was observed in the left lateral frontal cortex, the left lateral and mesial parietal cortex, and the left lateral posterior temporal cortex. Complementary Analyses In all clinical CJD subgroup analyses, inter-CJD analyses showed hypometabolism in more restricted areas than by CJD-control analyses. Inter-CJD analyses probably better reflect sign specific areas, since areas with hypometabolism generally-associated with CJD pathology were less visible as they were present in both compared clinical subgroups. For each clinical subgroup, we further looked for large hypometabolic areas on inter-CJD analyses other than those visible on analysis of the entire CJD group vs controls (i.e. lateral frontal, mesial parietal, and the lateral posterior temporal cortex), thus potentially related to the clinical sign. For CJD patients presenting with cerebellar ataxia, visual signs, myoclonus, apraxia, dystonia, and CBS, hypometabolic areas probably related to the specific sign were identified: hypometabolism in the pons and the middle cerebellar peduncles in CJD patients with cerebellar ataxia; hypometabolic occipital cortex in patients with visual signs; and prerolandic and parietal cortex hypometabolism in patients with CBS (and CBS-associated signs). For pyramidal signs, sensory loss, and parkinsonism, no brain areas typically involved in these clinical signs were observed on inter-CJD or CJD-controls analyses. Patients with genetic CJD (n D 2) did not show any specific FDG-PET metabolism modifications compared with sporadic CJD patients. DISCUSSION Although parkinsonism and pyramidal signs are often observed in CJD ("extrapyramidal or pyramidal signs" are one of the four main clinical signs required for probable CJD diagnosis according to the MRI-CJD Consortium criteria for sporadic CJD), basal ganglia hypometabolism was not observed in our study and prerolandic cortex involvement only observed in the dystonia and CBS subgroup but not in the pyramidal subgroup. In the subgroup with sensory signs, no specific hypometabolic area was identified. In contrast with the other clinical subgroups, subgroups with parkinsonism, pyramidal signs and sensory signs (i.e. the subgroup without hypometabolic areas corresponding to their clinical signs) has very small patient numbers (parkinsonism, n D 4; pyramidal signs, n D 5; sensory signs, n D 2), possibly explaining the lack of identifiable, statistically significant, corresponding hypometabolic brain areas. For the same reason, possibly, statistical differences lacked between genetic and sporadic CJD patients. For the subgroup with parkinsonism and pyramidal signs, another hypothesis may be that these signs might not be necessarily related to the specific brain structures classically explaining these signs (striatum and prerolandic cortex, respectively). For instance, parkinsonism and pyramidal signs might be related to widespread brain involvement, or possibly due to frontal lobe involvement (often associated with bradykinesia and hypertonia), or -in the case of parkinsonismsubstantia nigra hypometabolism (difficult to assess due to the small volume of this structure). 6,7 The lateralized brain FDG-PET metabolism in CJD patients probably led to an underestimation of the involved brain areas assessed by SPM in our study since patients with the same clinical sign often had different lateralization of brain hypometabolism. Even with this limitation together with the small number of patients, the fact that we still identified hypometabolic brain areas corresponding to most of the clinical signs probably reflected genuine clinical-PET correlation. The majority of our CJD patients had left lateralized brain hypometabolism, probably also explaining the left predominant brain areas involved in the clinical subgroup analyses. In corticobasal degeneration, asymmetric FDG-PET hypometabolism is typically seen in the posterior frontal, inferior parietal, and lateral temporal cortex, and in the striatum and the thalamus. 8,9 In CJD patients presenting with CBS, based on our study, CBS seemed to be related to posterior frontal and parietal (and to a lesser degree lateral temporal) cortex involvement rather than to striatal or thalamic hypometabolism not observed in our patients. 9 In our analyses of both the entire CJD group and the clinical CDJ subgroups, deep grey matter did not show decreased metabolism. This is in contrast with the MRI abnormalities which typically also involve the basal ganglia, and the widespread (including basal ganglia) histological abnormalities characterized by diffuse and symmetrical involvement, suggesting (at least partially) different pathophysiological mechanisms leading to MRI, PET, and histological abnormalities. 10,11 FDG-PET data in our patients has to be interpreted with caution since volumetric MRI analyses and partial volume corrected-PET assessment were not performed in our study. In general, MRI abnormalities (together with electroencephalogram and CSF changes) are typically seen in symptomatic CJD patients (and even can precede clinical symptoms), making FDG-PET non-essential in the diagnosis of CJD. However, in case of lack of complete (i.e. MRI, electroencephalogram, and/or CSF) work-up for CJD (e.g. when MRI is contraindicated [e.g. pace-maker] or difficult to interpret [e.g. due to motion artifact related to agitation; also making also electroencephalogram difficult to interpret and sometimes lumbar puncture difficult to perform]), FDG-PET (and the knowledge of expected FDG-PET abnormalities in CJD) might be useful in the diagnosis of CJD and its clinical subgroups. In particular, in addition to lateral frontal and mesial parietal hypometabolism generally found in CJD patients, hypometabolism can be observed in the pons and the middle cerebellar pedoncules in CJD patients with ataxia, in the occipital cortex in CJD patients with visual signs, or in the prerolandic and lateral parietal cortex in CJD patients with CBS (and CBSassociated signs). Larger patient numbers are needed to further analyze the relationship between clinical presentation and FDG-PET metabolism. DISCLOSURE OF POTENTIAL CONFLICTS OF INTEREST We have no conflict of interest to declare. Molecular Interfaces of the Galactose-binding Protein Tectonin Domains in Host-Pathogen Interaction* β-Propeller proteins function in catalysis, protein-protein interaction, cell cycle regulation, and innate immunity. The galactose-binding protein (GBP) from the plasma of the horseshoe crab, Carcinoscorpius rotundicauda, is a β-propeller protein that functions in antimicrobial defense. Studies have shown that upon binding to Gram-negative bacterial lipopolysaccharide (LPS), GBP interacts with C-reactive protein (CRP) to form a pathogen-recognition complex, which helps to eliminate invading microbes. However, the molecular basis of interactions between GBP and LPS and how it interplays with CRP remain largely unknown. By homology modeling, we showed that GBP contains six β-propeller/Tectonin domains. Ligand docking indicated that Tectonin domains 6 to 1 likely contain the LPS binding sites. Protein-protein interaction studies demonstrated that Tectonin domain 4 interacts most strongly with CRP. Hydrogen-deuterium exchange mass spectrometry mapped distinct sites of GBP that interact with LPS and with CRP, consistent with in silico predictions. Furthermore, infection condition (lowered Ca2+ level) increases GBP-CRP affinity by 1000-fold. Resupplementing the system with a physiological level of Ca2+ did not reverse the protein-protein affinity to the basal state, suggesting that the infection-induced complex had undergone irreversible conformational change. We propose that GBP serves as a bridging molecule, participating in molecular interactions, GBP-LPS and GBP-CRP, to form a stable pathogen-recognition complex. The interaction interfaces in these two partners suggest that Tectonin domains can differentiate self/nonself, crucial to frontline defense against infection. In addition, GBP shares architectural and functional homologies to a human protein, hTectonin, suggesting its evolutionarily conservation for ∼500 million years, from horseshoe crab to human. ␤-Propeller proteins function in catalysis, protein-protein interaction, cell cycle regulation, and innate immunity. The galactose-binding protein (GBP) from the plasma of the horseshoe crab, Carcinoscorpius rotundicauda, is a ␤-propeller protein that functions in antimicrobial defense. Studies have shown that upon binding to Gram-negative bacterial lipopolysaccharide (LPS), GBP interacts with C-reactive protein (CRP) to form a pathogen-recognition complex, which helps to eliminate invading microbes. However, the molecular basis of interactions between GBP and LPS and how it interplays with CRP remain largely unknown. By homology modeling, we showed that GBP contains six ␤-propeller/Tectonin domains. Ligand docking indicated that Tectonin domains 6 to 1 likely contain the LPS binding sites. Protein-protein interaction studies demonstrated that Tectonin domain 4 interacts most strongly with CRP. Hydrogen-deuterium exchange mass spectrometry mapped distinct sites of GBP that interact with LPS and with CRP, consistent with in silico predictions. Furthermore, infection condition (lowered Ca 2؉ level) increases GBP-CRP affinity by 1000-fold. Resupplementing the system with a physiological level of Ca 2؉ did not reverse the protein-protein affinity to the basal state, suggesting that the infection-induced complex had undergone irreversible conformational change. We propose that GBP serves as a bridging molecule, participating in molecular interactions, GBP-LPS and GBP-CRP, to form a stable pathogenrecognition complex. The interaction interfaces in these two partners suggest that Tectonin domains can differentiate self/ nonself, crucial to frontline defense against infection. In addition, GBP shares architectural and functional homologies to a human protein, hTectonin, suggesting its evolutionarily conservation for ϳ500 million years, from horseshoe crab to human. The ␤-propeller protein family members have diverse functions: enzyme catalysis, protein-protein interactions, and cell cycle regulation (1,2). A subset of this family of proteins has pathogen-binding properties (1,(3)(4)(5)(6)(7)(8), indicating a role in defense against microbial infection. Pathogen binding occurs through the recognition of evolutionarily conserved structures on pathogens, referred to as pathogen-associated molecular patterns (PAMPs), 5 e.g. lipopolysaccharide (LPS) of Gram-negative bacteria and lipoteichoic acid (LTA) of Gram-positive bacteria. Within the subset of pathogen binding ␤-propeller protein family, several members are classified as having Tectonin domains (4,5,(7)(8)(9). The Tectonin domains were first found in the Tectonins I and II proteins of the slime mold, Physarum polycephalum. The Tectonins I and II are expressed on the cell surface and are involved in the formation of a signaling complex during phagocytosis (5). Because Physarum feeds on bacteria, it has been suggested that the Tectonin domains recognize LPS in the substratum of Gram-negative bacteria (10). However, whether the Tectonin domains can directly bind to PAMPs such as LPS has not been demonstrated experimentally. The galactose-binding protein (GBP) of the horseshoe crab, Carcinoscorpius rotundicauda, is a plasma lectin that contains Tectonin domains. It was proposed to bind PAMPs while interacting with other pattern-recognition receptors (PRRs) to form a pathogen-recognition interactome (11,12). The C-reactive protein (CRP), an acute phase protein whose level increases rapidly and dramatically upon acute phase infection-inflammation, interacts with GBP (13). Previously, we found that interaction between GBP and CRP is induced by infection (12), likely through infection-activated serine proteases, Factor C and C2/Bf, which catalyze the assembly of the PRR-interactome (14). Because of its relative abundance in the plasma and its propensity to form an PRR-interactome, GBP is a useful model for studying the role of Tectonin domain-containing proteins in antimicrobial defense. We hypothesized that GBP plays a critical bridging role in the PRR-interactome formation. How-ever, the molecular basis of the interactions between GBP and

PAMP, and GBP and CRP is still unknown. Furthermore, it is not yet fully understood how microbial infection induces interaction between GBP and CRP (15). Here, we examined the molecular interfaces between GBP and LPS, and GBP and CRP under normal and infection conditions. We demonstrated that of the six ␤-propellers or Tectonin domains of GBP, domains 6 to 1, interact with LPS, and domain 4 interacts strongly with CRP. GBP isolated from infected animals binds both LPS and CRP with dramatically increased affinities. In addition, we showed that hTectonin (15), a human tectonin domain-containing protein, shares structural and functional homology to GBP. This warrants further analysis of the structure-function of ␤-propeller Tectonin domains in infection and immune response. Altogether, our results define the molecular basis for GBP-LPS and GBP-CRP interactions, support a fundamental role of these interactions in boosting immune defense, and demonstrate the conservation and importance of Tectonin domain-containing proteins in innate immune response throughout evolution. MATERIALS AND METHODS Organisms-Horseshoe crabs were collected from the Kranji estuary, Singapore. The animals were infected intracardially with 1.2 ϫ 10 6 colony-forming units of Pseudomonas aeruginosa/100 g of body weight. Before and 6 h after infection, the animals were partially bled, and cell-free plasma was obtained by centrifugation at 150 ϫ g for 15 min at 4°C (12). The animals were handled according to the guidelines of the National Advisory Committee for Laboratory Animal Research, Singapore. Purification of GBP-The cell-free plasma was incubated overnight at 4°C with Sepharose CL-6B (Pharmacia) pre-equilibrated with 10 mM Tris, 150 mM NaCl (TBS), pH 8.8, and washed with Ͼ10 column volumes until a steady base line was obtained. GBP was eluted with TBS, pH 7.4, containing 0.4 M GlcNAc (Sigma). GlcNAc was removed from the eluted protein by ultrafiltration through 3-kDa molecular weight cutoff micropore filters (Amicon). Purified GBP from the plasma of naïve and infected animals is referred as GBP n and GBP i , respectively. Yeast Two-hybrid Assay-Cotransformations of the different bait and prey plasmids into Saccharomyces cerevisiae were performed to study protein-protein interactions. For details, see supplemental Materials and Methods. ELISA to Test for Bacterial Ligand Binding-The GBP ligands were immobilized on ELISA plates. Their interactions with GBP were quantified (supplemental Materials and Methods). Surface Plasmon Resonance Analysis (SPR)-Real-time biointeractions between GB and ligands (GlcNAc, LPS, ReLPS, and lipid A from Salmonella minnesota) and GBP and CRP were performed using a Biacore 2000. The purified GBP solution contained hetero-oligomers, albeit with reasonable representation of monomeric GBP. Although earlier studies (4) with hetero-oligomeric solutions of proteins from another species of horseshoe crab have utilized a Langmuir 1:1 binding equation as a standard for protein-ligand binding affinity calculations, here, we have analyzed the binding affinities for both native GBP and dithiothreitol-treated GBP (which gave more monomeric forms) and tested the SPR data by both the Langmuir 1:1 binding as well as the two-state conformational change binding and compared the binding affinity values for both fits. Details on SPR are in the supplemental Materials and Methods. Amide Hydrogen Exchange Mass Spectrometry and Data Analysis (HDMS)-To determine the interaction interface for protein-protein and protein-ligand interaction, HDMS was performed. For details, see supplemental Materials and Methods. Protein Homology Modeling and Docking-GBP was homology-modeled using the crystal data of tachylectin-1 (TL-1), 6 (16), which shares 66.7% sequence identity with GBP (17). The three-dimensional model of the horseshoe crab CRP was prepared by homology modeling from the crystal structure of human CRP (18) and human serum amyloid protein, which share 30 and 31% sequence similarity, respectively (supplemental Fig. 1). Details on molecular modeling and docking are in the supplemental Materials and Methods. Protein-Protein Docking-The HADDOCK 2.0 program (19,20) was used to generate the three-dimensional models of GBP-CRP heterodimer by protein-protein docking. Peptide sequences from the HDMS analysis involved in protein dimerization with Ͼ30% solvent-accessible surface area/residue (NACCESS program) (21) were defined as active residues in the guided docking procedure, whereas amino acids within 3 Å interatomic distance from them were considered passive. Generation, refinement, and scoring of the random GBP-CRP dimer models were performed similarly. For details, see supplemental Materials and Methods. The three-dimensional model of the GBP-CRP binding described here enables structural interpretation of the observed HDMS data on the peptide sequences involved in the protein-protein interactions. The ligand-GBP models were used for structural rationalization of the SPR data on the binding affinities of LPS components to the GBP and comparison with other sugar-binding proteins containing Tectonin domains. The observed data were compared with structural information and cross-checked by comparison with binding affinity data predicted from force field-based molecular mechanics calculations. The three-dimensional models are intended to represent FIGURE 2. GBP binds sugar moieties of LPS with high affinity. A, chemical structure of LPS. GlcNAc is located on the outer core of LPS. Hep, heptose; P, phosphate; PE, phosphoethanolamine; KDO, 3-deoxy-␣-D-manno-octulosonic acid; Ara, arabinose. The outermost sugar residue of each LPS truncate is colored. B-E, ELISA to measure GBP-ligand binding. The GBP ligands (LPS, ReLPS, lipid A, LTA, or GlcNAc-bovine serum albumin (BSA)) were incubated overnight in binding buffer (see supplemental Materials and Methods) on 96-well Polysorp TM microplates. The unbound sites were blocked with 1% bovine serum albumin, and serially diluted GBP (with or without preincubation with GlcNAc) was added to each well. Anti-GBP antibody was added followed by horseradish peroxidase-linked secondary antibody. The peroxidase enzyme activity was determined at 405 nm. F, SPR-derived binding constants of GBP to LPS, LPS-truncates, or GlcNAc. The apparent K D values were calculated by using BIAevaluation software version 4.1. Suffix n and i refer to naïve (uninfected) and infected experimental conditions, respectively. G, SPR analysis of GBP binding with LPS, with and without dithiothreitol (DTT) treatment. working models that are sufficient for interpretation and rationalization of the experimental data. RESULTS Native GBP Has a Propensity to Oligomerize-GBP was purified from the plasma, through binding to the repeating units of ␣-1,6-linked D-galactose and 3,6-anhydro-L-galactose on the Sepharose CL-6B (supplemental Fig. 2). On reducing SDS-PAGE, GBP showed three bands: 52 kDa (nonreducible dimer), 26 kDa (monomer), and 18 kDa (N-terminal domain) (Fig. 1A, lanes R), which were confirmed by mass spectrometry (Fig. 1B). Under nonreducing conditions, native GBP in the crude plasma was predominantly in larger oligomeric forms, although purified GBP showed substantial representation of dimeric and monomeric forms (Fig. 1A, lower panel, lanes NR). FIGURE 3. Three-dimensional model of GBP. A, sequence alignment of GBP to TL-1 is shown. B, homology model of GBP predicted a 6-bladed ␤-propeller protein, containing 8 cysteine residues (yellow). C, protein sequence of GBP shows six Tectonin domain repeats with an 8-residue tail. The modeled ␤-sheets are numbered accordingly. ␤-Strands (underlined) are predicted by PSIPRED. D, Ramachandran plot shows that the outlier residues remain close to the boundaries of the permittedvalues (light blue contours), indicating a reliably modeled structure. E, GBP is predominantly hydrophilic (blue) with scattered hydrophobic patches (red). The molecule folds into a toroidal structure around a funnel-shaped tunnel with a larger cavity on the top and a smaller crevice at the bottom. MARCH 26, 2010 • VOLUME 285 • NUMBER 13 GBP Binds to the Sugar Moieties of Gram-negative Bacterial LPS-Because GBP binds to the Gal residues of Sepharose and was eluted by GlcNAc, we envisaged that GBP binds to the sugar moieties of bacterial LPS ( Fig. 2A). ELISA showed that purified GBP bound GlcNAc specifically (Fig. 2B). GBP binds to immobilized LPS, but this binding was inhibited when GBP was incubated with GlcNAc prior to being added to LPS (Fig. 2C). The same was also observed with ReLPS and lipid A (Fig. 2, D and E). Likewise, the binding of GBP to Gram-positive bacterial LTA was abrogated by GlcNAc (supplemental Fig. 3). Thus, we can assume that GBP binds to LPS or LTA through their sugar moieties. To confirm this observation, we evaluated the avidity of GBP for LPS, lipid A, and GlcNAc by SPR measurements using purified GBP. Because the purified GBP more likely contains monomeric as well as oligomeric forms of the protein, we used the term "apparent K D " to refer to the potential avidity of GBP to its ligands. We found that GBP-GlcNAc, GBP-lipid A, and GBP-LPS showed similar apparent K D values of 1.52-2.52 ϫ 10 Ϫ7 M (Fig. 2F), corroborating the notion that GBP binds LPS via its GlcNAc moiety because all of these PAMPs contain GlcNAc. A SPR binding experiment for GBP-LPS under reducing conditions (1 mM dithiothreitol) also showed a similar apparent K D of 2.66 ϫ 10 Ϫ7 M, albeit with about 1 order of magnitude higher values of rate constants of the analyteligand association and dissociation (Fig. 2G). This indicates the presence of increased numbers of smaller and faster diffusing monomeric forms of GBP in the mass transport-limited processes on the chip surface and suggests that monomeric GBP recognizes and binds to bacterial LPS rather than its oligomeric forms. Molecular Interfaces of Tectonin Domains in GBP GBP Is a Six-bladed ␤-Propeller Protein-By homology modeling to TL-1, we predicted GBP to be a six-bladed ␤-propeller protein containing six Tectonin domains (Fig. 3, A and B). Each of the Tectonin domains is made up of four ␤-sheets (Fig. 3C, arrows), which is in agreement with the secondary structure predictions and the Tectonin domain classification scheme. The Ramachandran plot of the GBP structure shows only minimal number of and outliers ( Fig. 3D and Table 1). The surface of GBP is predominantly hydrophilic, with several scattered hydrophobic patches (Fig. 3E). The GBP forms a hexagonal torus with a larger "cavity" on the top of the central tunnel and a smaller "crevice" at the bottom. Specific Tectonin Domains of GBP Bind CRP Preferentially-Based on the homology-modeled GBP structure, we subcloned the six Tectonin domains individually, in duos (domains 1-2, 2-3, 3-4, 4 -5, 5-6), and in trios (domains 1-2-3, 4 -5-6). Yeast two-hybrid analysis showed that each domain appears to interact differentially with GBP or CRP (Fig. 4). The GBP Tectonin domains 3-4 and 4 -5 may interact more efficiently with CRP as suggested by the comparatively faster growth of the co-transformed yeast cells on the quadruple dropout plate. Saccharides and Lipid A Dock to Similar Sites in GBP-To define the binding sites on GBP that interact Single, double, and triple GBP Tectonin domain subclones were tested for their interaction with CRP and with full-length GBP. The pGBKT7 vector containing GBP Tectonins domains/full-length GBP and pGADT7 vector containing CRP/full-length GBP were co-transformed and spotted on SD-Leu-Trp plates (double-dropout control) and SD-His-Ade-Leu-Trp (quadruple-dropout). The strength of interaction is indicated as ϩ/Ϫ. with LPS and saccharides, we utilized the three-dimensional model structure of GBP for docking studies. Proteins containing ␤-propeller repeats such as TL-2 are known to undergo protein-sugar interactions via the backbone atoms of the conserved binding site residues, which are flanked by adjacent ␤-sheet blades of the Tectonin domains (3,24,25). Because GBP has high affinity for GlcNAc and other sugar moieties of the LPS (see Fig. 2), it is reasonable to expect that the sugar binding sites are also localized between the adjacent ␤-sheet blades. Computational docking predicted that from among a set of monosaccharides and monosaccharide N-acetylamines (Gal, GalNAc, Gln, GlcNAc, KDO, heptose), Gal binds GBP with the highest affinity ( Table 2). The highest affinity binding site for GlcNAc (Fig. 5A) is located between the Tectonin domains 1 and 6 (Fig. 5B). Additional possible binding sites were predicted in clefts between other adjacent ␤-propellers (Fig. 5B) resembling those in TL-2 (3), as well as in the central cavity similar to the predicted binding site in TL-1 (26). 2-N-Acetyl-3-O-acetyl-␤-D-glucosamine (GlcNAcOAc), the principal component of the disaccharide head group of lipid A, was predicted to show an enhanced affinity (E int ) toward GBP ( Fig. 5B and Table 2). Phosphate groups at position 1 or 4 of the GlcNAcOAc did not significantly affect the binding affinity with GBP. However, significant affinity toward GBP was predicted for the polar disaccharide head group (1,4Ј-bisphospho-␤-(1,6)-2,2Ј-N-acetyl-3,3Ј-O-acetyl-D-glucosamine disaccharide) of the lipid A (Fig. 5A), which was higher than the sum of the E int of its components (GlcNAcOAc-1-Phos, GlcNAcOAc-4-Phos). The core lipid A (head group together with its fatty acid chains) showed binding affinity similar to that of the head group itself. Molecular docking predicted that the lipid A head group binding site coincides with the

GlcNAc binding site (Fig. 5C, zoomed view; GlcNAc is overlapped by the head group of the larger lipid A molecule). GBP Interacts with LPS and CRP via Distinct Interaction Surfaces-Because each of the Tectonin domains folds into structurally similar ␤-propellers, we asked how these domains differentiate self from nonself molecules. We used computational docking to predict, and HDMS (27,28) to validate and map, the lipid A and CRP binding sites on the Tectonin domains (Fig. 5, supplemental Fig. 4, and supplemental Tables 1 and 2). HDMS of the GBP n -lipid A complex showed GBP peptide 205-222 with decreased deuterium uptake, suggesting a lipid A binding site within domains 6 to 1 (Fig. 5D, yellow sur-face), in agreement with docking predictions (Fig. 5C). Interestingly, GBP i showed an additional lipid A-binding peptide (24, 25, 29 -36), supporting our postulate of an infection-related conformational change. Furthermore, this peptide contains an LPS-binding motif, HINGK, resembling the pattern of lipid A-binding residues, BHB(P)HB (B, basic; H, hydrophobic; P, polar) (25). Following from HDMS-identified GBP-CRP interaction surfaces, a guided docking run showed a nonsymmetric heterodimer model with a higher score (higher stability) than that generated by random docking (supplemental Fig. 5). This confirms the preference of specific Tectonin domains participating in the GBP-CRP interaction. Taken together, the interaction domains indicated by yeast two-hybrid assay and the HDMS-identified interaction interfaces between CRP and GBP are in general agreement with the in silico docking. This lends credence to the modeled structures of these two proteins. Nevertheless, further experimental evidence from x-ray crystallographic structures of the CRP and GBP, individually as well as co-crystals, would be needed to support the proposed model structures. Infection Conditions Increase the Affinity of GBP-LPS and GBP-CRP-GBP interacts with CRP only during infection, suggesting that certain infection conditions prime them for interaction (12). We found that infection resulted in increased affinity of GBP i for ReLPS (ReLPS i , apparent K D of 8.60 ϫ 10 Ϫ9 M) and lipid A (lipid A i , apparent K D of 5.11 ϫ 10 Ϫ8 M) (Fig. 2F). Next, we characterized the affinities between GBP n and CRP n , and GBP i and CRP i . The purified CRP n or CRP i was injected separately over the GBP n or GBP i that were preimmobilized on the lipid A surfaces of the Biacore chip. Fig. 6, A and B, show that GBP n -CRP n interacted with an apparent K D of 2.10 ϫ 10 Ϫ7 M, whereas GBP i -CRP i interacted with an apparent K D of 1.66 ϫ 10 Ϫ10 M, indicating that infection caused a 1000-fold increase in affinity between GBP and CRP. Such a dramatic increase in affinity probably resulted from protein conformational changes that take place during a microbial infection. in the presence of EGTA, which depletes Ca 2ϩ , thus mimicking a possible infection condition. The resulting apparent K D was 3.1 ϫ 10 Ϫ10 M, a 1000-fold increase in affinity (Fig. 6C), similar to that between GBP i and CRP i . However, supplementing the infected proteins with a physiological level of 2.5 mM Ca 2ϩ , or even higher, at 10 mM Ca 2ϩ did not revert the affinity between GBP i and CRP i to basal level (Fig. 6, D and E). Because Ca 2ϩ did not affect the GBP-LPS interaction (supplemental Fig. 6), these results indicate that infection causes irreversible conformational changes to the PRRs (GBP-CRP interaction), which likely recruit other proteins (14) to form the pathogen-recognition interactome ( Fig. 6F and supplemental Fig. 7). Antiendotoxic Potentials of GBP and CRP-Because GBP and CRP bind LPS, we tested their antiendotoxic potentials. First, we confirmed that the purified GBP and CRP were pyrogenfree. Then, we showed that when reacted with increasing doses of LPS (0.5-2 enzyme units), the proteins bound and probably disrupted the LPS micelles to increase the overall endotoxicity (supplemental Fig. 8). Human Tectonin, a Domain Architectural Homolog of GBP-Although protein sequence BLAST against the human genome did not reveal any homologs of GBP, SMART analysis (9,40) yielded three hypothetical proteins, Q7Z6L1, Q15040, and O95714, which contain Tectonin domains (15). The QZ7L1 was found to interact with human ficolin (15), the homolog of horseshoe crab carcinolectin 5. We have shown earlier that during infection, GBP interacts with carcinolectin 5 (12). Yeast 2-hybrid screening with hTectonin as bait against the human leukocyte cDNA library showed potential interaction partners such as neutrophil cytosol factor 1, Src-like adaptor 2, and ubiquitin-specific-processing protease (supplemental Fig. 9 and supplemental Table 3), all of which are immunoregulatory proteins. DISCUSSION By using both experimental and in silico approaches, we have shown that GBP, a representative Tectonin protein, with 6 ␤-propeller/Tectonin repeats, can distinguish host from bacteria, thus conferring self (GBP-CRP)/nonself (GBP-LPS) molecular interactions. Consistent with reports that individual ␤-propeller domains can self-assemble into larger multipropeller structures, the purified GBP molecules seemed to present as a mixture of monomers, dimers, and larger polymers (Fig. 1). Its propensity to homo-oligomerize may provide a supramolecular structure of Tectonin domains that contributes a stable bridge for the host-pathogen network. Real-time biointeraction analysis showed that GBP binds strongly to LPS, ReLPS, and LA, most likely through the GlcNAc sugar moiety. Calculations of the SPR data using either the Langmuir 1:1 binding and the two-state conformation change binding of both the native GBP solution, and the dithiothreitol-treated GBP (containing more GBP monomers) showed closely similar binding affinities of 3.32 ϫ 10 Ϫ7 M and 3.78 ϫ 10 Ϫ7 M, respectively. The GBP-LPS interaction seems to show a slower association (k a ) and dissociation (k d ) rate compared with GBP-GlcNAc, suggesting that GBP interacts with multiple sugar moieties of LPS. Interestingly, GBP binds ReLPS with a 10-fold greater affinity compared with the full-length LPS, suggesting that other sugar moieties, e.g. glucose and 2-keto-3-deoxyoctonate in LPS ( Fig. 2A), are also available for GBP to bind to. The three-dimensional model of GBP (Fig. 3B) served as a basis for us to explore the interactions between GBP and its interacting protein partners or bacterial ligands via computational docking and simulations and provides a platform to map experimental results visually to gain a structural perspective on the molecular interactions taking place. Molecular docking of GlcNAc to the GBP model predicted that GlcNAc has the highest binding affinity for GBP, occurring between Tectonin domains 6 and 1. The lipid A structure binds GBP through its glucosamine residues instead of the fatty acid chains. Therefore, GBP recognizes and preferentially binds the glucosamine disaccharide head group of the lipid A, consistent with the observation that lipid A and GlcNAc share similar binding sites in GBP. Yeast two-hybrid analyses of the GBP subclones suggested that three contiguous Tectonin domains are sufficient to interact as strongly as the full-length GBP with itself and with CRP. Furthermore, at least two consecutive Tectonin domains are needed for consistent interactions between GBP and CRP. HDMS showed the GBP-lipid A and GBP-CRP interfaces to be consistent with docking predictions. HDMS also confirmed that lipid A preferentially binds to the cleft between domains 6 and 1, which interfaces the ␤-propeller folds, whereas CRP binds at domain 4. This is consistent with our earlier observations through SPR analyses that the GBP peptides synthesized from domains 6 to 1 bind to LPS (15). We observed that infection caused a 10-fold increase in binding affinity between GBP i and LPS, with a slower release (k d rate) of LPS from GBP i , suggesting that after initial recognition and binding to the sugar moieties, the adjacent chemical groups of the LPS molecule enhances the anchorage of GBP onto the bacterium. The effect of infection is clearly demonstrated with a 1000-fold increase in affinity between GBP i and CRP i . Furthermore, the chelation of Ca 2ϩ seemed to mimic the state of infection by producing binding affinity similar to that in an infected condition. Fluctuations in cation levels during infection were reported (36 -39) to affect protein-protein interactions and consequently, regulate the immune response. However, Ng et al. (12) showed that plasma factors other than Ca 2ϩ may also enhance the interaction of GBP and CRP. This led us to postulate that although Ca 2ϩ depletion seems to represent the state of infection, the conformational change in these plasma PRRs is irreversible and that their binding to PAMPs would likely enable them to recruit other PRRs (14) to form the pathogen-recognition interactome ( Fig. 6F and supplemental Fig. 7), which triggers downstream effectors for opsonization by macrophages. The physiological implication of GBP was indicated by its endotoxic potential, where its interaction with LPS increased the endotoxicity. It is likely that GBP disrupts the LPS micelles, which exposes/unmasks the endotoxic potency of LPS. We suggest that in vivo, GBP and CRP bind to the bacterial surface and break down the LPS on the outer membrane of the invading bacteria. This exposure may possibly lead to the recruitment and activation of other host factors to mount a more efficient antimicrobial response. In conclusion, we have demonstrated the structural and functional basis of the Tectonin domaincontaining proteins in antimicrobial defense. The apparently similar Tectonin domains of GBP can differentiate self from nonself. The horseshoe crab and the human are separated by ϳ500 million years of evolutionary distance, yet the remarkable conservation in the architecture and function of Tectonin domain-containing proteins suggests their critical role in frontline defense against microbes. Intravascular fracture of the Impella device during removal Source of funding: Richard T. and Angela Clark Innovation Fund in Cardiac Electrophysiology and the F. Harlan Batrus Research Fund at the University of Pennsylvania. Address reprint requests and correspondence: Dr Pasquale Santangeli, Assistant Professor of Medicine, Hospital of the University of Pennsylvania, 9 Founders Pavilion – Cardiology, 3400 Spruce St, Philadelphia, PA 19104. E-mail address: pasquale.santangeli@uphs. upenn.edu. Introduction Mechanical percutaneous left ventricular assist devices (P-LVADs) are being increasingly adopted for high-risk invasive electrophysiological procedures, such as during catheter ablation of hemodynamically unstable ventricular tachycardia (VT). 1 In select patients with advanced heart failure status and/or with periprocedural acute hemodynamic decompensation due to a potentially reversible cause such as VT storm, P-LVADs can also be left in place for a few days after the procedure as a bridge to recovery. 1 The Impella P-LVAD (Abiomed, Danvers, MA) is inserted with a 14F sheath into the common femoral artery and advanced to the left ventricle (LV) via a retrograde transaortic valve approach. The catheter is composed of an inlet area (positioned in the LV), motorized pump, and outlet area (positioned in the aorta). Whereas the body of the catheter is 9F, the motorized pump is 12F ( Figure 1A). In this case report, we describe a serious complication related to the extraction of an Impella 2.5 catheter a few days after the initial implant, namely, the intravascular fracture of the Impella catheter occurring at the level of the arteriotomy site. Case report A 67-year-old man with severe nonischemic cardiomyopathy (LV ejection fraction 10%) and recurrent implantable cardioverter-defibrillator shocks for sustained hemodynamically unstable VT was referred to our institution for catheter ablation. Owing to his comorbidities (diabetes, kidney disease, obesity), he was deemed to be a poor heart transplant candidate. Because of the high-risk profile, insertion of a P-LVAD (Impella 2.5) was planned up front. 1 The left common femoral artery (LCFA) was accessed under ultrasound guidance, and the arteriotomy site was "pre-closed" by deploying 2 Perclose (Abbott Vascular, Santa Clara, CA) devices (left untied), as previously reported. 1 The 14F Impella sheath was advanced in the LCFA to allow the insertion of the Impella catheter. After sheath insertion, the left lower limb pulses were lost and a repeat femoral arteriogram revealed complete occlusion of the common femoral artery by the 14F sheath ( Figure 1A). The sheath was removed, and the Impella catheter was advanced into position and the previously placed Perclose tightened around the Impella without cinching the knots. There was no significant bleeding around the access site, and left lower extremity perfusion significantly improved. The case proceeded but, despite adequate flows with the Impella, the patient suffered a pulse electrical activity arrest. Because of the Impella, mean arterial pressures were never below 50 mm Hg. Once the patient was resuscitated and hemodynamics were stabilized, the case was concluded and he was

transferred to the cardiac critical care unit with the sheathless Impella left in place, for continued hemodynamic support. The patient's clinical course stabilized, and the P-VAD was eventually removed on day 8. Upon removal of the Impella, visual inspection revealed that the end of the Impella had broken off and remained within the patient's LCFA ( Figure 1A and B). Endovascular retrieval was discussed with the vascular surgery colleagues, 2 and the decision was that surgical retrieval was deemed more appropriate for this case; thus, the patient was urgently brought to the operating room, where the Perclose devices and retained Impella tip were surgically removed without complication ( Figure 1C and D). Discussion P-LVADs can be used to provide hemodynamic support for patients with severe LV dysfunction undergoing catheter ablation of hemodynamically unstable VT and may allow for prolonged induction, mapping, and ablation of hemodynamically unstable VT. 3 Intravascular injury represents one of the most common complications of Impella use. 3 Despite the fact that other device fractures had been previously reported in different segments of the device, 2 device tip fracture during removal has, to our knowledge, not previously been described as a complication of Impella use. Leaving an Impella in place for prolonged periods of time may be problematic if the arterial size is too small to accommodate the 14F sheath and the device is left in place without a sheath. Because the proximal portion of the catheter (9F) is significantly smaller than the distal portion (12F), if the arteriotomy site heals around the smaller portion, percutaneous removal may result in intravascular device fracture. KEY TEACHING POINTS Percutaneous left ventricular assist devices can be used as a bridge to recovery in hemodynamically unstable patients with ventricular tachycardia. Leaving an Impella for a prolonged period of time can cause a complication during device removal; because the proximal portion of the catheter is smaller than the distal part, the arteriotomy site can heal around the smaller part. Fractured device retrieval would be on a case-bycase basis, by either a surgical or an endovascular approach. The human papillomavirus type 16 L1 protein directly interacts with E2 and enhances E2-dependent replication and transcription activation The human papillomavirus (HPV) E2 protein is a multifunctional protein essential for the control of virus gene expression, genome replication and persistence. E2 is expressed throughout the differentiation-dependent virus life cycle and is functionally regulated by association with multiple viral and cellular proteins. Here, we show for the first time to our knowledge that HPV16 E2 directly associates with the major capsid protein L1, independently of other viral or cellular proteins. We have mapped the L1 binding region within E2 and show that the α-2 helices within the E2 DNA-binding domain mediate L1 interaction. Using cell-based assays, we show that co-expression of L1 and E2 results in enhanced transcription and virus origin-dependent DNA replication. Upon co-expression in keratinocytes, L1 reduces nucleolar association of E2 protein, and when co-expressed with E1 and E2, L1 is partially recruited to viral replication factories. Furthermore, co-distribution of E2 and L1 was detected in the nuclei of upper suprabasal cells in stratified epithelia of HPV16 genome-containing primary human keratinocytes. Taken together, our findings suggest that the interaction between E2 and L1 is important for the regulation of E2 function during the late events of the HPV life cycle. INTRODUCTION Human papillomaviruses (HPVs) are small, doublestranded DNA viruses that infect epithelia in multiple areas of the body, causing benign warts or, in some cases, cancer. Infection is established in the undifferentiated basal layer of the epithelia, and expression of the early genes E6, E7, E1 and E2 is initiated from the early promoter (P97 in HPV16). The combined expression of the E6 and E7 oncoproteins delays cell cycle exit and cellular differentiation, which are necessary for replication and amplification of viral genomes (Doorbar et al., 2012). The E2 protein is a specific DNA-binding protein that is important for the replication of HPV genomes, by recruiting the viral helicase E1 to the origin of replication (Ori) (Sanders & Stenlund, 2001). In addition, E2 controls transcription of the early genes by association with the transcriptional enhancer immediately upstream of the early promoter (Bernard et al., 1989;Kovelman et al., 1996). The E2 protein is folded into three distinct domains; the N-terminal transactivation domain, which is separated from the C-terminal DNA-binding and dimerization domain (DBD) by a disordered and flexible hinge region (Giri & Yaniv, 1988). E2 does not possess enzymic activity, but by association with a plethora of viral and cellular proteins, co-ordinates virus genome replication, transcriptional regulation, viral genome partitioning and cell cycle control (reviewed by McBride, 2013). The limited number of proteins encoded within the 8 kb HPV genome forces an unusual economy; not only do most HPV proteins have multiple roles in the virus life cycle, but associations between HPV proteins increase the functional significance of the differentiation-dependent timing of viral protein expression. Previous work has demonstrated an association between E2 and the early proteins E1, E6 and E7. Interaction with E1 is important for viral genome replication (Mohr et al., 1990), while association with E7 inhibits E7-dependent transformation (Gammoh et al., 2006). The interaction between E2 and E6 causes relocalization of both proteins to nuclear speckles and a corresponding decrease in E2-dependent virus repli-proteins (Grm et al., 2005). Concomitant with activation of late gene expression in the virus life cycle, E2 protein accumulates (Xue et al., 2010). This is thought to result in repression of the E6-and E7-encoding early transcripts, promoting cellular differentiation and production of late transcripts (Bouvard et al., 1994;Steger & Corbach, 1997;Thierry & Yaniv, 1987). E2 also forms a complex with E1^E4 and L2, which are expressed in the late stages of the life cycle. Interaction with E1^E4 stabilizes E2, potentially contributing to E2 protein accumulation (Davy et al., 2009). Association of E2 and the minor capsid protein L2 facilitates recruitment of E2 to ND10 bodies (also known as PML-oncogenic domains) within the nucleus (Day et al., 1998) and repression of E2-dependent transcription (Heino et al., 2000). It is hypothesized that interaction of E2 with L2 is important for virus genome encapsidation. At the end of the life cycle, newly synthesized L1 protein is imported into the nucleus as pentameric capsomeres through the karyopherin a2b1 heterodimer, where virus assembly takes place (Bird et al., 2008;Merle et al., 1999). The mature virion contains the major capsid protein, L1, and the minor protein, L2. L1 and L2 interact and, although the binding interface between L1 and L2 is poorly defined, studies indicate that L2 binds to hydrophobic residues of L1 and is therefore positioned in the central cavity of L1 pentamers (Finnen et al., 2003;Lowe et al., 2008). Sequences at the C terminus of L1 are important for non-specific interaction with DNA (Li et al., 1997) and it has been suggested that key features in the L1 protein resemble histone chaperone proteins and that L1 may bind histones to facilitate genome packaging (Buck et al., 2013). In this study, we hypothesized that E2 associates with the major capsid protein, L1, and that this interaction is important in regulating E2 function in the late stages of the virus life cycle. We have confirmed this interaction in human keratinocytes and show for the first time that L1 co-operates with E2 to enhance transcription activation and virus DNA replication. Furthermore, we demonstrate that L1 affects the localization of E2 protein and that L1 is partially recruited to E1/E2 viral replication foci. We hypothesize therefore that L1 contributes to the regulation of E2 in the virus life cycle. In silico analysis of E2 and L1 interaction The interaction between E2 and L1 was computationally analysed and the best-docked complexes were obtained based on energy minimization. These complexes were further analysed to determine the residues that were in close proximity at the predicted binding interface (Fig. 1). Based on consensus from 21 best-docked complexes, it was concluded that aa 335-365 of E2 have a high likelihood of association with L1. These residues make up the a-2 helix of the E2 DBD. The region of L1 predicted to bind to E2 was within an external loop between aa 250 and aa 290, which is also predicted to bind L2 (Lowe et al., 2008). Characterization of the interaction between HPV16 E2 and L1 To determine whether E2 associates with L1 in a cell-based assay, co-immunoprecipitation experiments were carried out. HPV-negative cervical carcinoma-derived C33a cells were co-transfected with HPV16 E2 and codon-optimized L1 expression constructs alone or in combination, and the proteins immunoprecipitated with E2-specific antibody or isotype control (IgG). L1 protein was robustly coimmunoprecipitated with E2-specifc antibody when co-expressed with E2 and only a minimal amount of L1 protein was non-specifically immunoprecipiated in the absence of E2 protein, demonstrating specificity of the assay (Fig. 2a). We also performed the reverse co-immunoprecipitation, where complexes were immunoprecipitated with L1 protein-specific antibody and co-precipitated E2 was detected by Western blotting (Fig. 2a). To further test our in silico analysis of the E2-L1 binding surfaces, domain mapping experiments using full-length and truncated glutathione-S-transferase (GST)-tagged E2 proteins were carried out. GST-tagged E2 proteins bound to glutathione-agarose beads were incubated with purified L1 capsomeres. As expected, L1 capsomeres bound with high affinity to full-length E2 while no binding was observed to the affinity resin alone or the GST-bound resin (Fig. 2b). Domain mapping revealed that the L1 binding site within E2 exists in the C-terminal transactivation domain as aa 202-365 bound L1 capsomeres, while aa 1-257 did not. Furthermore, aa 306-365 at the extreme C-terminal region of E2 bound L1 protein, while aa 202-306 were unable to bind L1. The L1-binding region between aa 306 and aa 365 is outside the DNA-binding surface of E2 (a-1 helices) but contains the a-2 helices that were predicted to bind L1 in our in silico analysis (Figs 1 and 2c), providing evidence that the binding model may reflect the true binding interface. These binding experiments demonstrate a previously uncharacterized direct interaction between HPV16 E2 and L1 proteins that could have important implications for the virus life cycle. As both L1 and E2 proteins are known to bind to DNA (Dell et al., 2003;Schäfer et al., 2002), and the L1 binding surface on E2 was within the C-terminal DNA-binding domain but outside the specific DNA-binding helices of E2, it is possible that the interaction is mediated by both proteins simultaneously associating with contaminating DNA. We therefore repeated co-immunoprecipitation experiments in the presence of ethidium bromide, which intercalates with DNA and prevents protein-DNA interactions. Incubation of the protein lysates with ethidium bromide did not affect the ability of E2 and L1 to form a complex (Fig. 2d). It is therefore unlikely that this novel protein-protein interaction is mediated by interaction with? DNA. L1 stimulates E2-dependent transcription activation and replication To determine whether the association between HPV16 E2 and L1 alters E2 function, the ability of E2 to activate transcription in the presence of L1 was analysed. C33a cells were transfected with a luciferase reporter plasmid containing six E2 binding sites upstream of a thymidine kinase promoter, which controls expression of firefly luciferase, along with full-length E2 and increasing amounts of L1 plasmid. Protein expression was confirmed by Western blotting (Fig. 3a). Expression of E2 alone resulted in an over 50-fold activation of transcription from the reporter plasmid (Fig. 3b). Expression of L1 protein alone resulted in a small increase in transcription in comparison with reporter alone, but this did not reach significance (P50.06). Interestingly, co-expression of L1 with E2 resulted in a dose-dependent increase in luciferase activity, indicating that E2 and L1 co-operate to stimulate transcriptional activation. The binding assays shown in Fig. 2b demonstrated that L1 protein associates with the C-terminal DNA-binding domain of E2. We therefore repeated the transcription assay using the truncated E2 protein E2-HC, which contains aa 200-365 of HPV16 E2. This E2 protein is able to bind to DNA and to L1 protein (Fig. 2b), but does not contain the transactivation domain of E2 and therefore should be severely crippled in its ability to activate the E2responsive reporter. Surprisingly, this truncated E2 protein was able to activate transcription from the synthetic reporter, but activity was fivefold lower than that of fulllength E2 ( Fig. 3c and 3d). Co-transfection of L1 with E2-HC resulted

in a further 10-fold activation of transcription, indicating that E2-dependent recruitment of L1 to the promoter is sufficient for transcriptional enhancement and that the inherent ability of E2 to function as a transcriptional activator is not necessarily required. Using a transient DNA replication assay, the effect of L1 on E2-dependent virus replication was assessed. Cells were transfected with a plasmid containing the viral Ori and E1 or E2 alone or in combination, along with increasing amounts of the L1 expression plasmid. Protein expression was detected by Western blotting (Fig. 3e) and replicated Ori-containing In silico analysis of potential binding interfaces between HPV16 E2 and L1. In silico modelling was performed using ZDOCK, ClusPro and Rosetta. Monomeric L1 protein is shown in green and the homodimeric DNA-binding domain of E2 (aa 285-365) in cyan with the region of the a-2 helices (a-2 and a-29) of E2 docked within 4 Å of L1 shown in red. The binding interface with the lowest energy was between an a-2 helix of E2 (aa 335-365) in close proximity to external loops between aa 250-290 of the L1 protein. plasmid was detected by quantitative PCR (qPCR) (Fig. 3f). As expected, co-expression of E1 and E2 resulted in a dramatic increase in Ori-dependent replication. This was enhanced by co-expression of L1 in a dose-dependent manner. Having demonstrated that the transcription and replication functions of E2 are stimulated by L1, it was important to determine whether these effects are due to alterations in E2 protein stability in the presence of L1. To determine the half-life of E2 alone or co-expressed with L1, C33a cells were transfected with E2 and L1 expression plasmids alone or in combination. Extracts of cells treated with cycloheximide for 0, 2, 4, 8, 10 and 24 h were analysed Fig. 2. Characterization of the HPV16 E2 and L1 interaction. (a) Upper panel: C33a cells were transfected with E2 and L1 expression constructs alone or in combination, and lysates were immunoprecipitated (IP) with sheep anti-E2 or pre-immune IgG control. Co-immunoprecipitated protein complexes were separated by SDS-PAGE and L1 and E2 proteins were detected by Western blotting with mouse anti-L1 and anti-E2 (TVG261) antibodies. On the left, 10 % input of cell lysates is shown. Lower panel: C33a cells were transfected with E2 and L1 expression constructs, and lysates were immunoprecipitated with sheep anti-E2 or mouse anti-L1 antibodies and isotype-matched IgG control. Co-immunoprecipitated protein complexes were separated by SDS-PAGE, and L1 and E2 proteins were detected by Western blotting with mouse anti-L1 and anti-E2 (TVG261) antibodies. On the left, 10 % input of cell lysates is shown. A short and a long exposure of the L1 blot are shown to allow visualization of the protein precipitated with L1-and E2-specific antibodies. (b) GST pull-down assays using GST, GST-E2 full-length and the truncations indicated in each lane. (c) C33a cells were co-transfected as described in (a) and (d) transcription activity of full-length E2 was compared with a truncated E2 protein containing aa 200-365 (E2-HC). (d) Luciferase activity was determined as described in (b). (e) C33a cells were co-transfected with HPV16 Ori plasmid, E2 and E1 expression plasmids and increasing amounts of L1 expression plasmid. Protein expression was detected by Western blotting. Molecular mass standards are indicated on the left. (f) Dpn Idigested DNA quantified by qPCR. The data are expressed as fold increase in replication over Dpn I-digested pOri16M alone. All data shown represent the mean¡SE of three independent experiments. Significance was tested using Student's ttest; *P,0.05, **P,0.01, ***P,0.001. by Western blotting (Fig. 4a). E2 protein levels were normalized to b-actin protein and used to determine the half-life of E2 in each experimental condition (Fig. 4b). It should be noted that an increase in E2 protein expression was observed following co-expression with L1 protein. As expression of both of these proteins is driven from a CMV promoter, we presume that the increase in E2 protein when co-expressed with L1 is due to the enhancement of transcription activity of E2, which can enhance CMV promoter activity. This effect was not observed in the transcription assays shown in Fig. 3 because the amount of plasmid used in the transcription assays was the equivalent of 10-fold less than the amount used in the stability assays. The calculated half-life of E2 protein was 4.5 h, which is in agreement with previous reports (King et al., 2011;Li et al., 2014). A small increase in the half-life of E2 was observed in the presence of L1 (5.8 h), but this increase did not reach significance, suggesting that the effect of L1 on E2 activity is not due to stabilization of E2. Taken together, these data provide evidence that L1 directly alters both the transcriptional activation and replication functions of E2. L1 co-localizes with E2 and prevents nucleolar accumulation of E2 To further characterize the interaction between E2 and L1, subcellular localization of these two proteins expressed alone or in combination was investigated by confocal microscopy. When expressed alone, E2 protein was localized to the nucleus, and in many cells the staining of large foci within the nucleus was noted (Fig. 5a). These E2 foci have been previously reported for HPV1 E2 (Prescott et al., 2014) and were shown to be nucleoli. It has also been demonstrated that treatment of cells with 100 mM salt prior to fixation results in strong nucleolar localization of HPV16 E2 (Sakakibara et al., 2013). To confirm that the nuclear structures stained with our E2 antibody were nucleoli, we co-stained E2-transfected cells with an antibody specific for a nucleolar marker, C23. Co-localization of E2 with C23 was observed, demonstrating that E2 localizes to nucleoli in a subset of transfected cells (Fig. 5b). Furthermore, we stained cells with a commercially available mouse monoclonal HPV16 E2-specific antibody and confirmed the presence of E2-positive nucleolar staining, demonstrating that the staining observed with the sheep polyclonal HPV16 E2 antibody was reproducible (Fig. 5c). When expressed alone, HPV16 L1 was also observed in the nucleus, but with nucleolar exclusion in the majority of cells imaged. Of particular note, when E2 and L1 were co-expressed, the proteins co-localized in the nucleus and the proportion of cells with nucleolar E2-staining was significantly reduced (Figs. 5a, d). E1-and E2-dependent virus genome replication has been shown to occur in discrete replication factories that form nuclear foci (Sakakibara et al., 2011(Sakakibara et al., , 2013. Owing to its ability to enhance E2-dependent replication, the localization of L1 protein to E1/E2 replication foci was studied. As previously described, when co-transfected with the viral Ori-containing plasmid, E1 and E2 co-localized in bright foci, which are thought to be replication factories (Sakakibara et al., 2013) and are distinct from the nucleolar staining described above. Co-transfection of L1 did not appear to alter the formation of E1/E2-associated replication foci and L1 was not enriched within the replication foci when cells were fixed in formaldehyde (Fig. 6a). However, extraction of the cells with buffer containing 100 mM NaCl prior to fixation revealed that a proportion of L1 protein co-localizes with E1/E2 replication foci, indicating that L1 may stimulate E2dependent replication by recruitment to replication factories (Fig. 6b). Co-localization of E2 and L1 in differentiating epithelium To determine whether the interaction between E2 and L1 is physiologically relevant, the co-localization of these two proteins was studied in primary human foreskin keratinocytes (HFKs) containing HPV16 episomes. Thirteen-dayold organotypic rafts were fixed and sections co-stained with E2 and L1-specific antibodies. E2 staining was observed in the nucleus and cytoplasm of cells in the middle and upper layers of the raft section (Fig. 7a). While some E2-positive cells were stained in both the Fig. 7b(ii)]. As described previously (Xue et al., 2010), E2 staining in the basal and lower layers of the raft was not observed, presumably because the amount of E2 protein expressed in these cells is below the level of detection (Fig. 7a). No staining was observed in organotypic raft sections derived from HPV-negative HFKs, demonstrating specificity of the antibody. Of note, nuclear L1 staining was observed in individual cells in upper layers of the raft sections. The nuclei of these cells also stained positive for E2 [ Fig. 7b(iii, iv)]. Some of the L1-positive cells contained distinct E2 foci within the nuclear compartment that were not observed in L1-negative cells, indicating that E2 may have a different biological function in differentiated L1-expressing cells. These data provide evidence that E2 and L1 are co-expressed in a physiologically relevant model system and that the physical association of these two viral proteins is likely to play a role in the HPV life cycle. DISCUSSION We predicted that the HPV replication and transcription factor E2 forms a complex with the late viral capsid protein L1. We initially tested this hypothesis by mapping potential interacting surfaces using protein-protein docking algorithms. These studies predicted that the a-2 helices of the C-terminal DNA-binding domain of E2 associate with L1 loops that lie on the surface of the capsomere knobs. The position of the predicted binding surface on L1 implies that E2 could bind to L1 when assembled as a pentameric capsomere, since the loops predicted to bind to E2 protrude from the surface of the capsomere knobs (Modis et al., 2002). Interestingly, the region of L1 predicted to associate with E2 overlaps with the L2 binding region predicted by Lowe et al. (2008), although since L1 protein is pentameric in solution, it is possible that L1-L2-E2 complexes could exist. The L1 binding surface within E2 was predicted to lie within the a-2 helices of the E2 DNAbinding domain, which is outside the DNA-binding region contained within the a-1 helices, and was confirmed by domain-mapping experiments that showed that aa 306-365 of E2 were sufficient for L1 binding. This specific location of the binding site on E2 suggests that E2 may be able to bind to L1 and DNA simultaneously. Although the exact binding interface between L1 and E2 needs further refinement, an interaction was confirmed by co-immunoprecipitation experiments in human cervical keratinocytes. In addition, we showed that the interaction is not mediated by association with DNA. Interestingly, E2 and L1 were co-distributed in a subset of cells in the upper layers of differentiating epithelium in a physiologically relevant HPV16 life cycle model system. Characterization of the effect of L1 on E2 activity revealed that L1 stimulates E2-dependent replication and transcription activation, without altering E2 protein stability. Although the effect of L1 overexpression on E2-dependent replication was statistically significant, only a 2.5-fold increase in replication was observed. It is possible that this increased replication is due to alteration of cell cycle progression of transfected cells, although changes in cellular proliferation were not noted. It is also possible that the effect of L1 on E2 activity is enhanced in differentiated cells, a possibility we are currently testing. Co-expression of L1 altered the subcellular localization of E2. When E2 was expressed alone, E2-specific nucleolar staining was observed in many cells. The localization of E2 at the nucleolus has not been widely reported, but has been previously observed in a range of human cell types in our own immunofluorescence experiments (J. L. Parish, unpublished) and reported by others for HPV1 E2, or for HPV16 E2 following salt extraction of cells (Prescott et al., 2014;Sakakibara et al., 2013). The function of E2 at the nucleolus is not known, but it is interesting to note that the Epstein-Barr virus nuclear antigen 1 (EBNA1) protein, which is functionally analogous to E2, is also recruited to the nucleolus (Shire et al., 2006). Furthermore, it has been shown that mutation of dipeptide recognition motifs of serine-arginine protein kinase 1 (SRPK1) in the hinge region of HPV1 E2 significantly increases enrichment of E2 at the nucleolus. HPV1 E1^E4 inhibits SRPK1 activity and enhances nucleolar localization of E2 (Prescott et al., 2014). Although HPV16 E2 does not contain SRPK1 recognition motifs, it is tempting to speculate that, in the context of the virus life cycle, the temporal expression of E1^E4 and L1 could regulate nucleolar localization of E2 as cells terminally differentiate. Further work is required to understand the function and control of E2 at the nucleolus, but emerging evidence suggests an interplay between viral and host cell proteins in the regulation of E2 localization and activity. Perhaps of greater interest is the observation that L1 protein partially co-localized with E1/E2 replication

factories following salt extraction of cells. These experiments indicate that a pool of L1 protein is recruited to replication factories, presumably to enhance virus replication. The mechanistic regulation of E2 activity in the context of the virus life cycle is not understood. However, characterization of the interaction with L1 and other viral proteins demonstrates the ability of the virus to self-regulate E2 activity in differentiating epithelium (Fig. 8). Association of E2 with E1 in the basal cells is important for viral genome replication (Sanders & Stenlund, 2001), while association with the E6 and E7 proteins appears to regulate oncoprotein activity (Gammoh et al., 2006;Grm et al., 2005). In addition, E6 appears to inhibit E2-dependent virus replication (Grm et al., 2005). Differentiationinduced expression of E1^E4 in the mid-layers of the epithelium results in a stabilization of E2 (Davy et al., 2009), which is consistent with the observed increased expression of E2 in the mid-and upper layers of cervical epithelia (Xue et al., 2010) and organotypic raft cultures of HPV16-positive primary HFKs (Fig. 7). Whether E2 is , and co-transfected with an L1 expression plasmid (lower panel). E2 protein was stained with sheep anti-E2 antibody (red), E1 with rabbit anti-HA antibody (green) and L1 with mouse anti-L1 antibody (magenta). DNA was stained with Hoechst (blue). (b) Cells were transfected as described for (a) and extracted with 100 mM NaCl prior to fixation as described in Methods. Images were captured by confocal microscopy. Bars, 10 mm. able to simultaneously interact with E1^E4 and L1 in differentiated cells remains to be determined. Our data show that L1 enhances E2-dependent virus replication and, following salt extraction of cells, we observed that L1 protein co-localizes with E1/E2 replication foci in the presence of viral origin of replication. Put together with the observation that E2 and L1 proteins are coexpressed in HPV16-genome-containing differentiating epithelium, it is possible that L1 contributes to E2dependent viral genome amplification in the late stages of the virus life cycle. We also demonstrate that L1 co-expression increases transcription from an E2-responsive reporter. This is somewhat surprising since E2 is thought to switch from a transcriptional activator to a repressor as E2 levels rise in differentiating epithelium, resulting in repression of the E6 and E7 oncoproteins and subsequent cell cycle exit (Thierry, 2009). However, our experiments were performed using a synthetic E2-responsive promoter, which is a useful assay in the measurement of E2 activity in transfected cell systems such as that used in this study, but does not truly reflect the function of E2 as a transcriptional regulator at the viral long control region in differentiating epithelium. It is also conceivable that E2 and L1 do not act synergistically on the synthetic promoter and that the enhancement of transcription observed is not a direct result of the E2-L1 protein-protein interaction but an additive effect of independent promoter stimulation by E2 and L1. Nonetheless, the enhancement of E2 activity by L1 is intriguing and is likely to contribute to the selfregulation of E2 throughout the virus life cycle. It is also possible that the interaction between L1 and E2 does not regulate E2 activity in the context of the HPV life cycle, but plays a role in an as yet understudied step in the life cycle, such as the formation of virus particles. Finally, in the upper layers of the epithelium, L2 expression is initiated, which inhibits E2-dependent replication and facilitates virus genome packaging (Day et al., 1998). In summary, the differential regulation of E2 activity by early and late viral proteins appears to allow the use of a single viral protein to support multiple important life cycle events. Our data provide evidence of an interaction between E2 and the capsid protein L1, further adding to the complexity of E2 regulation during late stages of the virus life cycle. Cell culture. C33a (human cervical carcinoma epithelial) cells were grown in Dulbecco's modified Eagle's medium containing 10% FBS at 37 uC, 5% CO 2 , using standard tissue culture techniques. The transfection of primary HFKs from neonatal foreskin epithelia (ethical approval number 06/Q1702/45) was performed in Dr S. Roberts' laboratory as previously described (Wilson et al., 2007). A plasmid containing the wild-type HPV16 114 kb genome (obtained from Ethel-Michele de Villiers, DKFZ, Germany) was digested with Bam HI and recircularized and transfected into early-passage primary HFKs with a neomycin resistance marker. Twenty-four hours later, cells were seeded onto irradiated J2-3T3 fibroblasts in the presence of G418 in E medium (Wilson & Laimins, 2005) for 8 days. Emerging colonies were pooled and the presence of episomal HPV16 genomes was determined by Southern blotting (C. D. James and S. Roberts, unpublished data). Organotypic raft cultures were prepared as previously described (Wilson & Laimins, 2005) and cultured for 13 days. Rafts were fixed in 3.7% paraformaldehyde and paraffin-embedded prior to sectioning (Propath). GST pull-down. GST fusion proteins were purified from bacteria induced with 0. Fig. 8. Model of differentiation-dependent E2 regulation via interaction with early and late HPV proteins. E2 protein associates with E1, E7, E1^E4 (E4), L1 and L2, the details of which are described in the text. As cells differentiate, E2 protein expression is increased. The functional consequence of interaction of E2 with other viral proteins is indicated. Replication assay. C33a cells (2.5|10 5) were seeded into each well of a six-well plate and left to adhere overnight. Cells were then cotransfected with 25 ng pOri16M, expression plasmids for L1 (100, 250, 500 ng), E2 (10 ng) and E1 (600 ng). Salmon sperm DNA was included to normalize the DNA amount in each transfection. Fortyeight hours later, cells were washed in PBS and DNA extracted using 250 ml Hirt extraction buffer (0.6% SDS, 10 mM EDTA). NaCl was added to a final concentration of 1.25 M, and samples were incubated overnight at 4 uC. The DNA was purified by phenol/chloroform/ isoamyl alcohol extraction followed by ethanol precipitation, and the DNA pellet was resuspended in 20 ml water. DNA was digested with Dpn I at 37 uC for 4 h and replicated pOri16M was measured by qPCR using Sensimix SyBr (Bioline) and an MXPro3005 PCR machine (Agilent) as previously described (Taylor & Morgan, 2003). Immunofluorescence. C33a cells were seeded onto glass coverslips prior to transfection with Lipofectamine 2000 (Invitrogen). All subsequent incubations were performed at room temperature. Twentyfour hours post-transfection, cells were fixed with 4% formaldehyde for 10 min and permeabilized in 0.2% Triton X-100/PBS for 10 min. Immunofluorescent staining of HFK raft sections was performed following an agitated low-temperature antigen retrieval as previously described (Watson et al., 2002). Cells were blocked (10% heat-inactivated goat serum, 2% BSA in PBS) for 1 h and stained as previously described (Parish et al., 2006a). Epifluorescent imaging was performed on a Nikon E600 epifluorescent microscope fitted with a DXM1200F digital camera, and confocal images were captured on a Zeiss LSM 510 META confocal microscope. Protein stability assays. C33a cells (6|10 6 ) were seeded in 15 cm dishes and transfected with X-TremeGENE 9 (Roche). Twenty-four hours later, cells were trypsinized, and counted, and 1|10 6 cells were reseeded in 6 cm dishes. The following day, cells were treated with 10 mg ml 21 cycloheximide (Sigma) and harvested at 0, 2, 4, 8, 10 and 24 h, lysed in urea lysis buffer (50 mM Tris/HCl, pH 7.4, 9 M urea, 5 mM DTT) and sonicated for 15 s at 30% amplitude. Protein concentration was quantified by Bradford assay and proteins detected by Western blotting. Relative amounts of proteins at each time point were quantified and normalized to b-actin using ImageJ software, and half-life was calculated using Graphpad Prism 4 software using a onephase exponential decay model. Increasing Incidence of Clostridium difficile-associated Disease, Singapore To the Editor: Clostridium difficile–associated disease (CDAD) has increased in incidence across North America and Europe (1). Recent reports document the emergence of an epidemic strain of C. difficile, NAP1/BI/027, associated with increased virulence (2,3). However, less information is available regarding CDAD epidemiology in Asia. We examined the incidence of C. difficile among hospitalized patients in Singapore from 2001 through 2006 and conducted a case–control study to evaluate risk factors for testing positive for C. difficile toxin (CDT) in our population. Tan Tock Seng Hospital (TTSH) is a 1,200-bed, acute-care general hospital in Singapore that serves an urban population of 4 million. We calculated CDAD incidence using the number of patients testing positive for CDT per 10,000 patient days from 2001 through 2006. We used this calculation because CDT testing would have been ordered for clinical indications. CDT testing was performed by using the same ELISA (Premier Toxins AB Meridian Bioscience, Inc., Cincinnati, OH, USA) throughout the entire period of investigation. Case-patients and controls were selected from patients hospitalized at TTSH from January 1 through December 31, 2004. Microbiology laboratory records were used to define 3 groups. Case-patients were defined as CDT-positive inpatients (group 1). Two sets of negative controls were defined: the first (group 2) consisted of patients who tested negative for CDT. However, because false-negatives could nullify differences between groups 1 and 2, we defined a second set of negative controls (group 3) from among 18,000 inpatients not tested for CDT. Seventy patients were selected from each group by using a random number generator program. Forty-eight, 61, and 56 records were retrieved for groups 1, 2, and 3, respectively. Standardized forms were used to extract data from hospital medical records. Demographic data and hospitalization details, including ward type (6-bed, 4-bed, or single room), were collected. We examined antimicrobial drug use within 30 days of admission and within 30 days of CDT testing. We also evaluated the use of proton pump inhibitors (PPIs) and H2 blockers because these have been reported as risk factors (1,4–6). Outcomes ascertained included the time to discharge after CDT testing, and death within 30 days after CDT testing. The study was approved by the institutional ethics review board. Characteristics of case-patients and controls were compared by using the Wilcoxon rank sum test for continuous variables and the Fisher exact test for categorical variables. Variables significantly associated with CDT in the univariate analysis were selected for inclusion in the multivariate regression model. A 2-sided p value <0.05 was considered significant for all comparisons. CDAD incidence rose sharply from 1.49 cases per 10,000 patient-days in 2001 to 6.64 cases per 10,000 patient-days in 2006 (Figure). During the same period, the percentage of CDT-positive samples increased from 7% to 11%, while the number of samples tested increased from 906 to 3,508. Figure Clostridium difficile–associated disease incidence, Singapore, 2001–2006. Comparing group 1 (CDT positive) with group 2 (CDT negative), a CDT-positive result was more likely to occur in those with prolonged hospital admissions (>14 days) than in those who had shorter hospital stays (<7 days; odds ratio [OR] 2.59, 95% confidence interval [CI] 1.01–6.63). Of the 19 CDT-positive patients on PPIs and the 34 CDT-negative patients on PPIs, the median exposures were 14 and 7 days, respectively (p = 0.01). In multivariate analysis, exposure to broad-spectrum antimicrobial drugs was a borderline significant risk factor (adjusted OR 2.24, 95% CI 1.00–5.02, p = 0.05). When group 1 (CDT positive) was compared with group 3 (not tested for CDT), quinolones (OR 6.67, 95% CI 1.85–24.03), anti-anaerobic antimicrobial agents (OR 7.29, 95% CI 2.39–22.26), and stay in a 6-bed ward (OR 3.15, 95% CI 1.01–9.82) were significant risk factors in multivariate analysis. Case-patients were more likely than controls to have a longer hospital stay after testing positive. The median hospital stay after CDT testing was 16 days for case-patients versus 11 days for controls (p = 0.03). This study documents a 4-fold rise in CDAD incidence among hospitalized patients in Singapore from 2001 through 2006. The current incidence, 6.64 per 10,000 patient-days, is comparable to that reported by large hospitals in Canada (7), which indicates that CDAD has emerged as an important nosocomial infection in Singapore. This incidence rate, based on the number of patients (rather than the number of isolates) who had positive CDT test results, and the rise in sample positivity from 7% to 11% suggests that the higher rates are due to a true increased occurrence rather than merely more testing. Possible factors driving the rise in CDAD include increased use of antimicrobial agents or changes in use patterns. The volume of quinolones and broad-spectrum

antimicrobial drugs used at TTSH doubled between 2002 and 2005, consistent with other studies implicating quinolones as a risk factor in CDAD (4). Rising incidence or virulence could herald the geographic spread of new C. difficile strains. Given the spread of NAP1/BI/027 strains in other parts of the world, this increased incidence in Singapore should heighten vigilance for the introduction of outbreak strains into Asia. The findings from this study have implications for hospital management and infection control. Environmental contamination has been described as a mode of transmission (1). Potential crowding in 6-bed wards may increase spread of CDAD and may be particularly relevant in busy healthcare facilities in Asia. CDAD is estimated to cost the healthcare system in the United States $3.2 billion annually (8). With longer hospitalization for persons after they test positive for CDT, as seen in our study, rising CDAD rates could increase hospital occupancy and result in excess healthcare expenditures. CDAD in Asia is an emerging challenge that needs to be recognized. Its control will ultimately depend on priority being given to epidemiologic surveillance, infection control, and stewardship of antimicrobial agents. Increasing Incidence of Clostridium diffi cile-associated Disease, Singapore To the Editor: Clostridium diffi cile-associated disease (CDAD) has increased in incidence across North America and Europe (1). Recent reports document the emergence of an epidemic strain of C. diffi cile, NAP1/ BI/027, associated with increased virulence (2,3). However, less information is available regarding CDAD epidemiology in Asia. We examined the incidence of C. diffi cile among hospitalized patients in Singapore from 2001 through 2006 and conducted a case-control study to evaluate risk factors for testing positive for C. diffi cile toxin (CDT) in our population. Tan Tock Seng Hospital (TTSH) is a 1,200-bed, acute-care general hospital in Singapore that serves an urban population of 4 million. We calculated CDAD incidence using the number of patients testing positive for CDT per 10,000 patient days from 2001 through 2006. We used this calculation because CDT testing would have been ordered for clinical indications. CDT testing was performed by using the same ELISA (Premier Toxins A&B; Meridian Bioscience, Inc., Cincinnati, OH, USA) throughout the entire period of investigation. Case-patients and controls were selected from patients hospitalized at TTSH from January 1 through December 31, 2004. Microbiology laboratory records were used to defi ne 3 groups. Case-patients were defi ned as CDTpositive inpatients (group 1). Two sets of negative controls were defi ned: the fi rst (group 2) consisted of patients who tested negative for CDT. However, because false-negatives could nullify differences between groups 1 and 2, we defi ned a second set of negative controls (group 3) from among 18,000 inpatients not tested for CDT. Letters Letters commenting on recent articles as well as letters reporting cases, outbreaks, or original research are welcome. Letters commenting on articles should contain no more than 300 words and 5 references; they are more likely to be published if submitted within 4 weeks of the original article's publication. Letters reporting cases, outbreaks, or original research should contain no more than 800 words and 10 references. They may have one Figure or Table and should not be divided into sections. All letters should contain material not previously published and include a word count. Seventy patients were selected from each group by using a random number generator program. Forty-eight, 61, and 56 records were retrieved for groups 1, 2, and 3, respectively. Standardized forms were used to extract data from hospital medical records. Demographic data and hospitalization details, including ward type (6-bed, 4-bed, or single room), were collected. We examined antimicrobial drug use within 30 days of admission and within 30 days of CDT testing. We also evaluated the use of proton pump inhibitors (PPIs) and H2 blockers because these have been reported as risk factors (1,(4)(5)(6). Outcomes ascertained included the time to discharge after CDT testing, and death within 30 days after CDT testing. The study was approved by the institutional ethics review board. Characteristics of case-patients and controls were compared by using the Wilcoxon rank sum test for continuous variables and the Fisher exact test for categorical variables. Variables signifi cantly associated with CDT in the univariate analysis were selected for inclusion in the multivariate regression model. A 2-sided p value <0.05 was considered signifi cant for all comparisons. CDAD incidence rose sharply from 1.49 cases per 10,000 patientdays in 2001 to 6.64 cases per 10,000 patient-days in 2006 (Figure). During the same period, the percentage of CDT-positive samples increased from 7% to 11%, while the number of samples tested increased from 906 to 3,508. Comparing group 1 (CDT positive) with group 2 (CDT negative), a CDT-positive result was more likely to occur in those with prolonged hospital admissions (>14 days) than in those who had shorter hospital stays (<7 days; odds ratio [OR] 2.59, 95% confi dence interval [CI] 1.01-6.63). Of the 19 CDT-positive patients on PPIs and the 34 CDT-negative patients on PPIs, the median exposures were 14 and 7 days, respectively (p = 0.01). In multivariate analysis, exposure to broad-spectrum antimicrobial drugs was a borderline signifi cant risk factor (adjusted OR 2.24, 95% CI 1.00-5.02, p = 0.05). When group 1 (CDT positive) was compared with group 3 (not tested for CDT), quinolones (OR 6.67, 95% CI 1.85-24.03), anti-anaerobic antimicrobial agents (OR 7.29, 95% CI 2.39-22.26), and stay in a 6-bed ward (OR 3.15, 95% CI 1.01-9.82) were signifi cant risk factors in multivariate analysis. Case-patients were more likely than controls to have a longer hospital stay after testing positive. The median hospital stay after CDT testing was 16 days for case-patients versus 11 days for controls (p = 0.03). This study documents a 4-fold rise in CDAD incidence among hospitalized patients in Singapore from 2001 through 2006. The current incidence, 6.64 per 10,000 patient-days, is comparable to that reported by large hospitals in Canada (7), which indicates that CDAD has emerged as an important nosocomial infection in Singapore. This incidence rate, based on the number of patients (rather than the number of isolates) who had positive CDT test results, and the rise in sample positivity from 7% to 11% suggests that the higher rates are due to a true increased occurrence rather than merely more testing. Possible factors driving the rise in CDAD include increased use of antimicrobial agents or changes in use patterns. The volume of quinolones and broad-spectrum antimicrobial drugs used at TTSH doubled between 2002 and 2005, consistent with other studies implicating quinolones as a risk factor in CDAD (4). Rising incidence or virulence could herald the geographic spread of new C. diffi cile strains. Given the spread of NAP1/BI/027 strains in other parts of the world, this increased incidence in Singapore should heighten vigilance for the introduction of outbreak strains into Asia. The fi ndings from this study have implications for hospital management and infection control. Environmental contamination has been described as a mode of transmission (1). Potential crowding in 6-bed wards may increase spread of CDAD and may be particularly relevant in busy healthcare facili- Cases/10,000 patient-days ties in Asia. CDAD is estimated to cost the healthcare system in the United States $3.2 billion annually (8). With longer hospitalization for persons after they test positive for CDT, as seen in our study, rising CDAD rates could increase hospital occupancy and result in excess healthcare expenditures. CDAD in Asia is an emerging challenge that needs to be recognized. Its control will ultimately depend on priority being given to epidemiologic surveillance, infection control, and stewardship of antimicrobial agents. Rural out-migration and return: perspectives on the role of the everyday reality and the idyll in Ireland The aim of this article is to add to understandings of the rural idyll as an influence on return migration. Interviews were conducted with thirty-four first generation rural returnees in Ireland and their responses were analysed in depth. Unemployment and constraints on career and personal fulfilment influenced migration overseas, usually, to a major city. Consciousness of the loss of features of the idyll emerged in adapting to life in the destination area. Memories of the positive features of family and rural life influenced return, particularly for those with children, but the capacity to return was dependent for most on economic circumstances. Certain features of the idyll were recaptured on return but everyday rural reality intruded also. Some people migrated again. An improved understanding of the idyll and of the everyday reality should help to better inform policy to re-attract out-migrants back to the countryside. Introduction Out-migration of young working age people is frequently a feature of rural areas located at substantial distances from centres of economic activity and employment (Jentch and Shucksmith, 2004;OECD, 2010). For many of them the countryside is a place of harsh reality characterised by limited economic opportunities, poor service facilities and restrictions on personal development. At the same time, idyllic imaginary qualities are associated with the countryside in general and with particular areas of countryside and can serve to attract new residents and second home owners (Halfacree, 1993(Halfacree, , 2012. Idyllic features of the rural for former out-migrants are less well understood. This paper explores the role of an idyllic imaginary, in contrast with the daily reality, in attracting out-migrants back to live in the countryside. In its poetic origins, in third-century Greece, the idyll lauded pastoral life in contrast with emerging urbanisation (Williams, 1973). Since the late nineteenth century, conceptualisation of the idyll has come to incorporate tropes of family and community, as well as pastoral landscapes, reflecting the influence of German sociologist Ferdinand Tönnies (1887Tönnies ( /1963 in distinguishing between a gemeinschaft rural communal society in contrast with a more urban-based associational gesellschaft. The everyday rural reality for the resident populations is often counter-idyllic (Cloke, 2003). A process of secular decline may be long-established which the arrival of new migrants does not necessarily reverse (Jentch and Shucksmith, 2004). In this context, the return of former outmigrants, whether working or retired, often brings greater benefits in terms of skills, experience, investment and support of local services (Dustmann et al., 2011). A remembered idyll is known to influence return (Ní Laoire, 2007;Farrell et al., 2012;Haartsen and Thissen, 2014;Cawley and Galvin, 2016;Morse, 2017). However, the idyll's presence in the memories of places of origin among economic out-migrants and its role in attracting them back has received much less attention than its influence in attracting new in-migrants to the countryside, as part of counterurbanisation processes, and deserves further attention (Haartsen and Thissen, 2014;Morse and Mudgett, 2017). This paper aims to contribute to understandings of the idyll as an influence on migrant return using evidence for rural Ireland which has a long history of out-migration. It does so with reference to a sample of international migrants (emigrants) who left and returned to places with less than 1500 population ('aggregate rural areas' in the Irish census), usually the same place. The respondents were asked to reflect on their reasons for departure, their experiences of living in cities overseas, their motivations for returning and their experiences following return. References to what may be described as idyllic features of rural life emerged unprompted from many of the narratives which were interlinked with stage in the life-course. Tensions emerged also with daily reality on return, both for those who held an idyllic imaginary and for those who did not. Policy makers need to be more aware of the different expectations and experiences of different groups of returnees. Concepts The loss of young working age people through migration to larger places is well recognised in rural areas that are distant geographically and economically from the main centres of economic activity (Jentch and Shucksmith, 2004;Haartsen and Thissen, 2014). Access to higher education also often involves migration from a rural area of origin (Thissen et al., 2010). In the Irish case, labour migration to cities within the state and internationally is long-established (MacLaughlin, 1994). A pattern of path-dependency is often at work where out-migrants follow established flows using links with relatives and friends in overseas cities (Walter, 1980). There are many reasons for continued out-migration among rural working age people. Farm incomes and agricultural employment continue to decline because of increased mechanisation and competition from imports in an increasingly globalised economy (Ploeg, 2012). Non-agricultural employment is often limited and advanced communications infrastructure, which has