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35951488 | It's More Than Language: Cultural Adaptation of a Proven Dementia Care Intervention for Hispanic/Latino Caregivers. | Although Hispanic/Latino older adults are at disproportionate and increased risk for Alzheimer's disease and related dementias, few evidence-based supportive care interventions are specifically developed for or adapted for this population. Adapting a supportive care intervention requires more than Spanish language translation; it necessitates an understanding of cultural nuances and care preferences of Hispanic/Latino families and staff who implement the intervention. This article describes the cultural adaptation of the Adult Day Service Plus intervention for delivery by staff to Hispanic/Latino caregivers, which was guided by the cultural adaptation process model. Also, using the Framework for Reporting Adaptations and Modifications-Enhanced, we discuss (a) when modifications were made, (b) who determined the modifications needed, (c) what aspects of the intervention were modified, (d) the relationship to fidelity and how fidelity was maintained, and (e) reasons for modifications. Modifications to the delivery and content were changed to reflect the values and norms of both the Hispanic/Latino staff and the caregivers they serve. As supportive interventions for caregivers are developed and implemented into real-world settings, inclusion of cultural elements may enhance research participation among Hispanic/Latino provider sites, people living with dementia, and their caregivers. Cultural adaptation is an essential consideration when developing, adapting, and implementing previously tested evidence-based interventions. Cultural adaptation offers an important lens by which to identify contextual factors that influence successful adoption to assure equity in the reach of evidence-based programs. |
35951482 | Developmental and epileptic encephalopathies: from genetic heterogeneity to phenotypic continuum. | Developmental and epileptic encephalopathies (DEEs) are a heterogeneous group of disorders characterized by early-onset, often severe epileptic seizures and EEG abnormalities on a background of developmental impairment that tends to worsen as a consequence of epilepsy. DEEs may result from both nongenetic and genetic etiologies. Genetic DEEs have been associated with mutations in many genes involved in different functions including cell migration, proliferation, and organization, neuronal excitability, and synapse transmission and plasticity. Functional studies performed in different animal models and clinical trials on patients have contributed to elucidate pathophysiological mechanisms underlying many DEEs and have explored the efficacy of different treatments. Here, we provide an extensive review of the phenotypic spectrum included in the DEEs and of the genetic determinants and pathophysiological mechanisms underlying these conditions. We also provide a brief overview of the most effective treatment now available and of the emerging therapeutic approaches. |
35951487 | Epidemiologic and Clinical Characteristics of Monkeypox Cases - United States, May 17-July 22, 2022. | Monkeypox, a zoonotic infection caused by an orthopoxvirus, is endemic in parts of Africa. On August 4, 2022, the U.S. Department of Health and Human Services declared the U.S. monkeypox outbreak, which began on May 17, to be a public health emergency (1,2). After detection of the first U.S. monkeypox case), CDC and health departments implemented enhanced monkeypox case detection and reporting. Among 2,891 cases reported in the United States through July 22 by 43 states, Puerto Rico, and the District of Columbia (DC), CDC received case report forms for 1,195 (41%) cases by July 27. Among these, 99% of cases were among men; among men with available information, 94% reported male-to-male sexual or close intimate contact during the 3 weeks before symptom onset. Among the 88% of cases with available data, 41% were among non-Hispanic White (White) persons, 28% among Hispanic or Latino (Hispanic) persons, and 26% among non-Hispanic Black or African American (Black) persons. Forty-two percent of persons with monkeypox with available data did not report the typical prodrome as their first symptom, and 46% reported one or more genital lesions during their illness; 41% had HIV infection. Data suggest that munity transmission of monkeypox has disproportionately affected gay, bisexual, and other men who have sex with men and racial and ethnic minority groups. Compared with historical reports of monkeypox in areas with endemic disease, currently reported outbreak-associated cases are less likely to have a prodrome and more likely to have genital involvement. CDC and other federal, state, and local agencies have implemented response efforts to expand testing, treatment, and vaccination. Public health efforts should prioritize gay, bisexual, and other men who have sex with men, who are currently disproportionately affected, for prevention and testing, while addressing equity, minimizing stigma, and maintaining vigilance for transmission in other populations. Clinicians should test patients with rash consistent with monkeypox, |
35951495 | Interim Guidance for Prevention and Treatment of Monkeypox in Persons with HIV Infection - United States, August 2022. | Monkeypox virus, an orthopoxvirus sharing clinical features with smallpox virus, is endemic in several countries in Central and West Africa. The last reported outbreak in the United States, in 2003, was linked to contact with infected prairie dogs that had been housed or transported with African rodents imported from Ghana (1). Since May 2022, the World Health Organization (WHO) has reported a multinational outbreak of monkeypox centered in Europe and North America, with approximately 25,000 cases reported worldwide; the current outbreak is disproportionately affecting gay, bisexual, and other men who have sex with men (MSM) (2). Monkeypox was declared a public health emergency in the United States on August 4, 2022. |
35951496 | Preoperative BRAF | The BRAF |
35951497 | Risk factors for mortality among hospitalized COVID-19 patients in Northern Ethiopia: A retrospective analysis. | COVID-19 is a deadly pandemic caused by an RNA virus that belongs to the family of CORONA virus. To counter the COVID-19 pandemic in resource limited settings, it is essential to identify the risk factors of COVID-19 mortality. This study was conducted to identify the social and clinical determinants of mortality in COVID-19 patients hospitalized in four treatment centers of Tigray, Northern Ethiopia. |
35951498 | Sympatric otariids increase trophic segregation in response to warming ocean conditions in Peruvian Humboldt Current System. | Determining trophic habits of munities is essential to measure interspecific interactions and response to environmental fluctuations. South American fur seals, Arctocephalus australis (SAFS) and sea lions Otaria byronia (SASL), coexist along the coasts of Peru. Recently, ocean warming events (2014-2017) that can decrease and impoverish prey biomass have occurred in the Peruvian Humboldt Current System. In this context, our aim was to assess the effect of warming events on long-term inter- and intra-specific niche segregation. We collected whisker from SAFS (55 females and 21 males) and SASL (14 females and 22 males) in Punta San Juan, Peru. We used δ13C and δ15N values serially archived in otariid whiskers to construct a monthly time series for 2005-2019. From the same period we used sea level anomaly records to determine shifts in the predominant oceanographic conditions using a change point analysis. Ellipse areas (SIBER) estimated niche width of species-sex groups and their overlap. We detected a shift in the environmental conditions marking two distinct periods (P1: January 2005-October 2013; P2: November 2013-December 2019). Reduction in δ15N in all groups during P2 suggests impoverished baseline values with bottom-up effects, a shift towards consuming lower trophic level prey, or both. Reduced overlap between all groups in P2 lends support of a more redundant assemblage during the colder P1 to a more trophically segregated assemblage during warmer P2. SASL females show the largest variation in response to the warming scenario (P2), reducing both ellipse area and δ15N mean values. Plasticity to adapt to changing environments and feeding on a more available food source without fishing pressure can be more advantageous for female SASL, albeit temporary trophic bottom-up effects. This helps explain larger population size of SASL in Peru, in contrast to the smaller and declining SAFS population. |
35951499 | Behavioral avoidance of contagious and non-contagious adults. | Evolutionary theories of disease avoidance propose that humans have a set of universal psychological processes to detect environmental cues indicative of infectious disease. These processes then initiate cognitive, emotional, and behavioral responses that function to limit contact with harmful pathogens. Here, we study the conditions under which people exhibit behavioral avoidance of others with a contagious illness or a physical injury (i.e., a broken leg), and the potential mechanisms that underlie this behavior. Across three studies, participants were given the option of sitting at one of two workstations previously occupied by two confederates, one of whom either showed visible symptoms of a cold (contagion condition), wore a lower-leg orthopedic boot and used crutches (broken leg condition), or showed no signs of illness or physical injury (control). We found strong evidence that adults explicitly avoid contact with individuals who show symptoms of a contagious illness. Further, we provide some evidence that adults also avoid individuals with a physical injury, but that this behavior might be driven by implicit, unconscious processes. The findings are discussed in terms of implications for the healthy avoidance of contagion, and the risk for potential stigmatization of non-contagious groups. |
35951500 | Accessing the stapedius muscle via novel surgical retrofacial approach during cochlear implantation surgery: Intraoperative results on feasibility and safety. | Human stapedius muscle (SM) can be directly and safely accessed via retrofacial approach, opening new approaches to directly measure the electrically evoked stapedius reflex threshold (eSRT). The measurement of the SM activity via direct surgical access represents a potential tool for objective eSRT fitting of cochlear implants (CI), increasing the benefit experienced by the CI users and leading to new perspectives in the development of smart implantable neurostimulators. 3D middle-ear reconstructions created after manual segmentation and related SM accessibility metrics were evaluated before the CI surgery for 16 candidates with assessed stapedius reflex. Retrofacial approach to access the SM was performed after facial recess exposure. In cases of poor exposition of SM, the access was performed anteriorly to the FN via drilling of the pyramidal eminence (PE). The total access rate of the SM via both the retrofacial and anterior approach of the FN was 100%. In 81.2% of cases (13/16), the retrofacial approach allowed to access the SM on previously categorized well exposed (8/8), partially exposed (4/5), and wholly concealed (1/3) SM with respect to FN. Following intraoperative evaluation in the remaining 18.8% (3/16), the SM was accessed anteriorly via drilling of the PE. Exposure of SM with respect to the FN and the sigmoid sinus's prominence was a predictor for the suitable surgical approach. The retrofacial approach offers feasible and reproducible access to the SM belly, opening direct access to electromyographic sensing of the eSRT. Surgical planner tools can quantitatively assist pre-surgical assessment. |
35951501 | Effect of right hemispheric damage on structured spoken conversation. | Patients with right hemisphere damage (RHD) plain of difficulties in conversation. A conversation is a type munication between the speaker and listener, and several elements are required for a conversation to take place. However, it is unclear which of those elements munication in patients with RHD. Therefore, we prospectively enrolled 11 patients with right hemispheric damage due to acute cerebral infarction, within 1 week of onset. To evaluate patients' conversational abilities, we used a structured conversation task, namely, the "Hallym Conversation and Pragmatics Protocol". The topics of conversation were "family", "leisure", and "other/friends". The conversation characteristics were classified according to three indices: the "conversational participation index", "topic manipulation index", and "conversational breakdown index". Patients with RHD pared with 11 age-, sex-, and years of education-matched healthy adults. The mon site of damage in the patients with RHD was the periventricular white matter. There was no significant difference in performance between the two groups according to the conversation participation index and in the discontinuance rate assessed with the conversational breakdown index. However, patients with RHD showed a lower topic maintenance rate and higher topic initiation and topic switching rates, according to the topic manipulation index. Therefore, we explored the characteristics of impaired conversation abilities in patients with RHD by assessing their ability to converse and manage topics during structured conversations, and found difficulties with pragmatics munication discourse in these patients. |
35951502 | Obesity and outcomes in patients undergoing upper airway surgery for obstructive sleep apnea. | Obesity is frequently debated as a factor associated with increased plications. Specifically, upper airway surgeries for obstructive sleep apnea (OSA), orbidity among obese patients, may plicated by obesity's impact on intraoperative ventilation. The aim of this retrospective study was to analyze the association of various degrees of obesity with postoperative es in patients undergoing surgery for OSA. |
35951503 | Understanding patient preferences in anti-VEGF treatment options for age-related macular degeneration. | (1) To investigate the relative importance of convenience (consultation frequency and injection frequency) against treatment es (visual and anatomical es) and out-of-pocket medical costs via a discrete choice experiment (DCE), and (2) to investigate how patient characteristics affect patient treatment preferences. |
35951504 | Clinical and growth outcomes after meconium-related ileus improved with Gastrografin enema in very low birth weight infants. | Meconium-related ileus in very low birth weight infants can lead to increased morbidity or mortality and prolonged hospitalization without prompt diagnosis and treatment. This study primarily aimed to identify the incidence of and factors associated with meconium-related ileus and secondarily sought to investigate clinical and growth es after water-soluble contrast media (Gastrografin) enema. |
35951506 | Assessing the progress on the implementation of policy and legislation actions to address the Non-Communicable Diseases crisis in the Pacific. | To assess the progress on the implementation of Non-Communicable Diseases (NCD) related policies and legislations in the Pacific Island Countries and Territories (PICTs). |
35951505 | Nine quick tips for pathway enrichment analysis. | Pathway enrichment analysis (PEA) is putational biology method that identifies biological functions that are overrepresented in a group of genes more than would be expected by chance and ranks these functions by relevance. The relative abundance of genes pertinent to specific pathways is measured through statistical methods, and associated functional pathways are retrieved from online bioinformatics databases. In the last decade, along with the spread of the internet, higher availability putational resources made PEA software tools easy to access and to use for bioinformatics practitioners worldwide. Although it became easier to use these tools, it also became easier to make mistakes that could generate inflated or misleading results, especially for beginners and putational biologists. With this article, we propose nine quick tips to mon mistakes and to out plete, sound, thorough PEA, which can produce relevant and robust results. We describe our nine guidelines in a simple way, so that they can be understood and used by anyone, including students and beginners. Some tips explain what to do before starting a PEA, others are suggestions of how to correctly generate meaningful results, and some final guidelines indicate some useful steps to properly interpret PEA results. Our nine tips can help users perform better pathway enrichment analyses and eventually contribute to a better understanding of current biology. |
35951507 | Preparation of acute midbrain slices containing the superior colliculus and periaqueductal Gray for patch-clamp recordings. | This protocol is a practical guide for preparing acute coronal slices from the midbrain of young adult mice for electrophysiology experiments. It describes two different sets of solutions with their respective incubation strategies and two alternative procedures for brain extraction: decapitation under terminal isoflurane anaesthesia and intracardial perfusion with artificial cerebrospinal fluid under terminal isoflurane anaesthesia. Slices can be prepared from wild-type mice as well as from mice that have been genetically modified or transfected with viral constructs to label subsets of cells. The preparation can be used to investigate the electrophysiological properties of midbrain neurons bination with pharmacology, opto- and chemogenetic manipulations, and calcium imaging; which can be followed by morphological reconstruction, immunohistochemistry, or single-cell transcriptomics. The protocol also provides a detailed list of materials and reagents including the design for a low-cost and easy to assemble 3D printed slice recovery chamber, general advice for mon issues leading to suboptimal slice quality, and some suggestions to ensure good maintenance of a patch-clamp rig. |
35951508 | A deep tensor-based approach for automatic depression recognition from speech utterances. | Depression is one of the significant mental health issues affecting all age groups globally. While it has been widely recognized to be one of the major disease burdens in plexities in definitive diagnosis present a major challenge. Usually, trained psychologists utilize conventional methods including individualized interview assessment and manually administered PHQ-8 scoring. However, heterogeneity in symptomatic presentations, which span somatic to plaints, impart substantial subjectivity in its diagnosis. Diagnostic accuracy is pounded by the cross-sectional nature of sporadic assessment methods during physician-office visits, especially since depressive symptoms/severity may evolve over time. With widespread acceptance of smart wearable devices and smartphones, passive monitoring of depression traits using behavioral signals such as speech presents a unique opportunity panion diagnostics to assist the trained clinicians in objective assessment over time. Therefore, we propose a framework for automated depression classification leveraging alterations in speech patterns in the well documented and extensively studied DAIC-WOZ depression dataset. This novel tensor-based approach requires a substantially simpler implementation architecture and extracts discriminative features for depression recognition with high f1 score and accuracy. We posit that such algorithms, which use significantly pute load would allow effective onboard deployment in wearables for improve diagnostics accuracy and real-time monitoring of depressive disorders. |
35951510 | Network diffusion model predicts neurodegeneration in limb-onset Amyotrophic Lateral Sclerosis. | Emerging evidences suggest that the trans-neural propagation of phosphorylated 43-kDa transactive response DNA-binding protein (pTDP-43) contributes to neurodegeneration in Amyotrophic Lateral Sclerosis (ALS). We investigated whether Network Diffusion Model (NDM), a biophysical model of spread of pathology via the brain connectome, could capture the severity and progression of neurodegeneration (atrophy) in ALS. |
35951511 | SARS-CoV-2 reliably detected in frozen saliva samples stored up to one year. | Viability of saliva samples stored for longer than 28 days has not been reported in the literature. The COVID-19 pandemic has spawned new research evaluating various sample types, thus large biobanks have been started. Residual saliva samples from university student surveillance testing were retested on SalivaDirect pared with original RT-PCR (cycle threshold values) and quantitative antigen values for each month in storage. We conclude that saliva samples stored at -80°C are still viable in detecting SARS-CoV-2 after 12 months of storage, establishing the validity of these samples for future testing. |
35951513 | Lipids and atrial fibrillation: New insights into a paradox. | In this Perspective, Dimitrios Sagris, Stephanie Harrison, and Gregory Lip discuss new evidence concerning the paradoxical relationship between circulating lipids and atrial fibrillation. |
35951512 | Resistance to obesity prevents obesity development without increasing spontaneous physical activity and not directly related to greater metabolic and oxidative capacity. | There are evidence that obese-resistant animals are more physically active, due to a higher rate of lipid oxidation. Efficiency in such pathways can favor greater spontaneous physical activity and, consequently, less body fat deposition. The aim of study was characterizing the nutritional profile and spontaneous physical activity in the condition of Resistance to Obesity (OR). Wistar rats were randomized into standard diet (SD; n = 50) and high-fat diet (HFD; n = 50) groups, after obesity induction, were redistributed into Control (C), False-control (FC), Propensity to obesity (OP) and OR, and then spontaneous physical activity was evaluated. Analyzed parameters: body mass (BM), epididymal (EF), retroperitoneal (RF), visceral (VF) and respective summations (∑), adiposity index (AI), nutritional, morphological, biochemical and metabolic parameters and protein quantification. parison of the groups was performed by ANOVA one or two factors, with 5% significance adopted. OP and FC presented high final MC pared to C and OR. OR had lower EF, RF, VF, ∑ and pared to OP. OR had similar values to C and higher HDL than FC and OP. In GTT, OR and C presented similar values and both were lower than OP in the 30 minutes. OP promoted higher values than C for glycemic AUC. OR had higher PPARγ content than C and OP, as well as levels similar to C for leptin and insulin. Spontaneous physical activity did not differ between groups. The results were not enough to show that OR animals have greater lipid oxidative capacity, as well as greater spontaneous physical activity. |
35951515 | In the eye of the beholder: Decision-making of lawyers in cases of sexual harassment. | The purpose of the present study was to examine the effect of deliberative vs. intuitive thinking styles on forensic judgments of legal professionals. Two hypotheses were tested: (a) that low deliberative thinking would be related to judgmental biases (b) that lawyers would report a greater tendency and preference toward deliberative thinking parison to students and make more rational judgments. |
35951514 | Lipid levels in midlife and risk of atrial fibrillation over 3 decades-Experience from the Swedish AMORIS cohort: A cohort study. | The role of cholesterol levels in the development of atrial fibrillation (AF) is still controversial. In addition, whether and to what extent apolipoproteins are associated with the risk of AF is rarely studied. In this study, we aimed to investigate the association between blood lipid levels in midlife and subsequent risk of new-onset AF. |
35951516 | Relationship between the cross-sectional area of the lumbar dural sac and lower urinary tract symptoms: A population-based cross-sectional study. | This study aimed to investigate the relationship between the cross-sectional area of the dural sac (DCSA) and lower urinary tract symptoms (LUTS). This study included 270 Japanese participants from munity health check-up in 2016. Overactive bladder (OAB) was diagnosed during the assessment of LUTS. The smallest DCSA of each participant was defined as the minimum DCSA (mDCSA). The cutoff size of the mDCSA in OAB was evaluated using receiver operating characteristic analysis. Multiple logistic regression analyses were performed to identify the independent risk factors for OAB, and a scoring system was developed for estimating these. The prevalence of OAB was 11.1%. Age and low back pain visual analogue scale (LBP VAS) scores were significantly higher, and the mean mDCSA was significantly lower in participants with OAB than in those without. The cutoff size of mDCSA in OAB was 69 mm2. There were significant correlations between OAB and age, LBP VAS score, and mDCSA<70 mm2. Lumbar spinal stenosis (LSS) should be considered a cause of LUTS when mDCSA is <69 mm2. Assessing the mDCSA with age and LBP VAS score was more valuable in detecting LUTS in LSS than the mDCSA alone. |
35951518 | Large socioeconomic gap in period life expectancy and life years spent with complications of diabetes in the Scottish population with type 1 diabetes, 2013-2018. | We report the first study to estimate the socioeconomic gap in period life expectancy (LE) and life years spent with and plications in a national cohort of individuals with type 1 diabetes. |
35951517 | Influenza vaccination of school teachers: A scoping review and an impact estimation. | Influenza vaccination, besides protecting traditional risk groups, can protect employees and reduce illness-related absence, which is especially relevant in sectors with staff shortages. This study describes current knowledge of influenza vaccination in teachers and estimates its potential impact. |
35951522 | Single-cell measurement quality in bits. | Single-cell measurements have revolutionized our understanding of heterogeneity in cellular response. However, there is no parable way to assess single-cell measurement quality. Here, we show how information theory can be used to assess pare single-cell measurement quality in bits, which provides a parable metric for information content. We anticipate that the experimental and theoretical approaches we show here will generally parisons of quality between any single-cell measurement methods. |
35951521 | Value of 3D printing technology combined with indocyanine green fluorescent navigation in complex laparoscopic hepatectomy. | Laparoscopic hepatectomy (LH) has achieved rapid progress over the last decade. However, it is still challenging to apply laparoscopy to lesions located in segments I, VII, VIII, and IVa and the hepatic hilar region due to difficulty operating plex anatomical structures. In this study, we applied three-dimensional printing (3DP) and indocyanine green (ICG) fluorescence imaging technology plex laparoscopic hepatectomy (CLH) to explore the effects and value of the modified procedure. |
35951520 | Association between serum uric acid levels and colonic diverticulosis in terms of sex. | The association between elevated serum uric acid (UA) levels and the risk of developing colonic diverticulosis has not yet been investigated. Thus, this cross-sectional study aimed to examine this correlation in individuals from Taiwan. |
35951525 | Low-dose abdominopelvic computed tomography in patients with lymphoma: An image quality and radiation dose reduction study. | This study aimed to evaluate image quality, the detection rate of enlarged lymph nodes, and radiation dose exposure of ultralow-dose and low-dose puted tomography (CT) in patients with lymphoma. Patients with lymphoma who underwent abdominopelvic CT using dual-source scanner were retrospectively recruited from a single center. CT images were obtained at 90 kVp dual-source mode reformatted in three data sets using the advanced modelled iterative reconstruction algorithm: 100% (standard-dose CT), 66.7% (low-dose CT), and 33.3% (ultralow-dose CT). Two radiologists analyzed subjective image quality and detection of abdominal enlarged lymph nodes on ultralow-dose, low-dose, and standard-dose CT blindly and independently. The results pared with reference standards. Three readers (two radiologists and one hematologist) reviewed overall image quality and spleen size. In total, 128 consecutive CT scans plete response, 44 partial response, 6 progressive disease, and 1 initial evaluation) from 86 patients (64 B-cell lymphoma, 14 T/NK-cell lymphoma, and 8 Hodgkin's lymphoma cases) were assessed. The enlarged lymph node-based detection rates for two readers were 97.0% (96/99) and 94.0% (93/99) on standard-dose CT, 97.0% (96/99) and 94.0% (93/99) on low-dose CT, and 94.0% (93/99) and 89.9% (89/99) on ultralow-dose CT. Overall image quality was 3.8 ± 0.5, 3.9 ± 0.5, and 4.1 ± 0.5 on ultralow-dose CT; 4.7 ± 0.4, 4.6 ± 0.5, and 4.8 ± 0.3 on low-dose CT; and 4.8 ± 0.4, 4.7 ± 0.4, and 4.9 ± 0.2 on standard-dose CT, according to two radiologists and one hematologist, respectively. Intraclass correlation coefficients of spleen size were 0.90 (95% confidence interval [CI], 0.87-0.93), 0.91 (95% CI, 0.88-0.93), and 0.91 (95% CI, 0.88-0.93) on ultralow-dose, low-dose, and standard-dose CT, respectively. Mean effective radiation doses of standard-dose, low-dose, and ultralow-dose CT were 5.7 ±1.8 mSv, 3.8 ± 1.2 mSv, and 1.9 ± 0.6 mSv, respectively. Our findings suggest that ultralow-dose and low-dose CT, even with radiation doses reduced by 66.7% and 33.3%, respectively, maintained adequate image quality. These imaging modalities may be employed for follow-up lymphoma evaluation in consideration of the long surveillance periods. |
35951523 | Host genotype controls ecological change in the leaf fungal microbiome. | Leaf fungal microbiomes can be fundamental drivers of host plant success, as they contain pathogens that devastate crop plants and taxa that enhance nutrient uptake, discourage herbivory, and antagonize pathogens. We measured leaf fungal diversity with amplicon sequencing across an entire growing season in a diversity panel of switchgrass (Panicum virgatum). We also sampled a replicated subset of genotypes across 3 additional sites pare the importance of time, space, ecology, and genetics. We found a strong successional pattern in the microbiome shaped both by host genetics and environmental factors. Further, we used genome-wide association (GWA) mapping and RNA sequencing to show that 3 cysteine-rich receptor-like kinases (crRLKs) were linked to a genetic locus associated with microbiome structure. We confirmed GWAS results in an independent set of genotypes for both the internal transcribed spacer (ITS) and large subunit (LSU) ribosomal DNA markers. Fungal pathogens were central to microbial covariance networks, and genotypes susceptible to pathogens differed in their expression of the 3 crRLKs, suggesting that host immune genes are a principal means of controlling the entire leaf microbiome. |
35951527 | Predicting curve progression for adolescent idiopathic scoliosis using random forest model. | Adolescent Idiopathic Scoliosis (AIS) is a three-dimensional (3D) spinal deformity characterized by coronal curvature and rotational deformity. Predicting curve progression is important for the selection and timing of treatment. Although there is a consensus in the literature regarding prognostic factors associated with curve progression, the order of importance, as well as bination of factors that are most predictive of curve progression is unknown. |
35951528 | Spatiotemporal spread of Plasmodium falciparum mutations for resistance to sulfadoxine-pyrimethamine across Africa, 1990-2020. | Sulfadoxine-pyrimethamine (SP) is mended in Africa in several antimalarial preventive regimens including Intermittent Preventive Treatment in pregnant women (IPTp), Intermittent Preventive Treatment in infants (IPTi) and Seasonal Malaria Chemoprevention (SMC). The effectiveness of SP-based preventive treatments are threatened in areas where Plasmodium falciparum resistance to SP is high. The prevalence of mutations in the dihydropteroate synthase gene (pfdhps) can be used to monitor SP effectiveness. IPTi-SP is mended only in areas where the prevalence of the pfdhps540E mutation is below 50%. It has also been suggested that IPTp-SP does not have a protective effect in areas where the pfdhps581G mutation, exceeds 10%. However, pfdhps mutation prevalence data in Africa are extremely heterogenous and scattered, with pletely missing from many areas. |
35951524 | Genetic architecture and temporal analysis of Caenorhabditis briggsae hybrid developmental delay. | Identifying the alleles that reduce hybrid fitness is a major goal in the study of speciation genetics. It is rare to identify systems in which hybrid patibilities with minor phenotypic effects are segregating in genetically diverse populations of the same biological species. Such traits do not themselves cause reproductive isolation but might initiate the process. In the nematode Caenorhabditis briggsae, a small percent of F2 generation hybrids between two natural populations suffer from developmental delay, in which adulthood is reached after approximately 33% more time than their wild-type siblings. Prior efforts to identify the genetic basis for this hybrid patibility assessed linkage using one or two genetic markers on chromosome III and suggested that delay is caused by a toxin-antidote element. Here, we have genotyped F2 hybrids using multiple chromosome III markers to refine the developmental delay locus. Also, to better define the developmental delay phenotype, we measured the development rate of 66 F2 hybrids and found that delay is not restricted to a particular larval developmental stage. Deviation of the developmental delay frequency from hypothetical expectations for a toxin-antidote element adds support to the assertion that the epistatic interaction is not fully penetrant. Our mapping and refinement of the delay phenotype motivates future efforts to study the genetic architecture of hybrid dysfunction between genetically distinct populations of one species by identifying the underlying loci. |
35951531 | The Use of Mean Gray Value (MGV) as a Guide to Tension-Reducing Strategies in Body Contouring Surgery Reduces Wound-Related Morbidity. | Currently there are no known structural parameters of the integument that can be measured noninvasively which are used in the planning of body contouring surgery. |
35951530 | Viral-mediated activation and inhibition of programmed cell death. | Viruses are ubiquitous intracellular genetic parasites that heavily rely on the infected cell plete their replication life cycle. This dependency on the host machinery forces viruses to modulate a variety of cellular processes including cell survival and cell death. Viruses are known to activate and block almost all types of programmed cell death (PCD) known so far. Modulating PCD in infected hosts has a variety of direct and indirect effects on viral pathogenesis and antiviral immunity. The mechanisms leading to apoptosis following virus infection is widely studied, but several modalities of PCD, including necroptosis, pyroptosis, ferroptosis, and paraptosis, are relatively understudied. In this review, we cover the mechanisms by which viruses activate and inhibit PCDs and suggest perspectives on how these affect viral pathogenesis and immunity. |
35951533 | Molecular architecture of bacterial type IV secretion systems. | Bacterial type IV secretion systems (T4SSs) are a versatile group of nanomachines that can horizontally transfer DNA through conjugation and deliver effector proteins into a wide range of target cells. ponents of T4SSs in gram-negative bacteria are organized into several large subassemblies: an inner plex, an outer membrane plex, and, in some species, an extracellular pilus. Cryo-electron tomography has been used to define the structures of T4SSs in intact bacteria, and high-resolution structural models are now available for isolated plexes from conjugation systems, the Xanthomonas citri T4SS, the Helicobacter pylori Cag T4SS, and the Legionella pneumophila Dot/Icm T4SS. In this review, pare the molecular architectures of these T4SSs, focusing especially on the structures of plexes. We discuss structural features that are shared by multiple T4SSs as well as evolutionary strategies used for T4SS diversification. Finally, we discuss how structural variations among T4SSs may confer specialized functional properties. |
35951534 | A systematic review: Solutions to problems caused by age transition between eating disorder services. | This systematic review examines age transition issues specific to young people with eating disorders, including the extent of, and reasons for, problematic transition. Suggested solutions are examined, with focus on age-integrated services. |
35951535 | Glial fibrillary acidic protein in cerebrospinal fluid of patients with spinal muscular atrophy. | Activated astroglia is involved in the pathophysiology of neurodegenerative diseases and has also been described in animal models of spinal muscular atrophy (SMA). Given the urgent need of biomarkers for treatment monitoring of new RNA-modifying and gene replacement therapies in SMA, we examined glial fibrillary acidic protein concentrations in cerebrospinal fluid (cGFAP) as a marker of astrogliosis in SMA. |
35951536 | Reductive Cross-Coupling of Unreactive Electrophiles. | Transition-metal-catalyzed reductive coupling of electrophiles has emerged as a powerful tool for the construction of molecules. While major achievements have been made in the field of cross-couplings between organic halides and pseudohalides, an increasing number of reports demonstrates reactions involving more readily available, low-cost, and stable, but unreactive electrophiles. This account summarizes the recent results in our laboratory focusing on this topic. These findings typically include deoxygenative C-C coupling of alcohols, reductive alkylation of alkenyl acetates, reductive C-Si coupling of chlorosilanes, and reductive C-Ge coupling of chlorogermanes.The reductive deoxygenative coupling of alcohols with electrophiles is synthetically appealing, but the potential of this chemistry remains to be disclosed. Our initial study focused on the reaction of allylic alcohols and aryl bromides by bination of nickel and Lewis acid catalysis. This method offers a selectivity that is opposite to that of the classic Tsuji-Trost reactions. Further investigation on the reaction of benzylic alcohols led to the foundation of a dynamic kinetic cross-coupling strategy with applications in the nickel-catalyzed reductive arylation of benzylic alcohols and cobalt-catalyzed enantiospecific reductive alkenylation of allylic alcohols. The titanium catalysis was later established to produce carbon radicals directly from unactivated tertiary alcohols via C-OH cleavage. The development of their coupling reactions with carbon fragments delivers new methods for the construction of all-carbon quaternary centers. These reactions have shown high selectivity for the functionalization of tertiary alcohols, leaving primary and secondary alcohols intact. Alkenyl acetates are inexpensive, stable, and environmentally friendly and are considered the most attractive alkenyl reagents. The development of reductive alkylation of alkenyl acetates with benzyl ammoniums and alkyl bromides offers mild approaches for the conversion of ketones into aliphatic alkenes.Extensive studies in this field have enabled us to extend the cross-electrophile coupling from carbon to silicon and germanium chemistry. These reactions harness the ready availability of chlorosilanes and chlorogermanes but suffer from the challenge of their low reactivity toward transition metals. Under reductive nickel catalysis, a broad range of alkenyl and aryl electrophiles couple well with vinyl- and hydrochlorosilanes. The use of alkyl halides as coupling partners led to the formation of functionalized alkylsilanes. The C-Ge coupling seems less substrate-dependent, and mon chlorogermanes couple well with aryl, alkenyl, and alkyl electrophiles. In general, functionalities such as Grignard-sensitive groups (e.g., acid, amide, alcohol, ketone, and ester), acid-sensitive groups (e.g., ketal and THP protection), alkyl fluoride and chloride, aryl bromide, alkyl tosylate and mesylate, silyl ether, and amine are tolerated. These methods provide new access to organosilicon and pounds, some of which are challenging to obtain otherwise. |
35951538 | Restorative solutions for anti-LGBT victimisation experiences: potential pathways for victims' wellbeing and key challenges and needs. | The victims of anti-LGBT hate crimes may have particularly negative experiences which affect their mental health and wellbeing. These incidents affect the victims' self-esteem, dignity and identity, and they also affect indirect victims in similar ways. As opposed to retributive justice, restorative justice may offer a more satisfactory justice experience for those affected, by addressing the harm caused to them. This is due to the fact that restorative processes require flexibility, adequacy and tailor-made design. Drawing on findings from a multi-site qualitative study conducted in six European countries, this article discusses the perceptions and experiences of key professionals regarding the potential of restorative justice to provide for victims of anti-LGBT hate crimes, particularly in relation to repairing the individual and collective harm caused by such crimes. |
35951539 | Does the journal impact factor predict individual article citation rate in otolaryngology journals? | Citation skew is a phenomenon that refers to the unequal citation distribution of articles in a journal. The objective of this study was to establish whether citation skew exists in Otolaryngology-Head and Neck Surgery (OHNS) journals and to elucidate whether journal impact factor (JIF) was an accurate indicator of citation rate of individual articles. |
35951541 | Electrosynthesis of 2-Substituted Benzoxazoles via Intramolecular Shono-Type Oxidative Coupling of Glycine Derivatives. | Herein, an atom-economical and eco-friendly electrochemical oxidation/cyclization of glycine derivatives through intramolecular Shono-type oxidative coupling is disclosed, leading to a variety of 2-substituted benzoxazoles in 51-85% yields. This oxidative cyclization proceeded in transition metal- and oxidant-free conditions and generated H |
35951540 | Phospholipid Monolayer/Graphene Interfaces: Curvature Effect on Lipid Morphology and Dynamics. | Phospholipids are an important class of lipids that are widely used as model platforms for the study of biological processes and interactions. These lipids can form stable interfaces with solid substrates, such as graphene, and these interfaces have potential applications in biosensing and targeted drug delivery. In this paper, we perform molecular dynamics simulations of graphene-supported lipid monolayers to characterize the lipid properties of such interfaces. We observed substantial differences between the supported monolayer and free-standing bilayer in terms of the lipid properties, such as the tail order parameters, density profiles, diffusion rates, and so on. Furthermore, we studied these interfaces on sinusoidally deformed graphene substrates to understand the effect of curvature on the supported lipids. Here, we observed that the nature of the substrate curvature, that is, concave or convex, can locally affect the lipid/substrate adhesion strength and induce structural and dynamic changes in the adsorbed lipid monolayer. Together, these results help characterize the properties of lipid/graphene interfaces and provide insights into the substrate curvature effect on these interfaces, which can enable the tuning of lipid properties for various sensor devices and drug delivery applications. |
35951542 | Palladium-Catalyzed Decarbonylative Cyanation of Carboxylic Acids with TMSCN. | The direct decarbonylative cyanation of benzoic acids with TMSCN was achieved through palladium catalysis. By this strategy, a wide range of nitriles including those with functional groups was synthesized in good to high yields. Moreover, this reaction applied to modifying bioactive molecules such as adapalene, probenecid, telmisartan, and 3-methylflavone-8-carboxylic acid. These results demonstrate that this new reaction has potential synthetic value in organic synthesis. |
35951543 | Thermal Electron Attachment to Pyruvic Acid, Thermal Detachment from the Parent Anion, and the Electron Affinity of Pyruvic Acid. | The kinetics of electron attachment to pyruvic acid (CH |
35951544 | Current clinical practice in managing somatosensory impairments and the use of technology in stroke rehabilitation. | Stroke-induced somatosensory impairments seem to be clinically overlooked, despite their prevalence and influence on motor recovery post-stroke. Interest in technology has been gaining traction over the past few decades as a promising method to facilitate stroke rehabilitation. This questionnaire-based cross-sectional study aimed to identify current clinical practice and perspectives on the management of somatosensory impairments post-stroke and the use of technology in assessing e measures and providing intervention. Participants were 132 physiotherapists and occupational therapists currently working with stroke patients in public hospitals and rehabilitation centres in Singapore. It was found that the majority (64.4%) of the therapists spent no more than half of the time per week on somatosensory interventions. Functional or task-specific training was the primary form of intervention applied to retrain somatosensory functions in stroke survivors. Standardised assessments (43.2%) were used less frequently than non-standardised assessments (97.7%) in clinical practice, with the sensory subscale of the Fugl-Meyer Assessment being the most popular e measure, followed by the Nottingham Sensory Assessment. While the adoption of technology for assessment was relatively scarce, most therapists (87.1%) reported that they have integrated technology into intervention. There was mon agreement that proprioception is an ponent in stroke rehabilitation, and that robotic bined with conventional therapy is effective in enhancing stroke rehabilitation, particularly for retraining proprioception. Most therapists identified price, technology usability, and lack of available space as some of the biggest barriers to integrating robotic technology in stroke rehabilitation. Standardised assessments and interventions targeting somatosensory functions should be more clearly delineated in clinical guidelines. Although therapists were positive about technology-based rehabilitation, obstacles that make technology integration challenging ought to be addressed. |
35951545 | Soft and Stretchable Liquid Metal-Elastomer Composite for Wearable Electronics. | Soft devices, especially capacitive stress (or strain) sensors, are important for applications, including wearable medical monitoring, electronic skin, and soft robotics. The incorporation of liquid metal particles (LMPs) into highly deformable elastomers as inclusions ameliorates the pliance caused by a rigid filler. The high dielectric constant and liquid feature of LMPs are suitable for soft sensors with high sensitivity and a large real-time dynamic detection range. Here, a class of posites are introduced with elastic and high dielectric properties, making them uniquely suitable for the application of soft stress sensors. The prepared stretchable soft stress sensor can detect the bending degree of the finger, monitor physiological signals in real time, and distinguish the vibration from the pronunciation of different letters. The nanoscale putational tomography (nano-CT) measurements indeed detect the changes of LMPs under stress, i.e., LMPs in the matrix distribute from uneven to relatively uniform, agglomerate, and even connect each other to have a conduction path in position with high LMP contents, which cause the changes in the physical properties of devices under operation. The cognition of LMP changes posites under stress is instructive for promoting their further applications in the field of soft devices. |
35951546 | MiR-495-3p regulates myoblasts proliferation and differentiation through targeting cadherin 2. | MircoRNAs (miRNAs) play an important role in skeletal muscle development. Previous study had found that miR-495-3p was differentially expressed in fetal and adult goat skeletal muscle, but its function in myogenic proliferation and differentiation are unclear. Herein, we found the expression of miR-495-3p in C2C12 was downregulated during proliferation stage and upregulated during differentiation stage. Functionally, overexpression of miR-495-3p in C2C12 inhibited proliferation, and promoted myogenic differentiation. Mechanistically, the luciferase reporter assay demonstrated that cadherin 2 ( |
35951547 | The Electronic Spectrum of Si | The optical spectrum of Si |
35951548 | Low temperatures lead to higher toxicity of the fungicide folpet to larval stages of Rana temporaria and Bufotes viridis. | Pesticides are one of the main drivers of the worldwide amphibian decline. Their actual toxicity depends on a number of factors, like the species in focus or the developmental stage of exposed individuals. As ectothermic species, the metabolism of amphibians is influenced by ambient temperature. Therefore, temperature also affects metabolic rates and thus processes that might enhance or reduce toxic effects. Studies about the interactive effect of temperature and toxicity on amphibians are rare and deliver contrasting results. To investigate the temperature-dependent pesticide sensitivity of larvae of two European species we conducted acute toxicity tests for the viticultural fungicide Folpan® 500 SC with the active ingredient folpet at different temperatures (6°C, 11°C, 16°C, 21°C, 26°C). Sensitivity of Rana temporaria and Bufotes viridis was highly affected by temperature: early larvae (Gosner stage 20) were about twice more sensitive to Folpan® 500 SC at pared to 21°C. Next to temperature, species and developmental stage of larvae had an effect on sensitivity. The most sensitive individuals (early stages of R. temporaria at 6°C) were 14.5 times more sensitive than the least sensitive ones (early stages of B. viridis at 26°C). Our results raise concerns about typical ecotoxicological studies with amphibians that are often conducted at temperatures between 15°C and 20°C. We suggest that future test designs should be performed at temperatures that reflect the temperature range amphibians are exposed to in their natural habitats. Variations in the sensitivity due to temperature should also be considered as an uncertainty factor in ing environmental risk assessments for amphibians. |
35951549 | Site- and Enantioselective Manganese-Catalyzed Benzylic C-H Azidation of Indolines. | A manganese-catalyzed highly site- and enantioselective benzylic C-H azidation of indolines has been described. The practical method is applicable for azidation of a tertiary benzylic C-H bond with good functional group tolerance, allowing facile access to structurally diverse tertiary azide-containing indolines in high efficiency with excellent site-, chemo-, and enantioselectivity. The generality of the method was further demonstrated by site- and enantioselective azidation of the secondary benzylic C-H bond for a range of secondary azide-containing indolines. The benzylic C-H azidation method allows to straightforwardly and enantioselectively install a variety of nitrogen-based functional groups and diverse bioactive molecules at the C |
35951550 | Dual Protection of a Li-Ag Alloy Anode for All-Solid-State Lithium Metal Batteries with the Argyrodite Li | All-solid-state lithium metal batteries (ASSLMBs) are considered promising candidates for next-generation energy storage systems. However, the growth of Li dendrites and interface side reactions hinder the practical application of ASSLMBs. To address these issues, a preformed Li-Ag alloy anode for an ASSLMB with the Li |
35951552 | Housing starts and the associated wood products carbon storage by county by Shared Socioeconomic Pathway in the United States. | Harvested wood products found in the built environment are an important carbon sink, helping to mitigate climate change, and their trends in use are determined by economic and demographic factors, which vary spatially. Spatially detailed projections of construction and stored carbon are needed for industry and public decision making, including for appreciating trends in values at risk from catastrophic disturbances. We specify econometric models of single-family and multifamily housing starts by U.S. Census Region, design a method for their spatial downscaling to the county level, and project their quantities and carbon content according to the five Shared Socioeconomic Pathways (SSPs). Starts are projected to decline across all scenarios and potentially drop to below housing replacement levels under SSP3 by mid-century. Wood products carbon stored nationally in structures in use and in landfills is projected to grow across all scenarios but with significant spatial heterogeneity related to disparate trends in construction across counties, ranging from strong growth in the urban counties of the coastal South and West to stagnation in rural counties of the Great Plains and the northern Rockies. The estimated average annual carbon stored in wood products used in and discarded from US residential housing units between 2015-2070 ranged from 51 million t CO2e in SSP3 to 85 million t CO2e in SSP5, representing 47% to 78% of total carbon uptake relative to uptake by all wood products in the United States in 2019. |
35951551 | Rapid Screening of Novel Dipeptidyl Peptidase-4 Inhibitory Peptides from Pea ( | Pea protein hydrolysates (PPHs) possess good hypoglycemic effects; however, their dipeptidyl peptidase-4 (DPP-4) inhibitory activity is poorly understood, and none of the DPP-4 inhibitory peptides have been identified from PPHs. This paper aims to rapidly screen these peptides from PPHs bining peptidomics and molecular docking. In this study, 543 peptides were identified by peptidomics, and four peptides (IPYWTY, IPYWT, LPNYN, and LAFPGSS) with DPP-4 half-maximal inhibitory concentration (IC |
35951553 | What matters most to patients with severe aortic stenosis when choosing treatment? Framing the conversation for shared decision making. | Guidelines mend including the patient's values and preferences when choosing treatment for severe aortic stenosis (sAS). However, little is known about what matters most to patients as they develop treatment preferences. Our objective was to identify, prioritize, and organize patient-reported goals and features of treatment for sAS. |
35951554 | Periodontal status and the incidence of selected bacterial pathogens in periodontal pockets and vascular walls in patients with atherosclerosis and abdominal aortic aneurysms. | The aim of the study was to examine the periodontal status of patients with atherosclerosis and abdominal aortic aneurysms. The occurrence of 5 periodontopathogens was evaluated in periodontal pockets and atheromatous plaques together with specimens from pathologically changed vascular walls of aortic aneurysms. The prised 39 patients who qualified for vascular surgeries. Patients with periodontitis and itant atherosclerosis or aneurysms were enrolled in the study. Periodontal indices were evaluated, and subgingival plaque samples were examined together with atheromatous plaques or specimens from vascular walls to identify, by polymerase chain reaction (PCR), the following periodontopathogens: Porphyromonas gingivalis, Tanarella forsythia, Aggregatibacter itans, Prevotella intermedia and Treponema denticola. The majority of patients had chronic severe generalized periodontitis in stages III and IV. Laboratory investigations showed the occurrence of one or more of the five targeted periodontopathogens in 94.6% of the periodontal pockets examined. Of the examined periodontopathogens, only Porphyromonas gingivalis was confirmed in 1 atheromatous plaque sample collected from the wall of an aortic aneurysm. Therefore, the occurrence of this bacterium in these vessels was considered to be occasional in patients with chronic periodontitis. |
35951556 | Kinetically Controlled Structural Transitions in Layered Halide-Based Perovskites: An Approach to Modulate Spin Splitting. | Two-dimensional hybrid organic-inorganic perovskite (HOIP) semiconductors with pronounced spin splitting, mediated by strong spin-orbit coupling and inversion symmetry breaking, offer the potential for spin manipulation in future spintronic applications. However, HOIPs exhibiting significant conduction/valence band splitting are still relatively rare, given the generally observed preference for (near)centrosymmetric inorganic (especially lead-iodide-based) sublattices, and few approaches are available to control this symmetry breaking within a given HOIP. Here, we demonstrate, using (S-2-MeBA) |
35951555 | Neutrophil autophagy and NETosis in COVID-19: perspectives. | The COVID-19 pandemic has caused substantial losses worldwide in people's lives, health, and property. Currently, COVID-19 is still prominent worldwide without any specific drug treatment. The SARS-CoV-2 pathogen is the cause of various systemic diseases, mainly acute pneumonia. Within the pathological process, neutrophils are recruited to infected sites, especially in the lungs, for the first stage of removing invading SARS-CoV-2 through a range of mechanisms. Macroautophagy/autophagy, a conserved autodegradation process in neutrophils, plays a crucial role in the neutrophil phagocytosis of pathogens. NETosis refers to neutrophil cell death, while auto-inflammatory factors and antigens release NETs. This review summarizes the latest research progress and provides an in-depth explanation of the underlying mechanisms of autophagy and NETosis in COVID-19. Furthermore, after exploring the relationship between autophagy and NETosis, we discuss potential targets and treatment options. This review keeps up with the latest research on COVID-19 from neutrophil autophagy and NETosis with a new perspective, which can guide the urgent development of antiviral drugs and provide guidance for the clinical treatment of COVID-19. |
35951558 | Interface Engineering in Chip-Scale GaN Optical Devices for Near-Hysteresis-Free Hydraulic Pressure Sensing. | In this work, pact, near-hysteresis-free hydraulic pressure sensor is presented through interface engineering in a GaN chip-scale optical device. The sensor consists of a monolithic GaN-on-sapphire device responsible for light emission and detection and a multilevel microstructured polydimethylsiloxane (PDMS) film prepared through a low-cost molding process using sandpaper as a template. The micro-patterned PDMS film functions as a pressure-sensing medium to effectively modulate the reflectance properties at the sapphire interface during pressure loading and unloading. The interface engineering endows the GaN optical device with near-hysteresis-free performance over a wide pressure range of up to 0-800 kPa. Verified by a series of experimental measurements on its dynamic responses, the tiny hydraulic sensor exhibits superior performance in hysteresis, stability, repeatability, and response time, indicating its considerable potential for a broad range of practical applications. |
35951557 | Fabrication and Characterization of Polyelectrolyte Coatings by Polymerization and Co-Deposition of Acrylic Acid Using the Dopamine in Weak Acid Solution. | Existing medical materials (such as silicone rubber, glass slides, etc.) fail to meet the functional requirements of biosensing, cell culture, and drug delivery due to their poor wettability. The preparation of polyelectrolyte coatings with excellent wettability and protein adsorption helps broaden the application of medical materials. Poly(acrylic acid) (PAA) is mon polyelectrolyte with stronger protein adsorption, but the existing methods for obtaining PAA coating have certain ings to limit their industrial applications. In this study, dopamine (DA) was used to polymerize and co-deposit acrylic acid (AA) in weak acid solution to functionalize the surface of materials, and the effects of different mass ratios of DA/AA on the wettability and protein adsorption of the coating were deeply investigated. The results demonstrate that PDA/PAA coating is successfully prepared on the surface of four substrates and greatly reduces the water contact angle of these surfaces. Moreover, these coatings show excellent protein adsorption, and the amount of adsorbed protein on the coated QCM chip is increased by 57.74% than the uncoated QCM chip. In addition, the coating has a certain pH responsiveness, and its wettability and protein adsorption are closely related to the pH of the solution. The preparation strategy proposed is simple and substrate-independent, which provides valuable insights into the application of the one-step polymerization and co-deposition strategy under weak acid conditions. |
35951560 | Dealing With Inaccurate Sensor Data in the Context of Mobile Crowdsensing and mHealth. | The technological capabilities and ubiquity of smart mobile devices favor bined utilization of Ecological Momentary Assessments (EMA) and Mobile Crowdsensing (MCS). In the healthcare domain, bination particularly enables the collection of ecologically valid and longitudinal data. Furthermore, the context in which these data are collected can be captured through the use of smartphone sensors as well as externally connected sensors. The TrackYourTinnitus (TYT) mobile platform uses these concepts to collect the user's individual subjective perception of tinnitus as well as an objective environmental sound level. However, the sound level data in the TYT database are subject to several possible sensor errors and therefore do not allow a meaningful interpretation in terms of correlation with tinnitus symptoms. To this end, a data-centric approach based on Principal Component Analysis (PCA) is proposed in this paper to cleanse MCS mHealth data sets from erroneous sensor data. To further improve the approach, additional information (i.e., responses to the EMA questionnaire) is considered in the PCA and a prior check for constant values is performed. To demonstrate the practical feasibility of the approach, in addition to TYT data, where it is generally unknown which sensor measurements are actually erroneous, a simulation with generated data was designed and performed to evaluate the performance of the approach with different parameters based on different quality metrics. The results obtained show that the approach is able to detect an average of 29.02% of the errors, with an average false-positive rate of 14.11%, yielding an overall error reduction of 22.74%. |
35951559 | Toward A Regulatory Pathway for the Use of in Silico Trials in the CE Marking of Medical Devices. | In Silico Trials methodologies will play a growing and fundamental role in the development and de-risking of new medical devices in the future. While the regulatory pathway for Digital Patient and Personal Health Forecasting solutions is clear, it is plex for In Silico Trials solutions, and therefore deserves a deeper analysis. In this position paper, we investigate the current state of the art towards the regulatory system for in silico trials applied to medical devices while exploring the European regulatory system toward this topic. We suggest that the European regulatory system should start a process of innovation: in principle to limit distorted quality by different internal processes within notified bodies, hence avoiding that the more innovative panies focus their attention on the needs of other large markets, like the USA, where the use of such radical innovations is already rapidly developing. |
35951561 | Reinforcement Learning Based Diagnosis and Prediction for COVID-19 by Optimizing a Mixed Cost Function From CT Images. | A novel coronavirus disease (COVID-19) is a pandemic disease has caused 4 million deaths and more than 200 million infections worldwide (as of August 4, 2021). Rapid and accurate diagnosis of COVID-19 infection is critical to controlling the spread of the epidemic. In order to quickly and efficiently detect COVID-19 and reduce the threat of COVID-19 to human survival, we have firstly proposed a detection framework based on reinforcement learning for COVID-19 diagnosis, which constructs a mixed loss function that can integrate the advantages of multiple loss functions. This paper uses the accuracy of the validation set as the reward value, and obtains the initial model for the next epoch by searching the model corresponding to the maximum reward value in each epoch. We also have proposed a prediction framework that integrates multiple detection frameworks using parameter sharing to predict the progression of patients' disease without additional training. This paper also constructed a higher-quality version of the CT image dataset containing 247 cases screened by professional physicians, and obtained more excellent results on this dataset. Meanwhile, we used the other two COVID-19 datasets as external verifications, and still achieved a high accuracy rate without additional training. Finally, the experimental results show that our classification accuracy can reach 98.31%, and the precision, sensitivity, specificity, and AUC (Area Under Curve) are 98.82%, 97.99%, 98.67%, and 0.989, respectively. The accuracy of external verification can reach 93.34% and 91.05%. What's more, the accuracy of our prediction framework is 91.54%. A large number of experiments demonstrate that our proposed method is effective and robust for COVID-19 detection and prediction. |
35951563 | SMDS-Net: Model Guided Spectral-Spatial Network for Hyperspectral Image Denoising. | Deep learning (DL) based hyperspectral images (HSIs) denoising approaches directly learn the nonlinear mapping between noisy and clean HSI pairs. They usually do not consider the physical characteristics of HSIs. This drawback makes the models lack interpretability that is key to understanding their denoising mechanism and limits their denoising ability. In this paper, we introduce a novel model-guided interpretable network for HSI denoising to tackle this problem. Fully considering the spatial redundancy, spectral low-rankness, and spectral-spatial correlations of HSIs, we first establish a subspace-based multidimensional sparse (SMDS) model under the umbrella of tensor notation. After that, the model is unfolded into an end-to-end network named SMDS-Net, whose fundamental modules are seamlessly connected with the denoising procedure and optimization of the SMDS model. This makes SMDS-Net convey clear physical meanings, i.e., learning the low-rankness and sparsity of HSIs. Finally, all key variables are obtained by discriminative training. Extensive experiments prehensive analysis on synthetic and real-world HSIs confirm the strong denoising ability, strong learning capability, promising generalization ability, and high interpretability of SMDS-Net against the state-of-the-art HSI denoising methods. The source code and data of this article will be made publicly available at for reproducible research. |
35951562 | An Integrated Molecular Communication System Based on Acoustic Tweezers. | In this work, a munication link integrated with a micro-electro mechanical system (MEMS) based environment has been designed and simulated. The motivation behind this approach is to explore the possibility of merging acoustic tweezing technique with a munication system to increase the accuracy and reliability of the munication link. The proposed design is simulated using finite element methods that mimic the actual environment for an accurate solution. We derive symbol error rate as a performance metric and further show that the proposed system outperforms the diffusion-based modulation techniques and facilitates a munication in the presence of fluid flow and while being insusceptible to external factors. |
35951564 | A Machine Learning Approach to Design of Aperiodic, Clustered-Dot Halftone Screens via Direct Binary Search. | Aperiodic, clustered-dot, halftone patterns have recently e popular mercial printing of continuous-tone images with laser, electrophotographic presses, because of their inherent stability and resistance to moiré artifacts. Halftone screens designed using the multistage, multipass, clustered direct binary search (MS-MP-CLU-DBS) algorithm can yield halftone patterns with very high visual quality. But the characteristics of these halftone patterns depend on three input parameters for which there are no known formulas to choose their values to yield halftone patterns of a certain quality level and scale. Using machine learning methods, two predictors are developed that take as input these three parameters. One predicts the quality level of the halftone pattern. The other one predicts the scale of the halftone pattern. To provide ground truth information for training these predictors, human subjects viewed a large number of halftone patches generated from MS-MP-CLU-DBS-designed screens and assigned each patch to one of four quality levels. For each patch, the location of the peak in the radially averaged power spectrum (RAPS) is calculated as a measure of the scale or effective line frequency of the pattern. Experimental results demonstrate the accuracy of the two predictors and the effectiveness of screen design procedures based on these predictors to generate both monochrome and color high quality halftone images. |
35951565 | Pattern-Based Reconstruction of K-Level Images From Cutsets. | We present a pattern-based approach for reconstructing a K-level image from cutsets, dense samples taken along a family of lines or curves in two- or three-dimensional space, which break the image into blocks, each of which is typically reconstructed independently of the others. The pattern-based approach utilizes statistics of human segmentations to generate a codebook of patterns, each of which represents a pair of a block boundary specification and the corresponding pattern in the block interior. We develop the approach for rectangular cutset topologies and show that it can be extended to general periodic sampling topologies. We also show that, for bilevel cutset reconstruction, the pattern-based can bined with the previously proposed cutset-MRF approach to substantially reduce the size of the codebook with a slight increase in reconstruction error. In addition, we present an algorithm for segmenting the cutset samples of an original grayscale or color image, followed by reconstruction of the full segmentation field via the pattern-based approach. Experimental results show that the proposed approaches outperform the cutset-MRF approaches in terms of both reconstruction error rate and perceptual quality. Moreover, this is plished without any side information about the structure of the block interior. parisons of the performance of different sampling topologies are also provided. |
35951566 | UIF: An Objective Quality Assessment for Underwater Image Enhancement. | Due plex and volatile lighting environment, underwater imaging can be readily impaired by light scattering, warping, and noises. To improve the visual quality, Underwater Image Enhancement (UIE) techniques have been widely studied. Recent efforts have also been contributed to evaluate pare the UIE performances with subjective and objective methods. However, the subjective evaluation is time-consuming and uneconomic for all images, while existing objective methods have limited capabilities for the newly-developed UIE approaches based on deep learning. To fill this gap, we propose an Underwater Image Fidelity (UIF) metric for objective evaluation of enhanced underwater images. By exploiting the statistical features of these images in CIELab space, we present the naturalness, sharpness, and structure indexes. Among them, the naturalness and sharpness indexes represent the visual improvements of enhanced images; the structure index indicates the structural similarity between the underwater images before and after UIE. bine all indexes with a saliency-based spatial pooling and thus obtain the final UIF metric. To evaluate the proposed metric, we also establish a first-of-its-kind large-scale UIE database with subjective scores, namely Underwater Image Enhancement Database (UIED). Experimental results confirm that the proposed UIF metric outperforms a variety of underwater and general-purpose image quality metrics. The database and source code are available at |
35951567 | Decision Fusion Networks for Image Classification. | Convolutional neural networks, in which each layer receives features from the previous layer(s) and then aggregates/abstracts higher level features from them, are widely adopted for image classification. To avoid information loss during feature aggregation/abstraction and fully utilize lower layer features, we propose a novel decision fusion module (DFM) for making an intermediate decision based on the features in the current layer and then fuse its results with the original features before passing them to the next layers. This decision is devised to determine an auxiliary category corresponding to the category at a higher hierarchical level, which can, thus, serve as category-coherent guidance for later layers. Therefore, by stacking a collection of DFMs into a classification network, the generated decision fusion network is explicitly formulated to progressively aggregate/abstract more discriminative features guided by these decisions and then refine the decisions based on the newly generated features in a layer-by-layer manner. Comprehensive results on four benchmarks validate that the proposed DFM can bring significant improvements for mon classification networks at a minimal putational cost and are superior to the state-of-the-art decision fusion-based methods. In addition, we demonstrate the generalization ability of the DFM to object detection and semantic segmentation. |
35951568 | Neuroadaptive Output Formation Tracking for Heterogeneous Nonlinear Multiagent Systems With Multiple Nonidentical Leaders. | This article investigates the practical time-varying output formation tracking (TVOFT) problem for heterogeneous nonlinear multiagent systems (MASs) having multiple leaders, where agents herein could have heterogeneous dynamics and interact with each other under munications. It is required that the outputs of followers not only track the predefined bination of multiple leaders but also achieve the desired time-varying formation simultaneously. The existing works on formation tracking problems for MASs with multiple leaders depend on the assumption that each follower is a well-informed or uninformed follower, where the well-informed follower is required to have all the leaders as its neighbor. To remove the limitation, a fully distributed observer-based formation tracking control protocol is developed and employed. First, an adaptive state observer with an edge-based event-triggered mechanism for estimating the states of multiple leaders is proposed based on the neighboring interactions, which eliminates the unexpected Zeno behavior. Second, a novel observer is constructed for each follower by exploiting the output information of the follower, in which the adaptive neural network (NN)-based approximation is exploited pensate for the unknown nonlinearity. A practical TVOFT control protocol is then generated by the proposed observers, where the parameters are determined by an algorithm including five steps. With the help of Lyapunov stability theory and output regulation method, a practical TVOFT criterion for the considered closed-loop system is derived. Finally, the effectiveness of the proposed control scheme is illustrated by a numerical example. |
35951569 | Bisection Neural Network Toward Reconfigurable Hardware Implementation. | A hardware-friendly bisection neural network (BNN) topology is proposed in this work for approximately implementing massive pieces plex functions in arbitrary on-chip configurations. Instead of the conventional reconfigurable fully connected neural network (FC-NN) circuit topology, the proposed hardware-friendly topology performs NN behaviors in a bisection structure, in which each neuron includes two constant synapse connections for both inputs and outputs. Compared with the FC-NN one, the reconfiguration of the BNN circuit topology eliminates the remarkable amount of dummy synapse connections in hardware. As the main target application, this work aims at building a general-purpose BNN circuit topology that offers a great amount of NN regressions. To achieve this target, we prove that the NN behaviors of the FC-NN circuit topologies can be migrated to the BNN circuit topologies equivalently. We introduce two approaches including the refining training algorithm and the inverted-pyramidal strategy to further reduce the number of neurons and synapses. Finally, we conduct the inaccuracy tolerance analysis to suggest the guideline for ultra-efficient hardware implementations. Compared with the state-of-the-art FC-NN circuit topology-based TrueNorth baseline, the proposed design can achieve 17.8-22.2 × hardware reduction and less than 1% inaccuracy. |
35951572 | EMCI: A Novel EEG-Based Mental Workload Assessment Index of Mild Cognitive Impairment. | As aging deepens, early detection of mild cognitive impairment (MCI) is increasingly important to prevent Alzheimer Dementia (AD) and improve the quality of life of older adults. In recent years, a large number of studies focus on the abnormal brain cognitive function of MCI, while ignoring the quantitative evaluation of MCI's mental workload. In this study, we propose a workload index for MCI screening, named EMCI, which is a linear discriminant cumulative estimate of subjects' electroencephalography (EEG) power spectra in α and β rhythms. Then, we design a matched prototype system to verify the effectiveness of EMCI. The results show that the EMCI is sensitive to changes of subjects' mental workload, and is significantly lower in MCI than in HC (Health control), which may be precisely caused by cognitive dysfunction. The proposed EMCI index can be used for online assessment of mental workload in older adults, which can help achieve quick screening of MCI and provide a critical window for clinical treatment interventions. |
35951573 | On the Deep Learning Models for EEG-Based Brain-Computer Interface Using Motor Imagery. | Motor imagery (MI) based puter interface (BCI) is an important BCI paradigm which requires powerful classifiers. Recent development of deep learning technology has prompted considerable interest in using deep learning for classification and resulted in multiple models. Finding the best performing models among them would be beneficial for designing better BCI systems and classifiers going forward. However, it is difficult to pare performance of various models through the original publications, since the datasets used to test the models are different from each other, too small, or even not publicly available. In this work, we selected five MI-EEG deep classification models proposed recently: EEGNet, Shallow & Deep ConvNet, MB3D and ParaAtt, and tested them on two large, publicly available, databases with 42 and 62 human subjects. Our results show that the models performed similarly on one dataset while EEGNet performed the best on the second with a relatively small training cost using the parameters that we evaluated. |
35951574 | Muscle-Effort-Minimization-Inspired Kinematic Redundancy Resolution for Replicating Natural Posture of Human Arm. | Replicating natural postures of human arms is essential to generate human-like behaviors in robotic applications for humans nearby. However, how to realize this requirement in interactive scenarios remains a challenge due to the kinematic redundancy and unknown postural control strategy of human arms. Inspired by the physiological characteristics that the musculoskeletal system is coordinated to minimize muscle effort in human behaviors, this paper aims to address the issue by solving a muscle effort minimization problem. It adopts a high-fidelity human arm musculoskeletal model (HAMM) and considers the implicit constraint (desired hand pose) and the inequality constraints (range of joint motion). The constrained minimization is in general nonconvex, consequently sensitive to initial guesses in iterative procedures. So, it is impracticable to solve it directly with existing gradient-based deterministic approaches or standard evolutionary algorithms. As the main contribution, a hybrid inverse kinematics algorithm was proposed for the HAMM with 7 independent and 13 mimic joints to obtain the feasible arm postures satisfying the minimization constraints. Using the arm swivel angle that parametrizes the kinematic redundancy of the HAMM, geometrically equidistant initial guess candidates can be generated over the 1-dimension feasible posture manifold. As another contribution, we present a two-phase global minimization algorithm to handle the nonconvexity of the constrained minimization. It consists of a local-search phase on the null-space of the geometric Jacobian matrix and a global-search phase with an initial guess resampling strategy. The proposed approach was validated by replicating the natural arm postures of 5 right-handed subjects in daily tasks. |
35951571 | DFTNet: Dual-Path Feature Transfer Network for Weakly Supervised Medical Image Segmentation. | Medical image segmentation has long suffered from the problem of expensive labels. Acquiring pixel-level annotations is time-consuming, labor-intensive, and relies on extensive expert knowledge. Bounding box annotations, in contrast, are relatively easy to acquire. Thus, in this paper, we explore to segment images through a novel Dual-path Feature Transfer design with only bounding box annotations. Specifically, a Target-aware Reconstructor is proposed to extract target-related features by reconstructing the pixels within the bounding box through the channel and spatial attention module. Then, a sliding Feature Fusion and Transfer Module (FFTM) fuses the extracted features from Reconstructor and transfers them to guide the Segmentor for segmentation. Finally, we present the Confidence Ranking Loss (CRLoss) which dynamically assigns weights to the loss of each pixel based on the network's confidence. CRLoss mitigates the impact of inaccurate pseudo-labels on performance. Extensive experiments demonstrate that our proposed model achieves state-of-the-art performance on the Medical Segmentation Decathlon (MSD) Brain Tumour and PROMISE12 datasets. |
35951575 | A Machine Learning Perspective on fNIRS Signal Quality Control Approaches. | Despite a rise in the use of functional Near Infra-Red Spectroscopy (fNIRS) to study neural systems, fNIRS signal processing is not standardized and is highly affected by empirical and manual procedures. At the beginning of any signal processing procedure, Signal Quality Control (SQC) is critical to prevent errors and unreliable results. In fNIRS analysis, SQC currently relies on applying empirical thresholds to handcrafted Signal Quality Indicators (SQIs). In this study, we use a dataset of fNIRS signals (N = 1,340) recorded from 67 subjects, and manually label the signal quality of a subset of segments (N = 548) to investigate the pitfalls of current practices while exploring the opportunities provided by Deep Learning approaches. We show that SQIs statistically discriminate signals with bad quality, but the identification by means of empirical thresholds lacks sensitivity. Alternatively to manual thresholding, conventional machine learning models based on the SQIs have been proven more accurate, with end-to-end approaches, based on Convolutional Neural Networks, capable of further improving the performance. The proposed approach, based on machine learning, represents a more objective SQC for fNIRS and moves towards the use of fully automated and standardized procedures. |
35951576 | Visual Feedback in Augmented Reality to Walk at Predefined Speed Cross-Sectional Study Including Children With Cerebral Palsy. | In an augmented reality environment, the range of possible real-time visual feedback is extensive. This study aimed pare the impact of six scenarios in augmented bining four visual feedback characteristics on achieving a target walking speed. The six scenarios have been developed for Microsoft Hololens augmented reality headset. The four feedback characteristics that we have varied were: Color; Spatial anchoring; Speed of the feedback, and Persistence. Each characteristic could have different values (for example, the color could be unicolor, bicolor, or gradient). Participants had to walk for two consecutive walking trials for each scenario: at their maximal speed and an intermediate speed. Mean speed, percentage of time spent above or around target speed, and time to reach target speed pared between scenarios using mixed linear models. A total of 25 children with disabilities have been included. The feasibility and user experience were excellent. Mean speed during scenario 6, which displayed feedback with gradient color, attached to the world, with a speed relative to the player equal to his speed, and that disappeared over time, was significantly higher than other scenarios and control (p =0.003). Participants spent 80.98% of time above target speed during scenario 6. This scenario mixed the bination of feedback characteristics to exceed the target walking speed (p=0.0058). Scenarios 5 and 6, which shared the same feedback characteristics for spatial anchoring (world-locked) and feedback speed (equal to the player speed), decreased the time to reach the target speed (p=0.019). Delivering multi-modal feedback has been recognized as more effective for improving motor performance. Therefore, our results showed that not all visual feedback had the same impact on performance. Further studies are required to test the weight of each feedback characteristic and their possible interactions inside each scenario. This study was registered in the ClinicalTrials.gov database (NCT04460833). |
35951570 | Effectively Identifying Compound-Protein Interaction Using Graph Neural Representation. | Effectively pound-protein interactions (CPIs) is crucial for new drug design, which is an important step in silico drug discovery. Current machine learning methods for CPI prediction mainly use one-demensional pound/protein strings and/or the specific descriptors. However, they often ignore the fact that molecules are essentially modeled by the molecular graph. We observe that in real-world scenarios, the topological structure information of the molecular graph usually provides an overview of how the atoms are connected, and the local chemical context reveals the functionality of the protein sequence in CPI. These two types of information plementary to each other and they are both significant for pound-protein pairs. Motivated by this, we propose an end-to-end deep learning framework named GraphCPI, which captures the structural information pounds and leverages the chemical context of protein sequences for solving the CPI prediction task. Our framework can integrate any popular graph neural networks for pounds, and bines with a convolutional neural network for embedding sequences. pare our method with classic and state-of-the-art deep learning methods, we conduct extensive experiments based on several widely-used CPI datasets. The experimental results show the feasibility petitiveness of our proposed method. |
35951578 | VisRecall: Quantifying Information Visualisation Recallability via Question Answering. | Despite its importance for assessing the effectiveness municating information visually, fine-grained recallability of information visualisations has not been studied quantitatively so far. In this work, we propose a question-answering paradigm to study visualisation recallability and present VisRecall - a novel dataset consisting of 200 visualisations that are annotated with crowd-sourced human (N = 305) recallability scores obtained from 1,000 questions of five question types. Furthermore, we present the putational method to predict recallability of different visualisation elements, such as the title or specific data values. We report detailed analyses of our method on VisRecall and demonstrate that it outperforms several baselines in overall recallability and FE-, F-, RV-, and U-question recallability. Our work makes fundamental contributions towards a new generation of methods to assist designers in optimising visualisations. |
35951579 | Identify Representative Samples by Conditional Random Field of Cancer Histology Images. | Pathology analysis is crucial to precise cancer diagnoses and the succeeding treatment plan as well. To detect abnormality in histopathology images with prevailing patch-based convolutional neural networks (CNNs), contextual information often serves as a powerful cue. However, as whole-slide images (WSIs) are characterized by intense morphological heterogeneity and extensive tissue scale, a straightforward visual span to a larger context may not well capture the information closely associated with the focal patch. In this paper, we propose a novel pixel-offset based patch-location method to identify high-representative tissues, with a CNN backbone. Pathology Deformable Conditional Random Field (PDCRF) is proposed to learn the offsets and weights of neighboring contexts in a spatial-adaptive manner, to search for high-representative patches. A CNN structure with the localized patches as training input is then capable of consistently reaching superior classification es for histology images. Overall, the proposed method has achieved state-of-the-art performance, in terms of the test classification accuracy improvement to the baseline by 1.15-2.60%, 0.78-1.78%, and 1.47-2.18% on TCGA public datasets of TCGA-STAD, TCGA-COAD, and TCGA-READ respectively. It also achieves 88.95% test accuracy and 0.920 test AUC on Camelyon 16. To show the effectiveness of the proposed framework on downstream tasks, we take a further step by incorporating an active learning model, which noticeably reduces the number of manual annotations by PDCRF to reach a parallel patch-based histology classifier. |
35951580 | Optimal Control of Temporal Networks With Variable Input and Node-Source Connection. | Many networked systems built upon real-life physical or social interactions have time-varying connections among individual units, where the temporal changes in connectivity and/or interaction strength lead plicated dynamics. The temporal network model was proposed in the form of controlled linear dynamical systems acting in an ordered sequence of time intervals. One of the core challenges in network science is the control of networks and the optimization of the control strategy. However, most canonical frameworks for solving optimal control problems were established for static networks featuring constant topology. New theories and techniques are yet to be developed for the temporal networks, with an important case being that the input and the source-node connection are both variables. In this work, by formulating a quadratic energy cost without solving the Riccati differential equation, we show that the control effort can be reduced substantially by improving either the system trajectories or the input matrices. The two approaches are bined in a coordinate descent framework, integrating linearly constrained quadratic programming, and a projected gradient descent method. Taken together, the results underline the potential of temporal networks as energy-efficient control systems and present strategies to improve the control input. Moreover, the proposed algorithms can serve as a starting point for future engineering of real-world temporal networks. |
35951582 | A simple scoring of beam walking performance after spinal cord injury in mice. | Precise evaluation of motor functions using simple and reproducible tests for mouse models of spinal cord injury (SCI) are required. Overground walking of SCI mice has been tested by Basso Mouse Scale for otion (BMS). In contrast, only a few works quantify walking performances of SCI mice on narrow beams, a different task. Here, we established a novel scoring system using a single beam walking apparatus for SCI mice. The scoring system uses binary judgments of values such as retention, moving forward and reaching the goal on a beam for rating. In addition, high score was given to SCI mouse when the mouse efficiently used hindlimbs for otion on the beam. A high rate of concordance of the score derived from positions of hindlimbs between two observers was obtained. Mice displayed the lowest total score on the beam immediately after the SCI, then the score gradually increased like time course of BMS score. Furthermore, the total scores reflected gradation of severity of SCI in 2 strains of mice. The beam walking score proved to be strongly correlated with that of BMS score, indicating that performances between overground walking and beam walking are partly correlated in SCI mice. Collectively, the novel scoring system offers an opportunity to easily evaluate motor performances of mice with SCI. |
35951581 | Revving an Engine of Human Metabolism: Activity Enhancement of Triosephosphate Isomerase via Hemi-Phosphorylation. | Triosephosphate isomerase (TPI) performs the 5th step in glycolysis, operates near the limit of diffusion, and is involved in "moonlighting" functions. Its dimer was found singly phosphorylated at Ser20 (pSer20) in human cells, with this post-translational modification (PTM) showing context-dependent stoichiometry and loss under oxidative stress. We generated synthetic pSer20 proteoforms using cell-free protein synthesis that showed enhanced TPI activity by 4-fold relative to unmodified TPI. Molecular dynamics simulations show that the phosphorylation enables a channel to form that shuttles substrate into the active site. Refolding, kinetic, and crystallographic analyses of point mutants including S20E/G/Q indicate that hetero-dimerization and subunit asymmetry are key features of TPI. Moreover, characterization of an endogenous human TPI tetramer also implicates tetramerization in enzymatic regulation. S20 is highly conserved across eukaryotic TPI, yet most prokaryotes contain E/D at this site, suggesting that phosphorylation of human TPI evolved a new switch to optionally boost an already fast enzyme. plete characterization of TPI shows how endogenous proteoform discovery can prioritize functional versus bystander PTMs. |
35951583 | Relativistic Effects Stabilize Unusual Gold(II) Sulfate Structure via Aurophilic Interactions. | The crystal structure of gold(II) sulfate is strikingly different from other coinage metal(II) sulfates. Central to the unsual AuSO |
35951584 | Preliminary brain-behavioral neural correlates of anterior cruciate ligament injury risk landing biomechanics using a novel bilateral leg press neuroimaging paradigm. | Anterior cruciate ligament (ACL) injury risk reduction strategies primarily focus on biomechanical factors related to frontal plane knee motion and loading. Although central nervous system processing has emerged as a contributor to injury risk, brain activity associated with the resultant ACL injury-risk biomechanics is limited. Thus, the purposes of this preliminary study were to determine the relationship between bilateral motor control brain activity and injury risk biomechanics and isolate differences in brain activity for those who demonstrate high versus low ACL injury risk. Thirty-one high school female pleted a novel, multi-joint leg press during brain functional magnetic resonance imaging (fMRI) to characterize bilateral motor control brain activity. Athletes pleted an established biomechanical assessment of ACL injury risk biomechanics within a 3D motion analysis laboratory. Knee abduction moments during landing were modelled as a covariate of interest within the fMRI analyses to identify directional relationships with brain activity and an injury-risk group classification analysis, based on established knee abduction moment cut-points. Greater landing knee abduction moments were associated with greater lingual gyrus, intracalcarine cortex, posterior cingulate cortex and precuneus activity when performing the bilateral leg press (all z > 3.1, p < .05; parison corrected). In the follow-up injury-risk classification analysis, those classified as high ACL injury-risk had greater activity in the lingual gyrus, parietal cortex and bilateral primary and secondary motor cortices relative to those classified as low ACL injury-risk (all z > 3.1, p < .05; parison corrected). In young female athletes, elevated brain activity for bilateral leg motor control in regions that integrate sensory, spatial, and attentional information were related to ACL injury-risk landing biomechanics. These data implicate crossmodal visual and proprioceptive integration brain activity and knee spatial awareness as potential neurotherapeutic targets to optimize ACL injury-risk reduction strategies. |
35951585 | A reservoir bubble point pressure prediction model using the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique with trend analysis. | The bubble point pressure (Pb) could be obtained from pressure-volume-temperature (PVT) measurements; nonetheless, these measurements have drawbacks such as time, cost, and difficulties associated with conducting experiments at high-pressure-high-temperature conditions. Therefore, numerous attempts have been made using several approaches (such as regressions and machine learning) to accurately develop models for predicting the Pb. However, some previous models did not study the trend analysis to prove the correct relationships between inputs and outputs to show the proper physical behavior. Thus, this study aims to build a robust and more accurate model to predict the Pb using the adaptive neuro-fuzzy inference system (ANFIS) and trend analysis approaches for the first time. More than 700 global datasets have been used to develop and validate the model to robustly and accurately predict the Pb. The proposed ANFIS model pared with 21 existing models using statistical error analysis such as correlation coefficient (R), standard deviation (SD), average absolute percentage relative error (AAPRE), average percentage relative error (APRE), and root mean square error (RMSE). The ANFIS model shows the proper relationships between independent and dependent parameters that indicate the correct physical behavior. The ANFIS model outperformed all 21 models with the highest R of 0.994 and the lowest AAPRE, APRE, SD, and RMSE of 6.38%, -0.99%, 0.074 psi, and 9.73 psi, respectively, as the first rank model. The second rank model has the R, AAPRE, APRE, SD, and RMSE of 0.9724, 9%, -1.58%, 0.095 psi, and 13.04 psi, respectively. It is concluded that the proposed ANFIS model is validated to follow the correct physical behavior with higher accuracy than all studied models. |
35951577 | The Effect of Temperature on Tactile Softness Perception. | We are adept at discriminating object properties such as softness and temperature using touch. Previous studies have investigated the nature of each object property, but the interactions between these properties are not fully understood. Tactile softness perception relies on multiple sensory cues such as the size of the contact area, indentation depth, and force exerted. In addition to these cues, the temperature of the stimulus may contribute to tactile softness perception by changing the sensitivity to changes in pliance. To test this hypothesis, we conducted two psychophysical experiments in which the subjects estimated the magnitude of perceived softness after touching deformable objects. We varied pliance and temperature of the stimuli. The linear functions pliance fit to the magnitude estimates under cold conditions (9-15°C) were steeper than the functions fit to the magnitude estimates under room temperature (21-25°C). These results indicate that temperature can sharpen our tactile softness perception of deformable surfaces by increasing the sensitivity to differences pliance. |
35951586 | Infection prevention practices and its associated factors among hospital workers in a national medical center designated for COVID-19 in Tokyo, Japan. | While healthcare workers (HCWs) are at risk of occupational exposure to SARS-CoV-2 infection, the virus transmission involving them might be exceeding in the non-occupational settings. This study examined the extent of adherence to infection prevention practices (IPPs) against COVID-19 in their daily life and its associated factors among staff members in a national medical center designated for COVID-19 treatment in Tokyo, Japan. |
35951587 | Association between median household income, state Medicaid expansion status, and COVID-19 outcomes across US counties. | To study the relationship between county-level COVID-19 es (incidence and mortality) and county-level median household e and status of Medicaid expansion of US counties. |
35951588 | Machine learning-based predictive modeling of resilience to stressors in pregnant women during COVID-19: A prospective cohort study. | During the COVID-19 pandemic, pregnant women have been at high risk for psychological distress. Lifestyle factors may be modifiable elements to help reduce and promote resilience to prenatal stress. We used Machine-Learning (ML) algorithms applied to questionnaire data obtained from an international cohort of 804 pregnant women to determine whether physical activity and diet were resilience factors against prenatal stress, and whether stress levels were in turn predictive of sleep classes. A support vector machine accurately classified perceived stress levels in pregnant women based on physical activity behaviours and dietary behaviours. In turn, we classified hours of sleep based on perceived stress levels. This research adds to a developing consensus concerning physical activity and diet, and the association with prenatal stress and sleep in pregnant women. Predictive modeling using ML approaches may be used as a screening tool and to promote positive health behaviours for pregnant women. |
35951590 | Can we speak of a negative psychological tetrad in sports? A probabilistic Bayesian study on competitive sailing. | Researchers display an interest in studying aspects like the mental health of high-performance athletes; the dark side of sport, or the earliest attempts to study the so-called dark triad of personality in both initiation and high-performance athletes. Therefore, the objective of this paper is to determine the possible existence and magnitude of negative psychological aspects within a population petition sailors and from a probabilistic point of view, using Bayesian Network analysis. |
35951589 | Prioritized and predictive intelligence of things enabled waste management model in smart and sustainable environment. | Collaborative modelling of the Internet of Things (IoT) with Artificial Intelligence (AI) has merged into the Intelligence of Things concept. This recent trend enables sensors to track required parameters and store accumulated data in cloud storage, which can be further utilized by AI based predictive models for automatic decision making. In a smart and sustainable environment, effective waste management is a concern. Poor regulation of waste in surrounding areas leads to rapid spread of contagious disease risks. Traditional waste object management requires more working staff, increases effort, consumes time and is relatively ineffective. In this research, an Intelligence of Things Enabled Smart Waste Management (IoT-SWM) model with predictive capabilities is developed. Here, local sinks (LS) are deployed in specified locations. At every instant, the current status of smart bins in each LS is notified to users to determine the priority level of LS to be emptied. Based on aggregated sensor values for the three smart bins, LS weight and poison gas value, the priority order of emptying LS puted, and decision is made whether to notify the users with an alert message or not. It also helps in predicting the LS, which is likely to be filled up at a faster rate based on assigned timestamp. This model is implemented in real time with many LS and it was observed that bins, which were close to more crowded sites filled up pared to sparse populated areas. Random forest algorithm was used to predict whether an alert notification is to be sent or not. An average mean of 95.8% accuracy was noted while using 60 decision trees in random forest algorithm. The average mean execution latency recorded for training and testing sets is 13.06 sec and 14.39 sec respectively. Observed accuracy rate, precision, recall and f1-score parameters were 95.8%, 96.5%, 98.5% and 97.2% respectively. Model buildup and the validation puted were 3.26 sec and 4.25 sec respectively. It is also noted that at a threshold value of 0.93 in LS level, the maximum accuracy rate reached was 95.8%. Thus, based on the prediction of random forest approach, a decision to notify the users is taken. Obtained e indicates that the waste level can be efficiently determined, and the overflow of dustbins can be easily checked in time. |
35951591 | Influence of transurethral enucleation with bipolar of the prostate on erectile function: Prospective analysis of 51 patients at 12-month follow-up. | Transurethral enucleation with bipolar (TUEB) is a safe and effective surgery for benign prostatic obstruction (BPO). However, few data exist concerning the influence of TUEB on erectile function (EF) in patients with BPO. |
35951592 | Integrating hypertension and HIV care in Namibia: A quality improvement collaborative approach. | Hypertension (HTN) is highly prevalent among people with HIV (PWH) in Namibia, but screening and treatment for HTN are not routinely offered as part of HIV care delivery. We report the implementation of a quality improvement collaborative (QIC) to accelerate integration of HTN and HIV care within public-sector health facilities in Namibia. |
35951593 | The effect of continuous intravenous norepinephrine infusion on systemic hemodynamics in a telemetrically-monitored mouse model of sepsis. | Sepsis, a life-threatening organ dysfunction, results from dysregulated host responses to infection and still has a high incidence and mortality. Although administration of vasopressors to treat septic shock is standard of care, the benefits are not well established. We evaluated the effect of continuous intravenous norepinephrine infusion in a septic cecal ligation and puncture (CLP) mouse model, evaluating systemic hemodynamics and body temperature post-hoc. CLP surgery significantly decreased mean arterial blood pressure (MAP), heart rate, and body temperature within six hours. Continuous norepinephrine infusion (NE+, n = 12) started at the time of CLP surgery significantly increased MAP at 24 and 30 hours and heart rate at 6, 18, 24, and 30 hours after CLP vs CLP alone (NE-, n = 12). However, addition of norepinephrine did not improve survival rate (NE+ n = 34, NE- n = 31). Early (6 hours or earlier, when the animal became visibly sick) MAP did not predict 7-day mortality. However, heart rates at 3 and at 6 hours after CLP/norepinephrine (NE+) were highly predictive of mortality, as also been found in one clinical study. We conclude that limited hemodynamic support can be provided in a mouse sepsis model. We propose that heart rate can be used to stratify severity of illness in rodent preclinical studies of sepsis therapeutics. |
35951594 | The time to initiate trophic feeding and its predictors among preterm neonate admitted to neonatal intensive care unit, Multicenter study, Northwest Ethiopia. | Trophic feeding is a small volume, hypo-caloric feeding, gut priming or minimal enteral feeding acclimate the immature gut of enteral fasting preterm neonates. Delayed starting of trophic feeding had resulted in short and long-term physical and neurological sequels. The current study aimed to estimate the time to initiate trophic feeding and its predictors among preterm neonates admitted in the neonatal intensive care unit of Debre Markos, Felege Hiwot, and Tibebe prehensive specialized hospitals. |
35951595 | A graph-based approach to multi-source heterogeneous information fusion in stock market. | The stock market is an important part of the capital market, and the research on the price fluctuation of the stock market has always been a hot topic for scholars. As a dynamic plex system, the stock market is affected by various factors. However, with the development of information technology, information presents multisource and heterogeneous characteristics, and the transmission speed and mode of information have changed greatly. The explanation and influence of multi-source and heterogeneous information on stock market price fluctuations need further study. In this paper, a graph fusion and embedding method for multi-source heterogeneous information of Chinese stock market is established. Relational dimension information is introduced to realize the effective fusion of multi-source heterogeneous data information. A multi-attention graph neural network based on nodes and semantics is constructed to mine the implied semantics of fusion graph data and capture the influence of multi-source heterogeneous information on stock market price fluctuations. Experiments show that the proposed multi-source heterogeneous information fusion methods is superior to tensor or vector fusion method, and the constructed multi-attention diagram neural network has a better ability to explain stock market price fluctuations. |
35951596 | The role of religious narratives and religious orientation towards concerns for the natural environment and animal welfare. | Several studies show that religion hinders concerns for the natural environment preservation. Others, however, have found that the belief in God or the identification with a particular religion is not associated with measures for environmental concerns. This study investigates the influence of religious narrative framing and the relation between Allport's intrinsic personal (IP) and extrinsic social (ES) religious orientation towards general environmental apathy (GEA) and acceptability for harming animals (AIS). This study surveyed 657 teachers and school staff in East Java, Indonesia. Using ANOVA, we find that religious narrative affects participant's GEA and AIS. Participants in stewardship narrative group have significantly lower GEA and pared to participants in human dominance and the non-narratives control group. Using multiple regression, we also confirm the persistence of religious narrative's influence towards GEA. In addition, lower GEA and AIS correlate with higher IP and lower ES. Lastly, we identify and discuss significant demographic and other determinants relation to GEA and AIS. |
35951597 | A scoping review of Do-It-Yourself Automated Insulin Delivery system (DIY AID) use in people with type 1 diabetes. | User designed Automated Insulin Delivery systems (AID), termed Do-It-Yourself (DIY) AID include; AndroidAPS, OpenAPS and Loop. These unregulated systems provide challenges for healthcare providers worldwide, with potential legal and ethical barriers to supporting their use. We performed a scoping review of the currently available literature surrounding DIY AID systems, specifically to highlight the evidence available to facilitate healthcare providers to support persons with diabetes who may benefit from DIY AID. |