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0.561972 | b49c52e21f1d49428bb291495fd5279b | Pyocin expression in cells with catalytically inactive XerC is RecA dependent. (A) Representative growth curves (OD600) and luminescence traces (P07990-lux) of xerCY272F (MTC2339) treated (gray) or not (black) with 0.03 μg/mL ciprofloxacin (Cipro) or 0.1 μg/mL mitomycin C (MMC). Note that the y axis scales on the luminescence graphs vary. Light gray shading surrounding the traces indicates standard deviation from three technical replicates. Time is indicated in hours. (B) Representative growth curves and luminescence traces as in panel A, but for xerCY272F ΔrecA (MTC2444). (C and D) OD-normalized luminescence traces of the indicated strains from panels A and B, respectively, together with other strains shown for reference. | PMC9431673 | spectrum.01167-22-f005.jpg |
0.45749 | 94fa7ed80d694dc6bf2ae82976814f0e | Hexapeptide recombinase inhibitors do not stimulate pyocin expression. (A) Representative growth curves (OD600) and luminescence traces (P07990-lux) of wild-type PA14 (MTC2280) treated with the indicated concentrations of WRWYCR recombinase inhibitor peptide or with WKHYNY, a control peptide with no inhibitor activity (blue shades). Cells were also treated with 0.03 μg/mL ciprofloxacin (Cipro) as a control (gray). Light gray shading surrounding the traces indicates standard deviation from three technical replicates. Time is indicated in hours. (B) Representative growth curves and luminescence traces as in panel A, but for ΔxerC (MTC2297). (C and D) OD-normalized luminescence traces of the indicated strains and treatments from panels A and B, respectively. (E) Representative phase-contrast and GFP fluorescence (P07990-gfp) micrographs of wild-type PA14 (MTC2277) cells treated or not with 50 μM WRWYCR inhibitor peptide for 135 min. (F) Distributions of mean GFP fluorescence in individual cells treated as in panel E. As in our previous work, cells above a cutoff of 1.2× (gray dashed line) background fluorescence (black dashed line) were considered GFP positive. | PMC9431673 | spectrum.01167-22-f006.jpg |
0.491741 | 967d2d3a7ab54cff9acf8571f1ea02ae | Recombinase inhibitors do not stimulate pyocin expression at subinhibitory concentrations or in combination with ciprofloxacin. (A) Representative growth curves (OD600) and luminescence traces (P07990-lux) of wild-type PA14 (MTC2280) treated with the indicated concentrations of WRWYCR recombinase inhibitor peptide or with WKHYNY, a control peptide with no inhibitor activity (blue shades). Cells were also treated with 0.03 μg/mL ciprofloxacin (Cipro) as a control (gray). Light gray shading surrounding the traces indicates standard deviation from three technical replicates. Time is indicated in hours. (B) OD-normalized luminescence traces of the indicated treatments from panel A. (C) Representative growth curves (OD600) and luminescence traces (P07990-lux) of wild-type PA14 (MTC2280) treated with 0.03 μg/mL ciprofloxacin alone (gray) or with the indicated concentrations of WRWYCR inhibitor or WKHYNY control peptides (blue shades). Light gray shading surrounding the traces indicates standard deviation from three technical replicates. Time is indicated in hours. (D and E) OD-normalized luminescence traces of the indicated treatments from panel C. In panel D, ciprofloxacin-treated ΔxerC cells (MTC2297) are shown as a reference for the degree of pyocin induction in the absence of XerC. | PMC9431673 | spectrum.01167-22-f007.jpg |
0.40464 | 5d351cd8f7914461be8022d8b97f4f32 | Number of cases submitted to transferrin isoelectric focusing (TfIEF) per year at the Metabolism Inborn Errors Laboratory of the Hospital de Clínicas de Porto Alegre, Brazil. The number of altered cases per year and their percentage are highlighted. | PMC9432258 | gr1.jpg |
0.404158 | fb102e959409442b80e5b532f2bcb6cd | Serial MR findings of acute necrotizing encephalopathy in a 10-year-old boy.A. Initial MRI was done 10 hours after the first CT scan, which was unremarkable. T2WI and FLAIR images show significant edematous changes in both thalami. DWI and ADC map show focal diffusion restriction in the bilateral thalami. SWI shows no cerebral hemorrhage in the thalami.B. Follow-up MRI was done on the 10th day of the illness. T2WI and FLAIR images show an improvement in the thalami swelling and symmetrical high signal intensities in the bilateral thalami. DWI and ADC maps show distinct concentric structures in the bilateral thalami. Restricted diffusion was also observed in the splenium of the corpus callosum. SWI shows multiple diffuse petechial intracerebral hemorrhages in the periphery of the bilateral thalamic lesions, which correlated with areas of vasogenic edema; however, central diffusion-restricted lesions in the bilateral thalami were spared.C. Follow-up MRI was performed on the 17th day of the illness. T2WI and FLAIR images show decreased extent of signal change and swelling in the bilateral thalami with mildly aggravated hydrocephalus. DWI and ADC maps show almost complete resolution of the diffusion abnormalities in the bilateral thalami and splenium of the corpus callosum.D. Follow-up MRI was performed six months after the illness. On DWI and ADC maps, identifiable diffusion-restricted lesions were no longer visible. SWI shows a decreased extent of multifocal microhemorrhages and remained hemosiderin deposition in the bilateral thalami. ADC = apparent diffusion coefficient, DWI = diffusion-weighted image, FLAIR = fluid-attenuated inversion recovery, SWI = susceptibility-weighted image, T2WI = T2-weighted imageADC = apparent diffusion coefficient, DWI = diffusion-weighted image, FLAIR = fluid-attenuated inversion recovery, SWI = susceptibility-weighted image, T1CE = T1-weighted contrast-enhanced image, T2WI = T2-weighted image | PMC9432353 | jksr-82-1274-g001.jpg |
0.416117 | f161824f82b943259dac1b30bf12ceab | Structure of estrogen receptors (ERs). Six structural and functional domains are highlighted: A, B domain (amino-terminal or NH2-terminal domain [NTD], activation function 1 [AF1]); C domain (DNA binding domain [DBD]); D domain (hinge region connecting the C and E domain); E, F domain (carboxyl- or COOH-terminal, ligand-binding domain [LBD], AF2). | PMC9433670 | fendo-13-839005-g001.jpg |
0.449821 | cb6e04d96f74424e8815a0607c65ce32 | Estrogen receptor alpha (ERα) isoforms. Six structural and functional domains are highlighted: A, B domain (amino- or NH2-terminal domain [NTD], AF1), C domain (DNA binding domain [DBD]), D domain (hinge region connecting the C and E domain), E, F domain (carboxyl- or COOH-terminal, ligand-binding domain [LBD], AF2). | PMC9433670 | fendo-13-839005-g002.jpg |
0.409507 | 6b045bd4b4c040ab8a725897001ae5a5 | Estrogen receptor beta (ERβ) isoforms. Six structural and functional domains are highlighted: A, B domain (amino- or NH2-terminal domain [NTD], AF1), C domain (DNA binding domain [DBD]), D domain (hinge region connecting the C and E domain), E, F domain (carboxyl- or COOH-terminal, ligand-binding domain [LBD], AF2). | PMC9433670 | fendo-13-839005-g003.jpg |
0.442804 | 7f02fee8ffda41aeabcb6b0c8d35f372 | Structures of G-protein-coupled estrogen receptor 1 (GPER1). | PMC9433670 | fendo-13-839005-g004.jpg |
0.424983 | c305257100e74f3e8616e8765238ea63 | Estrogen signaling pathways. Estrogen or E2 (orange circle E in the graph) binds to the ERα/ERβ and GPER1, exerting its genomic and non-genomic effects. The genomic effect is shown in orange: the E2-receptor complex binds to EREs upon entry into the nucleus. The non-genomic effect is shown in blue: E2 binds to ERs in the membrane-like GPER1 and regulates the expression by modulating the ion channel opening or activation of related enzymes. E, estrogen or E2; ERα, estrogen receptor alpha; ERβ, estrogen receptor beta; GPER1, G protein-coupled estrogen receptor 1; ERE, estrogen response elements; PI3K, phosphatidylinositol 3-kinase; MAPK, mitogen-activated protein kinase. | PMC9433670 | fendo-13-839005-g005.jpg |
0.447298 | 48a3afcaa711411a8d9f4afbf36299a0 | The multifaceted role of ERs in various diseases. | PMC9433670 | fendo-13-839005-g006.jpg |
0.456639 | 4f032e58a5314c9b957528246d33c8dd | Mechanism of hyperglycaemia-induced cellular senescence. (A) Hyperglycaemia induces ROS overproduction via mitochondria overload which results in oxidative stress. ROS causes DNA damage response (DDR) activation, due to DNA oxidative damage, and p38 MAPK pathway activation. DDR and p38 MAPK determines cell cycle arrest and NF-κB upregulation. NF-κB activation results in SASP secretion. ROS also generates ER stress via chemical modification of ER proteins. ER stress activates the unfolded protein response (UPR). The activation of the ATF6α branch of the UPR causes expression of SA-β-Gal and changes in cellular morphology via cytoskeletal vimentin rearrangement. (B) Hyperglycaemia increases polyol pathway activity, causing reduced antioxidant glutathione synthesis due to reduce NADPH availability. Glutathione deficiency contributes to the inability of the cell to counteract oxidative stress. (C) Hyperglycaemia causes advance glycation end products (AGEs) via glycation of intracellular and extracellular proteins. Intracellular AGEs cause ER stress which results in SA-β-Gal activity and change in cellular morphology. Extracellular ages cause AGE receptor (RAGE) activation which results in ROS production and NF-κB activation. This ultimately results in cell cycle arrest and SASP secretion. (D) Hyperglycaemia results in increased hexosamine pathway activity due to increased glucose-6-phosphate production. This pathway produces N-acetyl glucosamine (GlcNAc) which induces TGF-β expression. TGF-β activates the p38 MAPK which results in cell cycle arrest and SASP secretion. (E) PKC signalling contributes to the activation of senescence pathways. Hyperglycaemia results in increased diacyl glycerol production and activation of PKC δ isoform. PKC δ activation causes TGF-β expression and ROS production which, in turn, activate PKC δ in a positive feedback loop mechanism. In addition, ROS also activate PKC η which induces SA-β-Gal activity. Downregulation of aPKC and cPKC results in inactivation of FoxO3a which results in ROS production. Cell cycle arrest, SASP secretion, change in cellular morphology and SA-β-Gal activity are the major characteristics of senescence. | PMC9434004 | fonc-12-975644-g001.jpg |
0.447128 | 0df4349a6c5d464b9a5b15bc58888146 | SASP activity within the tumour microenvironment. (A) Angiogenesis is stimulated by CCL23, VEGF and GDF15. CCL23 is secreted by senescent T cells, while VEGF and GDF15 are secreted by senescent fibroblasts. (B) Metastasis is promoted by GDF15 and CCL5, which are secreted by senescent fibroblasts and T cells, respectively. Senescent T cells contribute to tumorigenesis by inducing inflammation via the release of TNF-α. Metastasis is also induced in tumour cells that express the receptor CXCR3 via the SASP component CXCL11 secreted by senescent endothelial cells. However, CXCL11 also presents anti-tumorigenic activity by recruiting T cells and NK cells at the site of tumour. (C) Tumour apoptosis is induced by IL-29 secreted by senescent T cells. In addition, IL-29 contributes to cancer-specific immune response via the recruitment of NK cells. (D) Senescent tumour cells evade the immune system via the secretion of elevated CXCL12 levels, inducing CXCR4 internalisation in T cells and impairing T cell directional migration. | PMC9434004 | fonc-12-975644-g002.jpg |
0.426957 | 58f379b373d04ff096550f14839248c4 | Potential combination therapies for colorectal cancer. After chemotherapeutic treatment, tumour cells are either killed or become senescent. CAR T cell immunotherapy or senolytic therapy can be used to avoid escape from the senescent state and tumour relapse. CAR T cell immunotherapy targets antigens present on colorectal cancer cells such as NKG2DLs, HER-2, GUCY2C and uPAR. Senolytic therapy targets the SA-β-Gal via the compound SSK1 or inhibits the mitochondrial enzyme GLS1, which is important for tumour cell metabolism. | PMC9434004 | fonc-12-975644-g003.jpg |
0.462954 | 514993ffbfb344e3857bf56e06e97834 | The processes to investigate volume of CSF spaces, including the high-convexity subarachnoid space and CSF spaces of the Sylvian fissure region. Individual CSF images were segmented from 3D-T1-weighted images. Two regions of interest (ROIs) were created for the high-convexity area (blue) and Sylvian fissure region (red), and these ROIs defined by Talairach grid divisions were shown in the ICBM 152 stereotaxic space | PMC9434899 | 12987_2022_362_Fig1_HTML.jpg |
0.423234 | f8a2b9b3cc39403a920a9699c0980dd0 | Box and whisker plots of the normalized volumes for lateral ventricles, high-convexity subarachnoid space, and CSF spaces of the Sylvian fissure region for three groups. Normalized CSF space volumes were expressed as regional volume/intracranial volume | PMC9434899 | 12987_2022_362_Fig2_HTML.jpg |
0.398067 | 2e1c1794fcec4ce1b517f5737ddc32e5 | Relationship between normalized lateral ventricle volume and normalized volume for high-convexity subarachnoid space and normalized volume for CSF spaces of the Sylvian fissure region in patients with INPH and AD. Normalized CSF space volumes were expressed as regional volume/intracranial volume. Blue dots represent INPH subjects while red dots represent AD subjects | PMC9434899 | 12987_2022_362_Fig3_HTML.jpg |
0.535487 | a4c379a03ee94fe886ad30718f3dfa67 | Receiver operating characteristic (ROC) curve in classifying INPH patients and AD patients using lateral ventricle volume/high-convexity subarachnoid space volume ratio | PMC9434899 | 12987_2022_362_Fig4_HTML.jpg |
0.409897 | d70165956d9b49668166375716d7863a | Adherence to clinical checklist, diabetes case. | PMC9435052 | fpubh-10-953881-g0001.jpg |
0.431918 | 3549a42f4b67442589cc2feee885fe5a | Adherence to clinical checklist, angina case. | PMC9435052 | fpubh-10-953881-g0002.jpg |
0.477085 | 67f19b35985b4c00b48bdefbfe5273c9 | The know-do gap of diagnostic questions asked and diagnosis and treatment given for diabetes cases (*p < 0.05, **p < 0.01, ***p < 0.001). | PMC9435052 | fpubh-10-953881-g0003.jpg |
0.483174 | a02932b5fd734c74b2f76f076924e81b | The know-do gap of diagnostic questions asked and diagnosis and treatment given for angina cases (*p < 0.05, **p < 0.01). | PMC9435052 | fpubh-10-953881-g0004.jpg |
0.465213 | f50b6128274c460598cf564d2fe0e92e | Specialty of the clinical coordinator/head of the center. | PMC9437305 | fpubh-10-975527-g0001.jpg |
0.452846 | 5b3c8cb4fd9c468a9462a31b4d4139f4 | Specialist support available. | PMC9437305 | fpubh-10-975527-g0002.jpg |
0.44588 | 4d4e78c08b814a438fef5630e07e4bd9 | Cluster analysis and validation. Clusters were compared on: (A) NPSI (neuropathic pain symptom inventory), (B) BAI (Beck Anxiety Inventory), (C) BDI (Beck Depression Inventory), and (D) PCL-C (Post-traumatic Stress Disorder Checklist-Civilian version) total scores. ****p < 0.0001. | PMC9437424 | fpain-03-947562-g0001.jpg |
0.396515 | 5ee97f74c90b4cf09b6a8b6b7f0d30df | Thermal somatosensory function obtained from QST. Significant group differences were found on the proximal site with respect to: (A) ΔCPT-CDT (delta cold pain threshold-cool detection threshold) and (B) ΔHPT-WDT (delta hot pain threshold-warm detection threshold); and on the distal site with respect to (D) ΔHPT-WDT between the LNP-AS (low or no neuropathic pain-anxiety symptoms) and MNP-AS (moderate neuropathic pain-anxiety symptoms). On the distal site, no group differences were found regarding (C) ΔCPT-CDT (delta cold pain threshold-cool detection threshold). *p < 0.05. | PMC9437424 | fpain-03-947562-g0002.jpg |
0.48376 | 84af98f16f4740a1a5edba2de626d4b2 | Mechanical somatosensory factors obtained from QST. Group differences were not found with respect to (A) VDT (vibration detection threshold) on the proximal site, (B) PPT (pressure pain threshold) on the proximal site, (C) VDT on the distal site, and (D) PPT on the distal site between the LNP-AS (low or no neuropathic pain-anxiety symptoms) and MNP-AS (moderate neuropathic pain-anxiety symptoms). | PMC9437424 | fpain-03-947562-g0003.jpg |
0.482324 | 7035a6e290fb467097fa85d3b1170162 | Comparison of phenotypes with respect to NPSI subscores. NPSI, neuropathic pain symptom inventory; LNP-AS, low or no neuropathic pain-anxiety symptoms; MNP-AS, moderate neuropathic pain-anxiety symptoms. **p < 0.01, ***p < 0.001, ****p < 0.0001. | PMC9437424 | fpain-03-947562-g0004.jpg |
0.464479 | af248cb9b0194abdbe79fa1403c20529 | Psychosocial function. Comparison of phenotypes with respect to the Multidimensional Pain Inventory subscales: (A) pain severity, (B) life interference, (C) support, (D) affective distress and (E) life control. LNP-AS, low or no neuropathic pain-anxiety symptoms. MNP-AS, moderate neuropathic pain-anxiety symptoms. *p < 0.05, ***p < 0.001. | PMC9437424 | fpain-03-947562-g0005.jpg |
0.440113 | f2fb2e90e4bd4d3e8e3bb275916d54f4 | Innate immune response to pre-erythrocytic stages of Plasmodium parasites. Cytoplasmic Plasmodium RNA is sensed by MDA5 which signals via MAVS. MAVS activation ultimately leads to the phosphorylation of transcription factors IRF3 and IRF7 which drive the expression of Type I IFN genes such as IFNα and IFNβ. IFNα,β recruit NK cells to the liver which produce IFNγ which in turn increases autophagy pathways in hepatocytes. Another, yet unidentified, PRR might signal via MAVS to enhance this response. The cell type of origin of the initial Type I IFN response has not been identified and could either be infected hepatocytes or tissue resident innate cells that have taken up parasite material. TLR2 has been shown to be capable of sensing sporozoites, leading to reduced liver stage burden and enhanced inflammatory gene expression in mice. In addition, γδT-cells have been linked to favorable vaccination outcomes in humans and play a role in inducing a protective CD8 T-cell response in concert with CD8+ cDC1s in mice. Created with Biorender. | PMC9437427 | fimmu-13-914598-g001.jpg |
0.452214 | beead2d7b9d646508c0edbb8010425db | Innate sensing mechanisms of Plasmodium blood stages. TLR2 senses Plasmodium GPIs on the cell surface, while TLR7 and 9 recognize Plasmodium DNA in the endosome. In humans, TLR8 also senses degradation products of Plasmodium RNA. TLR engagement drives pro-inflammatory gene expression and a Type I IFN response (only TLR7, 8,9) that is dependent on MyD88 signaling. Plasmodium nucleic acids escape from the lysosome probably through direct association with hemozoin. In analogy to pre-erythrocytic stages, Plasmodium RNA in the cytoplasm is detected by MDA5 leading to MAVS activation and downstream Type I IFN gene expression. In addition, cytoplasmic double stranded (ds)DNA is sensed by AIM2 while Hemozoin is sensed by NLRP3, each leading to inflammasome assembly and enzymatic cleavage of pro-inflammatory mediators like Pro-IL1β. Akin to pre-erythorcytic stages, NK cells have been shown to produce IFNγ downstream of PRR recognition of parasite PAMPs. In ex vivo culture systems of human cells, NK cells have been shown to produce IFNγ in response to innate cell produced IL18 and IL12 which were dependent on TLR8. Created with Biorender. | PMC9437427 | fimmu-13-914598-g002.jpg |
0.494292 | 8c493983db11402a96d388a5e019d327 | Flowchart of policy documents reviewed. | PMC9438078 | bmjopen-2021-059228f01.jpg |
0.434849 | 36b462160f5043958138f9f89dc7acc9 | Results of The Connecticut Smell Test, produced by the CCCRC (Connecticut Chemosensory Clinical Research Center) in the elderly population evaluated in this study (n = 103 individuals) | PMC9438353 | 405_2022_7614_Fig1_HTML.jpg |
0.466589 | f5400c15f70f4a35a4cd1206928c75d0 | Demographic characteristics of individuals with normal olfactory function versus altered olfactory function according to The Connecticut Smell Test, produced by the CCCRC (Connecticut Chemosensory Clinical Research Center). *Fisher–Freeman–Halton test. **Chi-square test | PMC9438353 | 405_2022_7614_Fig2_HTML.jpg |
0.469565 | 4b1c94ea5d1c44c4b6783747929c13b2 | Mean age and standard deviation in the individuals in this research and according to the results of the olfactory test. *Mann–Whitney test | PMC9438353 | 405_2022_7614_Fig3_HTML.jpg |
0.476376 | a2a23c769a04449a8f2665261bf18475 | (A–C) Index colonoscopy with (A) multiple edematous, polypoid-appearing folds with a prominent vascular pattern throughout the proximal colon; biopsies showed mild active colitis with cryptitis and chronic inflammation of the lamina propria (B) erythematous polyps with central blanching in the sigmoid colon; biopsies showed moderate active colitis with superficial erosions, cryptitis, and chronic inflammation of the lamina propria associated with cytomegalovirus (CMV) (C) scattered deep ulcers in the rectum, with surrounding mucosal erythema; biopsies showed moderate-to-severe active proctitis associated with CMV. | PMC9439750 | ac9-9-e00851-g001.jpg |
0.430691 | 7ca98de8511e4f73b04bcfe4225825e6 | (A–B) Histologic findings from follow-up colonoscopy showing (A) persistent cytomegalovirus (CMV) infection with positive immunohistochemistry in sigmoid mucosa and (B) positive CD20 staining in sigmoid mucosa suggesting lymphoma. | PMC9439750 | ac9-9-e00851-g002.jpg |
0.437472 | 92dd87036cc94c0c82dcb6e6e1be3083 | Positron emission tomography (PET)/Computed tomography (CT) demonstrating diffuse hypermetabolic foci throughout the rectosigmoid colon, bilateral hypermetabolic adenopathy on both sides of the diaphragm, and equivocal bone marrow involvement. | PMC9439750 | ac9-9-e00851-g003.jpg |
0.497034 | 75c569d256af4ad2b136e99cf77aa968 | Spatial attention comparison between CBAM and FAM in SegNet. We visualized the spatial attention for sixteen attention modules of SegNet when using CBAM and FAM. c is the lung image segmented from the input CT image. d and e are corresponding lesion label and shape prior | PMC9441194 | 11554_2022_1249_Fig10_HTML.jpg |
0.487841 | 9c87eb47eaf440c08f54eb266272bb5d | The comparison of the segmentation results on lesions of COVID-19 CT images by applying various combinations of SegNet and attention modules | PMC9441194 | 11554_2022_1249_Fig11_HTML.jpg |
0.461553 | 71284c2883e34813b9defb9ad0548e17 | Diagram of training networks integrated with various attention modules. a–c and d–f show that FAM accelerates the network training as well as minimizes the loss | PMC9441194 | 11554_2022_1249_Fig12_HTML.jpg |
0.458394 | cd06788ad14841b99bde09af019a0c72 | The overview of focal attention module, which consists of channel attention module and spatial attention module | PMC9441194 | 11554_2022_1249_Fig1_HTML.jpg |
0.426174 | 49ee4602990040bb9b73a4de799b00b1 | a The channel attention module: max-pooling, average-pooling outputs, and a multi-layer perceptron; b the spatial attention module obtains a rough shape prior of the lesion region by median filtering and distance transformation | PMC9441194 | 11554_2022_1249_Fig2_HTML.jpg |
0.422725 | 722f590aa52f4809b11319676ce783aa | The process of eliminating noise pixels in the lung region of CT image step by step. a A lot of noise pixels (i.e. pulmonary trachea and pulmonary vessels inside the lung region). b Applying median filtering to partially eliminate the noise pixels. c Applying distance transformation to further eliminate the noise pixels and extract the main lesion region | PMC9441194 | 11554_2022_1249_Fig3_HTML.jpg |
0.410252 | 0ff1d756975e4bafa39d54971beeef81 | The distributions of connected regions in a lung image without/with applying sequential median filtering, with applying distance transformation | PMC9441194 | 11554_2022_1249_Fig4_HTML.jpg |
0.431028 | dfde2a5c25ec4a7db000a5789a9c0f35 | Distance maps of several lung images: a lung region is segmented from CT images in the dataset. b Distance maps of lung images obtained by distance transformation. c By comparing the distance map with the corresponding lesion label, the main lesion region is extracted | PMC9441194 | 11554_2022_1249_Fig5_HTML.jpg |
0.439979 | d9dc5d46e4a74b5c9d35a80976c5b276 | A numerical example of distance transformation: a a binary image containing several connected regions; b the distance map of (a); c is the normalization of (b) | PMC9441194 | 11554_2022_1249_Fig6_HTML.jpg |
0.423734 | 2d53c9ae8d1e4952a21c0707f1e97f01 | The dataset contains segmentation labels for the left lung, right lung and COVID-19 lesions. The lung region is segmented based on the lung label | PMC9441194 | 11554_2022_1249_Fig7_HTML.jpg |
0.492611 | 80bce0f9b50b4dfb86424cd9534b9d85 | The structure of the integration of FAM with the network | PMC9441194 | 11554_2022_1249_Fig8_HTML.jpg |
0.430405 | 1e37e728626f41afb086597db0c1e9e5 | The workflow of attention modules integrated with SegNet | PMC9441194 | 11554_2022_1249_Fig9_HTML.jpg |
0.419262 | 109d960899744ae697195f24bc28f508 | Characteristics of the gut microbiota composition among the four groups. (a) The distributions of the relative abundance of phylum level in the four groups. (b) The top 30 genera in the four groups were listed by heat map. SG: superficial gastritis; AG: atrophic gastritis; GMAH: gastric mucosal atypical hyperplasia; GC: gastric cancer. | PMC9441395 | JO2022-9971619.001.jpg |
0.452506 | 093978a2803f41969dd718af75852b0d | Comparison of the microbiota alpha diversity among the four groups. The community richness index ACE (a) and chao1 (b) and the community diversity index Shannon (c) and Simpson (d) were used to assess the alpha diversity. ∗p < 0.05. SG: superficial gastritis; AG: atrophic gastritis; GMAH: gastric mucosal atypical hyperplasia; GC: gastric cancer. | PMC9441395 | JO2022-9971619.002.jpg |
0.404708 | b24eac3a2b494706aa2115d8894caefb | Comparison of the microbiota beta diversity among the four groups. The PCoA was used to evaluate the beta diversity by unweighted UniFrac distances (a), weighted UniFrac distances (b), and Bray-Curtis distance matrix (c). ∗p < 0.05. SG: superficial gastritis; AG: atrophic gastritis; GMAH: gastric mucosal atypical hyperplasia; GC: gastric cancer. | PMC9441395 | JO2022-9971619.003.jpg |
0.469777 | 0694aa7aa8104160afc3b784dfb82e04 | Comparing the distributions of the gut microbiota structure and composition among the four groups. (a) The cladogram illustrates the phylogenetic distribution of microbial lineages among the four groups. Differently abundant microbiota is listed and marked by different color (b). SG: superficial gastritis; AG: atrophic gastritis; GMAH: gastric mucosal atypical hyperplasia; GC: gastric cancer; p: phylum; c: class; o: order; f: family; g: genus. | PMC9441395 | JO2022-9971619.004.jpg |
0.411008 | db1ce36cd9e84346b5f241037ff56ae1 | Comparison of the abundance of the 21 LDA-differentiated genera between non-HP and HP infection groups. Enterococcus (a), Lachnospiraceae_unclassified (b), Tyzzerella_3 (c), Roseburia (d), Butyricicoccus (e), and Dorea (f) were less abundant in the HP infection group, while the levels of Halomonas (g) and Burkholderiales_unclassified (h) were significantly higher in the HP infection group. ∗p < 0.05. HP: Helicobacter pylori. | PMC9441395 | JO2022-9971619.005.jpg |
0.439168 | a687021c3d2d4a569a5d1a0e359d95c4 | Comparison of the abundance of the 21 LDA-differentiated genera between ≤50 age and >50 age groups. The levels of Erysipelotrichaceae_unclassified (a), Actinomyces (b), Lachnospiraceae_unclassified (c), and Lachnoclostridium (d) genus were lower in the >50 age group, while Alloprevotella (e) and Halomonas (f) were significantly higher in the ≤50 age group. Moreover, Lachnoclostridium (g) and Prevotella_7 (h) were significantly different among underweight, normal, and overweight BMI groups. ∗p < 0.05. BMI: body mass index. | PMC9441395 | JO2022-9971619.006.jpg |
0.394268 | 89ddfd2af8364babb016a4a33351b274 | Comparison of KEGG pathways among the four groups. The pathways demonstrated significant differences between the SG and AG groups (a), the SG and GMAH groups (b), the SG and GC groups (c), the AG and GMAH groups (d), the AG and GC groups (e), and the GMAH and GC groups (f). ∗p < 0.05. SG: superficial gastritis; AG: atrophic gastritis; GMAH: gastric mucosal atypical hyperplasia; GC: gastric cancer. | PMC9441395 | JO2022-9971619.007.jpg |
0.473593 | f282d5f26d854662a8b2ce6d54165cb7 | Sideways (right and left) head movement. | PMC9442116 | gr1.jpg |
0.539678 | 5dc714255a1f48a2a9dfebbaa4bfb08f | Walking in a straight line while gazing forward; walking in a straight line while looking upwards and downwards. | PMC9442116 | gr10.jpg |
0.524437 | 31b91fc0ae46475ab2a03ef3a225df9b | Walking in a straight line while looking sideways; walking in a straight line while throwing a ball from one hand to the other. | PMC9442116 | gr11.jpg |
0.416755 | 89a3266ed04a46d294132726d4ba9a24 | Graphic representation of mean differences between the variables quantification of dizziness (Qtont), the Dizziness Handicap Inventory (DHI), the physical score (físico), the emotional score (emocional), and the functional score (funcional), before and after therapy. | PMC9442116 | gr12.jpg |
0.431447 | 76c7b0445022456c8c986bf24911b6f4 | Graphic representation of the correlation between the quantification of dizziness scale and the DHI test, before and after treatment, in the metabolic dizziness group. | PMC9442116 | gr13.jpg |
0.414276 | 0bd849d8e4e24fa6a507201275b6aee0 | Graphic representation of the correlation between the quantification of dizziness scale and the DHI test, before and after treatment, in the vascular dizziness group. | PMC9442116 | gr14.jpg |
0.497209 | ecf8edc01dad4c068aaf77326439a6bf | Upward and downward head movement. | PMC9442116 | gr2.jpg |
0.460346 | 84f180f378474c6e806b29301ebb2367 | Sideways (right and left) eye movement. | PMC9442116 | gr3.jpg |
0.45414 | f9639959ed8d4252b578a80ddf82f67f | Upward and downward eye movement. | PMC9442116 | gr4.jpg |
0.436685 | 8bea3e2d83804bf6bb2544ec6bcdb8e4 | Fixing the gaze on a finger that is moved further and closer. | PMC9442116 | gr5.jpg |
0.45419 | 6a61a5cedb38427cb8b56f89f803e7dc | Throwing a ball from one hand to the other while keeping the gaze fixed. | PMC9442116 | gr6.jpg |
0.533359 | d4d7bc5dd1dd4b3e8e5c26d4b91ebf38 | Sitting, standing up and sitting again. | PMC9442116 | gr7.jpg |
0.53356 | 4773fcd6436547f7beb3f48108d0f61d | Picking up objects on the floor while keeping the gaze fixed. | PMC9442116 | gr8.jpg |
0.456974 | fed973ae578b411d9df0919503a8a690 | Lifting and putting down a ball while keeping the gaze fixed. | PMC9442116 | gr9.jpg |
0.395851 | 811cbd4e37f349e5b40e6f00a0b6a9b6 | Ring theory of personhood. | PMC9442489 | bmjopen-2022-064029f01.jpg |
0.50902 | 1b69d6c4b5184a229c5f558be98b4d41 | SSR in SEBA process. SEBA, systematic evidence-based approach; SSR, systematic scoping review. | PMC9442489 | bmjopen-2022-064029f02.jpg |
0.445016 | 56f6896ab7354cdc90cbe3a81015de98 | Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) flow chart. | PMC9442489 | bmjopen-2022-064029f03.jpg |
0.429819 | 8953ecf0262143b29026c549949b698c | Framework to understand MD. MD, moral distress. | PMC9442489 | bmjopen-2022-064029f04.jpg |
0.492372 | d9b05734d4324f90b6bacaf5fc7566e7 | Different approaches are used by vaccines against SARS-CoV-2 | PMC9442597 | 11356_2022_22661_Fig1_HTML.jpg |
0.412286 | b6311ddbbfb74cf68ff25563386c2646 | Results of the clinical trial of inactivated vaccines against SARS-CoV-2 considering trials being conducted among people with different age groups, geographical diversity, and in distinct phases giving an idea that the maximum number of trials are being conducted in China and nearly 73.44% trials are being conducted among adults, i.e., 18 years and older and 1.56% on older adults and child, adult, and older adult. Also, maximum trials are in phase 3 of the clinical trial. Data obtained from clinicaltrial.gov (accessed on October 31, 2021) | PMC9442597 | 11356_2022_22661_Fig2_HTML.jpg |
0.409959 | 44c1b75c4efe41e7bcd3562b87f71e09 | Results of the clinical trial of nucleic acid-based vaccines effective against SARS-CoV-2 considering trials being conducted among people with different age groups, geographical diversity, and in distinct phases giving an idea that the maximum number of trials are being conducted in the US among adults, i.e., nearly 60.19% trials among 18 years and older and 0.93% of trials on child, adult. Also, maximum studies were found to be in phase 2 of the clinical trial, and the least number of trials were found to be in early phase 1. Data obtained from clinicaltrial.gov (accessed on October 31, 2021) | PMC9442597 | 11356_2022_22661_Fig3_HTML.jpg |
0.424151 | a736b041c67042219b712a463da4b582 | Results of the clinical trial of viral vector vaccines effective against SARS-CoV-2 considering trials being conducted among people with different age groups, geographical diversity, and in distinct phases giving an idea that the maximum number of trials are being conducted in China and 64.71% on adults, i.e., 18 years and older while only 1.96% trials on child, adult, and older adult. Also, maximum studies were found in phase 1 of the clinical trial. Data obtained from clinicaltrial.gov (accessed on October 31, 2021) | PMC9442597 | 11356_2022_22661_Fig4_HTML.jpg |
0.457641 | 39ceafb8e098480fa5f2f42638ec1643 | Results of the clinical trial of protein subunit vaccines effective against SARS-CoV-2 considering trials being conducted among people with different age groups, geographical diversity, and in distinct phases giving an idea that the maximum number of trials are being conducted in China among adults and 65.22% trials were conducted on adults, older adults, 1.45% trials on child, adult, and older adult. Also, maximum studies were found to be in phase 1 of the clinical trial. Data obtained from clinicaltrial.gov (accessed on October 31, 2021) | PMC9442597 | 11356_2022_22661_Fig5_HTML.jpg |
0.47153 | 7d6ea5b081d04342829343ad11f37c50 | Results of the clinical trial of live-attenuated, APC, and VLP vaccines effective against SARS-CoV-2 considering trials being conducted among people with different age groups, geographical diversity, and in distinct phases giving an idea that the maximum number of trials are being conducted in Canada and USA among adults, i.e., 18 years and older (54.55%), 9.09% in older adult and 9.09% in child, adult, and older adult. Also, maximum studies were found to be in phase 1 of the clinical trial and the least number of trials were found to be in phase 2ǀ3. Data obtained from clinicaltrial.gov (accessed on October 31, 2021) | PMC9442597 | 11356_2022_22661_Fig6_HTML.jpg |
0.453597 | 2aacffaf59ed455ba8b53c49ce524496 | Schematic (left) showing the microneedle (MN) patch design for vaccine delivery via skin and generating an immune response. MN patch loaded with the vaccine in tips (right) and delivered to mice via skin and transfection of DNA vaccine over 120 h, showing good reproducibility. Copyright (2021) American Chemical Society | PMC9442597 | 11356_2022_22661_Fig7_HTML.jpg |
0.421069 | cc86553446184698a22d4f72641c98c6 | A Commercially available Cissus quadrangularis powder; B Carrageenan hydrogel (control); C 10% w/v Cissus quadrangularis hydrogel; D 20% w/v Cissus quadrangularis hydrogel; E 30% w/v Cissus quadrangularis hydrogel | PMC9442992 | 12903_2022_2409_Fig1_HTML.jpg |
0.395741 | a114b59844bf4a8eaee13d2b381f8e0b | Comparative analysis of antioxidant activity among the study groups | PMC9442992 | 12903_2022_2409_Fig2_HTML.jpg |
0.387003 | bebe6537eaa540cb8b82f6625691fda3 | Comparative analysis of biocompatibility among the study groups | PMC9442992 | 12903_2022_2409_Fig3_HTML.jpg |
0.434964 | acf6531c5379429eb3232d3828845f60 | A Porous microstructure of carrageenan hydrogel. B 10% w/v aqueous extract of Cissus quadrangularis hydrogel showing evenly dispersed particles of Cissus quadrangularis
C 20% w/v aqueous extract of Cissus quadrangularis hydrogel showing evenly dispersed dense arrangement of Cissus quadrangularis particles. D 30% w/v aqueous extract of Cissus quadrangularis hydrogel showing clumping of Cissus quadrangularis particles | PMC9442992 | 12903_2022_2409_Fig4_HTML.jpg |
0.44002 | 7d701e3bc9144da2afdbd7c995a8a1c2 | Higher magnification view of 30% w/v Cissus quadrangularis hydrogel (Group IV) with evident clumping of Cissus quadrangularis particles | PMC9442992 | 12903_2022_2409_Fig5_HTML.jpg |
0.4795 | 0ed5321f87b64565ad0b86b7367101ff | Number of people in each age group according to the level of physical activity before the experiment | PMC9443638 | 10209_2022_911_Fig1_HTML.jpg |
0.445818 | 9d39a7706e43484aae58c8ec61d43153 | Number of people in each age group according to the level of physical activity after the experiment | PMC9443638 | 10209_2022_911_Fig2_HTML.jpg |
0.416978 | b9f0259132d74ba6809216a39c4e6237 | In a, c e d - bilateral sulcus vocalis (arrows); in b, sulcus vocalis to the left side (single arrow). | PMC9443704 | gr1.jpg |
0.464498 | 07a98fc6057441069c587944d9e447a8 | Trends in United States incidence rates (per 100,000) of oral cavity and pharynx cancers from 1975 to 2018 according to groupings of human papillomavirus (HPV)-like association*. *Surveillance, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) SEER*Stat Database: Incidence - SEER Research Data, 9 Registries, Nov 2020 Sub (1975-2018) - Linked To County Attributes - Time Dependent (1990-2018) Income/Rurality, 1969-2019 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2021, based on the November 2020 submission. | PMC9444004 | fonc-12-980900-g001.jpg |
0.457431 | 1c0bf1afb26e426f9bfa9a3d527e2627 | Age-specific, average annual (2014-2018) incidence rates (per 100,000) of oral cavity and pharynx cancers for various sex/race groups according to groupings of human papillomavirus (HPV)-like association**. **Surveillance, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) SEER*Stat Database: Incidence - SEER Research Data, 9 Registries, Nov 2020 Sub (1975-2018) - Linked To County Attributes - Time Dependent (1990-2018) Income/Rurality, 1969-2019 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2021, based on the November 2020 submission. (Asian Pacific Islander and American Indian and Alaskan Native case counts were too low within age/sex groups to permit the similar evaluation presented here and therefore were excluded from graphical representation.). | PMC9444004 | fonc-12-980900-g002.jpg |
0.569991 | e128b8ead6bd47b2b0cb4f5e4f829660 | Recent trends in United States relative five-year survival rates of oral cavity and pharynx cancers according to groupings of human papillomavirus (HPV)-like association***. ***Surveillance, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) SEER*Stat Database: Incidence - SEER Research Data, 18 Registries, Nov 2020 Sub (2000-2018) - Linked To County Attributes - Time Dependent (1990-2018) Income/Rurality, 1969-2019 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2021, based on the November 2020 submission. | PMC9444004 | fonc-12-980900-g003.jpg |
0.48225 | 0c943f1143774dfc8fba7200399714d0 | Hierarchical analysis fusion neural network model. | PMC9444362 | CIN2022-1926227.001.jpg |
0.408752 | 43a1b9ccb4444e1ab64b09f9c513401c | Prediction model. | PMC9444362 | CIN2022-1926227.002.jpg |
0.418068 | 23133c4fcbb84d2cbcd70b0c318d880d | Ecological planning flow chart. | PMC9444362 | CIN2022-1926227.003.jpg |
0.38928 | e55072628a2d46e0832a06d56c93b6a8 | Ecological spatial structure evaluation logic. | PMC9444362 | CIN2022-1926227.004.jpg |
0.48728 | f3406a110f3346b0852df577096af4c1 | Affiliation function diagram. | PMC9444362 | CIN2022-1926227.005.jpg |
0.583666 | 2be02d9e1b2e469188458a5bf6ddb1e8 | Plot of the inspection of the effect of training via the network. | PMC9444362 | CIN2022-1926227.006.jpg |
0.450794 | c10b7e51f243473ab1cdf5016ac1e733 | Neural network training state effect graph. | PMC9444362 | CIN2022-1926227.007.jpg |
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