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0.428574 | 367ba828676e451a8086f2e5eda691b5 | miRNA–microbiota axis in PD. Microbial dysbiosis can potentiate the dysregulation of certain miRNAs, which can then target mitochondria and inflammatory pathways in the gut, leading to a proinflammatory response and to the loss of intestinal barrier integrity. This will allow miRNAs to travel freely or within vesicles through the blood or through the vagus nerve and reach the brain. Within the brain, miRNAs can target mitochondria and activate neuronal innate immunity, ultimately leading to PD hallmarks. Created with Biorender. | PMC10215921 | biomedicines-11-01349-g005.jpg |
0.441902 | bfb0956d0877469fbfe49ebf9de88590 | Axial view of fusion (a,c,e,g,i,k) and T2-weighted (b,d,f,h,j,l) images from a DPN patient (54-year-old female). ROI placement for measurement of ADC and FA. The ROIs of seeding points were placed at two levels of one nerve root in the fusion images: one was at the level of middle spinal body (a,e,i) and another was at the level of inferior spinal disc (c,g,k). Yellow ROIs represent the L4 nerve roots; blue ROIs represent the L5 nerve roots; and green ROIs represent the S1 nerve roots. | PMC10216388 | brainsci-13-00828-g001.jpg |
0.397388 | fc8b49b48df74d4fb2677893a0385c4f | Lumbosacral nerve root fiber track. Fiber track of L4, L5, and S1 nerve roots is shown in different colors. (a) 55-year-old female HC. (b) 54-year-old female type 2 diabetes patient. The following parameters were used for fiber track processing: FA threshold 0.15, minimum fiber length 10 mm (smaller fibers were excluded), and smoothness 27. | PMC10216388 | brainsci-13-00828-g002.jpg |
0.472974 | 0ab50e45511248a88dc6320275c0375f | Box plots of DTI metrics in HC and DPN groups. FA values (a) were significant lower in DPN than in HCs (p < 0.001); ADC values (b) were higher in DPN than in HCs (p < 0.001). FA values have no unit; ADC values are 10−3 mm2/s. The plots illustrate the 25th and 75th percentiles (boxes), adjacent values (asterisk), outliers (dots), and median values of the groups (black horizontal lines in grey boxes). | PMC10216388 | brainsci-13-00828-g003.jpg |
0.411835 | 0a98767c902b4f79ab69f4850496c0c7 | ROC curves of the sensitivity and specificity of FA (a) and ADC (b) values in the lumbosacral nerve roots. The areas under the curves (AUC) are shown in the bottom right corner. FA had the best performance for diagnosing DPN (AUC values of FA is 0.716). | PMC10216388 | brainsci-13-00828-g004.jpg |
0.40701 | 1e27277a9e5449989dd0f7ced7b29ab6 | CONSORT flowchart of the analyzed study population. CT = computed tomography. | PMC10216416 | cancers-15-02850-g001.jpg |
0.456708 | 1eebfc944cbb4d5583f1939929af1644 | Calibration and discrimination for classification of PET positivity for different radiomic approaches. Results of penalized logistic regression (logit) and random forest are shown. In the lowess-smoothed calibration plot (first row), the observed outcome frequency is plotted against the predicted outcome probability. The closer the curve is to the diagonal, the better the calibration. The receiver operating characteristic (second row) plots the true positive rate against the false positive rate by varying thresholds (not shown). Discrimination is best for the curve that is closest to the left upper corner. Legend: PCA = principal component analysis; RF = random forest. | PMC10216416 | cancers-15-02850-g002.jpg |
0.386385 | d34da067434948f5aab5b21d18d61211 | Visualization of hand-crafted radiomic features and deep features. (A) is an example of a PET-positive lymph node. (B) is an example of a PET-negative lymph node. Selected hand-crafted and random selections of feature map outputs of the third layer of the deep CNN are presented, respectively. Sensitivity analysis: random forest. | PMC10216416 | cancers-15-02850-g003.jpg |
0.486035 | 777df28b05dc4ab4bdf788acb0fba348 | Time-dependent expression of IDO2 after treatment with TCDD in wildtype and AhR-knockout MCF-7 cells. Cells were treated with 1 nM TCDD for various time points for 3, 6, 12, 24, and 48 h and then harvested for RNA extraction and IDO2 expression analysis via qPCR after 24 h treatment. TCDD stock solution was dissolved in DMSO and control cells received 0.1% DMSO. The expression was corrected against the housekeeping gene ß-actin. Results are presented as mean ± SEM, and the y-axis represents mRNA expression level. The expression level of IDO2 mRNA in control cells is shown in dotted lines; * significantly higher than the control (p < 0.05). | PMC10216785 | cells-12-01433-g001.jpg |
0.366963 | 27237d7dbe154dbab63e6aefb49cc16f | Effect of AhR ligands on the expression of IDO1 and IDO2 in MCF-7 cells. MCF-7 cells were treated with FICZ (100 nM), Kyn (50 µM), TCDD (1 nM), BaP (2.5 µM), and TRAP PM (10 µg/mL) for 24 h. In addition, cells were treated with 100 U/mL IFNγ (data not shown), which induced a 245-fold increase in IDO1 but had no effect on IDO2 expression. Cells were harvested for RNA extraction and (A) IDO2 and (B) IDO1 expression analysis via qPCR after 24 h treatment. The expression was corrected against the housekeeping gene ß-actin. Results are presented as mean ± SD, and the y-axis represents the mRNA expression level; * significantly higher than control (p < 0.05). | PMC10216785 | cells-12-01433-g002.jpg |
0.427324 | b6f420b089384d60ac180ff824b631f9 | TCDD-induced IDO2 promoter activity is AhR- and XRE-dependent: (A) Schematic illustration of the promoter construct of the mouse ido2 gene containing 3275 bp upstream of the transcriptional start site cloned into a luciferase (luc) reporter vector. The positions of the short-tandem repeat (STR) at −2478 bp containing four putative XRE consensus sequences, two XRE consensus sites at −1949 bp and −1400 bp, and one recognition site for ISRE at −1333 bp are shown. (B) Wildtype (WT) and AhR-knockout (AhR−/−) MCF-7 cells were transfected with the IDO2 luciferase reporter construct containing 3275 bp of the human ido2 gene promoter region; a, significantly higher than WT control cells (p < 0.05); b, significantly lower than treated WT cells. (C) MCF-7 WT cells were transfected with the full-length (3275 bp) IDO2 reporter plasmid, a −2325 bp deletion construct, and a 432 bp (Δ−2563-2131) construct containing the STR sequence with four XRE core elements. Cells were transfected for 16 h and treated with 1 nM TCDD or 100 U/mL IFNγ for 6 h. Relative luciferase activity units are given as mean values of triplicates as a result of three independent experiments; *, significantly different from control cells (p < 0.05). | PMC10216785 | cells-12-01433-g003.jpg |
0.439543 | be6feff7b0874d738930dcccd43a56e9 | ChIP assay for STR region of the human IDO2 promoter. TCDD induces the recruitment of AhR to the STR region. MCF-7 WT cells were treated with 1 nM TCDD or 100 U/mL IFNγ, for 6 h, and anti-AhR antibodies were used for immunoprecipitation. Data show the ratio of the enrichment of the promoter region target in TCDD-treated cells. The increase in the enrichment was calculated relative to that of the negative control with anti-IgG. qPCR was performed to analyze the levels of AhR binding to the STR on the IDO2 promoter. Error bars indicate standard deviations from the mean of at least three experiments; * significantly higher than control (p < 0.05). | PMC10216785 | cells-12-01433-g004.jpg |
0.401208 | 276ce45e86214e87969848e0006a380b | Expression of IDO2 mRNA in cancer. The TIMER2.0 tool was used to assess IDO2 mRNA expression in the TCGA dataset across cancer types using the Gene_DE module under the “Exploration” Table Tumor expression is depicted in red, and when available, normal samples are depicted in blue. Samples in purple are metastatic samples (only available in SKCM). *: p-value < 0.05; **: p-value < 0.01; ***: p-value < 0.001. The abbreviations for cancer types are as follows: ACC—adrenocortical carcinoma, BLCA—bladder urothelial carcinoma, BRCA—breast invasive carcinoma, CESC—cervical and endocervical cancer, CHOL—cholangiocarcinoma, COAD—colon adenocarcinoma, DLBC—diffuse large B-cell lymphoma, ESCA—esophageal carcinoma, GBM—glioblastoma multiforme, HNSC—head and neck Cancer, KICH—kidney chromophobe, KIRC—kidney renal clear cell carcinoma, KIRP—kidney renal papillary cell carcinoma, LAML—acute myeloid leukemia, LGG—low-grade glioma, LIHC—liver hepatocellular carcinoma, LUAD—lung adenocarcinoma, LUSC—lung squamous cell carcinoma, MESO—mesothelioma, OV—ovarian serous cystadenocarcinoma, PAAD—pancreatic adenocarcinoma, PCPG—pheochromocytoma and paraganglioma, PRAD—prostate adenocarcinoma, READ—rectum adenocarcinoma, SARC—sarcoma, SKCM—skin cutaneous melanoma, STAD—stomach adenocarcinoma, TGCT—testicular germ cell tumors, THCA—thyroid carcinoma, THYM—thymoma, UCEC—uterine corpus endometrial carcinoma, UCS—uterine carcinosarcoma, UVM—uveal melanoma. | PMC10216785 | cells-12-01433-g005.jpg |
0.355797 | e7c43e6128db447d98e4d2f8b8fbdce5 | Expression of IDO2 in breast cancer: (A) The Breast Cancer Gene−Expression Miner v4.9 tool was used to assess IDO2 mRNA expression (RNA-seq) in the combined TCGA and GTEx datasets. (B) The Breast Cancer Gene−Expression Miner v4.9 tool was used to assess IDO2 mRNA expression (RNA-seq) in the combined TCGA and SCAN-B datasets as a function of PAM50 breast cancer subtypes, as indicated. For both (A,B), sample numbers are indicated in parentheses beneath the plot. Statistical analysis is an embedded feature of this tool, described in Materials and Methods. Welch t-test, p-value < 0.001. | PMC10216785 | cells-12-01433-g006.jpg |
0.466623 | 46e919658a6b481fa17e8a7bb44b3a66 | Expression of IDO2 in Ki67-low and Ki67-high breast cancers. The Breast Cancer Gene−Expression Miner v4.9 tool was used to assess IDO2 mRNA expression (1568638_a_at, Affymetrix expression data) in breast tumors that were Ki67-low vs. Ki67-high, as assessed via Ki67 immunohistochemistry. Statistical analysis is an embedded feature of this tool with the Welch t-test’s p-value included in the plot inset. Sample numbers are indicated in parentheses beneath the plot. | PMC10216785 | cells-12-01433-g007.jpg |
0.452871 | f2b7d5653395420194468ae2c64270df | Mutations in the nucleocapsid gene of SARS-CoV-2 from patients with COVID-19 and the strategy used to reveal the mutation responsible for the N gene (N2 target region) amplification delay in the GeneXpert® System and Cepheid Xpert Xpress SARS-CoV-2 assay kit (GX) results. Orange bases indicate the N2 target region for Sanger sequencing of the nucleocapsid gene; the genome positions are numbered according to the reference genome (Wuhan-HU-1; NC_045512.2). The primers and probe for the US Centers for Disease Control and Prevention (CDC) primer and probe targets, the Japan National Institute of Infectious Disease (NIID) primers, and the primers designed for the present study are shown. The GX primer targets were very similar to those of the CDC-published PCR primer sets. Green and blue bases indicate the location of the 29179: G/T mutation that spans five nucleotides upstream of the 3’ end of the CDC forward primer (possibly the same as the GX primer). Yellow and blue bases indicate other mutation locations: one within the CDC reverse primer (29218: C/T) and two in regions unrelated to any primer or probe (28983: A/G; 29253: C/T). Blue-only bases indicate previously described N gene mutations on the probe binding site that resulted in GX assay failure and instability (29197: C/T; 29200: C/T or A; 29203: C/T). | PMC10217001 | cimb-45-00262-g001.jpg |
0.449883 | 22ee8ba7f786488d89f6191066bb1ddc | Comparison between N2 and E Ct values analyzed through GX. A total of 354 cases with positive or presumptive positive GX results were correlated with two Ct values of N2 and E. Undetectable cases in which GX failed to yield Ct values were plotted with Ct values of 48. Red dots indicate cases with the G29179T mutation. | PMC10217001 | cimb-45-00262-g002.jpg |
0.485744 | 765b40f4490f4e3b89c9103418ec296d | Phylogeny of Nextclade and Pangolin lineages. Phylogenetic tree of SARS-CoV-2 showing the distribution of sequences from 33 cases in this study. Each strain classified by Pangolin Lineage is the same color-coded as in Table 1. The numbers also represent the case numbers as listed in Table 1. | PMC10217001 | cimb-45-00262-g003.jpg |
0.447796 | b3475480e6224ec19027eed3996eb7f4 | In vitro characterization of DTPA-700DX-MB. (A) Scheme for conjugation of IRDye700DX-NHS and DTPA-ITC to the minibody to generate DTPA-700DX-MB. (B) Normalized photophysical spectra (absorbance and emission at 620 excitation) of 5 µM NHS-IRDye700DX (left) and 5 µM DTPA-700DX-MB (right) in PBS. (C) Bound and internalized fractions of 111In-labelled DTPA-700DX-MB after 1, 2.5, or 24 h incubation of 3T3 or 3T3-FAP cells at 37 °C. (D) Half-maximal inhibitory concentration. (E) Singlet oxygen production as measured by bleaching of reporter molecule p-nitrosodimethylaniline (RNO). (F) Cell viability of 3T3 and 3T3-FAP cells after incubation of varying doses of DTPA-700DX-MB for 2.5 h and subsequent irradiation with 60 J/cm2 200 mW/cm2 690 nm light. Non-irradiated samples are taken as controls to determine dark toxicity of DTPA-700DX-MB. | PMC10217124 | cells-12-01420-g001.jpg |
0.401568 | 316947c1b3074e8ca53d96e9787803e8 | In vivo tumour targeting of DTPA-700DX-MB in subcutaneous PDAC299. (A) Characterization of the PDAC299 model, showing excessive tumour stroma formation and presence of activated fibroblasts, as illustrated by FAP expression and collagen deposition, as shown in the Sirius red staining. (B) In vivo biodistribution depicted as percentage of injected activity dose per gram of tissue at 4, 24, or 48 h after injection of 0.3 nmol 1 MBq 111In-labelled DTPA-700DX-MB. One group of mice was co-injected with a 7.4-fold excess unlabelled minibody. ** p < 0.01, *** p < 0.001. (C) Tumour-to-blood ratios calculated from the biodistribution data. (D) Fluorescence imaging of two mice at 24 h post injection of 0.3 nmol 111In-labelled DTPA-700DX-MB; one mouse was co-injected with a 7.4-fold excess unlabelled minibody (right). (E) Autoradiography of PDAC299 tumour sections upon injection of 0.3 nmol 10 MBq 111In-labelled DTPA-700DX-MB and FAP IHC density maps, which represent the FAP IHC staining in resolution comparable to the autoradiography. | PMC10217124 | cells-12-01420-g002.jpg |
0.451329 | 69c55dcb65e4482f8cd9dc1b233f8e5f | Radiographs at 13 years and 8 months postoperatively (26 years old) demonstrated stable
proximal hardware migration and soft tissue paucity. | PMC10233633 | 10.1177_15589447221130083-fig5.jpg |
0.476577 | 8843f1ebfe3a4b208f0d210a93f5bca6 | Preoperative examination at age 26 years demonstrated sinus tract with exposed
hardware. | PMC10233633 | 10.1177_15589447221130083-fig6.jpg |
0.457481 | 7031073274f84af3a47a462f2298f391 | Intraoperative examination revealed proximal migration of hardware with significant
bony incorporation. All hardware was successfully removed. | PMC10233633 | 10.1177_15589447221130083-fig7.jpg |
0.430552 | 2fcf6b6dd86b4c3c827ab86d29d9c796 | miR-181b-5p agomir promotes neurological function recovery and reduces infarct volume in MCAO rats.(A) Schematic overview of the construction of a stroke model in rat and miR-181b-5p treatment. (B) Neurological deficiency evaluation by Zea Longa scores (n = 10). **P < 0.01; ***P < 0.001 for comparison on day 14. (C) Infarct volume evaluation by TTC staining; the infarct lesion remained unstained and the contact brain tissue stained red. miR-181b-5p agomir treatment reduced cerebral infarction volume ratio compared with the agomir-Ctrl group, while miR-181b-5p antagomir induced larger infarction volume. (D) Quantitative analysis of infarction volume ratio (n = 5 per group). ***P < 0.001, vs. NC; ###P < 0.001, vs. Antagomir-Ctrl. Data are expressed as means ± SD and were analyzed using one-way analysis of variance followed by least significant difference test. Ctrl: Control; i.v.: intravenous injection; MCAO: middle cerebral artery occlusion; NC: normal control; ns: no significance; TTC: 2,3,5-triphenyltetrazolium chloride. | PMC10233761 | NRR-18-1983-g002.jpg |
0.409324 | 51bb455fceee477e8a3bd881a8c52972 | miR-181b-5p agomir promotes angiogenesis in rat brain after MCAO.(A) Microvessel density measurement using CD31 immunofluorescence (Alexa Fluor 594, red). After miR-181b-5p agomir treatment, CD31 expression levels were significantly upregulated, which indicated that miR-181b boosted angiogenesis in MCAO rat brain; the miR-181b-5p antagomir group showed a significant reduction of CD31 expression. Scale bars: 50 μm. (B) Quantitative analysis of CD31 immunofluorescence intensity. (C) Western blotting of ischemic penumbra brain tissues. After MCAO, miR-181b upregulation increased VEGF expression and decreased ES expression possibly through inhibiting the expression of PTEN and activating the Akt pathway. (D) Quantitative analysis of western blot results. Data are expressed as means ± SD (n = 5). ***P < 0.001, vs. NC; ##P < 0.01, ###P < 0.001, vs. Agomir-Ctrl or Antagomir-Ctrl (one-way analysis of variance followed by least significant difference test). Akt: Protein kinase B; Ctrl: control; DAPI: 4′,6-diamidino-2′-phenylindole; ES: endostatin; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; MCAO: middle cerebral artery occlusion; NC: normal control; p-Akt: phosphorylated-Akt; PTEN: phosphatase and tensin homolog; VEGF: vascular endothelial growth factor. | PMC10233761 | NRR-18-1983-g003.jpg |
0.420765 | 5555d8fdc8864559b5872e8063dbea11 | miR-181b promotes the cell proliferation, migration, and angiogenesis in OGD-induced BMVECs.(A) Cell Counting Kit-8 assay showing that OGD treatment decreased cell proliferation in BMVECs. Transfection of miR-181b-5p mimic increased cell viability and miR-181b-5p inhibitor decreased cell viability in OGD-induced BMVECs. (B) Flow cytometry analysis showing that OGD induced cell apoptosis in BMVECs. Overexpression of miR-181b reduced cell apoptosis, while inhibition of miR-181b increased cell apoptosis. (C) Quantitative analysis of apoptosis rates. (D) Cell migration. Transfection of miR-181b-5p mimic promoted cell migration and inhibition of miR-181b reduced migration. (E) Quantitative analysis of cell migration. (F) Tube formation assay showing that OGD treatment inhibited angiogenesis in BMVECs. Transfection of miR-181b-5p mimic promoted the tube formation ability of OGD-induced BMVECs, while downregulation of miR-181b inhibited angiogenesis in OGD-induced BMVECs. Scale bars: 50 μm in D, 100 μm in F. (G) Quantitative analysis of tube number. (H) Quantitative analysis of tube length. Data are expressed as means ± SD. The experiment was repeated three times. **P < 0.01, ***P < 0.001, vs. NC; #P < 0.05, ##P < 0.01, ###P < 0.001, vs. Mimic-Ctrl or Inhibitor-Ctrl (one-way analysis of variance followed by least significant difference test). BMVEC: Brain microvascular endothelial cell; Ctrl: control; NC: normal control; OGD: oxygen-glucose deprivation. | PMC10233761 | NRR-18-1983-g004.jpg |
0.478947 | e0ad50ba9586429baf47e9281d129bcd | miR-181b suppresses PTEN expression via binding to the 3’-UTR of PTEN mRNA.(A) Quantitative polymerase chain reaction assay confirming that miR-181b-5p mimic was highly expressed in brain microvascular endothelial cells and the expression of miR-181b was inhibited by the miR-181b-5p inhibitor. ***P < 0.001, vs. Mimic-Ctrl or Inhibitor-Ctrl. (B) Western blot showing that overexpression of miR-181b inhibits the expression of PTEN while inhibition of miR-181b promotes the expression of PTEN. (C) Quantitative analysis of the western blot results. ***P < 0.001, vs. Mimic-Ctrl or Inhibitor-Ctrl. (D) The predicted binding site between miR-181-5p and PTEN mRNA. (E) Dual luciferase reporter assay showing that miR-181b-5p mimic inhibited luciferase activity driven by the pMIR-PTEN-WT but not pMIR-PTEN-Mut (with the binding site mutated). **P < 0.01. Data are expressed as means ± SD. The experiment was repeated three times. Data were analyzed using one-way analysis of variance followed by least significant difference test. 3′-UTR: 3′-Untranslated region; Ctrl: control; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; Luc: luciferase; Mut: mutant type; NC: normal control; PTEN: phosphatase and tensin homolog; R-luc: renilla luciferase; WT: wild type. | PMC10233761 | NRR-18-1983-g005.jpg |
0.415886 | 5727a5f212834836ad4b6630e55d8f2f | Changes in angiogenesis and apoptosis-related proteins in OGD-induced BMVECs under miR-181b treatment.(A) Western blot analysis of OGD-induced BMVECs (n = 3). miR-181b inhibited the expression of PTEN, activated the Akt pathway, increased the expression of VEGF and decreased the expression of ES. Overexpression of miR-181b downregulated cleaved caspase-3/8/9 and Bax expressions and upregulated Bcl-2 expression. (B–E) Quantitative analysis of western blot results. Data are expressed as means ± SD. The experiment was repeated three times. Data were analyzed using one-way analysis of variance followed by least significant difference test. *P < 0.05, **P < 0.01, ***P < 0.001, vs. NC; #P < 0.05, ##P < 0.01, ###P < 0.001, vs. Mimic-Ctrl or Inhibitor-Ctrl. Akt: Protein kinase B; BMVEC: brain microvascular endothelial cell; Ctrl: control; ES: endostatin; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; NC: normal control; OGD: oxygen-glucose deprivation; p-Akt: phosphorylated-Akt; PTEN: phosphatase and tensin homolog; VEGF: vascular endothelial growth factor. | PMC10233761 | NRR-18-1983-g006.jpg |
0.412922 | 7de8ad500d7c4efc9424826819d36a6b | Research framework | PMC10233865 | 13020_2023_763_Fig1_HTML.jpg |
0.469506 | 7b5b182927b94bb292ac2dff5f2e4588 | Diagram of methods of applying algorithms on link prediction. In processes A, B and D, chemicals of TM were colored in orange and approved drugs in blue. Circle nodes labeled with “C” meant chemicals and hexagons labeled with “T” meant targets. Black lines represented the connection between chemicals and targets from known knowledge. A meant the dataset from the curated database. In B, two individual networks were connected by integrating the links between chemicals and targets to form the CCT and PPI, which were labeled as green lines. C shown here mainly reflects the operating principle of node2vec. In D, new predicted interactions were labeled as red solid and dashed edges. In this research, we paid attention to the interaction between chemicals of TM and targets of approved drugs, which were labeled as red solid lines | PMC10233865 | 13020_2023_763_Fig2_HTML.jpg |
0.442979 | d16d4efbaca94e1895b547568c262fc7 | Flow diagram of filtered chemicals. The blue boxes showed the excluded chemicals with related reasons. A show the filtered Western drugs for CVD, and the two numbers in parentheses indicated the sources of Drugbank and Drugcentral, respectively. B showed the filtered herbal chemicals; the numbers in parentheses meant DS and CX, respectively | PMC10233865 | 13020_2023_763_Fig3_HTML.jpg |
0.38318 | 7113b66e329e4e81aba67acc14eb17ac | Average AUROC and AP scores of five algorithms in nine datasets. A and B showed AUROC and AP, respectively | PMC10233865 | 13020_2023_763_Fig4_HTML.jpg |
0.395129 | 20f1bb5984e74595a572450dd0d00aa9 | AUROC and AP of five algorithms in CTC & CCC & PPI datasets. A and B show AUROC and AP, respectively. Numbers of 0.91 show the average value of AUROC or AP | PMC10233865 | 13020_2023_763_Fig5_HTML.jpg |
0.469528 | 55f370ef29404e62a2e0514046a0afce | In three groups, the ROC curve of five algorithms on the CTC & CCC & PPI datasets. A, B, and C represent the groups of DS-drug, CX-drug and DS-CX-drug, respectively | PMC10233865 | 13020_2023_763_Fig6_HTML.jpg |
0.403596 | 1b2bf3bf4d8c4523a73afe8b88a1d029 | CETSA indicated caffeic acid increased the thermal stability of the GGT1 protein but ligustilide did not affect the thermal stability of the MTNR1A protein. CETSA was performed in HUVECs cell lysates after coincubation with 20 μM caffeic acid (A) or 20 μM ligustilide (B), then subjected to heating (51–72 ℃) before western blotting | PMC10233865 | 13020_2023_763_Fig7_HTML.jpg |
0.545797 | 54f5b93de28d4cc2b7b8a7bfac494082 | mRNA expression of GGT1, FGF2, CES2, MTNR1A, ATP1A2 upon the treatment of predicated compounds in the HUVECs. HUVECs were treated with 20 μM compounds of caffeic acid, neocryptotanshinone, ligustilide and ginsenoside rb1 for 6 h respectively, then subjected to a standard qPCR operation to determine the mRNA change of GGT1 (A), FGF2 (B), CES2 (B), MTNR1A (C), ATP1A2 (D) (n = 5). P### < 0.001 vs the Ctrl group | PMC10233865 | 13020_2023_763_Fig8_HTML.jpg |
0.390295 | ebf89ba883af4860992280be87898af8 | Heat map of AQI and six major pollutants in China. | PMC10235078 | 41598_2023_36086_Fig1_HTML.jpg |
0.423274 | cc59772afabb48d5afa1030cc305ebd3 | Monthly distribution characteristics of AQI value and concentration value of six pollutants. | PMC10235078 | 41598_2023_36086_Fig2_HTML.jpg |
0.522637 | 4b22cbde1a6d4af5aad398a971e2714c | Spatial patterns of AQI in Chinese cities. Note: The map used in this study was generated based on the Alibaba Cloud Data Visualization platform, adhering to the GS (2022)1061 standard, with no modifications made to the base map boundaries. Data from Hong Kong, Macao, and Taiwan were not included. | PMC10235078 | 41598_2023_36086_Fig3_HTML.jpg |
0.417181 | a49ffbb602ae42b0b8cce98bae7b8974 | Heat map of the major pollutants in the ten cities with the worst air quality in China. | PMC10235078 | 41598_2023_36086_Fig4_HTML.jpg |
0.422711 | be5b5267932d4bb98d7ec94eed52a75b | (a) AQI time-series diagram. (b) Moving average and weighted moving average of AQI. (c) Seasonal difference and first-order difference sequence diagrams of AQI. (d) ACF and PACF of mean monthly AQI after the seasonal difference and first-order difference. | PMC10235078 | 41598_2023_36086_Fig5_HTML.jpg |
0.403979 | 3e9d49114c81488fb8d7a2f65799a0a5 | (a) The imitative effect of AQI simulated by \documentclass[12pt]{minimal}
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\begin{document}$$SARIMA(2,1,1)(0,1,1)^{12}$$\end{document}SARIMA(2,1,1)(0,1,1)12. (b) Residual diagram of SARIMA model. (c) Residual ACF and PACF after the seasonal difference and first-order difference. (d) Residual QQ Figure. | PMC10235078 | 41598_2023_36086_Fig6_HTML.jpg |
0.424943 | c104516efd5b48db9aea449eaa4594fe | (a) Prediction curve of the Random forest regression model. (b) Prediction residuals diagram of the Random forest model. (c) Residual ACF and PACF after the seasonal difference and first-order difference. (d) Residual QQ Figure. | PMC10235078 | 41598_2023_36086_Fig7_HTML.jpg |
0.437379 | d77e5cc363c646e3a01711cb5644746d | Diagnostic spirometry in patients with a new diagnosis of COPD.Comparison of COPD cohorts PRAXIS I, patients diagnosed in the period 2000–2003 (below) and PRAXIS II, patients diagnosed in the period 2004–2010 (above). | PMC10235108 | 41533_2023_345_Fig1_HTML.jpg |
0.434526 | 54b4d252224d4af1abf0e0cacaf8093e | Proportion of patients with spirometry result FEV1/FVC or FEV1/VC above/equal to or under 0.70.Patients with assessable spirometry data and performed diagnostic spirometries from COPD cohorts PRAXIS I (n = 295) and PRAXIS II (n = 567). | PMC10235108 | 41533_2023_345_Fig2_HTML.jpg |
0.486291 | bfa162c0e0e0462a9b2af0b996701b53 | Patient selection – PRAXIS II cohort.Patients with a new diagnosis of COPD and performed/not performed diagnostic spirometry. | PMC10235108 | 41533_2023_345_Fig3_HTML.jpg |
0.441962 | 29581c5471d346f4ba716111b2ae5b65 | Exercise effects are mediated by the action of exerkines. Exerkines are dependent on, and modulate, redox biology. The left side of the figure shows the proposed regulatory circuits for the production of exerkines and their effects on different tissues to modulate redox biology. The right side of the figure indicates the effects of each exerkine (blue panels), the target tissue affected (green panels), and if exercise is necessary for the effect to take place (Ex, yellow pannels).♢ indicates effects that interact with or modulate redox homeostasis, ♦ indicates effects that modulate redox homeostasis to reduce oxidative stress. | PMC10236471 | gr1.jpg |
0.488727 | 6c549032aa90427e9fe407cd490ff3a9 | Composition and structure of liposome vaccines. A Chemical structures of 4S, DPPC, CH, DOPC and PBS57. 4S is a lipid-modified CDG biomarker that can be loaded onto liposome membranes. DPPC, DOPC and CH are the main components of liposomes. Adjuvant PBS57 is added to enhance the switching of the antibody class from IgM to IgG. B Schematic structures of LP-4S, NLP, NLP-4S and NLP-4S-PBS57 liposome vaccines. LP-4S is prepared by DPPC, CH and loaded with CDG biomarker antigen 4S. NLP is prepared by DOPC and CH as the blank liposome. NLP-4S is prepared by DOPC, CH and loaded with CDG biomarker antigen 4S. NLP-4S-PBS57 is prepared by further loading PBS57 adjuvant into NLP-4S. | PMC10236646 | 12951_2023_1927_Fig2_HTML.jpg |
0.451739 | 5a0e3e36b4f241ecb4b0896f5fd45458 | Characterization of liposome vaccines. A Particle size distribution of liposomal nanoparticles. DLS measurements of LP-4S, NLP, NLP-4S and NLP-4S-PBS57 liposomes. B Zeta potential of the four liposome vaccines. C Representative TEM images of liposome vaccines. Liposomal nanoparticles have basically round-shape structures. NLP liposomes were treated by negative staining method, and LP-4S, NLP-4S and NLP-4S-PBS57 liposomes were dyed by positive staining method. Scale bar indicates 200 nm | PMC10236646 | 12951_2023_1927_Fig3_HTML.jpg |
0.493099 | 5ab59847b54a4a6d8544d810ffccf9e3 | Analysis of the immune response in liposome-vaccinated mice. A Schematic representation of the treatment schedule (immunization and sample collection). Female C57BL/6 mice were immunized s.c. at Days 1, 7, 14, 28 and 35. Sera were collected at Days 20, 34, 39 and 42 after vaccination. B Antibody titers of Day 39 sera. 4S was used as the coating antigen. Each data reflects an average of three measurements using pooled sera from each of the six groups (Day 39) and goat anti-mouse Ig(G + M). Error bars represent the standard error. C Antibody titers elicited by NLP-4S and NLP-4S-PBS57. 4S was used as the coating antigen. Each line represents the average of sera from Days 20, 34, 39 and 42 from 5 replicate mice (each dot) and goat anti-mouse Ig(G + M). Statistical differences were determined by two-tailed unpaired t test analysis and is indicated as either non-significant (ns) or *0.01 < P < 0.05 | PMC10236646 | 12951_2023_1927_Fig4_HTML.jpg |
0.410231 | d7a181fc0b4847d2ac80a1d43f328e1e | Analysis of the subtype and specificity of antibody. A Analysis of the antibody subtype (IgG and IgM). 4S was used as the coating antigen. Each data reflects the ranges of three measurements using pooled sera from the NLP-4S and NLP-4S-PBS57 groups (Day 39) and goat anti-mouse Ig(G + M), IgG or IgM. The lines represent the mean values. B Analysis of antibody specificity. Disaccharide (GlcNAc2-PP-Phy), trisaccharide (GalGlcNAc2-PP-Phy), 4S (SiaGalGlcNAc2-PP-Phy) and biantennary complex type N-glycan (SiaGalGlcNAc)2Man3GlcNAc2-AsnFmoc were used as the coating antigens respectively. Each data reflects an average of three measurements using pooled sera from the NLP-4S-PBS57 (Day 39) and goat anti-mouse IgG. Error bars represent the standard error. Statistical differences were determined by two-tailed unpaired t test analysis and is indicated as non-significant (ns), *0.01 < P < 0.05 or **0.001 < P ≤ 0.01 | PMC10236646 | 12951_2023_1927_Fig5_HTML.jpg |
0.437547 | 24e8d39fab194a39bc327abe4b501509 | Analysis of the IgG antibody subclasses elicited by NLP-4S and NLP-4S-PBS57. 4S was used as the coating antigen. Each data reflects an average of three measurements using pooled sera from the NLP-4S and NLP-4S-PBS57 groups (Day 39) and goat anti-mouse IgG1, IgG2b, IgG2c and IgG3 antibodies. Error bars represent the standard error. Statistical differences were determined by two-tailed unpaired t test analysis and is indicated as non-significant (ns) or *0.01 < P < 0.05 | PMC10236646 | 12951_2023_1927_Figa_HTML.jpg |
0.491483 | 17601e4228ca40569fc2cabc059b3fdf | Radiation measurement using real-time dosimeters. | PMC10236896 | gr1.jpg |
0.428759 | b31468d230ee4fb3885a499793964980 | Total equivalent radiation dose for operator 1 vs. operator 2 performing transfemoral TAVR. (The diamond denotes the mean. The top and the bottom ends denote the first and third quartiles. The whiskers are the maximum and minimum values closest to the upper and lower fence. The upper fence is obtained by adding the value of 1.5 times the interquartile range added to the third quartile. The lower fence is obtained by subtracting 1.5 times the interquartile range from the first quartile. The circles denote the outliers that are beyond the fences).Abbreviation: TAVR, transcatheter aortic valve replacement. | PMC10236896 | gr2.jpg |
0.460111 | 71eeca8e52564aa18ccb970cc8bc69e1 | Total equivalent radiation dose for operator 1 vs. operator 2 at the thorax level. (The diamond denotes the mean. The top and the bottom ends denote the first and third quartiles. The whiskers are the maximum and minimum values closest to the upper and lower fence. The upper fence is obtained by adding the value of 1.5 times the interquartile range added to the third quartile. The lower fence is obtained by subtracting 1.5 times the interquartile range from the first quartile. The circles denote the outliers that are beyond the fences). | PMC10236896 | gr3.jpg |
0.395405 | f871e177252f49689b76055985a47b1f | Total equivalent radiation dose for operator 1 vs. operator 2 at the eye level. (The diamond denotes the mean. The top and the bottom ends denote the first and third quartiles. The whiskers are the maximum and minimum values closest to the upper and lower fence. The upper fence is obtained by adding the value of 1.5 times the interquartile range added to the third quartile. The lower fence is obtained by subtracting 1.5 times the interquartile range from the first quartile. The circles denote the outliers that are beyond the fences). | PMC10236896 | gr4.jpg |
0.432139 | ef0e2faba39f4963a13300382f5e2661 | Workflow of the study. | PMC10237015 | fneur-14-1179761-g001.jpg |
0.493858 | fa522a75ecd6476685613b49c7d507a6 | Identification of prognostic factors in glioma. (A) Correlation diagram of all independent variables is presented in the figure. The Pearson correlations between the independent variables used in the analysis are displayed using colors, where yellow indicates a positive correlation and blue indicates a negative correlation. The deeper the color, the stronger the correlation. An asterisk is used to denote statistical significance with a value of p of less than 0.05. (B) Forest plot of hazard ratios from univariate Cox regression analysis of the risk factors in glioma. Red forest plots represent risky factors, and green forest plots represent protective factors. (C) Forest plot of hazard ratios from multivariable Cox regression analysis of the risk factors in glioma. (D) Boxplot of the proportion of “Male” among LGG and HGG groups. | PMC10237015 | fneur-14-1179761-g002.jpg |
0.440137 | 3e8c957c9b7a4a31aae56e08544e3f2c | Performance comparison of prediction models based on different machine learning methods. (A,B) showed different residual comparisons of the four algorithms. (A) Each boxplot describes the residuals within an algorithm. The red dot stands for the root mean square of residuals. (B) Reverse cumulative distribution curves for each algorithm. (C) Feature importance bar charts for several machine learning algorithms. The top 10 features of each group are shown. The abscissa represents RMSE loss after permutations. RMSE, Root mean square error. (D) Receiver operating characteristic (ROC) curves of the four machine learning methods. (E) Venn diagram showing the overlapping genes of XGB and univariate cox regression analysis. The top 10 features of each group are included. | PMC10237015 | fneur-14-1179761-g003.jpg |
0.453121 | fdaf14945c184d1ebead41ff0bc1213b | Kaplan-Meier survival plots in all glioma patients. (A) Age >47 vs. <=47, p<0.001. (B) CDK4 altered vs. unaltered, p=0.001. (C) CDK6 altered vs. unaltered, p<0.001. (D) CDKN2A altered vs. unaltered, p<0.001. (E) FGFR2 altered vs. unaltered, p<0.001. (F) IDH1 altered vs. unaltered, p=0.014. (G) KIT altered vs. unaltered, p=0.013. | PMC10237015 | fneur-14-1179761-g004.jpg |
0.460709 | 1ea753630c61411ea0e6c5d0b0baada1 | Kaplan–Meier plots of overall survival probability in patients with high-grade gliomas. (A) Age >47 vs. <=47, p<0.001. (B) CDK4 altered vs. unaltered, p<0.01. (C) CDK6 altered vs. unaltered, p=0.002. (D) CDKN2A altered vs. unaltered, p=0.01. (E) FGFR2 altered vs. unaltered, p=0.004. (F) IDH1 altered vs. unaltered, p=0.038. (G) KIT altered vs. unaltered, p=0.773. | PMC10237015 | fneur-14-1179761-g005.jpg |
0.449564 | e353c2b2d15347f0b2900ffe9b56c153 | Kaplan–Meier plots of overall survival probability in patients with low-grade gliomas. Kaplan-Meier survival plots in glioma patients. (A) Age >47 vs. <=47, p=0.009. (B) CDK4 altered vs. unaltered, p=0.386. (C) CDK6 altered vs. unaltered, p=0.709. (D) CDKN2A altered vs. unaltered, p=0.18. (E) FGFR2 altered vs. unaltered, p=0.123. (F) IDH1 altered vs. unaltered, p=0.44. (G) KIT altered vs. unaltered, p<0.0001. | PMC10237015 | fneur-14-1179761-g006.jpg |
0.435284 | 5b22e2bc22e04604bcac72c552f68aa0 | Predictor selection using the least absolute shrinkage and selection operator (LASSO) logistic regression model. (A–D) Construction of WHO5 risk signature scores using the LASSO regression model. (A) LASSO coefficient profiles of the 7 candidates. (B) Selection of the optimal parameter (lambda) in the LASSO model using the tenfold cross-validation. (C) Kaplan–Meier survival analysis for the overall survival curves of gliomas with a low or high risk of death, according the model based classifier risk score level. (D) The signature risk score distribution and the scatter plot of the sample survival overview in the training set. The blue and red dots, respectively, represent survival and death. (E–H) Construction of age and grade risk signature scores using the LASSO regression model. | PMC10237015 | fneur-14-1179761-g007.jpg |
0.43338 | 0cd1fffc6914433a9400daecd48bcf8b | The ROC curves for the WHO5 risk score, grade, age, and control risk model in the training cohort. (A) ROC curve of 1-year overall survival. (B) ROC curve of 2-year overall survival. (C) ROC curve of 3-year overall survival. (D) ROC curve of 4-year overall survival. (E) ROC curve of 5-year overall survival. (F) ROC curve of 6-year overall survival. | PMC10237015 | fneur-14-1179761-g008.jpg |
0.423574 | 3dc19d505f1547b387a3d896788975fd | Nomogram construction and validation. (A) Prediction nomogram integrated the predictors selected, including grade, sex, and WHO5 diagnosis. (B) ROC curve of the nomogram. (C) Calibration curves of the nomogram. (D) The c-index of the control model, WHO5 risk model, and nomogram. (E) Decision curve analysis for different models. (F) ROC curves of different models. | PMC10237015 | fneur-14-1179761-g009.jpg |
0.485286 | 61fcf1905da741e8ba8563ac3b5c6496 |
Temporal changes in laboratory parameters during treatment and follow-up. A: Blood glucose; B: Amylase; C: Serum creatinine; D: Serum sodium; E: C-reactive protein; F: Creatine kinase. | PMC10237137 | WJCC-11-3267-g001.jpg |
0.449383 | de34988a66a94031bfeb75c564d35044 |
Colonoscopy and abdominal computed tomography examination. A: Electronic colonoscopy image; B: Abdominal computed tomography scan. | PMC10237137 | WJCC-11-3267-g002.jpg |
0.503083 | 20accbe8fc7f4a068fe3b3163a6883a4 |
Hematoxylin and eosin-stained sections of terminal ileum. A: 5 times amplification by microscope of the lesions in intestine; B: 50 times amplification by microscope of the lesions in intestine; C: 100 times amplification by microscope of the lesions in intestine; D: 200 times amplification by microscope of the lesions in intestine. | PMC10237137 | WJCC-11-3267-g003.jpg |
0.431569 | caeef80691d443dcaaa568547a9a1abb | Inflammatory pathways activated during viral infection.During virus infection, PAMPs (Pathogen-associated molecular patterns) and DAMPs (Damage-associated molecular patterns) released from lysed cells, recognize by various PRRs (pattern recognition receptors) such as TLR (Toll-like Receptor), RLR (Retinoic Acid-Induced Gene – I like receptor), NLR (Nucleotide-binding oligomerization domain (NOD)-like receptor), cGAS (cyclic GMP–AMP synthase)-STING (stimulator of interferon genes). These PRRs recruit adaptor proteins and activate the downstream signaling which leads to the activation of different intracellular signaling pathways such as NF-κB (Nuclear Factor kappa-light-chain-enhancer of activated B-cells), IRFs (interferon regulatory factors), MAPK (Mitogen-Activated Protein Kinase), and inflammasome activation which stimulate the production of interferons, cytokines, and chemokines. Activation of inflammasome induce pyroptosis during virus infection. Disbalance of these pathways causes the dysregulated production of cytokines and chemokines which may be responsible for cytokine storm (Created with BioRender.com). | PMC10238879 | gr1.jpg |
0.387935 | ed27a43a859847b4993d5c7f3510b3d2 | Regulation of inflammatory pathways by miRNA.The management of various inflammatory pathways during RNA virus infection by miRNAs. Upon viral infection, miRNAs are known to dysregulate and can target different host factors associated with the intracellular inflammatory pathways by targeting the 3′ UTRs. This balance is maintained by miRNA that targets negative and positive regulators of these inflammatory pathways. Black colour indicates miRNAs indicating commonly found miRNA in several RNA virus infections. Red colour indicates miRNAs that are linked to IAV infection, whereas green and pink indicate miRNAs that are predicted and linked to dengue and SARS-CoV-2 infections, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.) | PMC10238879 | gr2.jpg |
0.46271 | d167cb2521c44141b0e6df0c7ba3ad54 | Erythrodermic involvement over the entire skin surface (a and c) and significant clearing after 4 days, likely due to marked T-cell depletion (b and d). Also note the eruptive appearance of numerous molluscum contagiosum extensively over the skin (c and d). | PMC10238989 | IJD-68-215-g001.jpg |
0.531719 | 5902065f74a54d9fb39eb331cd1c69fc | The proportion of patients undergoing isolated surgical aortic valve replacement (SAVR) for isolated aortic insufficiency (AI) increased in the post-TAVR era from 11% of isolated SAVRs in 2011 to 44% of isolated SAVRs in 2020. | PMC10239805 | fcvm-10-1103760-g001.jpg |
0.491499 | b1ee22396b7a4312a8a6e8c82f2ffec2 | The society of thoracic surgeons (STS) predicted risk of mortality (PROM) of patients undergoing isolated SAVR decreased in the post-TAVR era. Low risk (blue) = STS PROM ≤3%; Intermediate risk (orange) = 3%< STS PROM ≤8%; High risk (gray) = 8%< STS PROM ≤15%; Extreme risk (yellow) = STS PROM >15%. | PMC10239805 | fcvm-10-1103760-g002.jpg |
0.467578 | 74d84416be2b4aee8bb9c108b733caca | (A) The number of isolated surgical aortic valve replacements (SAVRs) performed annually decreased since the advent of transcatheter aortic valve replacement (TAVR) in 2011. (B) Over the years since TAVR approval, the number of TAVRs has increased while the number of SAVRs has decreased. TAVRs now make up a majority (90% in 2020) of isolated aortic valve replacements (AVRs) at a single institution with a structural heart center. | PMC10239805 | fcvm-10-1103760-g003.jpg |
0.519842 | 4c07c56f80d240c5b6c26d6deb3dc115 | The median size of the surgical aortic valve implanted increased in the post-TAVR era (25 [23, 27] mm) compared to the pre-TAVR era (23 [21, 25] mm). | PMC10239805 | fcvm-10-1103760-g004.jpg |
0.415832 | d6dfb8457c504a35bfb8323a688a1500 | Over the past two decades, utilization of bioprosthetic heart valves has increased while mechanical valves decreased; however, this trend pre-dated the TAVR era. Since 2018, mechanical valve use is on the rise. | PMC10239805 | fcvm-10-1103760-g005.jpg |
0.434894 | baaa3088fb2549a6958de234b50cd11c | Since the approval of TAVR in 2011, the number of TAVRs have been increasing while SAVRs have been decreasing. This trend at a quaternary heart center is similar to that seen nationally. | PMC10239805 | fcvm-10-1103760-g006.jpg |
0.426589 | 6e8530ab81d04ec8a503be25a4dbfd16 | Prevalence of ID in HF. Modified after Rocha et al. (11). | PMC10240352 | fcvm-10-1025957-g001.jpg |
0.416326 | a781809838214c69b241a780f6b100ea | Recommendations for the management of anemia and iron deficiency in patients with heart failure (28). | PMC10240352 | fcvm-10-1025957-g002.jpg |
0.428451 | 0663d1c45b7c42a992d9e526db73a024 | Intravitreal HKMtb generates acute panuveitis that is exacerbated and becomes chronic when preceded by a systemic prime.(A) Uveitis is induced with unilateral intravitreal injection of 5 μg heat killed mycobacterial antigen (HKMtb) in PBS with prior systemic CFA prime (PMU) or without the prime (UMU). (B) Optical coherence tomography (OCT) imaging is used to monitor inflammation longitudinally. Corneal edema, anterior chamber cells, and hypopyon (white arrow) are visible in anterior images. Posterior chamber images identify vitritis (red arrow) and retinal edema. (C) OCT inflammation score by day for PMU n = 17 (black filled circles), UMU n = 17 (open circles), and PBS/Sham injected eyes n = 7 (triangles). Symbol indicates mean score, error is SEM. (D) Comparison of day 1 and Day 56 OCT score by treatment condition. Bars indicate the mean and standard deviation. (E) Anterior chamber protein concentration from inflamed (R) and fellow (L) eyes. Sham (n = 13), UMU (n = 20), and PMU (n = 20) animals. Bars indicate the mean and standard deviation. (F) H&E staining of a day 1 PMU eye. (G) Day 56 histology of PMU eye with vitritis, perivascular leukocytes, and a retinal fold. (H) Day 56 UMU histology with no inflammation. (I) Comparison of histology scores between sham injected (triangle), UMU (open circles), and PMU (closed circles) animals on day 1 and day 56 (n = 5–13/condition). (J–L) Day 56 PMU retina with DAB+ (J) T cells (CD3+), (K) macrophages and retinal microglia (F4/80+) and (L) neutrophils (Gr-1+). (M) Quantification of DAB + cells on days 1 and day 56 in PMU, CD3 (black), F4/80 (pink), or GR1 (cyan). (N–P) Day 56 UMU retina with (N) rare T cells (CD3+), (O) few macrophages and retinal microglia (F4/80+) and (P) no neutrophils (GR-1+). (Q) Quantification of DAB + cells on days 1 and day 56 in UMU, CD3 (black), F4/80 (pink), or GR1 (cyan). Comparisons of OCT score, anterior chamber protein concentration, and histology score performed by day with Kruskal Wallis test with Dunn’s multiple comparisons.*p < 0.5, **p < 0.01, ***p < 0.001. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) | PMC10240933 | nihms-1899506-f0001.jpg |
0.39784 | 87edf562f1c24e899fe5e6b5ea0118d1 | Priming leads to significantly increased total ocular CD45þ cells and T cells by day 7 after IVT.(A) Ocular CD45+ cell number for injected right (R) and control left (L) eyes on days 1, 7 and 56 after intravitreal injection. Each point represents the cell count from an individual eye. Sham (Sham), primed sham (Pr. Sh), unprimed Mtb (UMU), primed Mtb (PMU). All comparisons indicated. Significance determined by Brown-Forsythe ANOVA with Dunnett’s T3 multiple comparison test. (B) Pie charts show the distribution of inflammatory cell types present as the percentage of CD45+ cells. Average number of CD45+ shown in the center of the pie chart. Neutrophils are the dominant population on day 1. T cells (dark blue) become the major cell population in PMU eyes on day 7. In contrast CD11bhi, Ly6Clo monocytes (pink) become the major population in UMU eyes. (C) Total number of ocular T cells on days 1, 7 and 56. PMU eyes have significantly more T cells than UMU eyes on days 7 and 56. Unpaired t-test with Welch’s correction. ns = not significant, *p < 0.05. NK = natural killer cell, NKT = natural killer T cell, Ly6Chi MΦ (macrophages), Ly6Clo MΦ (macrophages). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) | PMC10240933 | nihms-1899506-f0002.jpg |
0.464421 | 19280a691f63415f9923d4b03780e871 | Priming significantly increases vitreous cytokine concentrations on day 1 after intravitreal injection of HKMtb extract.Twelve cytokines were significantly increased in PMU vitreous when compared to UMU. Bar indicates mean concentration of all samples per condition (n = 5). Cytokine concentrations were also elevated when compared to control vitreous from naive (N) or primed naive (Pr) animals. Significant differences determined with Brown-Forsythe ANOVA with Dunnett’s T3 multiple comparison test. ns = not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. | PMC10240933 | nihms-1899506-f0003.jpg |
0.468593 | bb8830d306984f3aab8e8244ad854fbc | In primed animals, many vitreous cytokines remain elevated or increase seven days after HKMtb injection.Vitreous cytokines were measured on day 7 after IVT HKMtb and compared to primed naive (D0) and day 1 (D1) results. (A) Six cytokines demonstrated increased concentrations on D7. (B) Fourteen cytokines had decreased when compared to D1, but remained significantly elevated on D7 when compared to D0. Significant differences determined with Brown-Forsythe ANOVA with Dunnett’s T3 multiple comparison test. ns = not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. | PMC10240933 | nihms-1899506-f0004.jpg |
0.490352 | 6de2e2cecc2f402a8c4eabec8e785e8a | Innate immunity is necessary for uveitis in unprimed animals while adaptive immunity is necessary for increased uveitis severity and duration in primed animals.OCT inflammation score was compared in wild type, RAG-2 deficient, and MyD88 deficient animals in the primed (A,C) and unprimed (B, D) models. Symbols for wild type animals shown in black and white, RAG-2 deficient indicated by cyan squares, and MyD88 deficient indicated by pink triangles. Bar indicates mean score. Comparison performed with Kruskal Wallis test with Dunn’s multiple comparisons. (E) In wild type animals, twelve vitreous cytokines were significantly increased in primed (P) compared to unprimed (P) animals on day 1. In primed RAG-2 animals, vitreous cytokines were decreased when compared to wild-type primed animals, and not significantly different when compared to unprimed wild-type animals. *p < 0.5. **p < 0.01, ***p < 0.001,****p < 0.0001. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) | PMC10240933 | nihms-1899506-f0005.jpg |
0.428395 | faeb58a0a9ea4671be60b629a06883dc | Analysis of N. crassa WT, Δfrq, Δcpc-3, and cpc-3c ribo-seq data(A) Fraction of total reads mapping to the coding sequence (CDS) or 5′ or 3′ untranslated regions (5′ UTRs and-3′ UTRs) for the indicated strains.(B) Insert size distribution of ribosome-protected footprint (RPF) across the two biological replicates and time points for the indicated strains.(C) Frame analysis for RPF for the most highly phased population of reads, 31-mers. The RPF are color coded (dark, medium, light) according to the subcodon position alignments (phases 1, 2, and 3) for WT (black), Δfrq (blue), Δcpc-3 (red), and cpc-3c (green).(D) Read distribution of normalized RPF (left, black) and RNA abundance (right, gray) along the frq transcript from cells grown in constant dark (DD) and harvested at the indicated times (h).(E) Plot of the normalized RPF (black, left y axis) and RNA abundance (FPKM) (gray, right y axis) reads of frq mRNA from (D).Square symbols indicate the values from biological replicate 1 (black) and replicate 2 (gray). The bar at the bottom of the graph represents subjective day (gray) and subjective night (black) in this and all subsequent figures. | PMC10241597 | nihms-1904509-f0002.jpg |
0.393536 | d4c4354d7db84787998a80b70586f44e | A subset of mRNAs requires P-eIF2α for rhythmic translation(A) Venn diagrams showing the number of transcripts with rhythmic RPF counts in WT, Δcpc-3, and cpc-3c cells and arrhythmic RPF counts in Δfrq cells (left) or with rhythmic RPF counts in WT cells and arrhythmic RPF counts in Δfrq, Δcpc-3, and cpc-3c cells (right).(B) Heatmaps of the peak phase of genes with rhythmic RPF counts in WT cells and arrhythmic RPF counts in Δfrq, Δcpc-3, and cpc-3c cells (cTICs, N = 404) grown in DD and harvested at the indicated times (h). Genes are sorted by the peak phase in WT.(C) Phase distribution based on maximal RPF counts in WT for the 404 cTICs. The concentric circles emanate from zero at the center to increasing frequencies as indicated by the numeric legends. The numbers indicate circadian time (CT), with white shading designating subjective day (CT0–12) and gray shading designating subjective night (CT12–0) in this and all subsequent figures.(D) GO terms under the biological process category that are significantly enriched (p < 0.05) in rhythmically translated mRNAs that peak during the day (gray bars), and during the night (black bars). For visualization, the p values are plotted as −log10.See also Tables S4, S5, and S6. | PMC10241597 | nihms-1904509-f0003.jpg |
0.470046 | b83311d3677a41a4895798757707c2f2 | Genes that depend on clock-controlled eIF2α activity for rhythmic translation arise from cycling and non-cycling transcripts(A) Heatmaps of the peak phase of genes with rhythmic RPF counts in WT cells (right panel) and their corresponding mRNA expression (FPKM) profiles (left panel). The 404 cTICs are sorted by the peak phase of WT RPF count for each class. mRNA abundances and RPF levels are standardized within each gene (row) and independently for RNA-seq and ribo-seq columns (Z scores).(B) Phase distribution based on maximal RPF counts in WT for genes belonging to each class on the left panel: class I, in-phase rhythmic RPF and mRNA, class II, rhythmic RPF and mRNA with phase changes, and class III, rhythmic RPF and arrhythmic mRNAs.(C) Luciferase activity from HAM-7:LUC translational (black line) and Pham-7::luc transcriptional (gray line) fusions in WT cells grown in DD and recorded every 90 min over 4 days (h DD). The average bioluminescence signal is plotted (mean ± SEM, n = 12 technical replicates). The peak phase values (φ) for each trace are shown.(D) Luciferase activity from CPC-1:LUC translational (black line) and Pcpc-1::luc transcriptional (gray line) fusions in WT cells grown in DD and recorded every 90 min over 4 days (h DD). The average bioluminescence signal is plotted (mean ± SEM, n = 12 technical replicates), and the phase values are shown as in (C).See also Table S4. | PMC10241597 | nihms-1904509-f0004.jpg |
0.447935 | c2983cb8441e4cd0b364552f8a675bdb | Clock control of P-eIF2α levels and cmRNPg sequestration are required for rhythmic translation of zip-1(A) Highly represented sequences identified by MEME 5.3.0 from the 5′ leaders of class III cTICs. (B–E) Luciferase activity from ZIP-1:LUC translational (black line) and Pzip-1::luc transcriptional (gray line) fusions in (B) WT cells and ZIP-1:LUC in (C) Δfrq (blue line), (D) Δcpc-3 (red line), and (E) cpc-3c (green line) cells grown in DD and recorded every 90 min over 5 days (h DD). The data were normalized to the mean, and the average bioluminescence signal is plotted (mean ± SEM, n = 12 technical replicates). ZIP-1:LUC in WT cells was rhythmic as indicated by a better fit to a sine wave (dotted black lines, p < 0.05). ZIP-1:LUC in Δfrq, Δcpc-3, and cpc-3c cells was arrhythmic as indicated by a better fit of the data to a line (dotted blue, red, and green lines, p > 0.05) by F-test.See STAR Methods for statistical test for rhythmicity and Table S7. | PMC10241597 | nihms-1904509-f0005.jpg |
0.382921 | a33bbbca3950486d9442e84288de29fa | Robust ZIP-1 protein rhythms depend on cmRNPg sequestration(A) Luciferase activity from ZIP-1:LUC translational fusion in WT (black line) and Δsnr-1 (yellow line) cells. ZIP-1:LUC in WT cells was rhythmic as indicated by a better fit to a sine wave (dotted black line, p < 0.05), while ZIP-1:LUC in Δsnr-1 cells was arrhythmic as indicated by a better fit of the data to a line (dotted yellow line, p < 0.05). See STAR Methods for statistical test for rhythmicity.(B) Luciferase activity from ZIP-1:LUC translational fusion in WT (black line) and PB motif deletion ΔPBM (purple line) cells. Cells were grown in DD and recorded every 90 min over 5 days (h DD). The average bioluminescence signal is plotted (mean ± SEM, n = 36 technical replicates).(C) Mean period in h (mean ± SEM, n = 36 technical replicates, n.s., not significant, p > 0.05) of rhythmic ZIP-1:LUC bioluminescence traces in WT (black bar) and ΔPBM (purple bar) cells.(D) Mean amplitude (mean ± SEM, n = 36 technical replicates; ****p < 0.0001) of rhythmic ZIP-1:LUC bioluminescence traces in WT (black bar) and ΔPBM (purple bar) cells. p values were calculated by an unpaired t test with Welch correction. | PMC10241597 | nihms-1904509-f0006.jpg |
0.414759 | 3baa46a8a1c44a888f74c05b4d402d3c | The circadian clock regulates cytoplasmic cmRNPg formation(A) Averaged normalized RPF reads (black line) traces of rhythmic cmRNPg components eIF4E-T, snr-1, snr-7, and rnp-7 from WT cells grown in DD and harvested at the indicated times (h). Square symbols indicate the values from biological replicate 1 (black) and replicate 2 (gray).(B) Representative images showing SNR-1:dsRed as a cmRNPg marker and examined in WT or Δfrq cells grown in DD and imaged at the indicated times. Scale bar: 5 μm.(C) Quantification of the number of SNR-1:dsRed foci in WT or Δfrq hyphae grown in DD and imaged at the indicated times (mean ± SEM indicated by cross in boxplot, n = 60 hyphae, 3 biological replicates with 20 hyphae for each biological replicate representing technical replicates; **** p < 0.0001).(D) Quantification of the sizes of SNR-1:dsRed foci in WT or Δfrq hyphae grown in DD and imaged at the indicated times (mean ± SEM indicated by cross in boxplot, n = 60 hyphae, 3 biological replicates with 20 hyphae for each biological replicate representing technical replicates; n.s., not significant, p > 0.05). p values were calculated by an unpaired t test with Welch correction. | PMC10241597 | nihms-1904509-f0007.jpg |
0.416695 | 8cb9690170134928865aa5ce3b4f22d4 | Simplified life cycle of SARS-CoV-2. The virus enters a host’s cell and releases its genome in cytoplasm. Viral RNA is translated into two polyproteins: pp1a and pp1ab. Then, due to autocleavage, two viral proteases (PLpro and Mpro) are liberated. Their main role is to further process polyproteins, what results in a release of other nsps. Next, a group of nsps form replication and transcription complexes (RTCs). RTCs are further involved in a generation of copies of viral genomic RNA (g-RNA), as well as a set of sub-genomic RNAs (sg-RNA) responsible for synthesis of viral structural and accessory proteins. Virions are assembled in endoplasmic reticulum-Golgi intermediate compartments (ERGICs). g-RNA is coated with structural N-protein and enters the ERGIC containing M, E, and S glycoproteins. Then, the virions are released by exocytosis47,48. Inhibition of Mpro, PLpro, and N7-MTase may lead to suppression of virus replication. Protease inhibition stops the generation of nsps, while N7-MTase inhibition prevents the synthesis of stable transcripts of the viral RNA. Created with BioRender.com. | PMC10242237 | 41598_2023_35907_Fig1_HTML.jpg |
0.460994 | 4eb49f76d79a462bb6072a1f4a740607 | Plausible catalytic cycle of ebselen involving hydrogen peroxide reduction, including formation of the ebselen open form (dark blue color)33,37. | PMC10242237 | 41598_2023_35907_Fig2_HTML.jpg |
0.434643 | 1d7b0cd5b1a6416b9014aa31978abddf | Preparation of ebselen, its derivatives and their ‘dimeric’ form analogues 1–33. Reagents and conditions: (a) (i) aq. HCl, (ii) NaNO2, − 7 to + 7 °C, (b) (i) NaSeSeNa, MeOH, NaOH or LiSeSeLi, THF, HMPTA, − 7 to + 5 °C, (ii) aq. HCl, (c) 7 equiv SOCl2, cat. (DMF), benzene, reflux, (d) RNH2, Et3N, MeCN or DCM, (e) 3.5 equiv SOCl2, cat. (DMF), benzene, reflux, (f) RNH2, Na2CO3, DCM, (g) H2N-NH2∙H2O, MeOH, reflux. (Carried out in accordance with Refs.60,62–64. | PMC10242237 | 41598_2023_35907_Fig3_HTML.jpg |
0.430088 | 84f771c9c3bb4e6cb9641a74d12b3a92 |
Flow diagram for the evidence identification and selection process.
| PMC10242442 | lmt-12-59-g1.jpg |
0.404308 | c0ca9f11529b4449a355644e29a73e54 |
Risk of bias assessment.
(A) Risk of bias summary. (B) Risk of bias graph. All studies included in this assessment were open-label studies; however, considering the objective nature of the outcomes and assessment by independent reviewers, participants' knowledge of the allocation group was judged not to affect the study results. | PMC10242442 | lmt-12-59-g2.jpg |
0.4652 | e373d8452874487baa38de34d69bfaa0 |
Network geometry and forest plot for overall survival and progression-free survival comparing alectinib 600 mg with the other ALK inhibitors.
(A) Network geometry for OS. (B) Forest plot for OS for alectinib 600 mg compared to other ALK inhibitors. (C) Network geometry for PFS. (D) Forest plot for PFS for alectinib 600 mg compared to other ALK inhibitors.HR: Hazard ratio; OS: Overall survival; PFS: Progression-free survival. | PMC10242442 | lmt-12-59-g3.jpg |
0.425761 | 450e7e52d58440e59d9e6bd02439c6af |
Network geometry and forest plot for progression-free survival comparing alectinib 600 mg with the other ALK inhibitors among subgroups with/without CNS metastasis at baseline.
(A) Network geometry for progression-free survival of patients with CNS metastasis at baseline. (B) Forest plot for PFS for alectinib 600 mg compared to other ALK inhibitors among patients with CNS metastasis at baseline. (C) Network geometry for PFS of patients without CNS metastasis at baseline. (D) Forest plot for PFS for alectinib 600 mg compared to other ALK inhibitors among patients without CNS metastasis at baseline.HR: Hazard ratio; PFS: Progression-free survival. | PMC10242442 | lmt-12-59-g4.jpg |
0.420786 | 19310f07da7a42eb8a12b22305234a96 |
Network geometry and forest plot for serious adverse events comparing alectinib 600 mg with the other ALK inhibitors.
(A) Geometry for the network for SAEs. (B) Forest plot for SAEs for alectinib 600 mg compared to other ALK inhibitors.RR: Relatvie risk; SAE: Serious adverse event. | PMC10242442 | lmt-12-59-g5.jpg |
0.492203 | b2a364af9d6f487db483cc68518a8f99 | Histograms of DE-miRNAs in control compared with vaccinated water buffaloes. Significance was declared at P < 0.05 (*), P < 0.01 (**), and P < 0.001 (***). | PMC10242922 | 13567_2023_1175_Fig1_HTML.jpg |
0.410639 | cad910339f404576b1da05d197e61611 | Receiver-operator characteristics (ROC) curve comparing control and vaccinated water buffaloes.
A ROC of miR-148a-3p; B ROC of miR-370-3p; and C ROC of hv-miR-B6-5p. AUC, area under the curve; CI, confidence interval. | PMC10242922 | 13567_2023_1175_Fig2_HTML.jpg |
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