Table 3_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.xlsx by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Image 3_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.tif by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Table 7_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.xls by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Image 2_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.tif by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Table 8_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.xls by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Table 9_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.xls by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Image 7_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.tif by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Table 5_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.xlsx by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Image 4_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.tif by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Image 5_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.tif by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Table 6_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.xls by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Table 2_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.docx by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Table 4_Integrative RNA-seq and CLIP-seq analysis reveals hnRNP-F regulation of TNFα/NFκB signaling in high-glucose conditions.xlsx by Lan Wang (85307)

“…By analyzing CLIP-seq and RNA-seq data, we found that hnRNP-F may inhibit gene expression by binding to lncRNA SNHG1. Conversely, this upregulation led to a significant increase in alternative splicing events of genes implicated in DKD, such as hnRNPA2B1, OSML, UGT2B7, TRIP6, and IRF3. …”

Table 3_Global, regional, and national burden of premenstrual syndrome from 1990 to 2021 and projections to 2050: an analysis based on the 2021 Global Burden of Disease study.xlsx by Ruonan Qiang (22753394)

“…Background<p>Premenstrual syndrome (PMS) imposes significant psychological and mental health burdens on women’s reproductive and general well-being. …”

Table 2_Global, regional, and national burden of premenstrual syndrome from 1990 to 2021 and projections to 2050: an analysis based on the 2021 Global Burden of Disease study.xlsx by Ruonan Qiang (22753394)

“…Background<p>Premenstrual syndrome (PMS) imposes significant psychological and mental health burdens on women’s reproductive and general well-being. …”

Table 2_Epidemiology of second trimester induced abortion in Ethiopia: a systematic review and meta-analysis.docx by Mesfin Abebe (12400154)

“…The pooled prevalence of second-trimester induced abortion in Ethiopia was found to be 29.10% (95% CI: 19.96–38.24; I² = 97.84, P < 0.000). Delay in confirming pregnancy (POR = 4.33, 95% CI: 2.25, 8.32), nature of the menstrual cycle (POR = 0.32, 95% CI: 0.18, 0.56), residence (POR = 0.38, 95% CI: 0.30, 0.49), and pregnancy intention (POR = 0.28, 95% CI: 0.18, 0.42) were significantly associated with second-trimester induced abortion.…”

Consequences of SARS-CoV-2 infection on testis function. by Stefanos Giannakopoulos (15628394)

“…Significance (*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001) was determined using student’s t-test. …”

ROC analysis to mark selectivity results in mostly mixed-selective units. by Thomas S. Wierda (22404198)

“…The large number of mixed selective units also results in a significant decrease in accuracy when these neurons are targeted as compared to <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013559#pcbi.1013559.g006" target="_blank">Fig 6c</a> where there was no significant effect visible after targeting mixed selective units, likely because there were less mixed selective units present. …”

Table 3_Unveiling the immunological landscape of disseminated tuberculosis: a single-cell transcriptome perspective.xlsx by Zhen Gong (292434)

“…Analysis of the complementarity determining region 3 (CDR3) showed that the most frequent combination was TRAV1-2/TRAJ33, with the motif “CAAMD” being significantly reduced in DTB patients.…”

Image 3_Unveiling the immunological landscape of disseminated tuberculosis: a single-cell transcriptome perspective.jpeg by Zhen Gong (292434)

“…Analysis of the complementarity determining region 3 (CDR3) showed that the most frequent combination was TRAV1-2/TRAJ33, with the motif “CAAMD” being significantly reduced in DTB patients.…”