Table_1_Long Non-coding RNA ENST00000453774.1 Confers an Inhibitory Effect on Renal Fibrosis by Inhibiting miR-324-3p to Promote NRG1 Expression.DOCX by Shumei Tang (11728844)

“…Meanwhile, overexpression of lncRNA 74.1 or down-regulation of miR-324-3p increased the levels of ATG5, ATG7, LC3II, and LC3I, and decreased levels of P62, Collagen I, Fibronectin, and α-SMA, accompanied by elevated proportions of LC3 positive cells and autophagosomes. …”

Table2_Differences in global, regional, and national time trends in disability-adjusted life years for atrial fibrillation and flutter, 1990–2019: an age-period-cohort analysis fro... by Juan Tang (437969)

“…</p>Results<p>The global number of DALYs cases was 8,393,635 [95% uncertainty interval (UI): 6,693,987 to 10,541,461], indicating a 121.6% rise (95% UI: 111.5 to 132.0) compared to 1990. …”

DataSheet2_Effects of immune inflammation in head and neck squamous cell carcinoma: Tumor microenvironment, drug resistance, and clinical outcomes.ZIP by Li Zhu (67404)

“…</p><p>Results: Using univariate, LASSO, and multivariate cox regression analyses, we developed a prognostic risk model for HNSCC based on 13 genes associated with inflammatory factors (ITGA5, OLR1, CCL5, CXCL8, IL1A, SLC7A2, SCN1B, RGS16, TNFRSF9, PDE4B, NPFFR2, OSM, ROS1). …”

Biomarker Benchmark - GSE37199 by Anna Guyer (1390293)

“…LPD1 CRPC patients had significantly poorer overall survival (median 10.7 months, CI-95% 4.2-17.2) than CRPC patients in LPD2 to 4 (median 26.5 months, CI-95% 18.1-34.9, p=0.00007). LPD 1 membership remained the strongest prognostic factor in a multivariate analysis (HR 5.0, CI-95% 2.1-11.9, p=0.0002). …”

DataSheet1_Effects of immune inflammation in head and neck squamous cell carcinoma: Tumor microenvironment, drug resistance, and clinical outcomes.ZIP by Li Zhu (67404)

“…</p><p>Results: Using univariate, LASSO, and multivariate cox regression analyses, we developed a prognostic risk model for HNSCC based on 13 genes associated with inflammatory factors (ITGA5, OLR1, CCL5, CXCL8, IL1A, SLC7A2, SCN1B, RGS16, TNFRSF9, PDE4B, NPFFR2, OSM, ROS1). …”

Supplementary Material for: Impact of antibiotic therapy in patients with cholangiocarcinoma treated with chemoimmunotherapy by figshare admin karger (2628495)

Table1_Effects of immune inflammation in head and neck squamous cell carcinoma: Tumor microenvironment, drug resistance, and clinical outcomes.XLSX by Li Zhu (67404)

“…</p><p>Results: Using univariate, LASSO, and multivariate cox regression analyses, we developed a prognostic risk model for HNSCC based on 13 genes associated with inflammatory factors (ITGA5, OLR1, CCL5, CXCL8, IL1A, SLC7A2, SCN1B, RGS16, TNFRSF9, PDE4B, NPFFR2, OSM, ROS1). …”

Nkx1.2 mediates FGF-dependent FP competence. by Noriaki Sasai (217813)

“…<p>(A) Histogram summarizing the mRNA-seq analysis of RNA from [i] explants taken immediately after preparation (i), after 12 h in vitro culture without (ii) or with 5 nM FGF (iii). …”

Table2_Effects of immune inflammation in head and neck squamous cell carcinoma: Tumor microenvironment, drug resistance, and clinical outcomes.DOCX by Li Zhu (67404)

“…</p><p>Results: Using univariate, LASSO, and multivariate cox regression analyses, we developed a prognostic risk model for HNSCC based on 13 genes associated with inflammatory factors (ITGA5, OLR1, CCL5, CXCL8, IL1A, SLC7A2, SCN1B, RGS16, TNFRSF9, PDE4B, NPFFR2, OSM, ROS1). …”

Table_3_Identifying Temporally Regulated Root Nodulation Biomarkers Using Time Series Gene Co-Expression Network Analysis.xlsx by William L. Poehlman (7598351)

“…Following gene expression quantification, we identified 1,758 differentially expressed genes at various time points. We constructed a gene co-expression network (GCN) from the same data and identified link community modules (LCMs) that were comprised entirely of differentially expressed genes at specific time points post-inoculation. …”

Image_2_Identifying Temporally Regulated Root Nodulation Biomarkers Using Time Series Gene Co-Expression Network Analysis.tif by William L. Poehlman (7598351)

“…Following gene expression quantification, we identified 1,758 differentially expressed genes at various time points. We constructed a gene co-expression network (GCN) from the same data and identified link community modules (LCMs) that were comprised entirely of differentially expressed genes at specific time points post-inoculation. …”

Table_1_Identifying Temporally Regulated Root Nodulation Biomarkers Using Time Series Gene Co-Expression Network Analysis.xlsx by William L. Poehlman (7598351)

“…Following gene expression quantification, we identified 1,758 differentially expressed genes at various time points. We constructed a gene co-expression network (GCN) from the same data and identified link community modules (LCMs) that were comprised entirely of differentially expressed genes at specific time points post-inoculation. …”

Table_4_Identifying Temporally Regulated Root Nodulation Biomarkers Using Time Series Gene Co-Expression Network Analysis.xlsx by William L. Poehlman (7598351)

“…Following gene expression quantification, we identified 1,758 differentially expressed genes at various time points. We constructed a gene co-expression network (GCN) from the same data and identified link community modules (LCMs) that were comprised entirely of differentially expressed genes at specific time points post-inoculation. …”

Image_1_Identifying Temporally Regulated Root Nodulation Biomarkers Using Time Series Gene Co-Expression Network Analysis.tif by William L. Poehlman (7598351)

“…Following gene expression quantification, we identified 1,758 differentially expressed genes at various time points. We constructed a gene co-expression network (GCN) from the same data and identified link community modules (LCMs) that were comprised entirely of differentially expressed genes at specific time points post-inoculation. …”

Table_2_Identifying Temporally Regulated Root Nodulation Biomarkers Using Time Series Gene Co-Expression Network Analysis.xlsx by William L. Poehlman (7598351)

“…Following gene expression quantification, we identified 1,758 differentially expressed genes at various time points. We constructed a gene co-expression network (GCN) from the same data and identified link community modules (LCMs) that were comprised entirely of differentially expressed genes at specific time points post-inoculation. …”

Charge-Transfer Salts of Biferrocene Derivatives with F₂- and F₄‑Tetracyanoquinodimethane: Correlation Between Donor–Acceptor Ratios and Cation Valence States... by Tomoyuki Mochida (1473574)

“…F₂- and F₄-tetracyanoquinodimethane (TCNQ) produced salts with D/A ratios of 1:3 ([<b>D1</b>]­[F₂TCNQ]₃, [<b>D2</b>]­[F₂TCNQ]₃), 1:2 ([<b>D2</b>]­[F₄TCNQ]₂, [<b>D3</b>]­[F₄TCNQ]₂), 2:3 ([<b>D1</b>]₂­[F₄TCNQ]₃), and 1:1 ([<b>D2</b>]­[F₄TCNQ], [<b>D4</b>]­[F₂TCNQ], [<b>D4</b>]­[F₄TCNQ], [<b>D5</b>]­[F₄TCNQ]). …”

Hierarchical Structural Changes During Redox Cycling of Fe-Based Lamellar Foams Containing YSZ, CeO₂, or ZrO₂ by Stephen K. Wilke (8933240)

“…Volumetric shrinkage after the first five redox cycles is decreased from 66% (for pure-Fe foams) to 45% (for all Fe-composites containing 5 vol % SI). …”

Sodium Transporters Are Involved in Lithium Influx in Brain Endothelial Cells by Huilong Luo (1442794)

“…Our study shows that NHE1 and/or NHE5, NBCn1, and NKCC1 may play a significant role in the transport of Li⁺ through the plasma membrane of brain endothelial cells.…”

Data_Sheet_1_Trend of myopia through different interventions from 2010 to 2050: Findings from Eastern Chinese student surveillance study.docx by Xiyan Zhang (5680457)

“…The overall number of myopic people can be greatly decreased by implementing timely, steady, comprehensive interventions.…”

Table_1_Analysis of hospital and payer costs of care: aggressive warming versus routine warming in abdominal major surgery.DOCX by Shujia Song (17322790)

“…The potential benefit of aggressive warming was in the reduced extubation time (7.96 ± 4.33 min vs. 10.33 ± 5.87 min, p < 0.001), lower incidence of prolonged extubation (5.6% vs. 13.9%, p = 0.017), and decreased staff costs. …”