216 research outputs found

    Laboratory experiments reveal the influences of amplitude and duration of cyclic loading on earthquake-triggered landslides

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      The data describe the changes in the mechanical properties of the sample during vibration, all from experiments.</pre

    Image_1_Hot Tea Consumption and Esophageal Cancer Risk: A Meta-Analysis of Observational Studies.TIF

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    ObjectiveMany laboratory studies have shown that tea consumption protected against the development of esophageal cancer (EC). However, in epidemiological studies, inconsistent or even contradictory results were frequently observed, especially when drinking tea at higher temperatures.MethodsWe conducted a meta-analysis based on published observational studies to explore whether hot tea consumption was a risk factor of EC. Relevant studies were searched in PubMed, Embase, and Web of science up to October 13, 2021, and we also manually retrieved the literature in the included studies and recent reviews.ResultsA total of 23 eligible reports were identified, including 5,050 cases and 10,609 controls, and a meta-analysis with Comprehensive Meta-Analysis (CMA) software (version 2.0) was conducted. A statistically significant increased EC risk was observed when drinking tea at higher temperature (odds ratios (ORs) = 1.79, 95% CI: 1.48–2.15, p = 0.00). Except for esophageal adenocarcinoma (EAC), this increased risk was also found in the majority of subgroups, which are the European and Australian populations.ConclusionsThis meta-analysis showed that people who drank hot tea had a significantly increased risk of Esophageal squamous cell carcinoma (ESCC), but no significant association for EAC.</p

    MOESM6 of Transcriptome analysis reveals an important candidate gene involved in both nodal metastasis and prognosis in lung adenocarcinoma

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    Additional file 6: Table S5. The univariate Cox analysis of related clinical parameters and RN7SL494P in lung adenocarcinoma

    MOESM5 of Transcriptome analysis reveals an important candidate gene involved in both nodal metastasis and prognosis in lung adenocarcinoma

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    Additional file 5: Table S4. Clinical and laboratory features of the subjects included in the study

    MOESM7 of Transcriptome analysis reveals an important candidate gene involved in both nodal metastasis and prognosis in lung adenocarcinoma

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    Additional file 7: Table S6. KEGG analyses of the biological functions and pathways associated with the RN7SL494P identified

    MOESM1 of Transcriptome analysis reveals an important candidate gene involved in both nodal metastasis and prognosis in lung adenocarcinoma

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    Additional file 1: Table S1. The top 10 significant down- and up-regulated genes associated with lung adenocarcinoma

    Additional file 1 of Dopamine enhances recovery after traumatic brain injury through ubiquitylation and autophagic degradation of RIPK1

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    Additional file 1: Supplementary Table 1. Clinical information of human brain specimens. Supplemental fig 1. Assessment of siRNA on Drd1, Drd2, Drd3, Drd4 and Drd5. Supplemental fig 2. Assessment of E3 ligase proteins

    MOESM2 of Transcriptome analysis reveals an important candidate gene involved in both nodal metastasis and prognosis in lung adenocarcinoma

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    Additional file 2: Figure S1. The differentially-expressed genes analyses. A, B Total differential expression genes in lung adenocarcinoma (A heatmap, B volcano map); C, D The differential expression genes in nodal metastasis (C heatmap, D volcano map); E, F The differential expression genes in TNM staging (E heatmap, F volcano map)

    MOESM3 of Transcriptome analysis reveals an important candidate gene involved in both nodal metastasis and prognosis in lung adenocarcinoma

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    Additional file 3: Table S2. The KEGG pathway differential gene function annotation with Kobas algorithm

    MOESM4 of Transcriptome analysis reveals an important candidate gene involved in both nodal metastasis and prognosis in lung adenocarcinoma

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    Additional file 4: Table S3. The KEGG analysis of differentially expressed-genes with clusterProfiler R package
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