Table 6_The mechanism of gut microbiota in septic cardiomyopathy based on the bulk transcr

A research dataset from figshare, authored by Yuxia Tao and last updated on 2026-05-04, presents results from a study on septic cardiomyopathy. The analysis integrates genome-wide association study data, Mendelian randomization, and bulk transcriptome analysis to identify candidate biomarkers. It includes results for 5 gut microbiota, 22 metabolites, 461 targets, and 166 differentially expressed genes, culminating in the identification of STAT3 and SLC5A1 as key biomarkers.

Use Cases

• Validating candidate biomarkers STAT3 and SLC5A1 for septic cardiomyopathy based on the intersection of gut microbiota targets and differentially expressed genes.
• Conducting pathway enrichment analysis based on the valine, leucine, and isoleucine degradation pathways identified in the study.
• Investigating immune cell involvement in septic cardiomyopathy based on the analysis of MDSCs and activated dendritic cells.
• Exploring regulatory networks based on identified transcription factors (e.g., FOXC1) and microRNAs (e.g., miR-3120-3p) linked to the biomarkers.
• Performing molecular docking simulations based on the binding activity data for the metabolite propylene glycol with the biomarkers.

Strengths

• Dataset is openly licensed under CC-BY-4.0, permitting broad reuse.
• Analysis is based on multiple public data sources and methods, including GWAS, Mendelian randomization, and differential expression analysis.
• Findings are validated with clinical sample data, including ELISA for IL-6 and cTnI, GC-MS for propylene glycol, and RT-qPCR for gene expression.

Limitations

• The dataset is very small at 16.6 KB, indicating limited raw data and likely containing only summary results.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.

Provenance

Source

figshare, author Yuxia Tao.

Collection Method

Analysis of public GWAS and gut microbiota data using Mendelian randomization, differential expression analysis, and machine learning algorithms.

Freshness

Last updated 2026-05-04 09:32:33; freshness should be verified.