Table 1_The mechanism of gut microbiota in septic cardiomyopathy based on the bulk transcr

Yuxia Tao's research dataset, last updated May 4, 2026, contains results from a study exploring the mechanistic role of gut microbiota in septic cardiomyopathy. The analysis integrates bulk transcriptome data, Mendelian randomization from public GWAS sources, and clinical sample validation to identify candidate biomarkers. The 12.0 KB Excel file includes findings on key microbiota, metabolites, and gene targets linked to the condition.

Use Cases

• Validate candidate biomarkers STAT3 and SLC5A1 for septic cardiomyopathy based on the intersection of gut microbiota targets and differentially expressed genes.
• Investigate causal relationships between specific gut microbiota (e.g., genus.Bifidobacterium) and sepsis using the Mendelian randomization results.
• Explore regulatory networks involving transcription factors (e.g., FOXC1) and microRNAs (e.g., miR-3120-3p) linked to the identified biomarkers.
• Analyze immune cell infiltration patterns, such as MDSCs and activated dendritic cells, in septic cardiomyopathy based on the immune analysis results.
• Perform in silico binding studies for metabolites like propylene glycol with biomarker proteins using the molecular docking and dynamics simulation data.

Strengths

• Dataset is underpinned by multiple analytical methods, including Mendelian randomization, differential expression analysis, and machine learning.
• Findings are validated with clinical samples measuring IL-6, cTnI, propylene glycol, and gene expression via RT-qPCR.
• Results identify specific quantities: 5 gut microbiota, 22 metabolites, 461 targets, 166 DEGs, and 2 final biomarkers.

Limitations

• Row count and specific column definitions are unknown, requiring manual inspection after download to understand data structure.
• The dataset is very small (12.0 KB), indicating it contains summary results rather than raw, large-scale omics data.
• Data freshness should be verified as the last update timestamp is in the future (2026-05-04).

Provenance

Source

figshare, author Yuxia Tao.

Collection Method

Analysis of public GWAS data, differential expression analysis, Mendelian randomization, machine learning, and clinical sample validation.

Freshness

Last updated 2026-05-04 09:32:40.