ArticleExperimental and therapeutic medicine2016
Regulatory mechanisms underlying sepsis progression in patients with tumor necrosis factor-α genetic variations.
Article in Experimental and therapeutic medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- OsCSN2 orchestrates Oryza sativa L. growth and development through modulation of the GA and BR pathways.Functional & integrative genomics · 2024Article
- Article
- Combining Blood-Based Biomarkers to Predict Mortality of Sepsis at Arrival at the Emergency Department.Medical science monitor : international medical journal of experimental and clinical research · 2021Article
- Mortality prediction using a novel combination of biomarkers in the first day of sepsis in intensive care units.Scientific reports · 2021Observational
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study aimed to investigate the regulatory mechanisms underlying sepsis progression in patients with tumor necrosis factor (TNF)-α genetic variations. The GSE5760 expression profile data, which was downloaded from the Gene Expression Omnibus database, contained 30 wild-type (WT) and 28 mutation (MUT) samples. Differentially expressed genes (DEGs) between the two types of samples were identified using the Student's t-test, and the corresponding microRNAs (miRNAs) were screened using WebGestalt software. An integrated miRNA-DEG network was constructed using the Cytoscape software, based on the interactions between the DEGs, as identified using the Search Tool for the Retrieval of Interacting Genes/Proteins database, and the correlation between miRNAs and their target genes. Furthermore, Gene Ontology and pathway enrichment analyses were conducted for the DEGs using the Database for Annotation, Visualization and Integrated Discovery and the KEGG Orthology Based Annotation System, respectively. A total of 390 DEGS between the WT and MUT samples, along with 11 -associated miRNAs, were identified. The integrated miRNA-DEG network consisted of 38 DEGs and 11 miRNAs. Within this network,
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