Evidence map›Paper›PMID 40406682›Full record

ArticleJournal of inflammation research2025

Identification of Fatty Acid Metabolism Disorder-Related Gene Signature in Septic Cardiomyopathy.

Liman Li, Tiancong Zhang, Chuan Yang, Qiang Meng, Shuang Wang, Yang Fu

Abstract read
In one paragraph

Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Liman LiDepartment of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, Sichuan Province, People's Republic of China.
Tiancong ZhangDepartment of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, Sichuan Province, People's Republic of China.
Chuan YangLaboratory of Pulmonary Immunology and Inflammation, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China.
Qiang MengDepartment of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, Sichuan Province, People's Republic of China.
Shuang WangDepartment of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, Sichuan Province, People's Republic of China.
Yang FuDepartment of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, Sichuan Province, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Septic cardiomyopathy (SCM) is a prevalent complication of sepsis and a primary contributor to mortality in patients with sepsis. Although fatty acid metabolism (FAM) is known to regulate cardiac function, its specific role in the pathogenesis of SCM remains unclear. Methods: The SCM datasets were obtained from the NCBI GEO database. Differentially expressed genes (DEGs) were subjected to GO and KEGG pathway analyses. The fatty acid metabolism-related genes were obtained from the MSigDB database. CytoHubba and machine learning algorithms identified hub FAM-DEGs. Associated transcriptional factors and miRNAs of hub FAM-DEGs were predicted using Cytoscape software and miRWalk 3.0 database. The immune infiltration pattern in SCM was analyzed using the ImmuCellAI tool. The relationship between hub FAM-DEGs and immune infiltration abundance was investigated using Spearman method. Hub FAM-DEGs expression levels were validated in clinical samples and mouse models. Results: Five hub FAM-DEGs associated with SCM were identified, including Conclusion: This study revealed fatty acid metabolism played a crucial role in SCM and identified DHCR24 may act as a potential diagnostic biomarker and therapeutic target in SCM.

Indexed as

DHCR24fatty acid metabolismSepsisseptic-cardiomyopathy

Identifiers

PMID40406682
PMCPMC12096332

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.