Evidence mapPaperPMID 40510362Full record

ArticleFrontiers in immunology2025

Identification of diagnostic genes for myocardial ischemia reperfusion injury associated with metabolic syndrome through the integration of bioinformatics analysis, molecular docking and experimental validation.

Shufang Liu, Yan Zhang, Yanan Zhao, Ping Wu, Shouyuan Tian, Han-Qing Pang, Zhifang Wu, Sijin Li

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Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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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

8 authors.

Shufang LiuDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Yan ZhangDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Yanan ZhaoSchool of Anesthesiology, Shanxi Medical University, Taiyuan, China.
Ping WuDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Shouyuan TianDepartment of Anesthesiology, Shanxi Provincial People's Hospital, Taiyuan, China.
Han-Qing PangInstitute of Translational Medicine, School of Medicine, Yangzhou University, Yangzhou, China.
Zhifang WuDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.
Sijin LiDepartment of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Metabolic dysregulation in metabolic syndrome (MetS) exacerbates myocardial ischemia-reperfusion injury (MIRI). This study aimed to identify diagnostic biomarkers and therapeutic candidates for MetS-associated MIRI. Methods: Three MIRI and two MetS datasets from GEO were analyzed using differential expression analysis, WGCNA, and machine learning (LASSO/SVM-RFE). Hub genes were validated via qRT-PCR in hypoxia-induced H9C2 cells. Drug candidates were predicted via PPI networks, CTD, and molecular docking, followed by experimental evaluation of dexamethasone. Results: Five hub genes-DAK, GTF3C5, KCNMB1, TRAF1, and ZNF692-were identified, with distinct expression patterns (DAK/GTF3C5 downregulated; KCNMB1/TRAF1/ZNF692 upregulated). These genes were enriched in immune-related pathways, and their diagnostic performance was robust (AUCs: 0.875-0.969). Dexamethasone downregulated KCNMB1/TRAF1/ZNF692 and reduced apoptosis in H9C2 cells. Conclusion: This study reveals immune-metabolic dysregulation as a key driver of MetS-MIRI, proposes five biomarkers for diagnosis, and highlights dexamethasone as a promising therapeutic candidate.

Indexed as

Computational BiologyMetabolic SyndromeMyocardial Reperfusion InjuryAnimalsBiomarkersCell LineDexamethasoneGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksHumansMolecular Docking SimulationProtein Interaction MapsRatsBiomarkersDexamethasoneimmune infiltrationmachine learningmetabolic syndromemolecular dockingmyocardial ischemia reperfusion injury

Identifiers

PMID40510362
PMCPMC12158706

What Socratic holds

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Registered trials

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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 Socratic graph.