Evidence map›Paper›PMID 41866423›Full record

ArticleScientific reports2026

Identification of key genes in the pathogenesis of hepatic ischemia-reperfusion injury based on bioinformatics and experimental verification.

Tao Zhang, Zhixian Jiang, Qingqing Zhao, Junyi Qiu, Qin Xiong, Shi Zuo

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Tao ZhangSchool of Clinical Medicine, Guizhou Medical University, Guiyang, 550014, People's Republic of China.
Zhixian JiangSchool of Clinical Medicine, Guizhou Medical University, Guiyang, 550014, People's Republic of China.
Qingqing ZhaoClinical Research Center, Affiliated Hospital of Guizhou Medical University, Guiyang, 550001, People's Republic of China.
Junyi QiuSchool of Pharmaceutical Science and Technology, Guizhou Medical University, Guiyang, 550014, People's Republic of China.
Qin XiongSchool of Pharmaceutical Science and Technology, Guizhou Medical University, Guiyang, 550014, People's Republic of China.
Shi ZuoDepartment of Hepatobiliary Surgery, Affiliated Hospital of Guizhou Medical University, Guiyang, 550001, People's Republic of China. drzuoshi@gmc.edu.cn.

Funding

Guizhou Province High-Quality Development Medical Research Joint Fund 2024GZYXKYJJXM0020Guizhou Provincial Health Commission gzwkj2025-312Guizhou Provincial Science and Technology Projects ZK [2024]039The National Natural Science Foundation of China 82260535
6 · The paper itself

Abstract

Hepatic ischemia-reperfusion injury (HIRI) is a frequently encountered complication during liver surgical procedures, characterized by ischemia-induced damage and exacerbated inflammatory injury upon reperfusion. The underlying mechanisms remain incompletely understood, and few targeted therapies are currently available. By employing a mouse HIRI model and whole-transcriptome sequencing, we obtained gene expression profiles across different HIRI stages. 115 candidate genes were identified by differential and intersection analyses of the self-sequenced data, which were further prioritized using protein-protein interaction network analysis and machine learning algorithms. Ultimately, three key genes-Adh4, Akr1c14, and Cxcl1-were identified, which were mainly enriched in in pathways such as aerobic respiration, mitochondrial protein containing complex, ribonucleoprotein complex biogenesis. Immune infiltration analysis indicated significant changes in 13 immune cell types, including granulocytes and neutrophils. Construction of a molecular regulatory network highlighted potential regulators such as the long non-coding RNA Socs1, transcription factor NFKB1, and microRNA mmu-let-7b-5p. The key genes were verified at both transcriptional and translational levels with animal model samples. Notably, ladarixin, a non-competitive antagonist of CXCR1/2, exhibited a protective effect against HIRI, suggesting that Cxcl1 may serve as a promising therapeutic target. However, further comprehensive research is necessary to gain deeper insights into the exact mechanisms by which these genes function.

Indexed as

Computational BiologyLiverLiver DiseasesReperfusion InjuryAnimalsChemokine CXCL1Disease Models, AnimalGene Expression ProfilingGene Regulatory NetworksMaleMiceProtein Interaction MapsTranscriptomeChemokine CXCL1Cxcl1 protein, mouseGene set enrichment analysisHepatic ischemia-reperfusion injuryImmune infiltration analysisMachine learningTherapeutic targets

Identifiers

PMID41866423
PMCPMC13153378

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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.