Evidence map›Paper›PMID 40634559›Full record

ArticleScientific reports2025

Integrated bioinformatics and experimental analysis of mitochondrial-associated membrane function and mechanism in acute respiratory distress syndrome​​.

Yanqiong Zhou, Qiuying Chen, Xiaoxia Wang, Kaimin Lv, Hui Huang, Jifeng Feng, Bijun Luo

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Yanqiong Zhou *Department of Anesthesiology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, No.59 Xiangzhu Avenue, Nanning, 530002, Guangxi, China.
Qiuying Chen *Department of Anesthesiology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, No.59 Xiangzhu Avenue, Nanning, 530002, Guangxi, China.
Xiaoxia WangDepartment of Anesthesiology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, No.59 Xiangzhu Avenue, Nanning, 530002, Guangxi, China.
Kaimin LvDepartment of Anesthesiology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, No.59 Xiangzhu Avenue, Nanning, 530002, Guangxi, China.
Hui HuangDepartment of Anesthesiology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, No.59 Xiangzhu Avenue, Nanning, 530002, Guangxi, China.
Jifeng FengDepartment of Anesthesiology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, No.59 Xiangzhu Avenue, Nanning, 530002, Guangxi, China. 604282082@qq.com.
Bijun LuoDepartment of Anesthesiology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, No.59 Xiangzhu Avenue, Nanning, 530002, Guangxi, China. 13807719092@163.com.

Funding

"139" plan for high-level medical backbone talents of Guangxi Zhuang Autonomous Region G202002015Guangxi Medical and Health Appropriate Technology Developmental and Popularizational Application Project S2024084National Natural Science Foundation of China 82060024
6 · The paper itself

Abstract

Acute respiratory distress syndrome (ARDS) is a life-threatening lung condition characterized by severe inflammation, immune dysregulation, and oxidative stress, leading to high mortality (30-40%). This study explores the involvement of MAM-related genes in ARDS pathogenesis through bioinformatics and experimental validation. Publicly available RNA-sequencing data from ARDS and control samples were analyzed to identify differentially expressed genes (DEGs). Functional enrichment, gene set variation analysis (GSVA), and weighted gene co-expression network analysis (WGCNA) were performed to explore pathway alterations and hub gene interactions. Immune cell infiltration analysis was conducted using CIBERSORT. Candidate MAM-related genes were validated in a Poly I: C-induced ARDS mouse model and MLE-12 murine lung epithelial cells. The mouse model was assessed for lung histopathology, wet-to-dry lung weight ratio, bronchoalveolar lavage fluid (BALF) inflammatory cytokine levels (IL-1β and TNF-α), and lung injury scores. MLE-12 cells were treated with Poly I: C, and cell viability, lactate dehydrogenase (LDH) release, and apoptosis were evaluated. Protein-protein interaction (PPI) network analysis and drug prediction were used to identify potential therapeutic targets. A total of 3152 DEGs including 1549 upregulated and 1603 downregulated were identified in ARDS samples. Pathway analysis revealed autophagy suppression and immune activation, with 14 immune cell types significantly elevated in ARDS patients. Experimental validation confirmed that Poly I: C-induced ARDS mice exhibited severe lung injury and increased inflammatory reaction, while Poly I: C-treated MLE-12 cells showed increased cytotoxicity and LDH release. ZMAT2 and HBB were identified as key MAM-related hub genes, with ZMAT2 positively associated with disease progression and HBB negatively correlating with lung injury severity. Drug prediction analysis identified 29 pharmacological agents interacting with HBB, suggesting therapeutic potential. This study identifies ZMAT2 and HBB as key MAM-related genes contributing to ARDS pathogenesis, with potential diagnostic and therapeutic applications. The integration of bioinformatics with in vivo and in vitro validation provides novel insights into ARDS molecular mechanisms. Further clinical studies are needed to explore their translational relevance.

Indexed as

Computational BiologyMitochondriaRespiratory Distress SyndromeAnimalsApoptosisCell LineDisease Models, AnimalGene Expression ProfilingGene Regulatory NetworksHumansLungMaleMicePoly I-CProtein Interaction MapsPoly I-CARDSBioinformaticsMitochondria-associated membraneTherapeutic targetsViral pneumonia

Identifiers

PMID40634559
PMCPMC12241502

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.