Evidence map›Paper›PMID 33687057›Full record

ArticleBioscience reports2021

Mining the key genes for ventilator-induced lung injury using co-expression network analysis.

Zhao Li, Yajun Xiao, Li Xu, Qingxiu Wang

Abstract read
In one paragraph

Article in Bioscience reports, 2021. 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

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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

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Zhao LiDepartment of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai, P.R. China.
Yajun XiaoDepartment of Endocrinology, Affiliated Nanhua Hospital, University of South China, Hengyang, P.R. China.
Li XuDepartment of Anesthesiology, The First People's Hospital of Changde, Changde, P.R. China.
Qingxiu WangDepartment of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mechanical ventilation is extensively adopted in general anesthesia and respiratory failure management, but it can also induce ventilator-induced lung injury (VILI). Therefore, it is of great urgency to explore the mechanisms involved in the VILI pathogenesis, which might contribute to its future prevention and treatment. Four microarray datasets from the GEO database were selected in our investigation, and were subjected to the Weighted Gene Co-Expression Network Analysis (WGCNA) to identify the VILI-correlated gene modules. The limma package in R software was used to identify the differentially expressed genes (DEGs) between the VILI and control groups. WGCNA was constructed by merging the GSE9314, GSE9368, GSE11434 and GSE11662 datasets. A total of 49 co-expression network modules were determined as associated with VILI. The intersected genes between hub genes screened from DEGs for VILI and those identified using WGCNA were as follows: Tlr2, Hmox1, Serpine1, Mmp9, Il6, Il1b, Ptgs2, Fos and Atf3, which were determined to be key genes for VILI. Those key genes were validated by GSE86229 and quantitative PCR (qPCR) experiment to have significantly statistical difference in their expression between the VILI and control groups. In a nutshell, nine key genes with expression differences in VILI were screened by WGCNA by integrating multiple datasets.

Indexed as

Gene Regulatory NetworksTranscriptomeActivating Transcription Factor 3AnimalsComputational BiologyCyclooxygenase 2Heme Oxygenase-1InterleukinsMatrix Metalloproteinase 9Membrane ProteinsMicePlasminogen Activator Inhibitor 1Toll-Like Receptor 2Ventilator-Induced Lung InjuryActivating Transcription Factor 3Atf3 protein, mouseCyclooxygenase 2Heme Oxygenase-1Hmox1 protein, mouseInterleukinsMatrix Metalloproteinase 9Membrane ProteinsMmp9 protein, mousePlasminogen Activator Inhibitor 1Ptgs2 protein, mouseTlr2 protein, mouseToll-Like Receptor 2BioinformaticsVILIWGCNA

Identifiers

PMID33687057
PMCPMC7969703

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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.