Evidence map›Paper›PMID 33927789›Full record

ArticleDisease markers2021

Transcriptome-Wide Gene Expression in a Murine Model of Ventilator-Induced Lung Injury.

Zhao Li, Guoshao Zhu, Chen Zhou, Hui Wang, Le Yu, Yunxin Xu, Li Xu, Qingxiu Wang

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Disease markers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 52% of its field
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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
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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 at 3 institutions in 1 country.

Zhao LiDepartment of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China.ORCID https://orcid.org/0000-0001-6446-6123
Guoshao ZhuDepartment of Anesthesiology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou 362000, China.
Chen ZhouDepartment of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China.
Hui WangDepartment of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China.
Le YuDepartment of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China.
Yunxin XuDepartment of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China.
Li XuDepartment of Anesthesiology, The First People's Hospital of Changde, Changde 415000, China.ORCID https://orcid.org/0000-0002-4505-8340
Qingxiu WangDepartment of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China.ORCID https://orcid.org/0000-0003-1603-3977
Shanghai East Hospital · CNFujian Medical University · CNThe First People's Hospital of Changde · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMechanical ventilation could lead to ventilator-induced lung injury (VILI), but its underlying pathogenesis remains largely unknown. In this study, we aimed to determine the genes which were highly correlated with VILI as well as their expressions and interactions by analyzing the differentially expressed genes (DEGs) between the VILI samples and controls.

methodsGSE11434 was downloaded from the gene expression omnibus (GEO) database, and DEGs were identified with GEO2R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using DAVID. Next, we used the STRING tool to construct protein-protein interaction (PPI) network of the DEGs. Then, the hub genes and related modules were identified with the Cytoscape plugins: cytoHubba and MCODE. qRT-PCR was further used to validate the results in the GSE11434 dataset. We also applied gene set enrichment analysis (GSEA) to discern the gene sets that had a significant difference between the VILI group and the control. Hub genes were also subjected to analyses by CyTargetLinker and NetworkAnalyst to predict associated miRNAs and transcription factors (TFs). Besides, we used CIBERSORT to detect the contributions of different types of immune cells in lung tissues of mice in the VILI group. By using DrugBank, small molecular compounds that could potentially interact with hub genes were identified.

resultsA total of 141 DEGs between the VILI group and the control were identified in GSE11434. Then, seven hub genes were identified and were validated by using qRT-PCR. Those seven hub genes were largely enriched in TLR and JAK-STAT signaling pathways. GSEA showed that VILI-associated genes were also enriched in NOD, antigen presentation, and chemokine pathways. We predicted the miRNAs and TFs associated with hub genes and constructed miRNA-TF-gene regulatory network. An analysis with CIBERSORT showed that the proportion of M0 macrophages and activated mast cells was higher in the VILI group than in the control. Small molecules, like nadroparin and siltuximab, could act as potential drugs for VILI.

conclusionIn sum, a number of hub genes associated with VILI were identified and could provide novel insights into the pathogenesis of VILI and potential targets for its treatment.

Indexed as

TranscriptomeAnimalsGene Regulatory NetworksLungMiceMicroRNAsTranscription FactorsVentilator-Induced Lung InjuryMicroRNAsTranscription Factors

Identifiers

PMID33927789
PMCPMC8049808
OpenAlexW3145418854

What OpenQuestion holds

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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.