Evidence map›Paper›PMID 37081490›Full record

ArticleBMC pulmonary medicine2023

Identification of ferroptosis-related genes in male mice with sepsis-induced acute lung injury based on transcriptome sequencing.

Wen Hu, Zhen Wu, Mei Zhang, Shilin Yu, Xiaohua Zou

Open access · goldAbstract read
In one paragraph

Article in BMC pulmonary medicine, 2023. 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
1.0field-weighted citation impact, top 22% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Wen Hu *Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Zhen Wu *Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Mei ZhangGuizhou Medical University, Guiyang, 550004, Guizhou, China.
Shilin YuGuizhou Medical University, Guiyang, 550004, Guizhou, China.
Xiaohua ZouThe Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, Guizhou, China. zouxiaohuazxh@gmc.edu.cn.
Guiyang Medical University · CNAffiliated Hospital of Guizhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis can result in acute lung injury (ALI). Studies have shown that pharmacological inhibition of ferroptosis can treat ALI. However, the regulatory mechanisms of ferroptosis in sepsis-induced ALI remain unclear.

methodsTranscriptome sequencing was performed on lung tissue samples from 10 sepsis-induced mouse models of ALI and 10 control mice. After quality control measures, clean data were used to screen for differentially expressed genes (DEGs) between the groups. The DEGs were then overlapped with ferroptosis-related genes (FRGs) to obtain ferroptosis-related DEGs (FR-DEGs). Subsequently, least absolute shrinkage and selection operator (Lasso) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) were used to obtain key genes. In addition, Ingenuity Pathway Analysis (IPA) was employed to explore the disease, function, and canonical pathways related to the key genes. Gene set enrichment analysis (GSEA) was used to investigate the functions of the key genes, and regulatory miRNAs of key genes were predicted using the NetworkAnalyst and StarBase databases. Finally, the expression of key genes was validated with the GSE165226 and GSE168796 datasets sourced from the Gene Expression Omnibus (GEO) database and using quantitative real-time polymerase chain reaction (qRT-PCR).

resultsThirty-three FR-DEGs were identified between 1843 DEGs and 259 FRGs. Three key genes, Ncf2, Steap3, and Gclc, were identified based on diagnostic models established by the two machine learning methods. They are mainly involved in infection, immunity, and apoptosis, including lymphatic system cell migration and lymphocyte and T cell responses. Additionally, the GSEA suggested that Ncf2 and Steap3 were similarly enriched in mRNA processing, response to peptides, and leukocyte differentiation. Furthermore, a key gene-miRNA network including 2 key genes (Steap3 and Gclc) and 122 miRNAs, and a gene-miRNA network with 1 key gene (Steap3) and 3 miRNAs were constructed using NetworkAnalyst and StarBase, respectively. Both databases predicted that mmu-miR-15a-5p was the target miRNA of Steap3. Finally, Ncf2 expression was validated using both datasets and qRT-PCR, and Steap3 was validated using GSE165226 and qRT-PCR.

conclusionsThis study identified two FR-DEGs (Ncf2 and Steap3) associated with sepsis-induced ALI via transcriptome analyses, as well as their functional and metabolic pathways.

Indexed as

Acute Lung InjuryFerroptosisSepsisAnimalsApoptosisMaleMiceTranscriptomeFerroptosisGene set enrichment analysisMachine learning methodsTranscriptome sequencing

Identifiers

PMID37081490
PMCPMC10116744
OpenAlexW4366589815

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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.