Evidence map›Paper›PMID 37932341›Full record

ArticleScientific reports2023

Transcriptome analysis reveals the impact of NETs activation on airway epithelial cell EMT and inflammation in bronchiolitis obliterans.

Zhongji Wu, Xiaowen Chen, Shangzhi Wu, Zhenwei Liu, Hongwei Li, Kailin Mai, Yinghui Peng, Haidi Zhang, Xiaodie Zhang, Zhaocong Zheng and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. [Advances in growth impairment associated with pediatric respiratory diseases].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026
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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

12 authors at 2 institutions in 1 country.

Zhongji Wu *The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Xiaowen Chen *The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Shangzhi Wu *The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Zhenwei LiuThe First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Hongwei LiThe First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Kailin MaiGuangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Yinghui PengThe First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Haidi ZhangThe First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Xiaodie ZhangGuangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Zhaocong ZhengGuangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Zian FuThe First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, People's Republic of China.
Dehui ChenThe First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, People's Republic of China. dehuichen84@126.com.
Guangzhou Medical University · CNFirst Affiliated Hospital of Guangzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bronchiolitis obliterans (BO) is a chronic airway disease that was often indicated by the pathological presentation of narrowed and irreversible airways. However, the molecular mechanisms of BO pathogenesis remain unknown. Although neutrophil extracellular traps (NETs) can contribute to inflammatory disorders, their involvement in BO is unclear. This study aims to identify potential signaling pathways in BO by exploring the correlations between NETs and BO. GSE52761 and GSE137169 datasets were downloaded from gene expression omnibus (GEO) database. A series of bioinformatics analyses such as differential expression analysis, gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and gene set enrichment analysis (GSEA) were performed on GSE52761 and GSE137169 datasets to identify BO potential signaling pathways. Two different types of BO mouse models were constructed to verify NETs involvements in BO. Additional experiments and bioinformatics analysis using human small airway epithelial cells (SAECs) were also performed to further elucidate differential genes enrichment with their respective signaling pathways in BO. Our study identified 115 differentially expressed genes (DEGs) that were found up-regulated in BO. Pathway enrichment analysis revealed that these genes were primarily involved in inflammatory signaling processes. Besides, we found that neutrophil extracellular traps (NETs) were formed and activated during BO. Our western blot analysis on lung tissue from BO mice further confirmed NETs activation in BO, where neutrophil elastase (NE) and myeloperoxidase (MPO) expression were found significantly elevated. Transcriptomic and bioinformatics analysis of NETs treated-SAECs also revealed that NETs-DEGs were primarily associated through inflammatory and epithelial-to-mesenchymal transition (EMT) -related pathways. Our study provides novel clues towards the understanding of BO pathogenesis, in which NETs contribute to BO pathogenesis through the activation of inflammatory and EMT associated pathways. The completion of our study will provide the basis for potential novel therapeutic targets in BO treatment.

Indexed as

Bronchiolitis ObliteransExtracellular TrapsAnimalsComputational BiologyEpithelial CellsGene Expression ProfilingHumansInflammationMiceTranscriptome

Identifiers

PMID37932341
PMCPMC10628238
OpenAlexW4388407653

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LicenceCC BY
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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.