Evidence map›Paper›PMID 41811909›Full record

ArticleJournal of immunology research2026

Neutrophil Extracellular Trap-Related Gene Signatures and Molecular Clusters in Severe Influenza: Identification Through Integrative Transcriptome Analysis.

Libo Fei, Liang Chen

Abstract read
In one paragraph

Article in Journal of immunology research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Libo FeiDepartment of Critical Care and Emergency Medicine, The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China, njucm.edu.cn.ORCID https://orcid.org/0009-0003-9549-4209
Liang ChenDepartment of Infectious Diseases, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical College of Nanjing University, Nanjing, 210046, China.ORCID https://orcid.org/0000-0002-3147-5688

Funding

Nanjing Medical Science and Technique Development Foundation YKK22239
6 · The paper itself

Abstract

backgroundNeutrophil extracellular traps (NETs) are recently discovered structures in which neutrophils trap pathogens in web-like structures composed of chromatin and proteolytic material. NETs have been linked to tissue damage in severe influenza (sFlu) pathogenesis. The present article involved a thorough analysis of NET-related gene (NRG) expression patterns and immunological characteristics in sFlu.

methodsMicroarray datasets were downloaded from the GEO database. sFlu-related NRGs (sFlu-NRGs) were screened using differential expression analysis and weighted gene co-expression network analysis (WGCNA). Hub sFlu-NRGs were identified using LASSO regression, support vector machine (SVM), and random forest (RF) models. Hub genes were subsequently validated using an additional external dataset, clinical samples, and a nomogram model. The molecular clusters in sFlu were investigated based on the hub sFlu-NRGs using consensus clustering and related immune cell infiltration.

resultsA total of 13 sFlu-NRGs were identified. Using these 13 genes, five (PRTN3, MMP8, myeloperoxidase [MPO], bactericidal permeability-increasing [BPI], and LTF) hub sFlu-NRGs were identified using three machine learning algorithms. Nomogram calibration and receiver operating characteristic (ROC) analysis results suggested that accuracy was achieved in predicting sFlu. Two molecular clusters were defined in sFlu based on the five hub genes. Single-set gene expression analyses suggested that, compared with Cluster 2, Cluster 1 had a decreased adaptive immune response.

conclusionsFive hub NRGs and two distinct NET-related clusters were identified in sFlu patients, highlighting the mechanism of action of sFlu and identifying candidate anti-sFlu therapeutic targets.

Indexed as

Extracellular TrapsInfluenza, HumanNeutrophilsTranscriptomeComputational BiologyGene Expression ProfilingGene Regulatory NetworksHumansNomogramsimmunological characteristicsmolecular clustersneutrophil extracellular trapsevere influenzatranscriptome analysis

Identifiers

PMID41811909
PMCPMC13140821

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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.