ArticleBMC neurology2025
A novel neutrophil extracellular traps related diagnostic signature for intracranial aneurysm.
Article in BMC neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- A 'Tangled Web' in the CNS: unraveling neutrophil extracellular traps in neurological disorders.Molecular neurodegeneration · 2026Review
- Formyl peptide receptor 1 agonism selectively suppresses mitochondria-driven neutrophil extracellular trap formation while preserving antibacterial immunity.Molecular medicine (Cambridge, Mass.) · 2026Article
- Mitochondria as Inducers of Neutrophil Extracellular Traps.Inflammation · 2026Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neutrophil extracellular traps (NETs) released by neutrophils can exacerbate inflammation, leading to rupture of intracranial aneurysms (IA). This study aims to explore potential NETs-related genes in IA. RNA sequencing data for IA were downloaded from the Gene Expression Omnibus database. NETs-related genes were screened using weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. LASSO Cox regression analysis identified optimal genes for model construction. Immune cell infiltration in IA was studied using CIBERSORT. Five NETs-related hub genes were identified in IA, involved in pathways like neutrophil chemotaxis, Toll-like receptor signaling, and regulation of inflammatory response. A risk score model was developed based on TLR7, TLR2, IL1B, ENTPD4, and FPR1. Immune cell infiltration analysis showed significant variations between low-risk-IA and high-risk-IA groups. Monocytes and neutrophils infiltration proportions were significantly positively correlated with the risk score. The ROC analysis showed AUC values exceeding 0.85 for both training and validation sets, confirming the model's excellent performance. A novel NETs-related diagnostic signature for IA was created, offering new insights into the pathogenesis and diagnosis of IA.
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