ArticleInternational journal of chronic obstructive pulmonary disease2026
Identification of
Article in International journal of chronic obstructive pulmonary disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The processes of pyroptosis, apoptosis, and necroptosis (PANoptosis) play a crucial role in the development of chronic obstructive pulmonary disease (COPD). Our objective is to explore potential PANoptosis-related genes in COPD. Methods: Human COPD-related transcriptomic datasets (GSE8545, GSE20257, GSE11784 and GSE1650) were retrieved from the Gene Expression Omnibus (GEO). First, based on GSE8545 dataset, candidate genes were identified using differentially expressed gene (DEG) analysis, Weighted Gene Co-expression Network Analysis (WGCNA), Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Support Vector Machine-Recursive Feature Elimination (SVM-RFE). Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted for the relevant genes. Results: Three PANoptosis-related hub genes ( Conclusion: We identified
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Registered trials
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.