ArticleHeliyon2024
Bioinformatics-driven identification and validation of diagnostic biomarkers for cerebral ischemia reperfusion injury.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- mRNALocator-imb: an imbalance-tolerant ensemble framework integrating random forest and transformer for mRNA subcellular localization prediction.Frontiers in genetics · 2026Article
- Immunological Mechanisms and Therapeutic Strategies in Cerebral Ischemia-Reperfusion Injury: From Inflammatory Response to Neurorepair.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This article aims to identify genetic features associated with immune cell infiltration in cerebral ischemia-reperfusion injury (CIRI) development through bioinformatics, with the goal of discovering diagnostic biomarkers and potential therapeutic targets. Methods: We obtained two datasets from the Gene Expression Omnibus (GEO) database to identify immune-related differentially expressed genes (IRDEGs). These genes' functions were analyzed via Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Tools such as CIBERSORT and ssGSEA assessed immune cell infiltration. The Starbase and miRDB databases predicted miRNAs interacting with hub genes, and Cytoscape software mapped mRNA-miRNA interaction networks. The ENCORI database was employed to predict RNA binding proteins interacting with hub genes. Key genes were identified using a random forest algorithm and constructing a Support Vector Machine (SVM) model. LASSO regression analysis constructed a diagnostic model for hub genes to determine their diagnostic value, and PCR analysis validated their expression in cerebral ischemia-reperfusion. Results: We identified 10 IRDEGs (C1qa, Ccl4, Cd74, Cd8a, Cxcl10, Gmfg, Grp, Lgals3bp, Timp1, Vim). The random forest algorithm, and SVM model intersection revealed three key genes ( Conclusions: Our study elucidates immune and metabolic response mechanisms in CIRI, identifying two immune-related genes as key biomarkers and potential therapeutic targets in response to cerebral ischemia-reperfusion injury.
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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.