ArticleCellular and molecular neurobiology2025
Screening, Analysis, and Validation of Endoplasmic Reticulum Stress-Related DEGs in Epilepsy.
Article in Cellular and molecular neurobiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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1 citing paper in PubMed.
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Authors and funding
7 authors.
Funding
Abstract
To investigate the relationship between Endoplasmic Reticulum Stress (ERS) and epilepsy, as well as their biological functions. We downloaded the GSE143272 dataset from the GEO database, identified differentially expressed genes (DEGs), and cross-analyzed them with ERS-related genes from GeneCards and the Molecular Signatures Database (MSigDB). Protein-protein interaction (PPI) networks were constructed, and Hub genes were screened. ROC curve analysis was conducted to assess the diagnostic utility of these genes, followed by qRT-PCR validation. This study identified a total of 83 ERS-related DEGs in epilepsy. PPI network analysis revealed eight feature genes: C-X-C motif chemokine ligand 8 (CXCL8), Toll-like receptor 4 (TLR4), Matrix metalloproteinase 9 (MMP9), Tumor necrosis factor receptor superfamily member 1A (TNFRSF1A), Prostaglandin-endoperoxide synthase 2 (PTGS2), Signal transducer and activator of transcription 1 (STAT1), B-cell lymphoma 2 (BCL2), and RELA proto-oncogene, NF-κB subunit (RELA). ROC curve analysis demonstrated that the combination of these eight feature genes exhibited the highest diagnostic potential. Among them, CXCL8 was the most valuable gene. qRT-PCR analysis showed that CXCL8 mRNA expression was significantly lower in the case group compared to the control group (P < 0.01). The results suggest that ERS is involved in physiological processes such as inflammation and neuronal apoptosis in epilepsy. This provides a bioinformatics evidence for exploring the biological functions and pathology of ERS in epilepsy, as well as serving as a reference for clinical diagnosis and potential therapeutic targets.
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