<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>16(8)</volume><submitter>Hou L</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>Globally, ischemic stroke (IS) is ranked as the second most prevailing cause of mortality and is considered lethal to human health. This study aimed to identify genes and pathways involved in the onset and progression of IS.&lt;h4>Methods&lt;/h4>GSE16561 and GSE22255 were downloaded from the Gene Expression Omnibus (GEO) database, merged, and subjected to batch effect removal using the ComBat method. The limma package was employed to identify the differentially expressed genes (DEGs), followed by enrichment analysis and protein-protein interaction (PPI) network construction. Afterward, the cytoHubba plugin was utilized to screen the hub genes. Finally, a ROC curve was generated to investigate the diagnostic value of hub genes. Validation analysis through a series of experiment</pubmed_abstract><journal>Aging</journal><pagination>6852-6867</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11087101</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>ITGAM is a critical gene in ischemic stroke.</pubmed_title><pmcid>PMC11087101</pmcid><pubmed_authors>Hou L</pubmed_authors><pubmed_authors>Lv J</pubmed_authors><pubmed_authors>Li Z</pubmed_authors><pubmed_authors>Chong Z</pubmed_authors><pubmed_authors>Guo X</pubmed_authors><pubmed_authors>Xiao Y</pubmed_authors><pubmed_authors>Zhang L</pubmed_authors></additional><is_claimable>false</is_claimable><name>ITGAM is a critical gene in ischemic stroke.</name><description>&lt;h4>Background&lt;/h4>Globally, ischemic stroke (IS) is ranked as the second most prevailing cause of mortality and is considered lethal to human health. This study aimed to identify genes and pathways involved in the onset and progression of IS.&lt;h4>Methods&lt;/h4>GSE16561 and GSE22255 were downloaded from the Gene Expression Omnibus (GEO) database, merged, and subjected to batch effect removal using the ComBat method. The limma package was employed to identify the differentially expressed genes (DEGs), followed by enrichment analysis and protein-protein interaction (PPI) network construction. Afterward, the cytoHubba plugin was utilized to screen the hub genes. Finally, a ROC curve was generated to investigate the diagnostic value of hub genes. Validation analysis through a series of experiment</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Apr</publication><modification>2026-06-03T04:26:55.948Z</modification><creation>2026-04-24T03:09:42.137Z</creation></dates><accession>S-EPMC11087101</accession><cross_references><pubmed>38637126</pubmed><doi>10.18632/aging.205729</doi></cross_references></HashMap>