<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Juaiti M</submitter><funding>National Natural Science Foundation of China</funding><funding>Hunan Provincial Natural Science Foundation</funding><pagination>e29587</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11040037</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>10(8)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Pulmonary arterial hypertension (PAH) represents a substantial global risk to human health. This study aims to identify diagnostic biomarkers for PAH and assess their association with the immune microenvironment through the utilization of sophisticated bioinformatics techniques.&lt;h4>Methods&lt;/h4>Based on two microarray datasets, differentially expressed genes (DEGs) were detected, and hub genes underwent a sequence of machine learning analyses. After pathways associated with PAH were assessed by gene enrichment analysis, the identified genes were validated using external datasets and confirmed in a monocrotaline (MCT)-induced rat model. In addition, three algorithms were employed to estimate the proportions of various immune cell types, and the link between hub genes and i</pubmed_abstract><journal>Heliyon</journal><pubmed_title>Integrated bioinformatics analysis and experimental animal models identify a robust biomarker and its correlation with the immune microenvironment in pulmonary arterial hypertension.</pubmed_title><pmcid>PMC11040037</pmcid><funding_grant_id>82070055</funding_grant_id><pubmed_authors>Juaiti M</pubmed_authors><pubmed_authors>Feng Y</pubmed_authors><pubmed_authors>Zha L</pubmed_authors><pubmed_authors>Yu Z</pubmed_authors><pubmed_authors>Tang Y</pubmed_authors><pubmed_authors>Liang B</pubmed_authors></additional><is_claimable>false</is_claimable><name>Integrated bioinformatics analysis and experimental animal models identify a robust biomarker and its correlation with the immune microenvironment in pulmonary arterial hypertension.</name><description>&lt;h4>Background&lt;/h4>Pulmonary arterial hypertension (PAH) represents a substantial global risk to human health. This study aims to identify diagnostic biomarkers for PAH and assess their association with the immune microenvironment through the utilization of sophisticated bioinformatics techniques.&lt;h4>Methods&lt;/h4>Based on two microarray datasets, differentially expressed genes (DEGs) were detected, and hub genes underwent a sequence of machine learning analyses. After pathways associated with PAH were assessed by gene enrichment analysis, the identified genes were validated using external datasets and confirmed in a monocrotaline (MCT)-induced rat model. In addition, three algorithms were employed to estimate the proportions of various immune cell types, and the link between hub genes and i</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Apr</publication><modification>2026-07-01T03:22:00.959Z</modification><creation>2026-07-01T03:12:29.48Z</creation></dates><accession>S-EPMC11040037</accession><cross_references><pubmed>38660271</pubmed><doi>10.1016/j.heliyon.2024.e29587</doi></cross_references></HashMap>