<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Zhu Y</submitter><funding>National Natural Science Foundation of China</funding><funding>Shanghai Sailing Program of Science and Technology Commission of Shanghai Municipality</funding><funding>Chenguang Program from the Shanghai Education Committee</funding><pagination>612</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11221097</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>22(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Programmed cell death (PCD) has recently been implicated in modulating the removal of neutrophils recruited in acute myocardial infarction (AMI). Nonetheless, the clinical significance and biological mechanism of neutrophil-related PCD remain unexplored.&lt;h4>Methods&lt;/h4>We employed an integrative machine learning-based computational framework to generate a predictive neutrophil-derived PCD signature (NPCDS) within five independent microarray cohorts from the peripheral blood of AMI patients. Non-negative matrix factorization was leveraged to develop an NPCDS-based AMI subtype. To elucidate the biological mechanism underlying NPCDS, we implemented single-cell transcriptomics on Cd45+ cells isolated from the murine heart of experimental AMI. We finally conducted a Mendelian</pubmed_abstract><journal>Journal of translational medicine</journal><pubmed_title>Leveraging a neutrophil-derived PCD signature to predict and stratify patients with acute myocardial infarction: from AI prediction to biological interpretation.</pubmed_title><pmcid>PMC11221097</pmcid><funding_grant_id>31501166</funding_grant_id><funding_grant_id>32170423</funding_grant_id><funding_grant_id>15YF1405000</funding_grant_id><funding_grant_id>14CG49</funding_grant_id><pubmed_authors>Zhu Y</pubmed_authors><pubmed_authors>Chen Y</pubmed_authors><pubmed_authors>Zu Y</pubmed_authors></additional><is_claimable>false</is_claimable><name>Leveraging a neutrophil-derived PCD signature to predict and stratify patients with acute myocardial infarction: from AI prediction to biological interpretation.</name><description>&lt;h4>Background&lt;/h4>Programmed cell death (PCD) has recently been implicated in modulating the removal of neutrophils recruited in acute myocardial infarction (AMI). Nonetheless, the clinical significance and biological mechanism of neutrophil-related PCD remain unexplored.&lt;h4>Methods&lt;/h4>We employed an integrative machine learning-based computational framework to generate a predictive neutrophil-derived PCD signature (NPCDS) within five independent microarray cohorts from the peripheral blood of AMI patients. Non-negative matrix factorization was leveraged to develop an NPCDS-based AMI subtype. To elucidate the biological mechanism underlying NPCDS, we implemented single-cell transcriptomics on Cd45+ cells isolated from the murine heart of experimental AMI. We finally conducted a Mendelian</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Jul</publication><modification>2026-07-03T03:17:34.653Z</modification><creation>2024-10-16T07:26:13.837Z</creation></dates><accession>S-EPMC11221097</accession><cross_references><pubmed>38956669</pubmed><doi>10.1186/s12967-024-05415-0</doi></cross_references></HashMap>