{"doi":"10.1039/d4lc00640b","title":"Towards real-time myocardial infarction diagnosis: a convergence of machine learning and ion-exchange membrane technologies leveraging miRNA signatures","abstract":"cTn regardless of timing of AMI onset. However, miRNA-based AMI diagnosis can result in false positives due to miRNA content overlap between AMI and stable coronary artery disease (CAD). Accordingly, we explored the possibility of using a miRNA profile, rather than a single miRNA, to distinguish between CAD and AMI, as well as different stages following AMI onset. First we screened a library of 800 miRNA using plasma samples from 4 patient cohorts; no known CAD, CAD, ST-segment elevation myocardial infarction (STEMI) and STEMI followed by PCI, using Nanostring miRNA profiling technology. From this screening, based on machine learning SCAD and Lasso algorithms, we identified 9 biomarkers (miR-200b, miR-543, miR-331, miR-3605, miR-301a, miR-18a, miR-423, miR-142, and miR-132) that were differentially expressed in CAD, STEMI and STEMI-PCI and explored them to identify a miRNA profile for rapid and accurate AMI diagnosis. These 9 miRNAs were selected as the most frequently identified targets by SCAD and Lasso, as indicated in the \"drum-plot\" model in the machine learning approach. We used age-matched patient samples to validate selected 9 miRNA biomarkers using a multiplexed ion-exchange membrane-based miRNA sensor platform, which measures specific miRNAs, and cTn as a control, simultaneously as a point-of-care device. Findings from this study will inform timely and accurate diagnosis of AMI and its stages, which are essential for effective management and optimal patient outcomes.","journal":"Lab on a Chip","year":2024,"id":443402,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9599,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1210542,"name":"Ruyu Zhou","orcid":null,"position":1,"is_corresponding":false},{"id":885984,"name":"George Ronan","orcid":"0000-0003-1485-0914","position":2,"is_corresponding":false},{"id":636412,"name":"S. Gulberk Ozcebe","orcid":"0000-0002-5210-8086","position":3,"is_corresponding":false},{"id":1258015,"name":"Jiaying Ji","orcid":null,"position":4,"is_corresponding":false},{"id":361515,"name":"Satyajyoti Senapati","orcid":"0000-0001-7999-1561","position":5,"is_corresponding":false},{"id":353352,"name":"Keith L. March","orcid":"0000-0001-5677-0379","position":6,"is_corresponding":false},{"id":314521,"name":"Eileen Handberg","orcid":"0000-0002-7805-9577","position":7,"is_corresponding":false},{"id":885985,"name":"David Anderson","orcid":"0000-0001-7104-122X","position":8,"is_corresponding":false},{"id":255714,"name":"Carl J. Pepine","orcid":"0000-0002-6011-681X","position":9,"is_corresponding":false},{"id":361516,"name":"Hsueh‐Chia Chang","orcid":"0000-0003-2147-9260","position":10,"is_corresponding":false},{"id":1257543,"name":"Fang Liu","orcid":"0000-0003-4794-4319","position":11,"is_corresponding":false},{"id":256608,"name":"Pınar Zorlutuna","orcid":"0000-0002-3122-7553","position":12,"is_corresponding":false},{"id":256603,"name":"Xiang Ren","orcid":"0000-0002-8882-6362","position":0,"is_corresponding":true}],"reference_count":43,"raw_metadata":null,"created_at":"2026-07-19T02:01:24.471942Z","pmid":"39415669","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}