{"doi":"10.1016/j.crmeth.2023.100664","title":"Quantitative flow cytometry enables end-to-end optimization of cross-platform extracellular vesicle studies","abstract":"Flow cytometry (FCM) is a common method for characterizing extracellular particles (EPs), including viruses and extracellular vesicles (EVs). Frameworks such as MIFlowCyt-EV exist to provide reporting guidelines for metadata, controls, and data reporting. However, tools to optimize FCM for EP analysis in a systematic and quantitative way are lacking. Here, we demonstrate a cohesive set of methods and software tools that optimize FCM settings and facilitate cross-platform comparisons for EP studies. We introduce an automated small-particle optimization (SPOT) pipeline to optimize FCM fluorescence and light scatter detector settings for EP analysis and leverage quantitative FCM (qFCM) as a tool to further enable FCM optimization of fluorophore panel selection, laser power, pulse statistics, and window extensions. Finally, we demonstrate the value of qFCM to facilitate standardized cross-platform comparisons, irrespective of instrument configuration, settings, and sensitivity, in a cross-platform standardization study utilizing a commercially available EV reference material.","journal":"Cell Reports Methods","year":2023,"id":334936,"datarank":0.47032413238937254,"base_score":3.1354942159291497,"endowment":3.1354942159291497,"self_citation_contribution":0.47032413238937254,"citation_network_contribution":0.0,"self_endowment_contribution":0.47032413238937254,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":22,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9542,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":306821,"name":"Vera A. Tang","orcid":"0000-0003-3930-9139","position":1,"is_corresponding":false},{"id":226797,"name":"Joanne Lannigan","orcid":"0000-0002-3981-8681","position":2,"is_corresponding":false},{"id":226807,"name":"Jennifer Jones","orcid":"0000-0002-9488-7719","position":3,"is_corresponding":false},{"id":215734,"name":"Joshua A Welsh","orcid":"0000-0002-1097-9756","position":4,"is_corresponding":false},{"id":891062,"name":"Sean Cook","orcid":null,"position":0,"is_corresponding":true}],"reference_count":21,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:09:53.742667Z","pmid":"38113854","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":[]}