{"id":"W4411682608","doi":"10.1016/j.vascn.2025.108376","title":"From cellular waste to biomarkers; insights into past, present, and future methods to detect immune cell-derived extracellular vesicles using flow cytometry","year":2025,"lang":"en","type":"article","venue":"Journal of Pharmacological and Toxicological Methods","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Extracellular vesicles; Flow cytometry; Immune system; Vesicle; Extracellular; Cell biology; Chemistry; Cell; Cytometry; Microvesicles; Biology; Biochemistry; Immunology; Membrane","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001979797,0.0004679763,0.0007986704,0.0002937368,0.0002611136,0.0001118513,0.000579411,0.0005628124,0.0001080523],"category_scores_gemma":[0.0004142324,0.0003378846,0.0003120456,0.0005982473,0.0002598392,0.00002620865,0.0009728037,0.0005319389,0.000001679531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000638528,"about_ca_system_score_gemma":0.00008183852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004799596,"about_ca_topic_score_gemma":3.283187e-7,"domain_scores_codex":[0.9948347,0.002679798,0.0009699092,0.0007703633,0.0002534611,0.0004917633],"domain_scores_gemma":[0.997693,0.0006148305,0.0003567638,0.000295913,0.000214239,0.0008252483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001248676,0.0002840889,0.00009643225,0.00003809552,0.0003783965,0.0001564575,0.0001073799,0.0002091394,0.8532128,0.000009976128,0.0004534841,0.143805],"study_design_scores_gemma":[0.00146586,0.001248294,0.001307169,0.0000352512,0.0004666906,0.00002390429,0.0003974049,0.001473676,0.9574268,0.002683266,0.03307257,0.000399087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6080686,0.03232948,0.35774,0.0009188073,0.0005199696,0.0003574522,0.000006719243,0.00001260979,0.00004632523],"genre_scores_gemma":[0.3521191,0.0006639096,0.644659,0.000733585,0.001725144,0.0000191965,0.000004432481,0.00002053473,0.00005515911],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.286919,"threshold_uncertainty_score":0.9999073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02347618103874219,"score_gpt":0.3770494735468697,"score_spread":0.3535732925081275,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}