{"id":"W2013873415","doi":"10.1016/j.ymeth.2013.09.004","title":"Real-time imaging of exocytotic mucin release and swelling in Calu-3 cells using acridine orange","year":2013,"lang":"en","type":"article","venue":"Methods","topic":"Cystic Fibrosis Research Advances","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Cancer Institute; National Heart, Lung, and Blood Institute; Cystic Fibrosis Canada","keywords":"Acridine orange; Total internal reflection fluorescence microscope; Fluorescence; Fluorescence microscope; Biophysics; Mucin; Fluorescence-lifetime imaging microscopy; Mucus; Chemistry; Granule (geology); Secretion; Live cell imaging; Swelling; Microscopy; Confocal; Biology; Pathology; Optics; Biochemistry; Cell; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006362527,0.0006787773,0.0003826598,0.0004886343,0.0005954672,0.0007267946,0.0006199261,0.0007765109,0.002758842],"category_scores_gemma":[0.0002847307,0.0004426457,0.0004817271,0.0007514893,0.0007190453,0.0009757204,0.0003642741,0.002297684,0.0005380982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007184388,"about_ca_system_score_gemma":0.0003762568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001081707,"about_ca_topic_score_gemma":0.002394095,"domain_scores_codex":[0.9995296,0.00006695935,0.00004087486,0.0001267254,0.0001309923,0.0001049354],"domain_scores_gemma":[0.999566,0.0001643093,0.00008663037,0.00004741008,0.00006573875,0.0000698069],"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":[0.0001618355,0.00003954486,0.00007603037,0.0001147487,0.000007092654,0.00006167864,0.00007396843,0.00007750583,0.9977949,0.0002685299,0.00009984095,0.001224378],"study_design_scores_gemma":[0.00004943614,0.0001387819,0.003719836,0.00001180972,0.00001186333,0.0001491664,0.0001126793,0.004181657,0.9898594,0.0001244416,0.001618824,0.00002198784],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8698653,0.00409914,0.1145268,0.00106816,0.0005194695,0.0002101857,0.00181354,0.001267574,0.006629752],"genre_scores_gemma":[0.8457657,0.003474395,0.1371526,0.0003264604,0.00014322,0.0006837148,0.001060343,0.0002503028,0.01114337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002758842,"threshold_uncertainty_score":0.009229183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04121237944169141,"score_gpt":0.4034034593744965,"score_spread":0.362191079932805,"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."}}