{"id":"W4291882990","doi":"10.1016/j.biomaterials.2022.121729","title":"A human model of arteriovenous malformation (AVM)-on-a-chip reproduces key disease hallmarks and enables drug testing in perfused human vessel networks","year":2022,"lang":"en","type":"article","venue":"Biomaterials","topic":"Vascular Malformations Diagnosis and Treatment","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"Heart and Stroke Foundation; Toronto General Hospital; University Health Network; University of Toronto","funders":"National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research","keywords":"Adherens junction; Human brain; KRAS; Cancer research; Vascular permeability; Microvessel; Pathogenesis; Angiogenesis; Pathology; Blood vessel; Stroke (engine); Blood–brain barrier; Endothelial stem cell; Arteriovenous malformation; Biology; In vitro; Medicine; Mutation; Cell; Gene; Neuroscience; Internal medicine; Radiology; Central nervous system","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":[0.0003374542,0.0003122587,0.0002707051,0.0002353767,0.0002229893,0.000438937,0.0004453761,0.0008849174,0.002765964],"category_scores_gemma":[0.0003265743,0.0001919561,0.0003129946,0.0001764272,0.0003035192,0.0002255387,0.0002148656,0.0007638256,0.0007429502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001675088,"about_ca_system_score_gemma":0.0003216346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009665171,"about_ca_topic_score_gemma":0.001475571,"domain_scores_codex":[0.9998025,0.00003709171,0.000009445824,0.00005991687,0.00005849084,0.00003248713],"domain_scores_gemma":[0.9997802,0.00007786547,0.00002714786,0.00006516025,0.00002203534,0.00002750588],"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":[0.000349678,0.0004149132,0.0009654163,0.0003207186,0.00005368744,0.0009762897,0.0001096246,0.003394274,0.9709764,0.0031135,0.003789855,0.01553555],"study_design_scores_gemma":[0.000117914,0.00222462,0.006594246,0.00006939239,0.0002202091,0.005128859,0.0001587894,0.03466225,0.8754807,0.001715197,0.07357746,0.0000503854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8252536,0.003483028,0.1479902,0.0009471268,0.0009841942,0.0004633481,0.004858066,0.001451201,0.01456929],"genre_scores_gemma":[0.9476152,0.001096219,0.04304558,0.0003236409,0.00003954842,0.0003954704,0.001316991,0.00009586773,0.006071553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002765964,"threshold_uncertainty_score":0.009253025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03660781044514406,"score_gpt":0.2660405586663643,"score_spread":0.2294327482212202,"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."}}