{"id":"W2964395276","doi":"10.1093/cvr/cvz207","title":"Myocardial MMP-2 contributes to SERCA2a proteolysis during cardiac ischaemia–reperfusion injury","year":2019,"lang":"en","type":"article","venue":"Cardiovascular Research","topic":"Cardiac Fibrosis and Remodeling","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; University of Nottingham; Natural Sciences and Engineering Research Council of Canada; Nottingham Trent University; Heart and Stroke Foundation of Canada","keywords":"Phospholamban; SERCA; Proteolysis; Matrix metalloproteinase; Reperfusion injury; Cardiac muscle; Protease; Sarcolemma; Endoplasmic reticulum; Myocyte; Internal medicine; Ischemia; Chemistry; Endocrinology; Enzyme; Biology; Biochemistry; ATPase; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005457825,0.0003611013,0.001667948,0.0008503553,0.0004174511,0.0001585577,0.0003027157,0.0003861747,0.00009462186],"category_scores_gemma":[0.0005876899,0.0003105069,0.003409372,0.001663002,0.0001308453,0.0001585233,0.0007869504,0.001166412,0.001365789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000603132,"about_ca_system_score_gemma":0.0003447891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002748275,"about_ca_topic_score_gemma":7.415337e-7,"domain_scores_codex":[0.9936674,0.0006452025,0.0005053607,0.001198203,0.002728299,0.001255566],"domain_scores_gemma":[0.9956465,0.000119207,0.00003542568,0.002344779,0.001286701,0.0005673611],"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":[0.001346609,0.00009794045,0.03682936,0.000787253,0.006267365,0.00008756199,0.0005923802,0.001899528,0.9287158,0.0001025633,0.002932364,0.02034131],"study_design_scores_gemma":[0.006066763,0.0007819076,0.1364544,0.001675247,0.001586079,0.0001498657,0.001321307,0.0006390697,0.5046307,0.00006292904,0.3453948,0.001236994],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9781744,0.01065242,0.0001807305,0.0008666205,0.0008016279,0.004237131,0.00003390435,0.0001499925,0.004903097],"genre_scores_gemma":[0.9945941,0.0009279714,0.0003681789,0.0001203251,0.001237533,0.0003290796,0.00004384906,0.0001229732,0.002256017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4240851,"threshold_uncertainty_score":0.9999347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02580744487176753,"score_gpt":0.3204461727057396,"score_spread":0.294638727833972,"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."}}