{"id":"W2617233822","doi":"10.1016/j.cmet.2017.04.021","title":"Age-Associated Loss of OPA1 in Muscle Impacts Muscle Mass, Metabolic Homeostasis, Systemic Inflammation, and Epithelial Senescence","year":2017,"lang":"en","type":"article","venue":"Cell Metabolism","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":558,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Associazione Italiana per la Ricerca sul Cancro; Università degli Studi di Padova; Fondazione Cassa di Risparmio di Padova e Rovigo","keywords":"Senescence; Sarcopenia; Biology; Muscle atrophy; Endocrinology; Atrophy; Internal medicine; Mitochondrion; Homeostasis; Skeletal muscle; Premature aging; Unfolded protein response; Inflammation; Cell biology; Medicine; Immunology; Physiology; Genetics; Endoplasmic reticulum","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001551847,0.0003998831,0.000346751,0.0003366665,0.0001922328,0.0003422668,0.0001771232,0.0003365744,0.00123392],"category_scores_gemma":[0.000117487,0.0001427285,0.0003447294,0.0001697356,0.0003550221,0.0003617104,0.00037514,0.0006152813,0.00023049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002455787,"about_ca_system_score_gemma":0.0002051434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005206083,"about_ca_topic_score_gemma":0.0009398588,"domain_scores_codex":[0.9998801,0.00001153716,0.00001029129,0.00003732998,0.00003257833,0.00002820573],"domain_scores_gemma":[0.9998274,0.00001023141,0.00007599469,0.00001803759,0.00001633967,0.00005198068],"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":[0.0001689467,0.00002246804,0.001321984,0.00003699633,0.00001390356,0.00008803123,0.00001257095,0.0000375127,0.9961254,0.00006618901,0.00004422754,0.00206172],"study_design_scores_gemma":[0.00002532761,0.0008586437,0.1105006,0.00003213346,0.0001053886,0.00167649,0.0001405675,0.0006989227,0.88168,0.0003372512,0.003931948,0.00001265628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937689,0.003637226,0.001346566,0.0001624885,0.00003159297,0.000007533481,0.0003566066,0.00005593949,0.0006330426],"genre_scores_gemma":[0.9943722,0.001960511,0.0008290074,0.00007826353,0.00001380224,0.00001935094,0.0003915166,0.00001772028,0.002317703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00123392,"threshold_uncertainty_score":0.0041278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007948296839257863,"score_gpt":0.2346949514599176,"score_spread":0.2267466546206598,"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."}}