{"id":"W2892317818","doi":"10.1016/j.nano.2018.09.003","title":"High-content analysis for mitophagy response to nanoparticles: A potential sensitive biomarker for nanosafety assessment","year":2018,"lang":"en","type":"article","venue":"Nanomedicine Nanotechnology Biology and Medicine","topic":"Autophagy in Disease and Therapy","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Major State Basic Research Development Program of China; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics; National Natural Science Foundation of China; Intramural Research Program; Multiple Sclerosis Scientific Research Foundation","keywords":"Mitophagy; PINK1; Parkin; Mitochondrion; Autophagy; Cell biology; Viability assay; Chemistry; Biophysics; Biology; Cell; Biochemistry; Apoptosis; Medicine; Parkinson's disease","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001645492,0.0004694733,0.001552508,0.001406834,0.0004158094,0.000005416472,0.000202438,0.0007584174,0.0001374199],"category_scores_gemma":[0.001280261,0.0003310915,0.0002633719,0.001220046,0.002162302,0.00004667038,0.0001029523,0.0002426302,0.000009859005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001378112,"about_ca_system_score_gemma":0.0002365716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007850013,"about_ca_topic_score_gemma":0.00002648154,"domain_scores_codex":[0.9968471,0.0001740567,0.0008648789,0.001054116,0.0002115802,0.000848296],"domain_scores_gemma":[0.9971206,0.0007381884,0.0002654352,0.0006796913,0.0007371594,0.0004589845],"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":[0.02200857,0.0002541986,0.003814004,0.00005794036,0.002723767,0.00006112141,0.0003076104,8.596487e-7,0.945764,0.003510575,0.001338572,0.02015875],"study_design_scores_gemma":[0.05178672,0.0553535,0.3540399,0.0004666513,0.009368384,0.0004813854,0.002463785,0.00127641,0.4717112,0.005912896,0.04609668,0.001042406],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8483195,0.0009807562,0.09133417,0.05570316,0.0009284499,0.002357735,0.0001456764,0.0002090985,0.00002151386],"genre_scores_gemma":[0.9800686,0.0001958463,0.00851846,0.008833281,0.0008675293,0.000559909,0.0002828649,0.00004418872,0.0006293224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4740528,"threshold_uncertainty_score":0.9999141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03095545359553091,"score_gpt":0.3574606329111547,"score_spread":0.3265051793156237,"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."}}