{"id":"W3163681195","doi":"10.1038/s41587-021-00933-4","title":"In vivo adenine base editing of PCSK9 in macaques reduces LDL cholesterol levels","year":2021,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":377,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acuitas Therapeutics (Canada)","funders":"National Institute of Allergy and Infectious Diseases; National Heart, Lung, and Blood Institute; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"PCSK9; Clearance; In vivo; Point mutation; Biology; Messenger RNA; Lipoprotein; Cholesterol; RNA; LDL receptor; Mutation; Molecular biology; Immunology; Medicine; Gene; Endocrinology; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001075968,0.00013113,0.0001961781,0.0001724596,0.00001104188,0.000004960558,0.0001796083,0.001111327,0.00003351772],"category_scores_gemma":[0.0002528051,0.0001400148,0.00004539989,0.0002932356,0.00006356797,0.000003398756,0.0001459773,0.000506976,9.190546e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001315955,"about_ca_system_score_gemma":0.00004297544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001283682,"about_ca_topic_score_gemma":0.0002117231,"domain_scores_codex":[0.9990777,0.00002611139,0.0002399259,0.00034932,0.00007481639,0.0002321629],"domain_scores_gemma":[0.999578,0.00001094236,0.0000526367,0.0002898597,0.00004398138,0.00002457484],"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":[0.00001062769,0.00003876612,0.0009595227,0.00002764018,0.00001054179,0.00003967105,0.00002320977,0.00007506385,0.9958354,0.0001342275,0.0003853439,0.00245999],"study_design_scores_gemma":[0.0004524545,0.00006451408,0.002133498,0.00004986514,0.000004009758,0.00005431808,0.0001107231,0.00004746919,0.9850025,0.00006568331,0.01189463,0.0001203877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991546,0.005267825,0.0003684526,0.00218716,0.0002965178,0.00008055371,0.00002642276,0.00001810069,0.0002090031],"genre_scores_gemma":[0.9971212,0.0002270861,0.002074275,0.0001963524,0.0001713299,0.000008749995,0.00001677597,0.0000158053,0.000168402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01150929,"threshold_uncertainty_score":0.8571573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005635255797327141,"score_gpt":0.2937176011872165,"score_spread":0.2880823453898894,"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."}}