{"id":"W2921207188","doi":"10.1080/14756366.2019.1587416","title":"CRISPR/Cas9-based liver-derived reporter cells for screening of mPGES-1 inhibitors","year":2019,"lang":"en","type":"article","venue":"Journal of Enzyme Inhibition and Medicinal Chemistry","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"Medical Innovation Project of Fujian Province; Natural Science Foundation of Fujian Province","keywords":"Flow cytometry; CRISPR; Cas9; Inflammation; Reporter gene; Immunofluorescence; High-throughput screening; Fluorescence; Molecular biology; Biology; Chemistry; Cancer research; Cell biology; Biochemistry; Gene; Gene expression; Immunology; Antibody","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":[0.0006656221,0.000679715,0.0009611213,0.0006531367,0.0003135746,0.0006110187,0.0007291357,0.0007098544,0.001853415],"category_scores_gemma":[0.0004551577,0.0003575686,0.0004907296,0.0004915998,0.0003164783,0.0003316547,0.0003545827,0.001270031,0.001154692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004820217,"about_ca_system_score_gemma":0.0004403162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007634952,"about_ca_topic_score_gemma":0.001415668,"domain_scores_codex":[0.9992049,0.0001133318,0.0001186639,0.0001777792,0.0003037509,0.00008157535],"domain_scores_gemma":[0.9997512,0.00006915226,0.00006186284,0.00004082618,0.0000440712,0.00003290741],"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":[0.00006362944,0.00003947196,0.00009131236,0.00008974832,0.000009032029,0.00005783981,0.0000165396,0.0002976031,0.9969656,0.0002169431,0.0001531087,0.001999232],"study_design_scores_gemma":[0.00001623066,0.0001364083,0.0004247945,0.000008103592,0.00002016539,0.0001683443,0.00001318939,0.003298551,0.9909788,0.00005562662,0.004867802,0.00001202426],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6235681,0.00529702,0.345237,0.0007535893,0.0004374232,0.001311922,0.01092595,0.003504756,0.008964282],"genre_scores_gemma":[0.7573144,0.003856153,0.2121643,0.0002723409,0.00004369956,0.001200394,0.01133772,0.0004446975,0.0133662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001853415,"threshold_uncertainty_score":0.006200254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0086909725005621,"score_gpt":0.2731167711729139,"score_spread":0.2644257986723518,"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."}}