{"id":"W4281732954","doi":"10.21203/rs.3.rs-1699474/v1","title":"Improved Delivery of Mcl-1 and survivin siRNA combination in breast cancer cells with additive siRNA complexes","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Royal Golden Jubilee (RGJ) Ph.D. Programme; Natural Sciences and Engineering Research Council of Canada; National Research Council of Thailand; University of Alberta","keywords":"Survivin; Transfection; Small interfering RNA; Viability assay; Gene silencing; Flow cytometry; Apoptosis; Chemistry; MTT assay; Molecular biology; Cell; Cell growth; RNA interference; Cancer cell; Cancer research; Biology; Cancer; Gene; RNA; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002720745,0.0003593351,0.0003029416,0.0002873832,0.0001217653,0.0004239441,0.0002429526,0.0003339562,0.000614291],"category_scores_gemma":[0.0002580224,0.0001573233,0.0002086498,0.0001674376,0.000148832,0.0002553779,0.0002083625,0.0002798868,0.0002898783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003160727,"about_ca_system_score_gemma":0.0001849497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004490983,"about_ca_topic_score_gemma":0.0007245996,"domain_scores_codex":[0.9997104,0.00006111782,0.00003448665,0.00005874651,0.0001011137,0.000034226],"domain_scores_gemma":[0.999885,0.00002525314,0.0000308915,0.000009783123,0.00003568788,0.00001349339],"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":[0.00005056475,0.00002276569,0.00008538619,0.00006671811,0.00000824362,0.0000304869,0.00001558519,0.00007534413,0.9979565,0.00006444759,0.00003155537,0.001592366],"study_design_scores_gemma":[0.000005139268,0.0002069102,0.0004234294,0.000002764335,0.00002015669,0.00009084481,0.000007767771,0.0005581339,0.9973328,0.000006700434,0.001342257,0.000002983713],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867957,0.003600005,0.007285558,0.0001065144,0.00004948394,0.00007183157,0.0001172853,0.0001476208,0.001825933],"genre_scores_gemma":[0.9880826,0.001121425,0.008210716,0.00007020881,0.00001337401,0.00005312305,0.0001670239,0.00002363153,0.002257887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000614291,"threshold_uncertainty_score":0.002293229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02488627211911445,"score_gpt":0.3288792587546878,"score_spread":0.3039929866355733,"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."}}