{"id":"W3002412580","doi":"10.1016/j.ijpharm.2020.119078","title":"Cholic acid-based mixed micelles as siRNA delivery agents for gene therapy","year":2020,"lang":"en","type":"article","venue":"International Journal of Pharmaceutics","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Cholic acid; Micelle; Ethylene glycol; Chemistry; PEG ratio; Transfection; Copolymer; Gene delivery; Amphiphile; HeLa; Tertiary amine; Bile acid; Combinatorial chemistry; Biophysics; Polymer chemistry; Organic chemistry; Biochemistry; Cell; Aqueous solution; Polymer","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":[0.0003321366,0.0003123233,0.0002716211,0.0002504502,0.0001837839,0.0003916658,0.0001967868,0.0004303222,0.00053395],"category_scores_gemma":[0.000218448,0.0001842878,0.0002084599,0.0001430026,0.0001667313,0.0003761312,0.0002863254,0.0004578738,0.000388773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003313753,"about_ca_system_score_gemma":0.000406639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007804162,"about_ca_topic_score_gemma":0.001458641,"domain_scores_codex":[0.9998636,0.00004067504,0.00001328716,0.00002466302,0.00003209726,0.00002569057],"domain_scores_gemma":[0.9999235,0.00001521259,0.00001758793,0.000005039919,0.00002344423,0.00001517676],"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":[0.0001028304,0.00001367222,0.00003895684,0.00008679405,0.00000767206,0.00003663291,0.00001956804,0.00013448,0.99632,0.0001991098,0.00006710775,0.002973024],"study_design_scores_gemma":[0.00001747312,0.0001827597,0.0001694724,0.00000776715,0.00002441525,0.00006661694,0.000008946436,0.00133623,0.9953785,0.00004039208,0.00276132,0.000006143812],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9318833,0.02774702,0.03330118,0.0004059937,0.000244058,0.0002029856,0.0002279462,0.0003169226,0.005670633],"genre_scores_gemma":[0.9757271,0.0061234,0.01162153,0.0001388574,0.00002891304,0.00008573657,0.0001381676,0.00005782027,0.0060783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007804162,"threshold_uncertainty_score":0.002404273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07470936150812676,"score_gpt":0.3660702527517301,"score_spread":0.2913608912436033,"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."}}