{"id":"W2013523297","doi":"10.1016/j.biomaterials.2005.09.020","title":"Characterization of folate-chitosan-DNA nanoparticles for gene therapy","year":2005,"lang":"en","type":"article","venue":"Biomaterials","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":384,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Université de Montréal; Hôpital du Sacré-Cœur de Montréal","funders":"Canadian Institutes of Health Research; Arthritis Society; Stryker","keywords":"Zeta potential; Chitosan; Coacervate; Biocompatibility; Viability assay; Transfection; Materials science; MTT assay; Nanoparticle; Cytotoxicity; Gene delivery; DNA condensation; Agarose gel electrophoresis; Gel electrophoresis; Nanotechnology; Biophysics; DNA; Chromatography; Chemistry; In vitro; Biochemistry; Biology; Gene","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":[0.0002921821,0.0003696809,0.0001764289,0.0003579937,0.0002164988,0.0002634374,0.0002195415,0.0004248247,0.0008540525],"category_scores_gemma":[0.0005885434,0.0002016134,0.0001977863,0.0001688666,0.0002279157,0.0001935456,0.0001013759,0.0002134699,0.0002643477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006603791,"about_ca_system_score_gemma":0.0003670625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002865575,"about_ca_topic_score_gemma":0.002931606,"domain_scores_codex":[0.999848,0.00001914143,0.00001119363,0.00003217405,0.00005757215,0.00003193116],"domain_scores_gemma":[0.9997329,0.0001001643,0.00005108347,0.000020027,0.00006631554,0.00002943795],"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":[0.00003579818,0.000005020359,0.00004579499,0.00002157072,0.000002137826,0.00002426915,0.00001520188,0.0001087104,0.9989422,0.00005696921,0.00001637496,0.0007258505],"study_design_scores_gemma":[0.000003731313,0.00004979674,0.0005088215,0.000002192748,0.00000594731,0.00005142088,0.00000551182,0.0007580521,0.9979215,0.00001400991,0.0006763968,0.00000273839],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750471,0.001736675,0.01809302,0.0001543391,0.00003075785,0.0001575874,0.0003041281,0.0001270492,0.004349229],"genre_scores_gemma":[0.9894237,0.0003937515,0.006951055,0.00004285702,0.000006095385,0.00006493986,0.0002282694,0.00004023272,0.002849109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002865575,"threshold_uncertainty_score":0.005697727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01914490650258769,"score_gpt":0.2595254414858465,"score_spread":0.2403805349832588,"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."}}