{"id":"W4411186707","doi":"10.3390/ph18060864","title":"Engineering Lipid–Polymer Nanoparticles for siRNA Delivery to Cancer Cells","year":2025,"lang":"en","type":"article","venue":"Pharmaceuticals","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Internalization; Nucleic acid; RNA interference; Polymer; Cationic polymerization; Chemistry; Gene silencing; Nanoparticle; Computer science; Nanotechnology; Flexibility (engineering); Drug delivery; Rational design; Small interfering RNA; Combinatorial chemistry; Computational biology; RNA; Materials science; Cell; Biochemistry; Biology; Mathematics; Organic chemistry","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":[0.0003183032,0.0005290239,0.0002232052,0.0003050562,0.0001579157,0.000351386,0.0001924015,0.0003906903,0.0006995858],"category_scores_gemma":[0.0002252067,0.0002084261,0.0003961099,0.0001943328,0.0002406784,0.0003102024,0.0002928081,0.0003906158,0.0007032466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005103819,"about_ca_system_score_gemma":0.0003950365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003876686,"about_ca_topic_score_gemma":0.0006942542,"domain_scores_codex":[0.9998281,0.00002810929,0.0000191873,0.00004210876,0.00005380217,0.0000287038],"domain_scores_gemma":[0.9999157,0.00001876191,0.00002539075,0.000006288722,0.00002481468,0.000009009682],"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":[0.00001931501,0.00001165646,0.00006250768,0.00005610756,0.000004811431,0.000028478,0.00001393914,0.0004936237,0.9969543,0.0001202595,0.0000285618,0.002206338],"study_design_scores_gemma":[0.000005312888,0.00007065949,0.000116576,0.000003049602,0.000007498777,0.00003695582,0.000004519097,0.001414004,0.9967259,0.00004064923,0.001571504,0.000003342581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8511417,0.002660173,0.1403176,0.000307818,0.00007165198,0.0003771981,0.0003222598,0.0005257511,0.004275876],"genre_scores_gemma":[0.9020112,0.002128951,0.0918336,0.0001208342,0.00001406558,0.0003098123,0.0003582179,0.0001251705,0.003098139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006995858,"threshold_uncertainty_score":0.003703058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02332235976462419,"score_gpt":0.3418705305263436,"score_spread":0.3185481707617194,"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."}}