{"id":"W4387148605","doi":"10.1016/j.biomaterials.2023.122341","title":"Hyaluronan decorated layer-by-layer assembled lipid nanoparticles for miR-181a delivery in glioblastoma treatment","year":2023,"lang":"en","type":"article","venue":"Biomaterials","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Fonds de Recherche du Québec - Santé; Institut TransMedTech; Canadian Institutes of Health Research; CHU Sainte-Justine Foundation; Canada First Research Excellence Fund","keywords":"Nanocarriers; In vivo; Hyaluronic acid; In vitro; Transfection; microRNA; Cancer research; Glioma; Glioblastoma; Drug delivery; Chemistry; Medicine; Cell culture; Biology; Materials science; Nanotechnology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000167419,0.0002281879,0.0002777977,0.0001037905,0.00006196373,0.00006613251,0.0001396101,0.0001902566,0.00003589596],"category_scores_gemma":[0.00003271973,0.0002000956,0.0001120057,0.0001724314,0.00002628299,0.000008615288,0.00006873171,0.000006464475,0.0001250389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003675139,"about_ca_system_score_gemma":0.00007519098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008000639,"about_ca_topic_score_gemma":0.0001582456,"domain_scores_codex":[0.9986606,0.00007184165,0.0003530695,0.0004358494,0.00008465965,0.0003940215],"domain_scores_gemma":[0.9994478,0.00001900019,0.0000861869,0.000282511,0.00007931694,0.0000852483],"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":[0.0008602751,0.0001388548,0.0005666155,0.0000207075,0.00007805104,0.00001133849,0.00003079504,0.000007254642,0.9861426,0.000002665701,0.01015481,0.001985972],"study_design_scores_gemma":[0.001350434,0.002349405,0.001724745,0.00002313884,0.00002656892,0.000008509342,0.00004041635,0.00005370998,0.9779667,0.00001801782,0.01620805,0.0002302717],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985276,0.0001856117,0.00001130093,0.0001578867,0.0003664874,0.0004741472,0.0001941227,0.00005783447,0.0000250015],"genre_scores_gemma":[0.9982369,0.0001722158,0.000116036,0.0001268798,0.0001693836,0.0002713269,0.0003628637,0.0000358842,0.0005085424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008175925,"threshold_uncertainty_score":0.8159662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03404185161448759,"score_gpt":0.2970144886183259,"score_spread":0.2629726370038383,"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."}}