{"id":"W2336423858","doi":"10.3390/nano6040069","title":"Cationic Nanoparticles Assembled from Natural-Based Steroid Lipid for Improved Intracellular Transport of siRNA and pDNA","year":2016,"lang":"en","type":"article","venue":"Nanomaterials","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Donghua University; National Natural Science Foundation of China; Youth Innovation Promotion Association; Chinese Academy of Sciences; National Science Foundation","keywords":"Cationic polymerization; Intracellular; Nanoparticle; Chemistry; Steroid; Biophysics; Small interfering RNA; Transfection; Nanotechnology; Cell biology; Materials science; Biochemistry; Polymer chemistry; Gene; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001403457,0.0001253566,0.0002032879,0.00002353597,0.00003234047,0.00001516902,0.0001182151,0.0001119128,0.00002478516],"category_scores_gemma":[0.00004306147,0.00008941953,0.00006260307,0.00001962301,0.00004319054,0.000008352062,0.00001829733,0.00001095051,0.00000307795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007130614,"about_ca_system_score_gemma":0.00005912421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003005187,"about_ca_topic_score_gemma":0.00002788071,"domain_scores_codex":[0.9991865,0.00003614045,0.0002998387,0.000268694,0.00004755047,0.0001612629],"domain_scores_gemma":[0.9994668,0.00003090338,0.0001314655,0.0002315667,0.00009729448,0.00004193254],"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":[0.0003994145,0.000031216,0.0004998805,0.00002299936,0.00004199403,3.134676e-7,0.00001600172,5.506115e-7,0.9964825,0.00000793533,0.00008476212,0.002412435],"study_design_scores_gemma":[0.001199965,0.0003200962,0.001867421,0.00003501924,0.00003275499,9.531567e-7,0.000006864759,0.00002106854,0.994627,0.00007372975,0.001681701,0.0001334357],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976414,0.0004716069,0.0008800089,0.000186648,0.0003193797,0.0002704524,0.0002106944,0.00001400724,0.000005822194],"genre_scores_gemma":[0.9986778,0.0001009154,0.0006719514,0.00009314042,0.0001679764,0.00004706397,0.0001137011,0.00002012847,0.0001073472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002278999,"threshold_uncertainty_score":0.3646423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0084782841675079,"score_gpt":0.2274229094584743,"score_spread":0.2189446252909664,"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."}}