{"id":"W2070363546","doi":"10.1155/2013/252531","title":"Systemic siRNA Delivery via Peptide-Tagged Polymeric Nanoparticles, Targeting PLK1 Gene in a Mouse Xenograft Model of Colorectal Cancer","year":2013,"lang":"en","type":"article","venue":"International Journal of Biomaterials","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Gene knockdown; Polyethylene glycol; Chemistry; Biodistribution; Gene delivery; Cytotoxicity; PLK1; In vivo; Cancer research; Nanoparticle; PEG ratio; Peptide; In vitro; Transfection; Nanotechnology; Medicine; Cell; Materials science; Biochemistry; Apoptosis; Biology; Gene; Cell cycle","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":[0.0001871816,0.0005179652,0.0003691943,0.0002788385,0.0001284589,0.0002082775,0.0002157037,0.0003508372,0.000547905],"category_scores_gemma":[0.00008211251,0.0002129247,0.0002162618,0.0001406369,0.0001891688,0.0002283677,0.00009991269,0.0005368285,0.0002098201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003061827,"about_ca_system_score_gemma":0.0003169964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009619614,"about_ca_topic_score_gemma":0.001773159,"domain_scores_codex":[0.9999007,0.00001294122,0.00000887066,0.00003069411,0.00002616129,0.00002068404],"domain_scores_gemma":[0.999931,0.00001173646,0.00002488846,0.000006949817,0.00001093957,0.00001445037],"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":[0.0001199058,0.00005296653,0.00004204916,0.00003669808,0.000003276843,0.00002420317,0.00000762866,0.00009644555,0.9987187,0.00002524906,0.00002905428,0.0008437689],"study_design_scores_gemma":[0.00002110111,0.0008887785,0.0006341427,0.000002457454,0.00001628581,0.000099344,0.000006863652,0.0007395678,0.9970461,0.000009140942,0.0005331855,0.00000304323],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990038,0.001554544,0.00642888,0.0001333541,0.00005535451,0.0001023336,0.0003134378,0.000184077,0.001189996],"genre_scores_gemma":[0.9864272,0.001397619,0.007356816,0.00004783981,0.00001353778,0.0001414299,0.0003443558,0.00003964252,0.004231502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009619614,"threshold_uncertainty_score":0.002221584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027229457640361,"score_gpt":0.2462846697118613,"score_spread":0.2360123751354577,"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."}}