{"id":"W2402558378","doi":"10.3892/ol.2016.4596","title":"Applications of nanoparticle drug delivery systems for the reversal of multidrug resistance in cancer","year":2016,"lang":"en","type":"article","venue":"Oncology Letters","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Science and Technology Planning Project of Guangdong Province; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Multiple drug resistance; Drug delivery; Drug resistance; Cancer; Drug; Mesoporous silica; Pharmacology; Nanotechnology; Liposome; Biocompatibility; Cancer therapy; Chemotherapy; Medicine; Materials science; Chemistry; Biology; Internal medicine; Mesoporous material","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":[0.0008153411,0.00009239765,0.0002500684,0.00005999198,0.00005942431,0.000005864665,0.0003368484,0.00004421717,0.00002924093],"category_scores_gemma":[0.00006653518,0.00005873221,0.00005269122,0.0001815102,0.0003928664,0.0001251215,0.0000493353,0.0000427186,0.00001856735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002333899,"about_ca_system_score_gemma":0.0001425269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009690739,"about_ca_topic_score_gemma":0.001314761,"domain_scores_codex":[0.9987062,0.0001627337,0.0004436234,0.0002371075,0.0001554937,0.0002947976],"domain_scores_gemma":[0.9977766,0.001432577,0.0002847299,0.0003576385,0.0001084639,0.00004003333],"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":[0.0002237936,0.00009732552,0.002572194,0.00005852327,0.00001053096,0.000001815111,0.0003415954,0.0003359831,0.9892952,0.0003706927,0.005875142,0.0008171586],"study_design_scores_gemma":[0.001668628,0.00004205427,0.001104377,0.0001119485,0.00004578231,9.062459e-7,0.0002014999,0.0002575207,0.9828238,0.00006550948,0.01356387,0.000114087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859837,0.001032863,0.001805217,0.009917792,0.0003187894,0.0007795354,0.0001152574,0.00001941806,0.0000274226],"genre_scores_gemma":[0.9975707,0.00007975825,0.0009086966,0.000425934,0.00005965769,0.0008039288,6.220822e-7,0.00001212691,0.0001386095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01158696,"threshold_uncertainty_score":0.239503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01421449991432918,"score_gpt":0.2713862978778517,"score_spread":0.2571717979635226,"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."}}