{"id":"W2994772830","doi":"10.1016/j.msec.2019.110550","title":"Preparation of curcumin-poly (allyl amine) hydrochloride based nanocapsules: Piperine in nanocapsules accelerates encapsulation and release of curcumin and effectiveness against colon cancer cells","year":2019,"lang":"en","type":"article","venue":"Materials Science and Engineering C","topic":"Curcumin's Biomedical Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":68,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Arts Research Board, McMaster University; American University of Beirut","keywords":"Curcumin; Nanocapsules; Bioavailability; Piperine; Materials science; Fourier transform infrared spectroscopy; Zeta potential; Nuclear chemistry; In vivo; Dynamic light scattering; Controlled release; Nanoparticle; Chemistry; Nanotechnology; Organic chemistry; Chemical engineering; Pharmacology; Biochemistry; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001332362,0.0002733823,0.0002311132,0.0001686904,0.000134791,0.0001318242,0.0001897804,0.0003059393,0.001187463],"category_scores_gemma":[0.000168719,0.0001924934,0.0001975859,0.0001021059,0.0001414935,0.0002846498,0.0001452779,0.0003252597,0.0003470492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002518703,"about_ca_system_score_gemma":0.0002189027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004911059,"about_ca_topic_score_gemma":0.0008890303,"domain_scores_codex":[0.9999143,0.000007775135,0.00001187547,0.00003139499,0.0000165482,0.00001808258],"domain_scores_gemma":[0.9998971,0.00001641109,0.00003806708,0.00001172599,0.0000154456,0.00002121995],"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":[0.0000626957,0.00001130072,0.00003334955,0.00004285914,0.000002956883,0.00002793361,0.000009906486,0.00007560418,0.9988447,0.00003384871,0.00002756755,0.0008271245],"study_design_scores_gemma":[0.000005637587,0.00006560896,0.0002338678,0.000001612386,0.00000568098,0.00003211614,0.00000188339,0.0003137422,0.998913,0.000004719644,0.0004199853,0.000002051991],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893832,0.0009939068,0.007921102,0.00009579775,0.00005121106,0.00006025363,0.0001975226,0.00026792,0.0010291],"genre_scores_gemma":[0.988113,0.0003911276,0.008282605,0.00003550113,0.00001262266,0.00006014174,0.0001491647,0.00004797223,0.002907824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001187463,"threshold_uncertainty_score":0.003972471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003994859450018371,"score_gpt":0.2425672978803962,"score_spread":0.2385724384303778,"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."}}