{"id":"W2528752965","doi":"10.1021/jacs.6b08369","title":"Optimized DNA “Nanosuitcases” for Encapsulation and Conditional Release of siRNA","year":2016,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":237,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"DOD Prostate Cancer Research Program; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; McGill University; Fonds Québécois de la Recherche sur la Nature et les Technologies; Prostate Cancer Canada; Canada Research Chairs; Government of Canada","keywords":"Chemistry; Förster resonance energy transfer; Nuclease; DNA; Oligonucleotide; Computational biology; Biophysics; DNA nanotechnology; Drug delivery; Nucleic acid; In vitro; Cell biology; Nanotechnology; Fluorescence; Biochemistry; Biology","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":[0.0004926153,0.00052863,0.0002966286,0.0002491427,0.0001696916,0.000444266,0.0004529451,0.0004701754,0.0004641725],"category_scores_gemma":[0.0004969977,0.0002472425,0.000282203,0.0001845819,0.0002519644,0.000332604,0.0001708679,0.0004148518,0.0002461908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007143755,"about_ca_system_score_gemma":0.0003695695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006582804,"about_ca_topic_score_gemma":0.002496769,"domain_scores_codex":[0.9995395,0.00008781872,0.00004588102,0.00008791232,0.000174239,0.00006478114],"domain_scores_gemma":[0.9997466,0.00005741449,0.00008194981,0.00002169816,0.00005994604,0.00003237744],"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":[0.00002225984,0.00002868942,0.00008323366,0.00006075479,0.00000680347,0.00004504071,0.00001555107,0.001093196,0.9969218,0.0003317012,0.00003800205,0.001352911],"study_design_scores_gemma":[0.000003076584,0.00004612943,0.00009466733,0.00000137732,0.000003336615,0.00003521582,0.000003122656,0.001396257,0.9973409,0.00001408185,0.001057743,0.000004092845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9422622,0.001262549,0.05336441,0.0001674415,0.00005408768,0.0002636007,0.000341251,0.0003108301,0.001973627],"genre_scores_gemma":[0.9015184,0.0007871243,0.09342443,0.0000621225,0.00001277581,0.0002500258,0.0005545579,0.0001154635,0.003275139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007143755,"threshold_uncertainty_score":0.00518316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007383351949147894,"score_gpt":0.2678468381829097,"score_spread":0.2604634862337618,"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."}}