{"id":"W4298144072","doi":"10.3389/fbioe.2022.989888","title":"Engineering diabetic human skin equivalent for in vitro and in vivo applications","year":2022,"lang":"en","type":"article","venue":"Frontiers in Bioengineering and Biotechnology","topic":"Planarian Biology and Electrostimulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Canadian Institutes of Health Research; Réseau de Recherche en Santé Buccodentaire et Osseuse","keywords":"Keratinocyte; Skin equivalent; Diabetic foot; Diabetes mellitus; Basement membrane; Wound healing; Medicine; Fibroblast; In vivo; Human skin; Basal (medicine); Tissue engineering; Laminin; Extracellular matrix; In vitro; Chemistry; Endocrinology; Immunology; Cell biology; Pathology; Biology; Biomedical engineering; Biochemistry","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":[0.0003579543,0.000307074,0.0001513512,0.0002414657,0.0001087316,0.0002968411,0.0001583701,0.0003865219,0.001365931],"category_scores_gemma":[0.0001886004,0.000114383,0.0003135728,0.0001756042,0.00009588109,0.0001928962,0.0001801372,0.0004054112,0.0003291122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001136171,"about_ca_system_score_gemma":0.00009748004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002282323,"about_ca_topic_score_gemma":0.0005123306,"domain_scores_codex":[0.9998327,0.00001978258,0.00001844196,0.0000304035,0.00007725223,0.00002138069],"domain_scores_gemma":[0.9998634,0.00002345921,0.00002670311,0.00002227803,0.00004515702,0.00001901919],"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":[0.00002857576,0.00005616706,0.0001416256,0.00008521835,0.000005686099,0.0001359778,0.00001942661,0.0001820636,0.9963027,0.00008049444,0.00006211674,0.00289991],"study_design_scores_gemma":[0.00001062609,0.0004951446,0.002123916,0.00001986329,0.00003537503,0.0005678853,0.000047848,0.0008047202,0.9867975,0.00005848125,0.009030206,0.000008563771],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9420577,0.006570773,0.03862502,0.0001771971,0.0003964442,0.0003926258,0.001006997,0.0001354491,0.01063785],"genre_scores_gemma":[0.965775,0.003081256,0.02517655,0.000163846,0.0000236145,0.000217522,0.0007096246,0.00003096552,0.004821647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001365931,"threshold_uncertainty_score":0.004569471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004063750563280038,"score_gpt":0.2022849093525825,"score_spread":0.1982211587893024,"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."}}