{"id":"W4290466437","doi":"10.3390/cancers14153810","title":"Cancer-Associated Fibroblasts in a 3D Engineered Tissue Model Induce Tumor-like Matrix Stiffening and EMT Transition","year":2022,"lang":"en","type":"article","venue":"Cancers","topic":"Cellular Mechanics and Interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Extracellular matrix; Urothelium; Stroma; Epithelial–mesenchymal transition; Tumor microenvironment; Fibroblast; Cell biology; Chemistry; Cancer-Associated Fibroblasts; Tissue engineering; Cancer research; Pathology; Biology; Biomedical engineering; Downregulation and upregulation; Anatomy; Immunohistochemistry; Medicine; Tumor cells; In vitro; 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":[0.0001780219,0.0003073015,0.0001558474,0.0002418011,0.0001706885,0.0002166442,0.0001331524,0.000357849,0.0005598745],"category_scores_gemma":[0.00008697408,0.0001865131,0.0002919546,0.0001738124,0.0001465362,0.0001592067,0.0001586217,0.0004601649,0.000239222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001656781,"about_ca_system_score_gemma":0.0002059992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001160915,"about_ca_topic_score_gemma":0.002372396,"domain_scores_codex":[0.9998376,0.00002024486,0.00001456698,0.00003181417,0.00006913998,0.00002657823],"domain_scores_gemma":[0.9999,0.00002107344,0.00002571685,0.00001829971,0.00001094398,0.00002394648],"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":[0.00003305968,0.00003066895,0.0001713999,0.00002093372,0.000004586436,0.00008847981,0.00002505948,0.000388599,0.9984095,0.0001063959,0.00004236927,0.0006788882],"study_design_scores_gemma":[0.00001022771,0.0002058887,0.003576618,0.000005090941,0.00001765073,0.000332152,0.00003617098,0.005994491,0.987168,0.00005881149,0.002587448,0.000007519361],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845515,0.0005639229,0.01192618,0.00007637108,0.00006568979,0.00005782493,0.0003837768,0.0001414934,0.002233176],"genre_scores_gemma":[0.9868891,0.0003378385,0.01007541,0.00005194893,0.000007557513,0.00007606155,0.0003654191,0.00001958945,0.002177037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001160915,"threshold_uncertainty_score":0.002308309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008575440648101458,"score_gpt":0.2484354180351622,"score_spread":0.2398599773870608,"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."}}