{"id":"W7116699390","doi":"10.1016/j.biomaterials.2025.123942","title":"Metabolic microenvironment-forming porous hydrogels for the protection of phenylalanine ammonia-lyase in the intestine","year":2025,"lang":"en","type":"article","venue":"Biomaterials","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cegep de Saint Hyacinthe; Université de Montréal","funders":"Faculté de pharmacie, Université de Montréal; Association canadienne du médicament générique; Fonds de Recherche du Québec - Santé; Institut TransMedTech; Fonds de recherche du Québec; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Université de Montréal; Réseau Québécois de Recherche sur les Médicaments","keywords":"Self-healing hydrogels; Phenylalanine; Enzyme; Trypsin; Protease; Matrix (chemical analysis); In vitro; Amino acid","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005962902,0.0001285436,0.000170523,0.00004553093,0.000101515,0.00002532716,0.0003228415,0.00007900068,0.000008505733],"category_scores_gemma":[0.0001798669,0.00007697484,0.0000623306,0.0001159683,0.0001086209,0.000004093018,0.00008851393,0.00001236018,0.000003856918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000012059,"about_ca_system_score_gemma":0.00003373353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002709233,"about_ca_topic_score_gemma":0.0000502941,"domain_scores_codex":[0.9990895,0.00009727633,0.0003523985,0.0002186715,0.00006949565,0.0001725988],"domain_scores_gemma":[0.9993308,0.00003319754,0.0001405756,0.0004567431,0.00002512233,0.0000135195],"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":[0.00008201043,0.00007293929,0.0001170582,0.00003520531,0.00004684083,1.852006e-7,0.00006321452,0.000009428753,0.9923205,0.00007501219,0.0000920489,0.007085604],"study_design_scores_gemma":[0.0003113538,0.0000543514,0.001430105,0.00002135838,0.0000512168,0.00000849946,0.00008203504,0.00003983523,0.9561592,0.0001031014,0.04166219,0.00007675364],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934986,0.001483994,0.002530836,0.0008922256,0.00008612779,0.001392152,0.00006082911,0.00001050477,0.00004470439],"genre_scores_gemma":[0.9974309,0.0001233585,0.0007636537,0.0001661179,0.00009642575,0.001241271,0.00004264228,0.0000148693,0.0001207411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04157014,"threshold_uncertainty_score":0.3138943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01880569603172086,"score_gpt":0.2503475412582681,"score_spread":0.2315418452265473,"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."}}