{"id":"W4415472607","doi":"10.1021/acssensors.5c00957","title":"Gut-on-a-Chip-Based Real-Time miRNA-21 Monitoring and Anti-Inflammatory Drug Evaluation","year":2025,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Population and Public Health","funders":"Qilu University of Technology; Shandong Academy of Sciences; Natural Science Foundation of Shandong Province; Youth Innovation Team Project for Talent Introduction and Cultivation in Universities of Shandong Province; National Natural Science Foundation of China; Key Technology Research and Development Program of Shandong; Jinan Science and Technology Bureau","keywords":"Biomarker; Drug; Limiting; Therapeutic drug monitoring; Inflammatory bowel disease; Inflammation; Drug development; In vitro","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005564698,0.0007391432,0.000775891,0.0004470537,0.0001851729,0.0004331688,0.0006413354,0.001022393,0.0008369057],"category_scores_gemma":[0.0006285462,0.0003440123,0.0004809407,0.0002086677,0.000265756,0.0003229844,0.00040332,0.0006627738,0.0004867614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003877869,"about_ca_system_score_gemma":0.0003653797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005775352,"about_ca_topic_score_gemma":0.001495756,"domain_scores_codex":[0.999361,0.0001200517,0.00003506247,0.0001782782,0.0002243002,0.00008128884],"domain_scores_gemma":[0.9997916,0.00005882433,0.00002877359,0.00002133683,0.0000763838,0.00002311842],"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":[0.00007693313,0.00004899004,0.0002016216,0.0001375201,0.00002513268,0.00004602579,0.00001480186,0.0003953354,0.9914664,0.00011452,0.0003299414,0.007142673],"study_design_scores_gemma":[0.00001363078,0.0003320932,0.0009205504,0.000006627903,0.00003435143,0.0001140876,0.00001350914,0.007481272,0.9883373,0.00004929238,0.002669194,0.0000279508],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6560563,0.01305982,0.3174292,0.0007114347,0.0008764952,0.000785756,0.002252237,0.003335291,0.005493542],"genre_scores_gemma":[0.7354056,0.00370854,0.2534844,0.0008680811,0.00008937724,0.0008887742,0.001057251,0.00009076179,0.004407113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001022393,"threshold_uncertainty_score":0.00294292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008869295031158518,"score_gpt":0.2888645258274459,"score_spread":0.2799952307962874,"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."}}