{"id":"W4415629993","doi":"10.1021/acschembio.5c00753","title":"Exploring Metalloproteome Remodeling in Calprotectin-Stressed <i>Acinetobacter baumannii</i> Using Chemoproteomics","year":2025,"lang":"en","type":"article","venue":"ACS Chemical Biology","topic":"Bacterial Genetics and Biotechnology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"IONICS Mass Spectrometry (Canada)","funders":"Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases; National Institute of Allergy and Infectious Diseases; Division of Molecular and Cellular Biosciences; National Institute of General Medical Sciences","keywords":"Enzyme; Strain (injury); Host–pathogen interaction; Calprotectin; GTP'; Quantitative proteomics; Translation (biology); Pathogen; Metabolic pathway","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002410839,0.0003190924,0.0004161847,0.0001699907,0.00006222991,0.0000239135,0.0004473892,0.0007362932,0.00001226031],"category_scores_gemma":[0.0002077867,0.0003073986,0.000113548,0.0003498746,0.0002515549,0.000008264318,0.0005154633,0.0003990933,0.000004742173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005942061,"about_ca_system_score_gemma":0.00009253357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009082946,"about_ca_topic_score_gemma":0.00001943701,"domain_scores_codex":[0.99799,0.00006615432,0.0005127928,0.0007846112,0.00006177165,0.0005846987],"domain_scores_gemma":[0.9991641,0.00001823208,0.0001109468,0.0005523677,0.00008661086,0.00006773848],"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":[0.000169044,0.00005570041,0.0006810389,0.000026342,0.00004748311,0.000002403825,0.000009128504,0.00004040535,0.9933982,0.0004006723,0.00001410764,0.005155445],"study_design_scores_gemma":[0.0008621297,0.00008533433,0.0001431455,0.0000403022,0.00002044695,0.00001283264,0.00001975296,0.0002629317,0.9902101,0.0009115526,0.007112299,0.0003191811],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967985,0.0003444185,0.001302025,0.0004988811,0.0003166627,0.000419309,0.00001586385,0.00003851251,0.0002658937],"genre_scores_gemma":[0.9925293,0.000332301,0.006115892,0.000479556,0.0002271659,0.0001103669,0.0001216801,0.00002978518,0.0000539496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007098191,"threshold_uncertainty_score":0.9999378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05085497437255886,"score_gpt":0.2714608082605482,"score_spread":0.2206058338879893,"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."}}