{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001791752,0.0003485659,0.0002705682,0.0002048557,0.0002415071,0.0003674564,0.0002306947,0.0003017146,0.0006944124],"category_scores_gemma":[0.0001482607,0.0001292567,0.0002488998,0.0002673643,0.0002349167,0.0002218257,0.0002483371,0.0004057029,0.0002306386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002677847,"about_ca_system_score_gemma":0.0002368093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00208831,"about_ca_topic_score_gemma":0.002890289,"domain_scores_codex":[0.9998698,0.00001290621,0.000008507934,0.00003775965,0.00004061738,0.00003042395],"domain_scores_gemma":[0.9998958,0.00001301407,0.00003297281,0.000008717331,0.00002797117,0.00002146515],"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":[0.00006764405,0.0000157013,0.0007042348,0.00002187402,0.000003132464,0.00002721492,0.00001405556,0.00003573549,0.9986585,0.00001390167,0.00002631806,0.0004117102],"study_design_scores_gemma":[0.000006985373,0.0003223414,0.04542424,0.00001215002,0.00001673535,0.0002451346,0.0002373535,0.002043107,0.9499398,0.00006503175,0.001672635,0.00001446143],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965764,0.0002509304,0.001254877,0.00009835784,0.00001958101,0.00002856747,0.001092978,0.00006243079,0.0006158693],"genre_scores_gemma":[0.9894086,0.0004661554,0.006274634,0.0002274647,0.00001418853,0.00006556769,0.002357429,0.00004582687,0.001140217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00208831,"threshold_uncertainty_score":0.004152298,"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."}}