{"id":"W4313644357","doi":"10.3389/fmolb.2022.1067296","title":"Nicotinamide as potential biomarker for Alzheimer’s disease: A translational study based on metabolomics","year":2023,"lang":"en","type":"article","venue":"Frontiers in Molecular Biosciences","topic":"Tryptophan and brain disorders","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; International Society for Neurochemistry; Universität zu Köln; Agencia Nacional de Promoción Científica y Tecnológica; McGill University; Consejo Nacional de Investigaciones Científicas y Técnicas; Rheinische Friedrich-Wilhelms-Universität Bonn; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; Consortium canadien en neurodégénérescence associée au vieillissement","keywords":"Metabolomics; Nicotinamide adenine dinucleotide; NAD+ kinase; Metabolome; Dementia; Internal medicine; Biomarker; Alzheimer's disease; Endocrinology; Chemistry; Nicotinamide; Hippocampus; Amyloid (mycology); Disease; Biochemistry; Biology; Medicine; Pathology; Chromatography; Enzyme","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001376833,0.000477394,0.0005290028,0.0005745433,0.0001948044,0.0007716814,0.0002496549,0.0004896781,0.0008889121],"category_scores_gemma":[0.0004903979,0.0001049631,0.0003847198,0.0006471262,0.0003881871,0.0004598726,0.0003141758,0.000408829,0.0001608244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003910124,"about_ca_system_score_gemma":0.0007365313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008642104,"about_ca_topic_score_gemma":0.001126623,"domain_scores_codex":[0.9998174,0.00006941076,0.00001157057,0.00004995938,0.00003380617,0.00001776859],"domain_scores_gemma":[0.9996525,0.00006978964,0.0001024122,0.0000347764,0.00009166276,0.00004886304],"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":[0.005838752,0.001084345,0.1772679,0.002748609,0.00127109,0.0009463808,0.000355765,0.001137734,0.5134608,0.001875733,0.001586002,0.2924269],"study_design_scores_gemma":[0.0003029205,0.01568788,0.7767686,0.0006915528,0.002211671,0.004074327,0.0008184433,0.00796831,0.1605136,0.005507659,0.02532365,0.0001314337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8407089,0.1445341,0.008269151,0.002876623,0.0002328084,0.0001631168,0.0007007527,0.00009448711,0.002419983],"genre_scores_gemma":[0.9423414,0.04705284,0.007976177,0.0005968621,0.0002872122,0.00008562442,0.0006327804,0.00001173847,0.001015316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001376833,"threshold_uncertainty_score":0.007281482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02753951938128116,"score_gpt":0.2936521256801359,"score_spread":0.2661126062988547,"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."}}