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Record W2901468086 · doi:10.1002/9780470921920.edm144

Arylamine<i>N</i>‐Acetyltransferases

2016· other· en· W2901468086 on OpenAlexaff
Denis M. Grant

Bibliographic record

VenueEncyclopedia of Drug Metabolism and Interactions · 2016
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAcetyltransferasesAcetylationAromatic amineXenobioticBiochemistryChemistryEnzymeGeneArylamine N-acetyltransferaseIsozymeGeneticsBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Arylamine N ‐acetyltransferases (NATs) are phase II xenobiotic‐conjugating enzymes that have a restricted substrate preference for the N ‐ or O ‐acetylation of aromatic amine and their N ‐oxidized metabolites. Although the number of clinically useful drugs whose disposition depends on acetylation is relatively small, the risk for toxicity from these agents is significant. In addition, a much larger number of potentially hazardous environmental aromatic amines may be acetylated, and this process may contribute to either the detoxication or the metabolic activation of such chemicals into reactive electrophiles with the potential to damage cellular macromolecules. The structures of the two human NAT enzymes NAT1 and NAT2 have been determined; the structural features allow for the detailed description of a two‐step catalytic mechanism and for a rationalization of their distinct substrate preferences. Although the human isoniazid acetylation polymorphism is controlled by allelic variation at the NAT2 gene locus, a considerable variation exists in the NAT1 gene. Numerous associations have been reported between variable NAT function and risk for cancers associated with exposure to aromatic amines. In addition, possible novel roles for NAT1 and its mammalian orthologs in folate homeostasis and in cellular proliferation are being actively explored.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.091
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.253
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

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