Bibliographic record
Abstract
Abstract ArylamineN‐acetyltransferases (NATs) are phase II xenobiotic‐conjugating enzymes that have a restricted substrate preference for theN‐ orO‐acetylation of aromatic amine and theirN‐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 theNAT2gene locus, a considerable variation exists in theNAT1gene. 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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 0.014 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".