<i>In vivo</i> and <i>in vitro</i> metabolism of aromatic amines in transgenic mice with liver‐selective expression of human arylamine N‐acetyltransferase NAT2
Bibliographic record
Abstract
To aid studies into the role of liver‐selective expression of human arylamine N‐acetyltransferase NAT2 in tissue patterns of aromatic amine toxicity, we developed a transgenic mouse line that expresses human NAT2 selectively in liver by linking the human NAT2 protein‐coding exon to the mouse albumin promoter, injecting the transgene into mouse oocytes, and testing offspring for transgene incorporation by Southern blotting. We obtained one transgenic founder that possesses a single copy of the human NAT2 coding region. Transgenic animals and offspring of matings with Nat1/Nat2 null mice were assayed for human NAT2 expression using the human NAT2‐selective substrate sulfamethazine (SMZ) and the NAT1‐selective substrate p ‐aminosalicylate (PAS) in in vitro enzyme assays and in vivo plasma pharmacokinetic studies. SMZ‐NAT activity was present in liver cytosols from transgenic animals at levels comparable to those observed in livers from human NAT2 rapid acetylators, while activity was absent in Nat1/Nat2 null controls. Activity in colon was low and that in other tissues was undetectable. SMZ was more efficiently cleared in vivo by human NAT2 transgenic mice than non‐transgenics, while the clearance of PAS was similar between the strains. These mice will be a valuable tool to investigate the importance of liver NAT2 expression in the metabolism and toxicity of aromatic amines in humans.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".