Variation in enzymes of arylamine procarcinogen biotransformation among bladder cancer patients and control subjects
Bibliographic record
Abstract
Arylamines such as 2-naphthylamine and 4-aminobiphenyl are suspected human bladder procarcinogens that require bioactivation to DNA-reactive species to exert their carcinogenic potential. The goals of the present study were (i) to assay for the presence of the arylamine acetyltransferases NAT1 and NAT2, and of the cytochrome P450 isoform CYP1A2, in human bladder epithelium; and (ii) to determine whether the activities of these arylamine biotransforming enzymes differ between bladder cancer patients and control subjects. We measured in-vitro enzyme activities in biopsies of normal, undiseased bladder epithelium obtained from 103 bladder cancer patients. NAT1 activity was detectable in all samples, with mean levels higher than those found in human liver. Kinetic evidence also suggested low levels of NAT2 expression in this tissue, but there was no detectable CYP1A2 by either enzymatic or immunochemical measurements. We also compared several probe drug indices of in-vivo NAT1, NAT2 and CYP1A2 activity between 53 bladder cancer patients and 96 cancer-free control subjects who were carefully matched for age, gender and smoking status. NAT1 and NAT2 genotypes were also determined. No significant differences were found between bladder cancer patients and control subjects for a number of individual phenotypic or genotypic predictors of enzyme function. Our results suggest that although expression of particular arylamine biotransforming enzymes within the bladder tissue could play a significant role in locally bioactivating arylamine procarcinogens in theory, interindividual variations in CYP1A2, NAT1 and NAT2 activities do not significantly differ between bladder cancer patients and control subjects when potential arylamine exposures are controlled for
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".