Kinetics of Diol and Hydroxybenzo[a]pyrene Metabolites in Relation to DNA Adduct Formation and Gene Expression in Rats
Bibliographic record
Abstract
Benzo[a]pyrene (BaP) is a human carcinogen, but there are no validated biomarkers of exposure and the relationship of carcinogenesis with early biological alterations is not fully documented. This study aimed at better documenting the toxicokinetics of diolBaP and hydroxyBaP metabolites as potential biomarkers of exposure to BaP in relation to DNA adduct formation and gene expression. Rats were intravenously (iv) injected with 40 μmol/kg BaP. BaP and several metabolites were measured in blood, tissues, and excreta collected at frequent intervals over 72 h posttreatment. BaP diol epoxide (BaPDE)-DNA adduct formation and gene expression were assessed in lungs. 3-HydroxyBaP (3-OHBaP) and 4,5-diolBaP were the most abundant measured metabolites, and differences in time courses were apparent between the two metabolites. Over the 0-72 h period, mean proportions of BaP dose recovered in urine as 3-OHBaP and 4,5-diolBaP (±SD) were 0.017 ± 0.003% and 0.1 ± 0.03%. Corresponding values in feces were 1.5 ± 0.5% and 0.42 ± 0.052%. BaPDE-DNA adducts were significantly increased in lungs and a correlation was observed with urinary 3-OHBaP and 4,5-diolBaP. Analysis of gene expression showed a modulation of expression of metabolic genes (Cyp1a1, Cyp1b1, Nqo1, Ahr) and oxidative stress and repair genes (Nrf2, Rad51). However, BaPDE adducts formation did not exhibit any significant correlation with expression of genes, except a negative correlation with Rad51 expression. Similarly, there was no significant correlation between urinary excretion of OHBaP and diolBaP and expression of genes, except for urinary 7-OHBaP excretion, which was negatively correlated with Rad51 expression. Results indicate that concomitant measurements of diolBaP and OHBaP may serve to better assess the extent of exposure as compared to single metabolite measurements, given kinetic differences between metabolites. Further, although some urinary metabolites were correlated with BaPDE adducts, links with gene expression need to be further investigated.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".