Comparison of the kinetics of various biomarkers of benzo[<i>a</i>]pyrene exposure following different routes of entry in rats
Bibliographic record
Abstract
The effect of route of exposure on the kinetics of key biomarkers of exposure to benzo[a]pyrene (BaP), a known human carcinogen, was studied. Rats were exposed to an intravenous, intratracheal, oral and cutaneous dose of 40 µmol kg(-1) BaP. BaP and several metabolites were measured in blood, urine and feces collected at frequent intervals over 72 h post-treatment, using high-performance liquid chromatography/fluorescence. Only BaP and 3-hydroxyBaP (3-OHBaP) were detectable in blood at all time points. There were route-to-route differences in the excreted amounts (% dose) of metabolites but the observed time courses of the excretion rate were quite similar. In urine, total amounts of BaP metabolites excreted over the 0-72 h period followed the order: trans-4,5-dihydrodiolBaP (4,5-diolBaP) ≥ 3-OHBaP > 7-OHBaP ≥ 7,8-diolBaP after intravenous injection and intratracheal instillation; 3-OHBaP ≈ 7-OHBaP ≥ 4,5-diolBaP > 7,8-diolBaP after cutaneous application; 3-OHBaP ≥ 4,5-diolBaP ≈ 7-OHBaP > 7,8-diolBaP following oral administration. In feces, total amounts of BaP metabolites recovered were: 7-OHBaP ≈ 3-OHBaP > 4,5-diolBaP > 7,8-diolBaP > BaP-7,8,9,10-tetrol following all administration routes. For all exposure routes, excretion of 4,5- and 7,8-diolBaP was almost complete over the 0-24 h period in contrast with that of 3- and 7-OHBaP. This study confirms the interest of measuring multiple metabolites due to route-to-route differences in the relative excretion of the different biomarkers and in the time courses of diolBaPs versus OHBaPs. Concentration ratios of the different metabolites may help indicate time and main route of exposure.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".