Modeling of the Internal Kinetics of Benzo(a)pyrene and 3-Hydroxybenzo(a)pyrene Biomarker from Rat Data
Bibliographic record
Abstract
Measurements of 3-hydroxybenzo(a)pyrene (3-OHBaP) in urine has been proposed for the biomonitoring of exposure to benzo(a)pyrene (BaP) in workers. To allow a better understanding of the toxicokinetics of BaP and its key biomarker, a multicompartment model was developed based on rat data previously obtained by this group. According to the model, iv injected BaP is rapidly distributed from blood to tissues (t₁/₂ = 3.65 h), with particular affinity for tissue lipid components and liver and lung proteins. BaP is then rapidly distributed to lungs, where significant tissue uptake occurs, followed by the skin, liver, and adipose tissues. Once in liver, BaP is readily metabolized, and 3-OHBaP is formed with a t₁/₂ of 3.32 h. Lung metabolism of BaP was also accounted for, but its contribution to the whole kinetics was found to be negligible. Once formed, 3-OHBaP is distributed from blood to the various organs almost as fast as the parent compound (t₁/₂ = 2.26 h). In kidneys, 3-OHBaP builds up as a result of the smaller rate of 3-OHBaP urinary excretion (t₁/₂ = 4.52 h) as compared with its transfer rate from blood to kidneys (t₁/₂ = 27.8 min). However, overall clearance of 3-OHBaP from the body is driven by its biliary transfer from liver to the gastrointestinal tract (t₁/₂ = 3.81 h). The model provides a great fit to independent sets of published data on 3-OHBaP urinary excretion time course (χ² = 0.019). This model proves useful in establishing the main biological determinants of the overall kinetics of these compounds.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".