Determination of Biological Reference Values for Chlorpyrifos Metabolites in Human Urine Using a Toxicokinetic Approach
Bibliographic record
Abstract
Urinary biomarkers of chlorpyrifos (CPF) exposure are often measured in field studies, although biological reference values (BRVs) are not yet available to assess health risks. This study aimed at proposing BRVs for CPF metabolites in workers' urine based on a toxicokinetic approach. As a first step, a toxicokinetic model was developed, using published human kinetic data, to link the absorbed dose of CPF under a variety of exposure routes and temporal scenarios to the urinary excretion of its major metabolites, 3,5,6-trichloro-2-pyridinol (3,5,6-TCP) and alkyl phosphates (AP). The model was then used to propose BRVs for CPF metabolites in urine below which workers should not experience adverse health effects. This was achieved by linking (1) a literature-reported, repeated CPF no-observed-effect level (NOEL) daily exposure dose for the inhibition of red-blood-cell acetylcholinesterase activity to a corresponding absorbed daily dose, and (2) this absorbed daily dose to the urinary excretion of CPF metabolites. Model simulations under a variety of exposure scenarios showed that the safest BRVs are obtained from a dermal exposure scenario with the slowest absorption rate compatible with available literature data rather than from respiratory or oral exposure scenarios. Also, model simulations showed that, for a given total absorbed dose, absorption over 8 hours results in smaller 3,5,6-TCP and AP urinary excretion rates than those obtained from the same dose absorbed over shorter durations. From these considerations, BRVs were derived by simulating an 8-hour dermal CPF exposure such that the total absorbed daily dose corresponds to the absorbed NOEL. The reference values are proposed in the form of total amounts of 3,5,6-TCP and AP metabolites excreted in urine over chosen time periods (24 and 48 hours).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".