Toxicokinetic Modeling of Parathion and its Metabolites in Humans for the Determination of Biological Reference Values
Bibliographic record
Abstract
Abstract A multi-compartment kinetic model was developed to describe the kinetics of parathion and its metabolites, p-nitrophenol (p-NP) and alkyl phosphates (AP), in order to assess worker exposure and health risks. Model compartments represent body burdens and excreta of parathion and its metabolites; to minimize the number of compartments and free parameters, regrouping was carried out on the basis of the time scales of the kinetic processes involved. Burden variations in time were described mathematically by differential equations that ensure conservation of mass on a mole basis. Model parameter values were determined from statistical fits to published in vivo kinetic data in humans. Except for the dermal absorption fraction and absorption rate, which are known to be subject to wide intra- and inter-individual variability, a single set of parameter values for the internal body kinetics enabled the model to simulate accurately the available kinetic data. For dermal exposure to parathion, with a typical absorption rate of 0.085 h(-1), model simulations show that it takes 20 h to recover half of the total amounts of p-NP eventually excreted in urine and 30 h for the AP. The model can be used to estimate the dose of parathion absorbed under different exposure routes and temporal scenarios, based on measurements of amounts of metabolites accumulated in urine over given time periods. Using the above dose-excreta links and the human no-observed-effect level for parathion reported in the literature for the inhibition of cholinesterase activities, biological reference values are proposed in the form of specific amounts of urinary metabolites excreted over chosen time periods.
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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 | 0.001 | 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".