Physiologically Based Modeling of n-Hexane Kinetics in Humans Following Inhalation Exposure at Rest and Under Physical Exertion: Impact on Free 2,5-Hexanedione in Urine and on n-Hexane in Alveolar Air
Bibliographic record
Abstract
We used a modified physiologically based pharmacokinetic (PBPK) to describe/predict n-hexane (HEX) alveolar air concentrations and free 2,5-HD urinary concentrations in humans exposed to n-HEX by inhalation during a typical workweek. The effect of an increase in workload intensity on these two exposure indicators was assessed and, using Monte Carlo simulation, the impact of biological variability was investigated. The model predicted HEX alveolar air concentrations at rest of 19.0 ppm (25 ppm exposure) and 38.7 ppm (50 ppm exposure) at the end of the last working day (day 5), while free 2,5-HD urinary concentrations of 3.4 micromol/L (25 ppm) and 6.3 micromol/L (50 ppm) were predicted for the same period (last 4.5 hours of Day 5). Monte Carlo simulations showed that the range of values expected to occur in a group of 1000 individuals exposed to 50 ppm of HEX (95% confidence interval) for free 2,5-HD (1.7-14.7 micromol/L) is much higher compared with alveolar air HEX (33.4-46 ppm). Simulations of exposure at 50 ppm with different workloads predicted that an increase in workload intensity would not greatly affect both indicators studied. However, the alveolar air HEX concentration is more sensitive to modifications of workload intensity and time of sampling, after the end of exposure, compared with 2,5-HD. The PBPK model successfully described the HEX alveolar air concentrations and free 2,5-HD urinary concentrations measured in human volunteers and is the first, to our knowledge, to describe the excretion kinetics of free 2,5-HD in humans over a 5-day period.
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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".