Ethanol toxicokinetics resulting from inhalation exposure in human volunteers and toxicokinetic modeling
Bibliographic record
Abstract
Uncertainty exists regarding the validity of a previously developed physiologically-based pharmacokinetic model (PBPK) for inhaled ethanol in humans to predict the blood levels of ethanol (BLE) at low level exposures (<1000 ppm). Thus, the objective of this study is to document the BLE resulting from low levels exposures in order to refine/validate this PBPK model. Human volunteers were exposed to ethanol vapors during 4 h at 5 different concentrations (125-1000 ppm), at rest, in an inhalation chamber. Blood and exhaled air were sampled. Also, the impact of light exercise (50 W) on the BLE was investigated. There is a linear relationship between the ethanol concentrations in inhaled air and (i) BLE (women: r²= 0.98/men: r²= 0.99), as well as (ii) ethanol concentrations in the exhaled air at end of exposure period (men: r²= 0.99/women: r²= 0.99). Furthermore, the exercise resulted in a net and significant increase of BLE (2-3 fold). Overall, the original model predictions overestimated the BLE for all low exposures performed in this study. To properly simulate the toxicokinetic data, the model was refined by adding a description of an extra-hepatic biotransformation of high affinity and low capacity in the richly perfused tissues compartment. This is based on the observation that total clearance observed at low exposure levels was much greater than liver blood flow. The results of this study will facilitate the refinement of the risk assessment associated with chronic inhalation of low levels of ethanol in the general population and especially among workers.
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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 | 0.001 |
| 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".