Contributions of Dermal and Pulmonary Routes to Chloroform Exposure in Swimming Pool: A Comparison Between 3 Estimation Approaches
Bibliographic record
Abstract
PP-30-105 Background/Aims: Excluding ingestion, inhalation is commonly considered as the main route of exposure to chloroform (trichloromethane), an abundant water chlorination by-product suspected for carcinogenicity. However, cases were also reported concluding that dermal absorption could prevail (up to 80%). This work aimed at investigating this question by simulating swimming pool exposure scenarios excerpted from literature through 3 different estimation approaches, using the following: (i) a physiologically based pharmacokinetic (PBPK) model previously developed by our team; (ii) the swimmer exposure assessment model (SWIMODEL) developed by US Environmental Protection Agency; (iii) uptake factors (UF) as proposed by Villanueva et al (2007) on the basis of previous works of Whitaker et al (2003). Methods: Five studies documenting precisely the exposure conditions, especially both water and air trichloromethane concentrations (7–550 μg/L and 30–8000 μg/m3, respectively), as well as biological levels in blood and/or alveolar air of exposed volunteers, were selected for this simulation exercise. Ingestion, usually low (30 mL), was not accounted for. For the other parameters, typical default values were used. Results: Predicted uptakes vary greatly between the various approaches (eg, the range of uptake ratios were [0.18–2.98] and [0.17–3.25] for (ii)/(i) and (iii)/(i), respectively). Besides, the contributions of dermal absorption to global exposure comprised between (1%; 12%), and (7%; 87%), for the approach (i) and (ii) respectively (Not calculable by approach (iii)). Conclusion: Interestingly, the PBPK approach confirms the contradictory conclusions reported in the literature as for the relative importance of dermal and pulmonary absorptions. We believe PBPK modeling is the most reliable approach (still to be further improved, especially regarding simulation of the dermal pathway) to assess exposure in swimming pools for epidemiological purposes. Supported by AFSSET.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".