In Vitro Mammalian Mutagenicity of Complex Polycyclic Aromatic Hydrocarbon Mixtures in Contaminated Soils
Bibliographic record
Abstract
This study employed an in vitro version of the lacZ transgenic rodent mutation assay to assess the mutagenicity of nonpolar neutral and semipolar aromatic soil fractions from 10 PAH-contaminated sites, and evaluated the assumption of dose additivity that is routinely employed to calculate the risk posed by PAH mixtures. Significant mutagenic activity was detected in all nonpolar neutral fractions, and 8 of 10 semipolar aromatic fractions (nonpolar > semipolar). Mutagenic activity of synthetic PAH mixtures that mimic the PAH content of the soils (i.e., 5-PAH or 16-PAH mix) were greater than that of the PAH-containing soil fractions, with 5-PAH mix >16-PAH-mix. Predictions of mutagenic activity, calculated as the sum of the contributions from the mutagenic mixture components, were all within 2-fold of the observed activity of the nonpolar neutral fractions, with one exception. Observed differences in mutagenic activity are likely the result of dynamic metabolic processes, involving a complex interplay of AhR agonsim and saturation of metabolic machinery by competitive inhibition of mixture components. The presence of hitherto unidentified polar compounds present in PAH-contaminated soils may also contribute to overall hazard; however, these compounds are generally not included in current contaminated site risk assessment protocols.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".