Elevated Exposures to Polycyclic Aromatic Hydrocarbons and Other Organic Mutagens in Ottawa Firefighters Participating in Emergency, On-Shift Fire Suppression
Bibliographic record
Abstract
Occupational exposures to combustion emissions were examined in Ottawa Fire Service (OFS) firefighters. Paired urine and dermal wipe samples (i.e., pre- and post-event) as well as personal air samples and fire event questionnaires were collected from 27 male OFS firefighters. A total of 18 OFS office workers were used as additional controls. Exposures to polycyclic aromatic hydrocarbons (PAHs) and other organic mutagens were assessed by quantification of urinary PAH metabolite levels, levels of PAHs in dermal wipes and personal air samples, and urinary mutagenicity using the Salmonella mutagenicity assay (Ames test). Urinary Clara Cell 16 (CC16) and 15-isoprostane F 2t (8-iso-PGF 2α ) levels were used to assess lung injury and overall oxidative stress, respectively. The results showed significant 2.9- to 5.3-fold increases in average post-event levels of urinary PAH metabolites, depending on the PAH metabolite ( p < 0.0001). Average post-event levels of urinary mutagenicity showed a significant, event-related 4.3-fold increase ( p < 0.0001). Urinary CC16 and 8-iso-PGF 2α did not increase. PAH concentrations in personal air and on skin accounted for 54% of the variation in fold changes of urinary PAH metabolites ( p < 0.002). The results indicate that emergency, on-shift fire suppression is associated with significantly elevated exposures to combustion emissions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".