Urinary 1-hydroxypyrene and Skin Contamination in Firefighters Deployed to the Fort McMurray Fire
Bibliographic record
Abstract
BACKGROUND: In May 2016, firefighters from the province of Alberta, Canada deployed to a fire that engulfed the urban area of Fort McMurray. During the first days of the fire, firefighters experienced heavy smoke exposures during greatly extended work shifts. Urinary samples were collected post-deployment from three fire services for estimation of 1-hydroxypyrene (1-HP) concentration, reflecting exposure to polycyclic aromatic hydrocarbons (PAHs), to determine the effects of respiratory protective equipment (RPE) and skin hygiene in reducing internal dose. METHODS: Urine samples from one fire service (n = 62) were analyzed for 1-HP by two laboratories, using different assays (LC-MS/MS: GC-MS): remaining samples were analyzed just by LC-MS/MS. A Skin Exposure Mitigation Index (SEMI) was computed from questions on opportunities for changing clothing, showering, and washing during breaks. Regression analyses, using 1-HP ng/g creatinine as the dependent variable, assessed the effect of RPE and skin factors on PAH absorption, allowing for environmental exposure and potential confounders. Stratification identified key groups with equal delay in sample collection. RESULTS: 1-HP was detected in 71.0% of 62 samples by LC-MS/MS and 98.4% by GC-MS, with good mutual agreement between the methods. In 171 post-fire samples, 1-HP corrected for creatinine was related to current cigarette smoking and recent barbeque. Among those with samples collected within 48 h, urinary 1-HP was correlated with estimated exposure(r = 0.53, P < 0.001). In those with only one rotation before urine sample collection, no effect was seen of RPE use but I-HP was significantly lower (P = 0.003) in those with those with a high score on the SEMI scale, indicating better access to factors mitigating skin absorption. CONCLUSION: Skin exposure to PAHs is an important route of absorption in firefighters, which can be mitigated by good skin hygiene.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".