BTEX chrono-metabolism and leukemogenic effects of night shift work in workers of gasoline stations: the EXPOSOWORK prospective panel study in Bulgaria
Bibliographic record
Abstract
Background: Exposures to benzene, toluene, ethylbenzene and xylenes (BTEX) have been associated with impairment of the hematopoietic system, often leading to leukemogenesis. A prospective panel study: i) characterized the effect of night shift work (NSW) (12-hr night shift vs. 12-hr day shift) on urinary BTEX and metabolites in gasoline station workers in Plovdiv, Bulgaria, ii) evaluated the NSW effect on chrono-based BTEX genotoxic effects (as measured by 8-OHdG, a nonspecific biomarker of genotoxicity) including the influence of the downstream urinary metabolome. Methods: During a week's working period, workers (n=71) followed both day shift and night shift work schedules (12-h long each shift) collecting four urine samples per worker (pre and end of shift). Airborne BTEX exposures were evaluated over 12-h shift periods using wearable passive samplers. Urinary BTEX and the metabolome were measured using mass spectrometry. 8-OHdG was measured using an ELISA immunoassay. Associations were examined using mixed-effect regression models and corrected for false-discovery rates of 0.05. Results: for day and night work shifts, respectively, suggestive of a low-level BTEX study. Results supported a consistent trend of lower urinary BTEX levels in NSW than those observed in day shift, after adjusting for airborne BTEX and confounders. Metabolomic signatures revealed a few significant metabolites associated with NSW or 8-OHdG with 4-hydroxybenzeneacetic acid (level I) being associated with both NSW and 8-OHdG. The biological pathway with high metabolic pathway impact were glycine, serine and threonine metabolism. Conclusion: Larger NSW studies with longer and more frequent follow-up times are warranted to better delineate the possible influence of NSW chrono-modulated working activities in leukemogenic processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".