Genotoxic effects of pesticide exposure on farmworkers in the Fraser Valley of British Columbia
Bibliographic record
Abstract
This study measured micronuclei in peripheral blood lymphocytes from British Columbia seasonal farmworkers and controls. The farmworkers were employed to harvest berry crops and were occuparionally exposed to pesticides. In British Columbia, seasonal farmworkers are predominately of East Indian ancestry and the majority are female. Cytogenetic analysis was performed on 39 female subjects of East Indian descent; 18 farmworkers employed during 1993 season and 21 age-matched controls. The mean age was 55.9±9.8 years. An average of 2000 binucleated lymphocytes were scored per individual, and micronuclei were also scored for the presence of kinetochores using CREST anti-bodies. There was no significant difference between the farmworker group (21.68 ± 10.42 micronuclei per 1000 binucleates), and the control group (23.60 ± 10.87 micronuclei per 1000 binucleates). However, among the farmworkers employed during 1993, there was a weak positive association between micronucleated cell frequency and weeks worked: 18.46 ± 8.50 micronuclei per 1000 binucleates in those working less than to 20 weeks to 27.87 ± 15.33 micronuclei per 1000 binucleates in those working more than 23 weeks. In those who had ever been employed as farmworkers, there was an elevated frequency of micronucleated cells in the group with the longest history of employment as a farmworker (26.58 ± 10.53 micronuclei per 1000 binucleates) vs. those with the shortest employment history (17.60 ± 9.04 micronuclei per 1000 binucleates). This trend remained evident after adjusting for age, RBC folate, meat and coffee consumption, recent vaccination, and socioeconomic status. A positive association between the consumption of meat and micronucleus frequency was also noted. Non-meat eaters were likely life-long vegetarians. This study indicates that seasonal farmworkers may have an elevated risk of genetic damage, and steps should be taken to mitigate their exposure to pesticides. Further studies employing more subjects, internal controls and utilizing a larger battery of genotoxicity assays are required. Studies on farm sites also need to be undertaken to develop adequate analyses of farmworker tasks and exposure potential. Use of biological monitoring for pesticide metabolites or exposure modeling using dermal transfer coefficients may provide quantitative exposure data.
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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 | 0.000 |
| 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".