Exposure to persistent organic pollutants and sperm <scp>DNA</scp> methylation changes in Arctic and European populations
Why this work is in the frame
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Bibliographic record
Abstract
Persistent organic pollutants (POPs), such as PCBs (polychlorinated biphenyls) and DDT [1,1,1-trichloro-2,2-bis(4-chlorophenyl)ethane], are environmental contaminants with potential endocrine disrupting activity. DNA methylation levels in peripheral blood lymphocytes have been associated with serum concentrations of POPs in Greenland Inuit and Korean populations. Greenland Inuits are characterized by the highest worldwide POP levels. In this cross-sectional study we evaluated the relationship between serum POP concentrations and DNA methylation levels in sperm of non-occupationally exposed fertile men from Greenland, Warsaw (Poland), and Kharkiv (Ukraine). Serum levels of PCB-153 [1,2,4-trichloro-5-(2,4,5-trichlorophenyl)benzene], as a proxy of the total PCBs body burden, and of p,p'-DDE [1,1-dichloro-2,2-bis(4-chlorophenyl)ethylene], the main metabolite of DDT were measured. Sperm DNA methylation level was assessed globally by flow cytometric (FCM) immunodetection of 5-methyl-cytosines and at specific repetitive DNA sequences (Alu, LINE-1, Satα) by PCR-pyrosequencing after bisulfite conversion. Multivariate linear regression analysis was applied to investigate correlations between serum POP concentrations and DNA methylation. No consistent associations between exposure to POPs and sperm DNA methylation at repetitive DNA sequences were detected. A statistically significant global decrease in methylation was associated with exposure to either POP by FCM analysis. This is the first study to investigate environmental exposure to POPs and DNA methylation levels considering sperm as the target cells. Although POP exposure appears to have a limited negative impact on sperm DNA methylation levels in adult males, the global hypomethylation detected by one of the methods applied suggests that further investigation is warranted.
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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 it