Relationships between sperm DNA fragmentation, sperm apoptotic markers and serum levels of CB-153 and p,p′-DDE in European and Inuit populations
Bibliographic record
Abstract
Persistent organochlorine pollutants (POPs) are suspected to interfere with hormone activity and the normal homeostasis of spermatogenesis. We investigated the relationships between sperm DNA fragmentation, apoptotic markers identified on ejaculated spermatozoa and POP levels in the blood of 652 adult males (200 Inuits from Greenland, 166 Swedish, 134 Polish and 152 Ukrainian). Serum levels of 2, 2', 4, 4', 5, 5'-hexachlorobiphenyl (CB-153), as a proxy of the total POP burden, and of 1,1-dichloro-2,2-bis(p-chlorophenyl)-ethylene (p,p'-DDE), as a proxy of the total DDT exposure were determined. Sperm DNA fragmentation was measured by using the TUNEL assay, whereas immunofluorescence methods were utilized for detecting pro-apoptotic (Fas) and anti-apoptotic (Bcl-xL) markers. Both TUNEL assay and apoptotic markers were statistically differed across the four populations. No correlation between neither sperm DNA fragmentation nor apoptotic sperm parameters and the large variations in POPs exposure was observed for the separate study groups. However, considering the European populations taken together, we showed that both %TUNEL positivity and Bcl-xL were related to CB-153 serum levels, whereas our study failed to demonstrate any relations between DDE and %TUNEL positivity and apoptotic sperm biomarkers (Fas and Bcl-xL) in any region or overall regions. These results suggest that CB-153 and related chemicals might alter sperm DNA integrity and Bcl-xL levels in European adult males, but not in the highly exposed Inuit men. Additional issues (genetic background, lifestyle habits and characterization of total xeno-hormonal activities) need to be investigated in order to fully assess the population variations observed.
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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 | 0.000 | 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 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".