Exposure to Persistent Organic Pollutants Reduces Testosterone Concentrations and Affects Sperm Viability and Morphology during the Mating Peak Period in a Controlled Experiment on Farmed Arctic Foxes (<i>Vulpes lagopus</i>)
Bibliographic record
Abstract
We investigated testosterone production and semen parameters in farmed Arctic foxes by dietary exposure to persistent organic pollutants (POPs) for 22 months. Eight male foxes were given a diet of POP-contaminated minke whale blubber, whereas their eight male siblings were fed a control diet containing pig fat as the main fat source. The minke whale-based feed contained a ∑POPs concentration of 802 ng/g ww, whereas the pig-based feed contained ∑POPs of 24 ng/g ww. At the end of the experiment, ∑POP concentrations in adipose tissue were 8856 ± 2535 ng/g ww in the exposed foxes and 1264 ± 539 ng/g ww in the control foxes. The exposed group had 45-64% significantly lower testosterone concentrations during their peak mating season compared to the controls (p ≤ 0.05), while the number of dead and defect sperm cells was 27% (p = 0.07) and 15% (p = 0.33) higher in the exposed group. Similar effects during the mating season in wild Arctic foxes may affect mating behavior and reproductive success. On the basis of these results, we recommend testosterone as a sensitive biomarker of POP exposure and that seasonal patterns are investigated when interpreting putative endocrine disruption in Arctic wildlife with potential population-level effects.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".