Testosterone and persistent organic pollutants in East Greenland male polar bears (Ursus maritimus)
Bibliographic record
Abstract
Legacy persistent organic pollutants (POPs) such as polychlorinated biphenyls (PCBs) are chemicals that undergo long-range transport to the Arctic. These chemicals possess endocrine disruptive properties raising concerns for development and reproduction. Here, we report the relationship between concentrations of testosterone (T) and persistent organic pollutant (POPs) in 40 East Greenland male polar bears ( Ursus maritimus ) sampled during January to September 1999–2001. The mean ± standard concentrations of blood T were 0.31 ± 0.49 (mean ± SD) ng/mL in juveniles/subadults (n = 22) and 3.58 ± 7.45 ng/mL in adults (n = 18). The ∑POP concentrations (mean ± SD) in adipose tissue were 8139 ± 2990 ng/g lipid weight (lw) in juveniles/subadults and 11,037 ± 3950 ng/g lw in adult males, respectively, of which Σpolychlorinated biphenyls (ΣPCBs) were found in highest concentrations. The variation in T concentrations explained by sampling date (season), biometrics and adipose tissue POP concentrations was explored using redundancy analysis (RDA). The results showed that age, body length, and adipose lipid content in adult males contributed (p = 0.02) to the variation in POP concentrations. However, although some significant relationships between individual organochlorine contaminants and T concentrations in both juveniles/subadults and adult polar bears were identified, no significant relationships (p = 0.32) between T and POP concentrations were identified by the RDAs. Our results suggest that confounders such as biometrics and reproductive status may mask the endocrine disruptive effects that POPs have on blood T levels in male polar bears, demonstrating why it can be difficult to detect effects on wildlife populations.
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 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 | 0.000 | 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".