PCBs Are Associated With Altered Gene Transcript Profiles in Arctic Beluga Whales (<i>Delphinapterus leucas</i>)
Bibliographic record
Abstract
High trophic level arctic beluga whales (Delphinapterus leucas) are exposed to persistent organic pollutants (POP) originating primarily from southern latitudes. We collected samples from 43 male beluga harvested by Inuvialuit hunters (2008-2010) in the Beaufort Sea to evaluate the effects of POPs on the levels of 13 health-related gene transcripts using quantitative real-time polymerase chain reaction. Consistent with their role in detoxification, the aryl hydrocarbon receptor (Ahr) (r(2) = 0.18, p = 0.045 for 2008 and 2009) and cytochrome P450 1A1 (Cyp1a1) (r(2) = 0.20, p < 0.001 for 2008 and 2009; r(2) = 0.43, p = 0.049 for 2010) transcripts were positively correlated with polychlorinated biphenyls (PCBs), the dominant POP in beluga. Principal Components Analysis distinguished between these two toxicology genes and 11 other genes primarily involved in growth, metabolism, and development. Factor 1 explained 56% of gene profiles, with these latter 11 gene transcripts displaying greater abundance in years coinciding with periods of low sea ice extent (2008 and 2010). δ(13)C results suggested a shift in feeding ecology and/or change in condition of these ice edge-associated beluga whales during these two years. While this provides insight into the legacy of PCBs in a remote environment, the possible impacts of a changing ice climate on the health of beluga underscores the need for long-term studies.
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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 | 0.000 | 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) | 0.001 | 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".