PCB-Associated Changes in mRNA Expression in Killer Whales (<i>Orcinus orca</i>) from the NE Pacific Ocean
Bibliographic record
Abstract
Killer whales in the NE Pacific Ocean are among the world's most PCB-contaminated marine mammals, raising concerns about implications for their health. Sixteen health-related killer whale mRNA transcripts were analyzed in blubber biopsies collected from 35 free-ranging killer whales in British Columbia using real-time quantitative polymerase chain reaction. We observed PCB-related increases in the expression of five gene targets, including the aryl hydrocarbon receptor (AhR; r(2) = 0.83; p < 0.001), thyroid hormone α receptor (TRα; r(2) = 0.64; p < 0.001), estrogen α receptor (ERα; r(2) = 0.70; p < 0.001), interleukin 10 (IL-10; r(2) = 0.74 and 0.68, males and females, respectively; p < 0.001), and metallothionein 1 (MT1; r(2) = 0.58; p < 0.001). Best-fit models indicated that population (dietary preference), age, and sex were not confounding factors, except for IL-10, where males differed from females. While the population-level consequences are unclear, the PCB-associated alterations in mRNA abundance of such pivotal end points provide compelling evidence of adverse physiological effects of persistent environmental contaminants in these endangered killer whales.
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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".