Biomarkers of the cholinergic and dopaminergic signaling pathways in Arctic beluga whales (<i>Delphinapterus leucas</i>): relationship to methylmercury and selenium
Bibliographic record
Abstract
There are increasing concerns about potential neurotoxicity of chronic methylmercury (MeHg) exposure in Arctic wildlife and human populations. The relationships between mercury (Hg), MeHg, inorganic Hg (iHg), and selenium (Se) exposure, and neurochemical and molecular biomarkers in beluga whales (Delphinapterus leucas (Pallas, 1776)) were characterized. Samples were collected in 2008 (n = 20) and 2010 (n = 15) in the Canadian Arctic from hunter-harvested beluga whales. Total Hg concentrations in the temporal cortex and cerebellum were 21.0 ± 22.6 mg kg−1 dry weight (dw) and 14.9 ± 18.9 mg kg−1 dw, respectively. Monoamine oxidase (MAO) activity was predicted by MeHg and the molar ratio of total Hg to Se (Hg:Se, p < 0.05); MAO-A mRNA transcription levels were predicted by iHg and Se (p < 0.05). Muscarinic AChR binding was predicted by MeHg (p < 0.05) and Hg:Se molar ratio (p < 0.05), and mRNA transcription levels of mAChR m1 was predicted by the Hg:Se molar ratio (p < 0.05). These results suggest that the cholinergic and dopaminergic signaling pathway in Eastern Beaufort Sea beluga whales may be sensitive to MeHg exposure. The response of beluga whales to MeHg exposure at a physiological and population level remains to be elucidated.
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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".