Methylmercury and selenium speciation in different tissues of beluga whales ( <i>Delphinapterus leucas</i> ) from the western Canadian Arctic
Bibliographic record
Abstract
Monitoring data have shown that the total monomethylmercury (CH(3) Hg(+) and its complexes; collectively referred as MeHg hereafter) concentrations in Arctic marine mammals have remained very high in recent decades. Toward a better understanding of the metabolic and toxicological implications of these high levels of MeHg, we report here on the molecular forms of MeHg in the muscle, brain, liver, and kidneys of 10 beluga whales from the western Canadian Arctic. In all tissues analyzed, monomethylmercury was found to be dominated by methylmercuric cysteinate, a specific form of MeHg believed to be able to transport across the blood-brain barrier. Another MeHg-thiol complex, methylmercuric glutathionate, was also detected in the muscle and, to a much lesser extent, in the liver and brain tissues. Furthermore, a profound inorganic Hg peak was detected in the liver and brain tissues, which showed the same retention time as a selenium (Se) peak, suggesting the presence of an Hg-Se complex, most likely an inorganic Hg complex with a selenoamino acid. These results provide the first analytical support that the binding of MeHg with glutathione and Se may have protected beluga whales from the toxic effect of high concentrations of MeHg in their body.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".