Molecular and Neurochemical Biomarkers in Arctic Beluga Whales (<i>Delphinapterus leucas</i>) Were Correlated to Brain Mercury and Selenium Concentrations.
Bibliographic record
Abstract
Mercury (Hg) concentrations have increased in western Arctic beluga whales (Delphinapterus leucas) since the industrial revolution. Methylmercruy (MeHg) is a known neurotoxicant, yet little is known about the risk of exposure for beluga whales. Selenium (Se) has been linked to demethylation of MeHg in cetaceans, but its role in attenuating Hg toxicity in beluga whales is poorly understood. The objective of this study is to explore relationships between Hg and Se concentrations and neurochemical biomarkers in different brain regions of beluga whales in order to assess potential neurotoxicological risk of Hg exposure in this population. Brain tissue was sampled from hunter-harvested beluga whales from the western Canadian Arctic in 2008 and 2010. Neurochemical and molecular biomarkers were measured with radioligand binding assays and quantitative PCR, respectively. Total Hg (HgT) concentration ranged from 2.6-113 mg kg(-1) dw in temporal cortex. Gamma-amminobutyric acid type A receptor (GABAA-R) binding in the cerebellum was negatively associated with HgT, MeHg and total Se (SeT) concentrations (p ≤ 0.05). The expression of mRNA for GABAA-R subunit α2 was negatively associated with HgT and MeHg (p ≤ 0.05). Furthermore, GABAA-R binding was positively correlated to mRNA expression for GABAA-R α2 subunit, and negatively correlated to the expression of mRNA for GABAA-R α4 subunit (p ≤ 0.05). The expression of N-methyl-d-aspartate receptor (NMDA-R) subunit 2b mRNA expression was negatively associated with iHglabile concentration in the cerebellum (p ≤ 0.05). Variation of molecular and/or biochemical components of the GABAergic and glutamatergic signaling pathways were associated with MeHg exposure in beluga whales. Our results show that MeHg exposure is associated with neurochemical variation in the cerebellum of beluga whales and Se may partially protect from MeHg-associated neurotoxicity.
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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) | 0.001 | 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".