Response of oxidative stress transcripts in the brain of wild yellow perch (Perca flavescens) exposed to an environmental gradient of methylmercury Toxicology & pharmacology
Bibliographic record
Abstract
Methylmercury (MeHg) exposure and adverse health effects in fishes have been documented, but the molecular mechanisms involved in toxicity have not been fully characterized. The objectives of the current study were to (1) determine whether total Hg (THg) in the muscle was predictive of MeHg concentrations in the brain of wild female yellow perch (Perca flavescens) collected from four lakes in Kejimkujik National Park, a known biological mercury (Hg) hotspot in Nova Scotia, Canada and (2) to determine whether transcripts involved in the oxidative stress response were altered in abundance in fish collected across five lakes representing a MeHg gradient. In female yellow perch, MeHg in whole brain (0.38 to 2.00μg/g wet weight) was positively associated with THg in muscle (0.18 to 2.13μg/g wet weight) (R²=0.61, p<0.01), suggesting that muscle THg may be useful for predicting MeHg concentrations in the brain. Catalase (cat) mRNA levels were significantly lower in brains of perch collected from lakes with high Hg when compared to those individuals from lakes with relatively lower Hg (p=0.02). Other transcripts (cytochrome c oxidase, glutathione peroxidase, glutathione-s-transferase, heat shock protein 70, protein disulfide isomerase, and superoxide dismutase) did not show differential expression in the brain over the gradient. These findings suggest that MeHg may be inversely associated with catalase mRNA abundance in the central nervous system of wild fishes.
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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) | 0.000 | 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".