Short-term mercury exposure disrupts muscular and hepatic lipid metabolism in a migrant songbird
Bibliographic record
Abstract
Methylmercury (MeHg) is a global pollutant that can cause metabolic disruptions in animals and thereby potentially compromise the energetic capacity of birds for long-distance migration, but its effects on avian lipid metabolism pathways that support endurance flight and stopover refueling have never been studied. We tested the effects of short-term (14-d), environmentally relevant (0.5 ppm) dietary MeHg exposure on lipid metabolism markers in the pectoralis and livers of yellow-rumped warblers (Setophaga coronata) that were found in a previous study to have poorer flight endurance in a wind tunnel than untreated conspecifics. Compared to controls, MeHg-exposed birds displayed lower muscle aerobic and fatty acid oxidation capacity, but similar muscle glycolytic capacity, fatty acid transporter expression, and PPAR expression. Livers of exposed birds indicated elevated energy costs, lower fatty acid uptake capacity, and lower PPAR-γ expression. The lower muscle oxidative enzyme capacity of exposed birds likely contributed to their weaker endurance in the prior study, while the metabolic changes observed in the liver have potential to inhibit lipogenesis and stopover refueling. Our findings provide concerning evidence that fatty acid catabolism, synthesis, and storage pathways in birds can be dysregulated by only brief exposure to MeHg, with potentially significant consequences for migratory performance.
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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".