Organic and inorganic contamination impacts on metabolic capacities in American and European yellow eels
Bibliographic record
Abstract
American (Anguilla rostrata) and European (Anguilla anguilla) eel populations are declining since the 1980s, and contamination is thought to play a role. To determine the influence of organic (organochlorinated pesticides (OCPs), polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs)) and inorganic (Zn, As, Cd, Cu, Pb, Cr, Ni, Ag, Se, Hg) contaminants on wild yellow eels liver and muscle metabolic capacities, enzymatic assays were performed. In A. rostrata liver, G6PDH moderate negative correlations with Ag, Pb, and As suggest impacts on lipid metabolism, and correlations between Cd and age (positive) and between Cd and relative condition factor (Kn; negative) indicate impacts on older eels health. Anguilla anguilla liver proteins, pyruvate kinase (PK), and lactate dehydrogenase (LDH) were positively linked to Zn, Pb, and Cu, suggesting effects on glycolytic and anaerobic capacities. In A. anguilla muscle, absence of correlation between age and lipids plus strong positive correlations between age and OCPs, PBDEs, PCBs, and Hg suggest lipid storage impairment in older contaminated eels. Overall, our study indicates contamination impacts on both species’ metabolic capacities, but the broader range of contaminants found in A. anguilla brings greater impacts compared with A. rostrata.
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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".