Fasting Augments PCB Impact on Liver Metabolism in Anadromous Arctic Char
Bibliographic record
Abstract
Anadromous arctic char (Salvelinus alpinus) undertake short feeding migrations to seawater every summer and accumulate lipids, while the rest of the year is spent in fresh water where the accumulated lipid reserves are mobilized. We tested the hypothesis that winter fasting and the associated polychlorinated biphenyls' (PCBs) redistribution from lipid depots to critical tissues impair the liver metabolic capacity in these animals. Char were administered Aroclor 1254 (0, 1, 10, and 100 mg/kg body mass) orally and maintained for 4 months without feeding to mimic seasonal winter fasting, while fed groups (0 and 100 mg Aroclor 1254/kg) were maintained for comparison. A clear dose-related increase in PCB accumulation and cytochrome P4501A (CYP1A) protein content was observed in the livers of fasted fish. This PCB concentration and CYP1A response with the high dose of Aroclor were 1.5-fold and 3-fold greater in the fasted than in the fed fish, respectively. In fed fish, PCB exposure lowered liver glycogen content, whereas none of the other metabolic indicators were significantly affected. In fasted fish, PCB exposure depressed liver glycogen content and activities of glucose-6-phosphate dehydrogenase, alanine aminotransferase, lactate dehydrogenase, and phosphoenolpyruvate carboxykinase and elevated 3-hydroxyacylcoA dehydrogenase activity and glucocorticoid receptor protein expression. There were no significant impacts of PCB on heat shock protein 70 (hsp70) and hsp90 contents in either fed or fasted fish. Collectively, our study demonstrates that winter emaciation associated with the anadromous lifestyle predisposes arctic char to PCB impact on hepatic metabolism including disruption of the adaptive metabolic responses to extended fasting.
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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".