Fasting modulates metabolic responses to cortisol, GH and IGF‐I in Arctic charr hepatocytes
Bibliographic record
Abstract
Hepatocytes in primary culture from fed and 2 month fasted Arctic charrSalvelinus alpinuswere exposed to physiological doses of either cortisol, salmon growth hormone (GH), salmon insulin‐like growth factor‐I (IGF‐I) or a combination of salmon GH and salmon IGF‐I. Fasting significantly lowered medium glucose levels compared to the fed fish, but had no significant effects on hepatocyte glycogen content or on the activities of enzymes involved in the intermediary metabolism. Cortisol treatment had no effect on hepatocyte glycogen content or on the enzyme activities investigated, but resulted in a significant increase in medium glucose concentration in hepatocytes isolated from fasted, but not fed fish. GH and IGF‐I treatments, both singly and in combination, significantly increased the glycogen content of hepatocytes isolated from fed fish, with less pronounced effects on hepatocytes isolated from fasted fish. The combination of GH and IGF‐I significantly increased lactate dehydrogenase activity regardless of the feeding state and significantly reduced the phosphenolpyruvate carboxykinase activity and medium glucose concentration in hepatocytes isolated from fed fish. Further, GH and IGF‐I significantly increased the activities of alanine aminotransferase and aspartate aminotransferase in hepatocytes isolated from fasted fish, but not fed fish. There were no effects of GH, IGF‐I, or their combination, on glucose 6‐phosphate dehydrogenase or 3‐hydroxyacyl‐CoA dehydrogenase activities. The results demonstrated that nutritional status of the animal modulates hepatocyte responsiveness to metabolic hormones, and suggested a role for GH and IGF‐I in hepatic glycogen conservation.
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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".