Chronic cortisol and the regulation of food intake and the endocrine growth axis in rainbow trout
Bibliographic record
Abstract
To gain a better understanding of the mechanisms by which cortisol suppresses growth during chronic stress in fish, we characterized the effects of chronic cortisol on food intake, mass gain, the expression of appetite-regulating factors, and the activity of the GH/IGF axis. Fish given osmotic pumps that maintained plasma cortisol levels at ∼70 or 116 ng/ml for 34 days were sampled 14, 28 and 42 days post-implantation. Relative to shams, the cortisol treatments reduced food intake by 40-60% and elicited marked increases in liver leptin (lep-a1) and brain preoptic area (POA) corticotropin-releasing factor (crf) mRNA levels. The cortisol treatments also elicited 40-80% reductions in mass gain associated with increases in pituitary gh, liver gh receptor (ghr), liver igfI and igf binding protein (igfbp)-1 and -2 mRNA levels, reduced plasma GH and no change in plasma IGF1. During recovery, while plasma GH and pituitary gh, liver ghr and igfI gene expression did not differ between treatments, the high cortisol-treated fish had lower plasma IGF1 and elevated liver igfbp1 mRNA levels. Finally, the cortisol-treated fish had higher plasma glucose levels, reduced liver glycogen and lipid reserves, and muscle lipid content. Thus, our findings suggest that the growth-suppressing effects of chronic cortisol in rainbow trout result from reduced food intake mediated at least in part by increases in liver lep-a1 and POA crf mRNA, from sustained increases in hepatic igfbp1 expression that reduce the growth-promoting actions of the GH/IGF axis, and from a mobilization of energy reserves.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".