Social status affects lipid metabolism in rainbow trout,<i>Oncorhynchus mykiss</i>
Bibliographic record
Abstract
Juvenile rainbow trout ( Oncorhynchus mykiss) confined in pairs form social hierarchies in which socially subordinate fish display characteristic traits, including reduced growth rates and altered glucose metabolism. These effects are, in part, mediated by chronically elevated cortisol levels and/or reduced feeding. To determine the effects of social status on lipid metabolism, trout were held in pairs for 4 days, following which organismal and liver-specific indexes of lipid metabolism were measured. At the organismal level, circulating triglycerides were elevated in dominant trout, whereas subordinate trout exhibited elevated concentrations of circulating free fatty acids (FFAs) and lowered plasma total cholesterol levels. At the molecular level, increased expression of lipogenic genes in dominant trout and cpt1a in subordinate trout was identified, suggesting a contribution of increased de novo lipogenesis to circulating triglycerides in dominant trout and reliance on circulating FFAs for β-oxidation in the liver of subordinates. Given the emerging importance of microRNAs (miRNA) in the regulation of hepatic lipid metabolism, candidate miRNAs were profiled, revealing increased expression of the lipogenic miRNA-33 in dominant fish. Because the Akt-TOR-S6-signaling pathway is an important upstream regulator of hepatic lipid metabolism, its signaling activity was quantified. However, the only difference detected among groups was a strong increase in S6 phosphorylation in subordinate trout. In general, the changes observed in lipid metabolism of subordinates were not mimicked by either cortisol treatment or fasting alone, indicating the existence of specific, emergent effects of subordinate social status itself on this fuel.
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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".