Energy intake-independent modulation of triglyceride metabolism by glucocorticoids in the rat
Bibliographic record
Abstract
This study aimed to dissociate the peripheral effects of adrenalectomy (ADX) on triglyceride (TG) metabolism from those it exerts centrally on energy intake and to determine the impact of diet composition therein. Rats were fed either rodent chow or a diet high in sucrose and fat (HSF) and were adrenalectomized or left intact and pair fed to the ADX animals. Liver TG content, an index of hepatic TG production, was not affected by ADX, but was increased twofold by the HSF diet. ADX decreased the rate of hepatic TG secretion by 41% in chow-fed but not in HSF-fed animals. Triglyceridemia and postheparin plasma lipase activities remained largely unchanged by treatments. ADX decreased insulinemia fivefold in chow-fed rats, but less so in HSF-fed animals. Likewise, subcutaneous and visceral adipose depots were 40-60% smaller in ADX than in intact pair-fed rats given chow, but the effect of ADX was dampened by consumption of the HSF diet. Although smaller, adipose tissues of ADX rats maintained a higher activity of lipoprotein lipase (LPL) than those of intact pair-fed rats, whereas muscle LPL was decreased. The study confirms that in the presence of reduced energy intake, corticosterone contributes to the maintenance of adipose stores and that the consequences of its absence tend to be attenuated when a high-energy diet is fed. The study further shows that, contrary to ad libitum feeding conditions, most determinants of TG metabolism, such as hepatic TG stores, triglyceridemia, postheparin plasma LPL, and adipose tissue LPL, are minimally affected by glucocorticoids when consumption of a high-energy diet is restricted, suggesting that glucocorticoids affect TG metabolism mostly indirectly through their central action on ingestive behavior.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".