Glucocorticoid antagonism limits adiposity rebound and glucose intolerance in young male rats following the cessation of daily exercise and caloric restriction
Bibliographic record
Abstract
Severe caloric restriction (CR), in a setting of regular physical exercise, may be a stress that sets the stage for adiposity rebound and insulin resistance when the food restriction and exercise stop. In this study, we examined the effect of mifepristone, a glucocorticoid (GC) receptor antagonist, on limiting adipose tissue mass gain and preserving whole body insulin sensitivity following the cessation of daily running and CR. We calorically restricted male Sprague-Dawley rats and provided access to voluntary running wheels for 3 wk followed by locking of the wheels and reintroduction to ad libitum feeding with or without mifepristone (80 mg·kg(-1)·day(-1)) for 1 wk. Cessation of daily running and CR increased HOMA-IR and visceral adipose mass as well as glucose and insulin area under the curve during an oral glucose tolerance test vs. pre-wheel lock exercised rats and sedentary rats (all P < 0.05). Insulin sensitivity and glucose tolerance were preserved and adipose tissue mass gain was attenuated by daily mifepristone treatment during the post-wheel lock period. These findings suggest that following regular exercise and CR there are GC-induced mechanisms that promote adipose tissue mass gain and impaired metabolic control in healthy organisms and that this phenomenon can be inhibited by the GC receptor antagonist mifepristone.
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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) | 0.001 | 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".