Does a failure to normalize diurnal glucocorticoids negate the benefits of exercise training?
Bibliographic record
Abstract
Glucocorticoids (GCs) are released by the hypothalamic‐pituitary‐adrenal (HPA) axis in response to a variety of stressors. Although acute elevations of GCs are beneficial, prolonged exposure has significant and detrimental metabolic consequences, most notably seen in Cushing's syndrome. Here, we created an animal model of Cushing's syndrome and investigated the impact of exercise training on various metabolic parameters. Male Sprague‐Dawley rats were divided into exercise and sedentary groups and further subdivided into control (SHAM) and corticosterone (CORT) groups. Exercising animals had access to running wheels for 6 weeks, while sedentary animals remained in standard cages. A 300mg corticosterone pellet was implanted subcutaneously in CORT rats while SHAM rats received a wax pellet. Within 1 week, both sedentary and exercising CORT rats demonstrated a ≈15‐and 1.7‐fold elevation in nadir and peak GCs levels respectively, resulting in an abolished diurnal pattern. Relative to body weight, sedentary CORT animals had more epididymal fat when compared to sedentary controls. Conversely, exercise CORT rats had epididymal fat content comparable to that of exercise SHAM animals. This study proposes a new animal model of Cushing's syndrome and reveals that regular exercise attenuates the accumulation of visceral fat mass in this animal model. This study was funded by NSERC.
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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 | 0.001 |
| 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".