Exercise Reverses Metabolic Syndrome in High-Fat Diet-Induced Obese Rats
Bibliographic record
Abstract
PURPOSE: Chronic consumption of a high-fat diet induces obesity. We investigated whether exercise would reverse the cardiometabolic disorders associated with obesity without it being necessary to change from a high- to normal-fat diet. METHODS: Sprague-Dawley rats were placed on a high-fat (HFD) or control diet (CD) for 12 wk. HFD rats were then divided into four groups: sedentary HFD (HFD-S), exercise trained (motor treadmill for 12 wk) HFD (HFD-Ex), modified diet (HFD to CD; HF/CD-S), and exercise trained with modified diet (HF/CD-Ex). Cardiovascular risk parameters associated with metabolic syndrome were measured, and contents of aortic Akt, phospho-Akt at Ser (473), total endothelial nitric oxide synthase (eNOS), and phospho-eNOS at Ser (1177) were determined by Western blotting. RESULTS: Chronic consumption of HFD induced a metabolic syndrome. Exercise and dietary modifications reduced adiposity, improved glucose and insulin levels and plasma lipid profile, and exerted an antihypertensive effect. Exercise was more effective than dietary modification in improving plasma levels of thiobarbituric acid-reacting substance and in correcting the endothelium-dependent relaxation to acetylcholine and insulin. Furthermore, independent of the diet used, exercise increased Akt and eNOS phosphorylation. CONCLUSIONS: Metabolic syndrome induced by HFD is reversed by exercise and diet modification. It is demonstrated that exercise training induces these beneficial effects without the requirement for dietary modification, and these beneficial effects may be mediated by shear stress-induced Akt/eNOS pathway activation. Thus, exercise may be an effective strategy to reverse almost all the atherosclerotic risk factors linked to obesity, particularly in the vasculature.
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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 | 0.000 |
| 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".