Substituting food restriction by resistance training prevents liver and body fat regain in ovariectomized rats
Bibliographic record
Abstract
OBJECTIVE: Fat mass gain and regain following weight loss are major concerns and may be even more critical after menopause. The present study was undertaken to evaluate the effect of a resistance training protocol on body weight and fat mass in ovariectomized Sprague-Dawley rats following diet-induced weight loss. DESIGN: Rats were randomly divided into ovariectomized (Ovx) and sham-operated (Sham) groups. Five weeks after ovariectomy, Ovx rats were subjected to a 26% food restriction (OvxFR) for 8 weeks. Following this period, OvxFR rats went back to a normal ad libitum feeding and were divided into two groups: either sedentary or undergoing a resistance training program for an additional 5 weeks, which consisted of climbing a 6-m vertical grill, 20-40 times, with progressively increasing load four times/week. RESULTS: The food restriction program decreased (p < 0.01) body mass, fat pad weight (intra-abdominal and subcutaneous), and liver triacylglycerol (TAG) levels as compared to normally fed Ovx rats. Stopping the food restriction program over a 5-week period resulted in a partial regain in body weight and intra-abdominal fat pad weight (p < 0.05), and in an almost complete regain in liver TAG compared to normally fed Ovx rats. On the other hand, no significant increases in these variables were noted when the food restriction was replaced by resistance training over the same 5-week period. CONCLUSION: These results indicate that a resistance training program could be useful in preventing body weight as well as adipose tissue and liver fat regain in Ovx rats, following diet-induced weight loss. It is suggested that changing from a food restriction regimen to a resistance training program can be an interesting strategy to promote successful long-term weight reduction in postmenopausal women.
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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 | 0.000 |
| 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".