Effects of <i>Tribulus terrestris</i> saponins on exercise performance in overtraining rats and the underlying mechanisms
Bibliographic record
Abstract
The objective of this study was to determine the effects of Tribulus terrestris L. (TT) saponins on exercise performance and the underlying mechanisms. A rat overtraining model was established and animals were treated with TT extracts (120 mg/kg body mass) 30 min before each training session. Serum levels of testosterone and corticosterone and levels of androgen receptor (AR) and insulin growth factor-1 receptor (IGF-1R) in the liver, gastrocnemius, and soleus were determined by ELISA and Western blot. Treatment of rats with TT saponins significantly improved the performance of the overtraining rats, reflected by the extension of time to exhaustion, with a concomitant increase in body mass, relative mass, and protein levels of gastrocnemius. Overtraining alone induced a significant decrease in the serum level of testosterone. In contrast, treatment with TT saponins dramatically increased the serum level of testosterone in overtraining rats to about 150% of control and 216% of overtraining groups, respectively. In addition, TT saponins resulted in a further significant increase in AR in gastrocnemius and significantly suppressed the overtraining-induced increase in IGF-1R in the liver. These results indicated that TT saponins increased performance, body mass, and gastrocnemius mass of rats undergoing overtraining, which might be attributed to the changes in androgen-AR axis and IGF-1R signaling.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".