Adaptation to physical training in rats orally supplemented with glycerol
Bibliographic record
Abstract
We evaluated training adaptation and physical performance parameters in rats orally supplemented with glycerol, glucose, or saline, and submitted to moderate aerobic exercise. Thirty male rats were trained for 6 weeks and administered the supplements during the last 4 weeks of the experiment. Animals were distributed in a completely randomized factorial 2 × 3 design (with or without exercise and 3 substrates). Data were subjected to analysis of variance (ANOVA) and means were compared using the Student-Newmann-Keuls test at 5%. Among the trained animals, none of the substances caused differences in the percentages of protein, fat, or water content in the carcass. Compared with the sedentary animals, the trained animals supplemented with saline and glucose showed a higher protein percentage in the carcass. The relative mass of the heart and adrenal glands was higher in the trained animals. Glycerol improved the protein content in non-trained animals and increased the relative adrenal mass in both groups. Glycerol reduced the variation in levels of lactate and aspartate aminotransferase (AST) during the last exercise session. There was no difference between groups regarding the relative mass of the thymus and gastrocnemius or with the diameter of muscle fibers or the neutrophil-lymphocyte ratio. Supplementation with glycerol was efficient at attenuating variation in AST and lactate levels during exercise.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".