Safety of chronic exercise in a rat model of kidney disease
Bibliographic record
Abstract
DARNLEY, M. J., N. M. DIMARCO, and H. M. AUKEMA. Safety of chronic exercise in a rat model of kidney disease. Med. Sci. Sports Exerc., Vol. 32, No. 3, pp. 576–580, 2000. Purpose: The objective of this study was to determine the effect of treadmill running on polycystic kidney disease (PKD) progression and bone mineral density in Han:SPRD-cy rats, an animal model of PKD. Methods: Using a 2 × 2 design, normal and polycystic male rats were divided randomly into exercise and sedentary groups at 4 wk of age. The exercising group performed treadmill exercise (14 m·min−1) for 30 min 3 d·wk−1 for 6 wk, whereas the control group remained sedentary. This 6-wk period represents the period of greatest cyst growth in this model. Results: Both exercised and sedentary polycystic animals had significantly greater kidney weights, as well as greater concentrations of serum urea nitrogen and serum creatinine than control animals. Exercise did not alter these parameters in either normal or polycystic animals. In addition, bone mineral density and bone mineral content, determined by dual-energy x-ray absorptiometry, were not altered by exercise in these animals. Bone mineral content, however, was marginally lower in polycystic animals. Conclusions: These results support the safety of moderate exercise in PKD. Additional research in this area is needed since there may be other benefits that are derived from exercise in this population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".