Resistance exercise attenuates skeletal muscle oxidative stress, systemic pro-inflammatory state, and cachexia in Walker-256 tumor-bearing rats
Bibliographic record
Abstract
The aim of this study was to investigate the effects of resistance exercise training (RET) on oxidative stress, systemic inflammatory markers, and muscle wasting in Walker-256 tumor-bearing rats. Male (Wistar) rats were divided into 4 groups: sedentary controls (n = 9), tumor-bearing (n = 9), exercised (n = 9), and tumor-bearing exercised (n = 10). Exercised and tumor-bearing exercised rats were exposed to resistance exercise of climbing a ladder apparatus with weights tied to their tails for 6 weeks. The physical activity of control and tumor-bearing rats was confined to the space of the cage. After this period, tumor-bearing and tumor-bearing exercised animals were inoculated subcutaneously with Walker-256 tumor cells (11.0 × 107 cells in 0.5 mL of phosphate-buffered saline) while control and exercised rats were injected with vehicle. Following inoculation, rats maintained resistance exercise training (exercised and tumor-bearing exercised) or sedentary behavior (control and tumor-bearing) for 12 more days, after which they were euthanized. Results showed muscle wasting in the tumor-bearing group, with body weight loss, increased systemic leukocytes, and inflammatory interleukins as well as muscular oxidative stress and reduced mTOR signaling. In contrast, RET in the tumor-bearing exercised group was able to mitigate the reduced body weight and muscle wasting with the attenuation of muscle oxidative stress and systemic inflammatory markers. RET also prevented loss of muscle strength associated with tumor development. RET, however, did not prevent the muscle proteolysis signaling via FBXO32 gene messenger RNA expression in the tumor-bearing group. In conclusion, RET performed prior tumor implantation prevents cachexia development by attenuating tumor-induced systemic pro-inflammatory condition with muscle oxidative stress and muscle damage.
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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".