Nitric oxide and voluntary exercise together promote quadriceps hypertrophy and increase vascular density in female 18-mo-old mice
Bibliographic record
Abstract
Age-related sarcopenia reduces the size, strength, and function of muscle, and the diameter of muscle fibers. It also disrupts the dystrophin-glycoprotein complex, dislocating nitric oxide synthase 1 (NOS-1) and reducing sarcolemmal integrity. This study of quadriceps muscle in 18-mo-old mice showed that NO-donor treatment with isosorbide dinitrate (I) for 6 wk, in combination with voluntary exercise for 3 wk, increased muscle mass by 25% and stimulated cell proliferation. The resulting fiber hypertrophy was accompanied by a lower ratio of protein:DNA, consistent with myogenic-cell hyperplasia. Treatment enhanced the ratio of NOS-1:β-dystroglycan in correlation with fiber diameter, improved sarcolemmal integrity, and increased vascular density after an increase in vascular endothelial growth factor protein at 3 wk. Results demonstrate that age-related muscle refractoriness to exercise can be overcome with NO-donor treatment. Since activation of muscle stem cells and vascular perfusion are limiting factors in the maintenance, regeneration, and growth of aged muscle, results suggest the feasibility of using NO-donor drugs to combat atrophy and muscle ischemia. Improved function and quality of life from the NO-amplified effects of exercise may be useful in aging and other conditions such as disuse, insulin resistance, or microgravity.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".