Sympathetic vasoconstriction in skeletal muscle: modulatory effects of aging, exercise training, and sex
Bibliographic record
Abstract
The sympathetic nervous system (SNS) is a critically important regulator of the cardiovascular system. The SNS controls cardiac output and its distribution, as well as peripheral vascular resistance and blood pressure at rest and during exercise. Aging is associated with increased blood pressure and decreased skeletal muscle blood flow at rest and in response to exercise. The mechanisms responsible for the blunted skeletal muscle blood flow response to dynamic exercise with aging have not been fully elucidated; however, increased muscle sympathetic nerve activity (MSNA), elevated vascular resistance, and a decline in endothelium-dependent vasodilation are commonly reported in older adults. In contrast to aging, exercise training has been shown to reduce blood pressure and enhance skeletal muscle vascular function. Exercise training has been shown to enhance nitric oxide-dependent vascular function and may improve the vasodilatory capacity of the skeletal muscle vasculature; however, surprisingly little is known about the effect of exercise training on the neural control of circulation. The control of blood pressure and skeletal muscle blood flow also differs between men and women. Blood pressure and MSNA appear to be lower in young women than in men. However, females experience a larger increase in MSNA with aging compared with males. The mechanism(s) underlying the altered SNS control of vascular function in females remains to be determined. Novelty: This review summarizes our current understanding of the effects of aging, exercise training, and sex on sympathetic vasoconstriction at rest and during exercise. Areas where additional research is needed are also identified.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".