Endothelium-dependent control of cerebrovascular functions through age: exercise for healthy cerebrovascular aging
Bibliographic record
Abstract
Cognitive performances are tightly associated with the maximal aerobic exercise capacity, both of which decline with age. The benefits on mental health of regular exercise, which slows the age-dependent decline in maximal aerobic exercise capacity, have been established for centuries. In addition, the maintenance of an optimal cerebrovascular endothelial function through regular exercise, part of a healthy lifestyle, emerges as one of the key and primary elements of successful brain aging. Physical exercise requires the activation of specific brain areas that trigger a local increase in cerebral blood flow to match neuronal metabolic needs. In this review, we propose three ways by which exercise could maintain the cerebrovascular endothelial function, a premise to a healthy cerebrovascular function and an optimal regulation of cerebral blood flow. First, exercise increases blood flow locally and increases shear stress temporarily, a known stimulus for endothelial cell maintenance of Akt-dependent expression of endothelial nitric oxide synthase, nitric oxide generation, and the expression of antioxidant defenses. Second, the rise in circulating catecholamines during exercise not only facilitates adequate blood and nutrient delivery by stimulating heart function and mobilizing energy supplies but also enhances endothelial repair mechanisms and angiogenesis. Third, in the long term, regular exercise sustains a low resting heart rate that reduces the mechanical stress imposed to the endothelium of cerebral arteries by the cardiac cycle. Any chronic variation from a healthy environment will perturb metabolism and thus hasten endothelial damage, favoring hypoperfusion and neuronal stress.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".