Elevated Aerobic Fitness Sustained Throughout the Adult Lifespan Is Associated With Improved Cerebral Hemodynamics
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Age-related impairments in cerebral blood flow and cerebrovascular reactivity to carbon dioxide (CVRCO2) are established risk factors for stroke that respond favorably to aerobic training. The present study examined to what extent cerebral hemodynamics are improved when training is sustained throughout the adult lifespan. METHODS: Eighty-one healthy males were prospectively assigned to 1 of 4 groups based on their age (young, ≤30 years versus old, ≥60 years) and lifetime physical activity levels (trained, ≥150 minutes recreational aerobic activity/week versus sedentary, no activity). Middle cerebral artery blood velocity (MCAv, transcranial Doppler ultrasound), mean arterial pressure (MAP, finger photoplethysmography), and end-tidal partial pressure of carbon dioxide (PETCO2, capnography) were recorded during normocapnia and 3 mins of iso-oxic hypercapnea (5% CO2). Cerebrovascular resistance/conductance indices (CVRi/CVCi) were calculated as MAP/MCAv and MCAv/MAP, respectively, and CVRCO2 as the percentage increase in MCAv from baseline per millimeter of mercury (mm Hg) increase in PETCO2. Maximal oxygen consumption ( O2MAX, online respiratory gas analysis) was determined during cycling ergometry. RESULTS: By design, older participants were active for longer (49±5 versus 6±4 years, P<0.05). Physical activity attenuated the age-related declines in O2MAX, MCAv, CVCi, and CVRCO2 and increase in CVRi (P<0.05 versus sedentary). Linear relationships were observed between O2MAX and both MCAv and CVRCO2 (r=0.58-0.77, P<0.05). CONCLUSIONS: These findings highlight the importance of maintaining aerobic fitness throughout the lifespan given its capacity to improve cerebral hemodynamics in later-life.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".