The Role of Lifelong Physical Activity on Cardiovascular Function
Bibliographic record
Abstract
Introduction Ageing is associated with vascular dysfunction and a reduced capacity of the central circulation to deliver O 2 to the contracting muscles. The purpose of present study was to investigate the role of lifelong physical activity level on vascular function and hemodynamics during whole‐body exercise. Methods Vascular function was determined by femoral arterial Ach infusion (10, 25 and 100 μg/min/kg leg mass) and central (ICG) and limb (thermodilution) hemodynamics were measured during incremental cycling to exhaustion with and without simultaneous arm cycling (50w) were determined in 9 young (Y) (23±1 years; mean±SEM), 9 lifelong sedentary elderly (SE) (66±2 years), 8 lifelong moderately‐active elderly (MAE) (64±2 years) and 8 lifelong very active elderly (VAE) (65±2 years) men. Data was analyzed with one‐way repeated measure ANOVA (within groups) and two‐way ANOVA (between groups). Results The vasodilatory response to ACh was lowest in the SE, higher in MAE and VAE ( P < 0.05) and highest in the Y ( P < 0.05). During incremental cycling, peak workload was higher in the VAE (313±10 W) and MAE (274±14 W) compared to Y and SE (247±13; 191±3 W; P< 0.05). Leg blood flow (LBF) increased similarly in VAE, MAE and SE, but peak values were higher in VAE, MAE and Y compared to SE (7.8±0.5; 7.9±0.9; 8.6±0.4 vs. 6.4±0.4 L/min; P <0.05). Leg a‐vO 2 difference was higher in VAE and MAE compared to the Y and SE at all workloads ( P <0.05), whereas leg VO 2 was higher in VAE, MAE and Y compared to SE at exhaustion ( P< 0.05). During combined arm and leg cycling LBF, leg a‐vO 2 difference and VO 2 was lower in Y and SE compared to leg cycling alone ( P< 0.05). Mean arterial pressure increased in all groups, but was lower in Y ( P <0.05). Conclusions These results demonstrate that lifelong moderate physical activity can maintain aerobic power despite a lower vascular function and exercise hyperemia by an increase in O 2 extraction.
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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) | 0.002 | 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".