Greater cardiorespiratory fitness is associated with higher cerebral blood flow and lower oxygen extraction fraction in healthy older adults
Bibliographic record
Abstract
Abstract Aerobic exercise training promotes cardiovascular, brain and cognitive health. Regular exercise is associated with higher cardiorespiratory fitness, commonly assessed by peak oxygen uptake (VO 2peak ) during maximal effort testing. Higher cardiorespiratory fitness has been linked to preserved brain health, particularly higher grey matter volume and perfusion. The brain relies heavily on oxidative metabolism, yet the relationship between cardiorespiratory fitness and brain oxidative metabolism remains underexplored. This study investigated the association between VO 2peak and two key cerebral metabolic parameters: the cerebral metabolic rate of oxygen consumption (CMRO 2 ) and oxygen extraction fraction (OEF), which represents the balance between cerebral blood flow (CBF) and CMRO 2 . Thirty-seven healthy adults aged ≥50 underwent maximal cardiopulmonary exercise testing for VO 2peak assessment. Neuroimaging included dual calibrated functional MRI (dc-fMRI) and quantitative susceptibility mapping (QSM). Higher VO 2peak correlated positively with higher CBF across whole-brain grey matter but showed no relationship with CMRO 2 . Conversely, higher VO 2peak negatively correlated with lower OEF from both dc-fMRI and QSM. These findings suggest that greater cardiorespiratory fitness enhances cerebral perfusion without changing resting metabolic rate in healthy older adults, resulting in a reduced oxygen extraction. These results are consistent with exercise yielding improved vascular– metabolic coupling, which would reduce the likelihood of transient hypoxic episodes.
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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 | 0.001 |
| 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".