Sex-specific effects of intensity and dose of physical activity on BOLD-fMRI cerebrovascular reactivity and cerebral pulsatility
Bibliographic record
Abstract
Cerebrovascular reactivity (CVR) and cerebral pulsatility (CP) are important indicators of cerebrovascular health and have been shown to be associated with physical activity (PA). Sex differences have been shown to influence the impact of PA on cerebrovascular health. However, the sex-specific effects of PA on CP and CVR, particularly in relation to intensity and dosage of PA, remains unknown. Thus, this cross-sectional study aimed to evaluate the sex-specific effects of different intensities and doses of PA on CVR and CP. The Human Connectome - Aging dataset was used, including 626 participants (350 females, 276 males) aged 36-85 (mean age: 58.8 ± 14.1 years). Females were stratified into premenopausal and postmenopausal groups to assess the potential influence of menopausal status. Novel tools based solely on resting state fMRI data were used to estimate both CVR and CP. The International Physical Activity Questionnaire was used to quantify weekly self-reported PA as metabolic equivalent of task. Results indicated that both sexes and menopausal subgroups revealed negative linear relationships between relative CVR and PA. Furthermore, females presented a unique non-linear relationship between relative CVR and total PA in the cerebral cortex. In females, there were also relationships with total and walking PA in occipital and cingulate regions. In males, we observed relationships between total or vigorous PA and CVR in parietal and cingulate regions. Sex-specific effects were also observed with CP, whereby females benefited across a greater number of regions and intensities than males, especially in the postmenopause group. Overall, males and females appear to benefit from different amounts and intensities of PA, with menopause status significantly influencing the effect of PA on cerebrovascular outcomes, underscoring the need for sex-specific recommendations in promoting cerebrovascular health.
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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 | 0.001 | 0.002 |
| 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".