Cerebral blood flow and cerebrovascular reactivity are modified by maturational stage and exercise training status during youth
Bibliographic record
Abstract
Abstract Global cerebral blood flow (gCBF) and cerebrovascular reactivity to hypercapnia () are modulated by gonadal hormone activity, while insulin‐like growth factor 1 facilitates exercise‐mediated cerebral angiogenesis in adults. Whether critical periods of heightened hormonal and neural development during puberty represent an opportunity to further enhance gCBF and is currently unknown. Therefore, we used duplex ultrasound to assess gCBF and in n = 128 adolescents characterised as endurance‐exercise trained (males: n = 30, females: n = 36) or untrained (males: n = 29, females: n = 33). Participants were further categorised as pre‐ (males: n = 35, females: n = 33) or post‐ (males: n = 24, females: n = 36) peak height velocity (PHV) to determine pubertal or ‘maturity’ status. Three‐factor ANOVA was used to identify main and interaction effects of maturity status, biological sex and training status on gCBF and . Data are reported as group means (SD). Pre‐PHV youth demonstrated elevated gCBF and slower mean response times than post‐PHV counterparts (both: P ≤ 0.001). gCBF was only elevated in post‐PHV trained males when compared to untrained counterparts (634 (43) vs. 578 (46) ml min −1 ; P = 0.007). However, mean response time was faster in pre‐ (72 (20) vs. 95 (29) s; P ≤ 0.001), but not post‐PHV ( P = 0.721) trained youth when compared to untrained counterparts. Cardiorespiratory fitness was associated with gCBF in post‐PHV youth ( r 2 = 0.19; P ≤ 0.001) and mean response time in pre‐PHV youth ( r 2 = 0.13; P = 0.014). Higher cardiorespiratory fitness during adolescence can elevate gCBF while exercise training during childhood primes the development of cerebrovascular function, highlighting the importance of exercise training during the early stages of life in shaping the cerebrovascular phenotype.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".