Studies of Twin Responses to Understand Exercise THerapy (STRUETH): cerebrovascular function
Bibliographic record
Abstract
Abstract We studied monozygotic (MZ) and dizygotic (DZ) twin pairs following resistance (RES) and endurance (END) training to assess genetic and environmental contributions to cerebrovascular function. Cerebrovascular function (rest, autoregulation, hypercapnia, exercise) was assessed in 86 healthy same‐sex MZ (30 pairs) and DZ (13 pairs) twins, who underwent 3 months of END and RES. Carbon dioxide (), mean arterial pressure (MAP) and middle cerebral artery velocity (MCAv) were measured and MCAv resistance (MCACVRi) was calculated. Resting MCAv reduced by −2.8 cm/s following RES (P = 0.024), with no change following END (−0.3 cm/s, P = 0.758). Change in MCACVRi following RES was +0.11 mmHg/cm/s (P < 0.001), which was significantly greater than END (+0.02 mmHg/cm/s, P = 0.030). MAP also increased following RES (+4 mmHg, P = 0.010), but not END (+1 mmHg, P = 0.518). No changes were apparent in . At rest, positive response rates following RES ranged from 27 to 71% and from 40 to 64% following END. Intraclass correlations between twins were moderate for most variables at baseline. In response to training, only MZ pairs were significantly correlated for a change in MCAv (P = 0.005) and low frequency phase (P = 0.047) following RES.This study is the first to compare cerebrovascular function following RES and END in MZ and DZ twins. Most individuals who did not respond to one modality were able to respond by switching modality, and baseline heritability estimates were higher than training response. Exercise professionals should therefore consider modality and environmental factors when optimising interventions. Key points Characterising individual responses to resistance and endurance exercise training can inform optimal strategies for exercise prescription. This study utilised monozygotic and dizygotic twins in a randomised cross‐over study to determine individual responsiveness to different modalities of exercise training. The influence of environment vs. genetics on cerebrovascular responses to training was determined. It is apparent that individuals respond differently to distinct exercise stimuli and that switching modality may be a beneficial way to obtain positive responses in cerebrovascular function. This study has implications for improving individualised exercise prescription to maintain or improve cerebrovascular structure and function.
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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 | 0.003 |
| 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".