Combined whole-body vibration training and <scp>l</scp>-citrulline supplementation improves pressure wave reflection in obese postmenopausal women
Bibliographic record
Abstract
Postmenopausal women have increased wave reflection (augmentation pressure (AP) and index (AIx)) and reduced muscle function that predispose them to cardiac diseases and disability. Our aim was to examine the combined and independent effects of whole-body vibration training (WBVT) and l-citrulline supplementation on aortic hemodynamics and plasma nitric oxide metabolites (NOx) in postmenopausal women. Forty-one obese postmenopausal women were randomized to 3 groups: l-citrulline, WBVT+l-citrulline and WBVT+Placebo for 8 weeks. Brachial and aortic systolic blood pressure, diastolic blood pressure, AP, AIx, AIx adjusted to 75 beats/min (AIx@75), and NOx were measured before and after 8 weeks. All groups similarly decreased (P < 0.05) brachial and aortic pressures as well as AP, and similarly increased (P < 0.05) NOx levels. AIx and AIx@75 decreased (P < 0.01) in the WBVT+l-citrulline and WBVT+Placebo groups, but not in the l-citrulline group. The improvement in AIx@75 (-10.5% ± 8.8%, P < 0.05) in the WBVT+l-citrulline group was significant compared with the l-citrulline group. l-Citrulline supplementation and WBVT alone and combined decreased blood pressures. The combined intervention reduced AIx@75. This study supports the effectiveness of WBVT+l-citrulline as a potential intervention for prevention of hypertension-related cardiac diseases in obese postmenopausal women.
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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) | 0.001 | 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".