Isometric handgrip training does not improve flow-mediated dilation in subjects with normal blood pressure
Bibliographic record
Abstract
Isometric HG (handgrip) training lowers resting arterial BP (blood pressure), yet the mechanisms are elusive. In the present study, we investigated improved systemic endothelial function as a mechanism of arterial BP modification following isometric HG training in normotensive individuals. This study employed a within-subject repeated measures design primarily to assess improvements in BA FMD (brachial artery flow-mediated dilation; an index of endothelium-dependent vasodilation), with the non-exercising limb acting as an internal control. Eleven subjects performed four 2-min unilateral isometric HG contractions at 30% of maximal effort, three times per week for 8 weeks. Pre-, mid- and post-training resting ABP and BA FMD (exercised arm and non-exercised arm) were measured via automated brachial oscillometry and ultrasound respectively. BA FMD (normalized to the peak shear rate experienced in response to the reactive hyperaemic stimulus) remained unchanged [exercised arm, 0.029+/-0.003 to 0.026+/-0.003 to 0.029+/-0.004%/s(-1) (pre- to mid- to post-training respectively); non-exercised arm, 0.023+/-0.003 to 0.023+/-0.003 to 0.024+/-0.003%/s(-1) (pre- to mid- to post-training respectively); P=0.22]. In conclusion, improved systemic endothelial function is unlikely to be responsible for lowering arterial BP in this population.
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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) | 0.001 | 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".