Endothelial function of young healthy males following whole body resistance training
Bibliographic record
Abstract
Given the increasing emphasis on performance of resistance exercise as an essential component of health, we evaluated, using a prospective longitudinal design, the potential for resistance training to affect arterial endothelial function. Twenty-eight men (23 +/- 3.9 yr old; mean +/- SE) engaged in 12 wk of whole body resistance training five times per week using a repeating split-body 3-day cycle. Brachial endothelial function was measured using occlusion cuff-induced flow-mediated dilation. After occlusion of the forearm for 4.5 min, brachial artery dilation and postocclusion blood flow was measured continuously for 15 and 70 s, respectively. Peak and 10-s postocclusion blood flow, shear rate, and brachial artery flow-mediated dilation (relative and normalized to shear rate) were measured pretraining (Pre), at 6 wk of training (Mid), and at 13 wk of training (Post). Results indicated an increase of mean brachial artery diameter by Mid and Post vs. Pre. Peak and 10-s postocclusion blood flow increased by Mid and remained elevated at Post; however, shear rates were not different at any time point. Relative and normalized flow-mediated dilation was also not different at any time point. This study is the first to show that peripheral arterial remodeling does occur with resistance training in healthy young men. In addition, the increase in postocclusion blood flow may indicate improved resistance vessel function. However, unlike studies involving endurance training, flow-mediated dilation did not increase with resistance training. Thus arterial adaptations with high-pressure loads, such as those experienced during resistance exercise, may be quite different compared with endurance training.
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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) | 0.000 | 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".