Acute psychological and physical stress transiently enhances brachial artery flow-mediated dilation stimulated by exercise-induced increases in shear stress
Bibliographic record
Abstract
Exercise elevates conduit artery shear stress and stimulates flow-mediated dilation (FMD). However, little is known regarding the impact of acute psychological and physical stress on this response. The purpose of this study was to examine the impact of the Trier Social Stress Test (TSST (speech and arithmetic tasks)) and a cold pressor test (CPT) with and without social evaluation (SE) on exercise-induced brachial artery FMD (EX-FMD). A total of 59 healthy male subjects were randomly assigned to 1 of 3 conditions: TSST, CPT, or CPT with SE. During 6 min of handgrip exercise, brachial artery EX-FMD was assessed before and 15 and 35 min poststress with echo and Doppler ultrasound. Shear stress was estimated as shear rate, calculated as brachial artery mean blood velocity/brachial artery diameter. Results are means ± SD. All conditions elicited significant physiological stress responses. Salivary cortisol increased from 4.6 ± 2.4 nmol/L to 10.0 ± 5.0 nmol/L (p < 0.001; condition effect: p = 0.292). Mean arterial pressure increased from 98.6 ± 12.1 mm Hg to 131.9 ± 18.7 mm Hg (p < 0.001; condition effect: p = 0.664). Exercise shear rate did not differ between conditions (p = 0.592), although it was modestly lower poststress (prestress: 72.3 ± 4.5 s(-1); 15 min poststress: 70.8 ± 5.4 s(-1); 35 min poststress: 70.6 ± 6.1 s(-1); trial effect: p = 0.011). EX-FMD increased from prestress to 15 min poststress in all conditions (prestress: 6.2% ± 2.8%; 15 min poststress: 7.9% ± 3.2%; 35 min poststress: 6.6% ± 2.9%; trial effect: p < 0.001; condition effect: p = 0.611). In conclusion, all conditions elicited similar stress responses that transiently enhanced EX-FMD. This response may help to support muscle perfusion during stress.
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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) | 0.000 | 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) | 0.002 | 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".