Impact of controlling shear rate on flow-mediated dilation responses in the brachial artery of humans
Bibliographic record
Abstract
The reactive hyperemia test (RHtest) evokes a transient increase in shear stress as a stimulus for endothelial-dependent flow-mediated vasodilation (EDFMD). We developed a noninvasive method to create controlled elevations in brachial artery (BA) shear rate (SR, estimate of shear stress), controlled hyperemia test (CHtest), and assessed the impact of this vs. the RHtest approach on EDFMD. Eight healthy subjects participated in two trials of each test on 3 separate days. For the CHtest, SR was step increased from 8 to 50 s(-1), created by controlled release of BA compression during forearm heating. For the RHtest, transient increases in SR were achieved after 5 min of forearm occlusion. BA diameter and blood flow velocity (ultrasound) were measured upstream of compression and occlusion sites. Both tests elicited significant dilation (RHtest: 6.33 +/- 3.12%; CHtest: 3.00 +/- 1.05%). The CHtest resulted in 1) reduced between-subject SR and EDFMD variability vs. the RHtest [SR coefficient of variation (CV): 4.9% vs. 36.6%; EDFMD CV: 36.16% vs. 51.80%] and 2) virtual elimination of the impact of BA diameter on the peak EDFMD response (peak EDFMD vs. baseline diameter for RHtest, r(2) = 0.64, P < 0.01, vs. CHtest, r(2) = 0.14, P < 0.01). Normalization of the RHtest EDFMD response to the magnitude of the SR stimulus eliminated test differences in between-subject response variability. Reductions in trial-to-trial and day-to-day SR variability with the CHtest did not reduce EDFMD variability. Between-subject SR variability contributes to EDFMD variability with the RHtest. SR controls with the CHtest or RHtest response normalization are essential for examining EDFMD between groups differing in baseline arterial diameter.
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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 | 0.002 | 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 | 0.001 | 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".