Are the dynamic response characteristics of brachial artery flow-mediated dilation sensitive to the magnitude of increase in shear stimulus?
Bibliographic record
Abstract
The purpose of this study was to determine the dynamic characteristics of brachial artery dilation in response to step increases in shear stress [flow-mediated dilation (FMD)]. Brachial artery diameter (BAD) and mean blood velocity (MBV) (Doppler ultrasound) were obtained in 15 healthy subjects. Step increases in MBV at two shear stimulus magnitudes were investigated: large (L; maximal MBV attainable), and small (S; MBV at 50% of the large step). Increase in shear rate (estimate of shear stress: MBV/BAD) was 76.8 +/- 15.6 s(-1) for L and 41.4 +/- 8.7 s(-1) for S. The peak %FMD was 14.5 +/- 3.8% for L and 5.7 +/- 2.1% for S (P < 0.001). Both the L (all subjects) and the S step trials (12 of 15 subjects) elicited a biphasic diameter response with a fast initial phase (phase I) followed by a slower final phase. Relative contribution of phase I to total FMD when two phases occurred was not sensitive to shear rate magnitude (r(2) = 0.003, slope P = 0.775). Parameters quantifying the dynamics of the FMD response [time delay (TD), time constant (tau)] were also not sensitive to shear rate magnitude for both phases (phase I: TD r(2) = 0.03, slope P = 0.376, tau r(2) = 0.04, slope P = 0.261; final phase: TD r(2) = 0.07, slope P = 0.169, tau r(2) = 0.07, slope P = 0.996). These data support the existence of two distinct mechanisms, or sets of mechanisms, in the human conduit artery FMD response that are proportionally sensitive to shear stimulus magnitude and whose dynamic response is not sensitive to shear stimulus magnitude.
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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 | 0.001 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".