The relationship between shear stress and flow‐mediated dilatation: implications for the assessment of endothelial function
Bibliographic record
Abstract
Endothelium-dependent flow-mediated dilatation (FMD) describes the vasodilatory response of a vessel to elevations in blood flow-associated shear stress. Nitric oxide (NO), one of many vasoactive substances released by the endothelium in response to shear stress, is of particular interest to researchers as it is an antiatherogenic molecule, and a reduction in its bioavailability may play a role in the pathogenesis of vascular disease. The goal of many human studies is to create a shear stress stimulus that produces an NO-dependent response in order to use the FMD measurements as an assay of NO bioavailability. The most common non-invasive technique is the 'reactive hyperaemia test' which produces a large, transient shear stress profile and a corresponding FMD. Importantly, not all FMD is NO mediated and the stimulus creation technique is a critical determinant of NO dependence. The purpose of this review is to (1) explain that the mechanisms of FMD depend on the nature of the shear stress stimulus (stimulus response specificity), (2) provide an update to the current guidelines for FMD assessment, and (3) summarize the issues that surround the clinical utility of measuring both NO- and non-NO-mediated FMD. Future research should include (1) the identification and partitioning of mechanisms responsible for FMD in response to various shear stress profiles, (2) investigation of stimulus response specificity in coronary arteries, and (3) investigation of non-NO FMD mechanisms and their connection to the development of vascular disease and occurrence of cardiovascular events.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".