Flow-mediated dilation in human brachial artery after different circulatory occlusion conditions
Bibliographic record
Abstract
Different magnitudes and durations of postocclusion reactive hyperemia were achieved by occluding different volumes of tissue with and without ischemic exercise to test the hypotheses that flow-mediated dilation (FMD) of the brachial artery would depend on the increase in peak flow rate or shear stress and that the position of the occlusion cuff would affect the response. The brachial artery FMD response was observed by high-frequency ultrasound imaging with curve fitting to minimize the effects of random measurement error in eight healthy, young, nonsmoking men. Reactive hyperemia was graded by 5-min occlusion distal to the measurement site at the wrist and the forearm and proximal to the site in the upper arm. Flow was further increased by exercise during occlusion at the wrist and forearm positions. For the two wrist occlusion conditions, flow increased eightfold and FMD was only 1 to 2% (P > 0.05). After the forearm and upper arm occlusions, blood flow was almost identical but FMD after forearm occlusions was 3.4% (P < 0.05), whereas it was significantly greater (6.6%, P < 0.05) and more prolonged after proximal occlusion. Forearm occlusion plus exercise caused a greater and more prolonged increase in blood flow, yet FMD (7.0%) was qualitatively and quantitatively similar to that after proximal occlusion. Overall, the magnitude of FMD was significantly correlated with peak forearm blood flow (r = 0.59, P < 0.001), peak shear rate (r = 0.49, P < 0.002), and total 5-min reactive hyperemia (r = 0.52, P < 0.001). The prolonged FMD after upper arm occlusion suggests that the mechanism for FMD differs with occlusion cuff position.
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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 | 0.001 |
| 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".