Sodium nitroglycerin induces middle cerebral artery vasodilatation in young, healthy adults
Bibliographic record
Abstract
New Findings What is the central question of this study? Nitric oxide causes dilatation in peripheral vessels; however, whether nitric oxide affects basal cerebral artery dilatation has not been explored. What is the main finding and its importance? This study demonstrated that vasodilatation occurs in the right middle cerebral artery in response to exogenous nitric oxide. However, blood velocity decreased and, therefore, overall cerebral blood flow remained unchanged. This study provides new insight into the role of nitric oxide in cerebral blood flow control. Abstract Recent evidence indicates that basal cerebral conduit vessels dilate with hypercapnia, with a nitric oxide (NO) mechanism explaining one way in which parenchymal cerebral arterioles dilate. However, whether NO affects basal cerebral artery dilatation remains unknown. This study quantified the effect of an exogenous NO donor [sodium nitroglycerin (NTG); 0.4 mg sublingual spray] on the right middle cerebral artery (rMCA) cross‐sectional area (CSA), blood velocity and overall blood flow. Measures of vessel CSA (7 T magnetic resonance imaging) and MCA blood velocity (transcranial Doppler ultrasound) were made at baseline (BL) and after exogenous NTG or placebo (PLO) administration in young, healthy individuals ( n = 10, two males, age range 20–23 years). The CSA increased in the rMCA [BL, 5.2 ± 1.2 mm 2 ; PLO, 5.4 ± 1.5 mm 2 ; NTG, 6.6 ± 1.5 mm 2 , P < 0.05; mean ± SD]. Concurrently, rMCA blood velocity decreased from BL during NTG compared with PLO (BL, 67 ± 10 cm s −1 ; PLO, 62 ± 10 cm s −1 ; NTG, 59 ± 9.3 cm s −1 , P < 0.05; mean ± SD]. However, total MCA blood flow did not change with NTG or PLO [BL, 221 ± 37.4 ml min −1 ; PLO, 218 ± 35.0 ml min −1 ; NTG, 213 ± 46.4 ml min −1 ). Therefore, exogenous NO mediates a dilatory response in the rMCA, but not in its downstream vascular bed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".