The Effect of a Neuronal Nitric Oxide Synthase Inhibitor on Neurovascular Regulation in Humans
Bibliographic record
Abstract
Background: Neurovascular coupling (NVC) is a key process in cerebral blood flow regulation. NVC ensures adequate brain perfusion to changes in local metabolic demands. Neuronal nitric oxide synthase (nNOS) is suspected to be involved in NVC; however, this has not been tested in humans. Our objective was to investigate the effects of nNOS inhibition on NVC in humans. Methods: We performed a 3-visit partially randomized, double-blinded, placebo-controlled, crossover study in 12 healthy subjects. On each visit, subjects received an intravenous infusion of either S-methyl-L-thiocitrulline (a selective nNOS-inhibitor), 0.9% saline (placebo control), or phenylephrine (pressor control). The NVC assessment involved eliciting posterior circulation hyperemia through visual stimulation while measuring posterior and middle cerebral arteries blood velocity. Results: nNOS inhibition blunted the rapidity of the NVC response versus pressor control, evidenced by a reduced initial rise in mean posterior cerebral artery velocity (−3.3% [−6.5, −0.01], P =0.049), and a reduced rate of increase (ie, acceleration) in posterior cerebral artery velocity (slope reduced −4.3% [−8.5, −0.1], P =0.045). The overall magnitude of posterior cerebral artery response relative to placebo control or pressor control was not affected. Changes in BP parameters were well-matched between the S-methyl-L-thiocitrulline and pressor control arms. Conclusions: Neuronal NOS plays a role in dynamic cerebral blood flow control in healthy adults, particularly the rapidity of the NVC response to visual stimulation. This work opens the way to further investigation of the role of nNOS in conditions of impaired NVC, potentially revealing a therapeutic target.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".