Folic Acid Prevents Nitroglycerin-Induced Nitric Oxide Synthase Dysfunction and Nitrate Tolerance
Bibliographic record
Abstract
BACKGROUND: In healthy humans, continuous treatment with nitroglycerin (GTN) causes nitric oxide synthase dysfunction, probably through the reduced bioavailability of tetrahydrobiopterin. Recent studies proposed that folic acid is involved in the regeneration of tetrahydrobiopterin in different disease states. Therefore, we investigated whether folic acid administration would prevent this phenomenon. We also sought to determine if folic acid supplementation could prevent the development of tolerance to GTN. METHODS AND RESULTS: On the first visit, 18 healthy male volunteers (aged 19 to 32 years) were randomized to receive either oral folic acid (10 mg once a day) or placebo for 1 week in a double-blind designed study. All subjects also received continuous transdermal GTN (0.6 mg/h). On the second visit, forearm blood flow was measured with venous occlusion strain gauge plethysmography in response to incremental infusions of acetylcholine (7.5, 15, and 30 microgram/min), N-monomethyl-L-arginine (1, 2, and 4 micromol/min), and GTN (11 and 22 nmol/min). Folic acid prevented GTN-induced endothelial dysfunction, as assessed by responses to intraarterial acetylcholine and N-monomethyl-L-arginine (P<0.01). Moreover, in the subjects treated with folic acid plus transdermal GTN, responses to intraarterial GTN were significantly greater than those observed after transdermal GTN plus placebo (P<0.05). CONCLUSION: Our data demonstrate that supplemental folic acid prevents both nitric oxide synthase dysfunction induced by continuous GTN and nitrate tolerance in the arterial circulation of healthy volunteers. We hypothesize that the reduced bioavailability of tetrahydrobiopterin is involved in the pathogenesis of both phenomena. Our results confirm the view that oxidative stress contributes to nitrate tolerance.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".