Pentaerythrityl Tetranitrate and Nitroglycerin, but not Isosorbide Mononitrate, Prevent Endothelial Dysfunction Induced by Ischemia and Reperfusion
Bibliographic record
Abstract
BACKGROUND: Short term exposure to nitroglycerin (GTN) has protective properties that are similar to ischemic preconditioning. Whether other organic nitrates such as pentaerithrityl tetranitrate (PETN) and isosorbide mononitrate (ISMN) have similar protective effects has not been explored. METHODS AND RESULTS: In a randomized, parallel, double blind, controlled trial, 37 healthy young volunteers received no therapy (n=10), transdermal GTN 1.2 mg for 2 hours (n=9), PETN 80 mg (n=9), or ISMN 40 mg (n=9). Twenty-four hours later, endothelium-dependent flow-mediated vasodilation (FMD) was measured before and after local exposure to ischemia and reperfusion (IR). In the no therapy group, IR blunted FMD (FMD after IR: 1.9+/-0.6%, P<0.05), an effect that was prevented by GTN (FMD after IR: 5.3+/-1.4%, P<0.05 compared with no therapy). PETN had the same protective effect (FMD after IR: 8.1+/-1.3%, P<0.05 compared with no therapy), whereas ISMN had no significant pharmacological preconditioning effect (FMD after-IR: 3.6+/-0.8%, P=ns compared with no therapy). While it blocked the effect of GTN, Vitamin C (n=8) did not modify PETN preconditioning (FMD after IR: 6.3+/-0.9%, P=ns compared with before IR), showing that this phenomenon is not mediated by oxygen free radical production. In an effort to identify the mechanism of PETN preconditioning, isolated human endothelial cells were incubated with PETN, GTN, or ISMN. Only PETN induced expression of the genes encoding for heme oxygenase and ferritin, which have been involved in ischemic and pharmacological preconditioning. CONCLUSIONS: We show important differences among organic nitrates in their capacity to prevent IR-induced endothelial dysfunction. GTN and PETN, but not ISMN, have this preconditioning effect. The potential clinical implications of these data warrant further investigation.
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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 | 0.001 | 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) | 0.000 | 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".