Nitric oxide, superoxide, and peroxynitrite in myocardial ischaemia‐reperfusion injury and preconditioning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There appears to be a controversy in the study of myocardial ischaemia-reperfusion injury and preconditioning whether nitric oxide (NO) plays a protective or detrimental role. A number of findings and the interpretation of the results to date do not support such a controversy. An understanding of the latest developments in NO, superoxide (O(2)(-)*) and peroxynitrite (ONOO(-)) biology, as well as the various ischaemic animal models utilized is necessary to resolve the apparent controversy. NO is an important cardioprotective molecule via its vasodilator, antioxidant, antiplatelet, and antineutrophil actions and it is essential for normal heart function. However, NO is detrimental if it combines with O(2)(-)* to form ONOO(-) which rapidly decomposes to highly reactive oxidant species. There is a critical balance between cellular concentrations of NO, O(2)(-)*, and superoxide dismutase which physiologically favour NO production but in pathological conditions such as ischaemia and reperfusion result in ONOO(-) formation. In contrast, exposure of the heart to brief episode(s) of ischaemia markedly enhances its ability to withstand a subsequent ischaemic injury. The triggering of this endogenous cardioprotective mechanism known as preconditioning requires both NO and O(2)(-)* synthesis. However, preconditioning in turn attenuates the overproduction of NO, O(2)(-)* and ONOO(-) during a subsequent episode of ischaemia and reperfusion, thereby protecting the heart. Here we review the roles of NO, O(2)(-)*, and ONOO(-) in both ischaemia-reperfusion injury and preconditioning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| 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 it