Reactive oxygen species in vascular biology: role in arterial hypertension
Bibliographic record
Abstract
The cellular metabolism of oxygen generates potentially deleterious reactive oxygen species, including superoxide anion, hydrogen peroxide and hydroxyl radical. Under normal physiologic conditions, the rate and magnitude of oxidant formation is balanced by the rate of oxidant elimination. However, an imbalance between pro-oxidants and antioxidants results in oxidative stress, which is the pathogenic outcome of the overproduction of oxidants that overwhelms the cellular antioxidant capacity. There is growing evidence that increased oxidative stress and associated oxidative damage are mediators of vascular injury in cardiovascular pathologies, including hypertension, atherosclerosis and ischemia-reperfusion. This development has evoked considerable interest because of the possibilities that therapies targeted against reactive oxygen intermediates by decreasing the generation of reactive oxygen species and/or by increasing availability of antioxidants may be useful in minimizing vascular injury. This review focuses on the vascular actions of reactive oxygen species, the role of oxidative stress in vascular damage in hypertension and the therapeutic potential of modulating oxygen radical bioavailability in hypertension. In particular, the following topics will be highlighted: chemistry and sources of reactive oxygen species, antioxidant defense mechanisms, signaling events mediated by reactive oxygen species, role of reactive oxygen species in hypertension and the putative therapeutic role of antioxidants in cardiovascular disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".