Reactive Oxygen Species, Vascular Oxidative Stress, and Redox Signaling in Hypertension
Bibliographic record
Abstract
Metabolism of oxygen by cells generates potentially deleterious reactive oxygen species (ROS). Under normal conditions the rate and magnitude of oxidant formation is balanced by the rate of oxidant elimination. However, an imbalance between prooxidants and antioxidants results in oxidative stress, which is the pathogenic outcome of oxidant overproduction that overwhelms the cellular antioxidant capacity. The kidney and vasculature are rich sources of NADPH oxidase-derived ROS, which under pathological conditions play an important role in renal dysfunction and vascular damage. Strong experimental evidence indicates that increased oxidative stress and associated oxidative damage are mediators of renovascular injury in cardiovascular pathologies. Increased production of superoxide anion and hydrogen peroxide, reduced nitric oxide synthesis, and decreased bioavailability of antioxidants have been demonstrated in experimental and human hypertension. These findings have evoked considerable interest because of the possibilities that therapies targeted against free radicals by decreasing ROS generation or by increasing nitric oxide availability and antioxidants may be useful in minimizing vascular injury and renal dysfunction and thereby prevent or regress hypertensive end-organ damage. This article highlights current developments in the field of ROS and hypertension, focusing specifically on the role of oxidative stress in hypertension-associated vascular damage. In addition, recent clinical trials investigating cardiovascular benefits of antioxidants are discussed, and some explanations for the rather disappointing results from these studies are addressed. Finally, important avenues for future research in the field of ROS, oxidative stress, and redox signaling in hypertension are considered.
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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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".