Oxidative stress, Noxs, and hypertension: Experimental evidence and clinical controversies
Bibliographic record
Abstract
Reactive oxygen species (ROS) are signaling molecules that influence many physiological processes. Increased ROS bioavailability and altered redox signaling (oxidative stress) have been implicated in chronic diseases including hypertension. Although oxidative stress may not be the sole cause of hypertension, it amplifies blood pressure elevation in the presence of other prohypertensive factors (salt, renin-angiotensin system, sympathetic hyperactivity). A major source for cardiovascular ROS is a family of non-phagocytic NADPH oxidases (Nox1, Nox2, Nox4, Nox5). Other sources of ROS involve mitochondrial electron transport enzymes, xanthine oxidase, and uncoupled nitric oxide synthase. Although evidence from experimental and animal studies supports a role for oxidative stress in the pathogenesis of hypertension, there is still no convincing proof that oxidative stress is a cause of human hypertension. However, what is clear is that oxidative stress is important in the molecular mechanisms associated with cardiovascular and renal injury in hypertension and that hypertension itself can contribute to oxidative stress. The present review addresses the putative function of ROS in the pathogenesis of hypertension and focuses on the role of Noxs in ROS generation in vessels and the kidney. Implications of oxidative stress in human hypertension are discussed, and clinical uncertainties are highlighted.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".