Redox signaling, Nox5 and vascular remodeling in hypertension
Bibliographic record
Abstract
PURPOSE OF REVIEW: Extensive data indicate a role for reactive oxygen species (ROS) and redox signaling in vascular damage in hypertension. However, molecular mechanisms underlying these processes remain unclear, but oxidative post-translational modification of vascular proteins is critical. This review discusses how proteins are oxidatively modified and how redox signaling influences vascular smooth muscle cell growth and vascular remodeling in hypertension. We also highlight Nox5 as a novel vascular ROS-generating oxidase. RECENT FINDINGS: Oxidative stress in hypertension leads to oxidative imbalance that affects vascular cell function through redox signaling. Many Nox isoforms produce ROS in the vascular wall, and recent findings show that Nox5 may be important in humans. ROS regulate signaling by numerous processes including cysteine oxidative post-translational modification such as S-nitrosylation, S-glutathionylation and sulfydration. In vascular smooth muscle cells, this influences cellular responses to oxidative stimuli promoting changes from a contractile to a proliferative phenotype. SUMMARY: In hypertension, Nox-induced ROS production is increased, leading to perturbed redox signaling through oxidative modifications of vascular proteins. This influences mitogenic signaling and cell cycle regulation, leading to altered cell growth and vascular remodeling in hypertension.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".