Free radical biology of the cardiovascular system
Bibliographic record
Abstract
Most cardiovascular diseases (CVDs), as well as age-related cardiovascular alterations, are accompanied by increases in oxidative stress, usually due to increased generation and/or decreased metabolism of ROS (reactive oxygen species; for example superoxide radicals) and RNS (reactive nitrogen species; for example peroxynitrite). The superoxide anion is generated by several enzymatic reactions, including a variety of NADPH oxidases and uncoupled eNOS (endothelial NO synthase). To relieve the burden caused by this generation of free radicals, which also occurs as part of normal physiological processes, such as mitochondrial respiratory chain activity, mammalian systems have developed endogenous antioxidant enzymes. There is an increased usage of exogenous antioxidants such as vitamins C and E by many patients and the general public, ostensibly in an attempt to supplement intrinsic antioxidant activity. Unfortunately, the results of large-scale trails do not generate much enthusiasm for the continued use of antioxidants to mitigate free-radical-induced changes in the cardiovascular system. In the present paper, we review the clinical use of antioxidants by providing the rationale for their use and describe the outcomes of several large-scale trails that largely display negative outcomes. We also describe the emerging understanding of the detailed regulation of superoxide generation by an uncoupled eNOS and efforts to reverse eNOS uncoupling. SIRT1 (sirtuin 1), which regulates the expression and activity of multiple pro- and anti-oxidant enzymes, could be considered a candidate molecule for a 'molecular switch'.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".