Bibliographic record
Abstract
Increases in reactive oxygen species (ROS) and tissue evidence of oxidative injury are common in patients with inflammatory processes or tissue injury. This has led to many clinical attempts to scavenge ROS and reduce oxidative injury. However, we live in an oxygen rich environment and ROS and their chemical reactions are part of the basic chemical processes of normal metabolism. Accordingly, organisms have evolved sophisticated mechanisms to control these reactive molecules. Recently, it has become increasingly evident that ROS also play a role in the regulation of many intracellular signaling pathways that are important for normal cell growth and inflammatory responses that are essential for host defense. Thus, simply trying to scavenge ROS is likely not possible and potentially harmful. The 'normal' level of ROS will also likely vary in different tissues and even in different parts of cells. In this paper, the terminology and basic chemistry of reactive species are reviewed. Examples and mechanisms of tissue injury by ROS as well as their positive role as signaling molecules are discussed. Hopefully, a better understanding of the nature of ROS will lead to better planned therapeutic attempts to manipulate the concentrations of these important molecules. We need to regulate ROS, not eradicate them.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".