Harmful and Beneficial Role of ROS
Bibliographic record
Abstract
Reactive oxygen species (ROS) are an unavoidable byproduct of oxygen metabolism and their cellular concentrations are determined by the balance between their rates of production and their rates of clearance by various antioxidant compounds and enzymes.For a long time ROS were thought to cause exclusively toxic effects which were associated with various pathologies, including carcinogenesis, neurodegeneration, atherosclerosis, diabetes, and aging.However, to date, it is known that while prolonged exposure to high ROS concentrations may lead to various disorders, low ROS concentrations exert beneficial effects regulating cell signaling cascades.The papers reported in this issue focus attention on some aspects of ROS biology including the impact of ROS production on various body districts and the defense arising from endogenous and exogenous antioxidants, beneficial effects of ROS production, and ROS regulation of signaling pathways.However, the examination of the manuscripts clearly shows that the passage of time has partly changed the approach to various topics.For example, although in some works different substances, including antioxidants, have yet been used, in other works different procedures and substances, including products or extracts, have been successfully used in the treatment of oxidative stress and related disorders due to the complex bioactive compounds they contain.Thus, A. V. Maksimenko studied the effects of intravenous injection of the superoxide dismutase-chondroitin sulfatecatalase (SOD-CHS-CAT) conjugate in a rat model of endotoxin shock.In this way he demonstrated the effectiveness of the conjugate in prevention and medication of oxidative stress damage, which is only partly due to prevention of NO conversion in peroxynitrite.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".