Bibliographic record
Abstract
Reactive oxygen species are constantly produced in aerobic organisms as by-products of normal oxygen metabolism and include free radicals such as superoxide anion (O2 (-)) and hydroxyl radical (OH(-)), and non-radical hydrogen peroxide (H2O2). The mitochondrial respiratory chain and enzymatic reactions by various enzymes are endogenous sources of reactive oxygen species. Exogenous reactive oxygen species -inducing stressors include ionizing radiation, ultraviolet light, and divergent oxidizing chemicals. At low concentrations, reactive oxygen species serve as an important second messenger in cell signaling; however, at higher concentrations and long-term exposure, reactive oxygen species can damage cellular macromolecules such as DNA, proteins, and lipids, which leads to necrotic and apoptotic cell death. Oxidative stress is a condition of imbalance between reactive oxygen species formation and cellular antioxidant capacity due to enhanced ROS generation and/or dysfunction of the antioxidant system. Biochemical alterations in these macromolecular components can lead to various pathological conditions and human diseases, especially neurodegenerative diseases. Neurodegenerative diseases are morphologically featured by progressive cell loss in specific vulnerable neuronal cells, often associated with cytoskeletal protein aggregates forming inclusions in neurons and/or glial cells. Deposition of abnormal aggregated proteins and disruption of metal ions homeostasis are highly associated with oxidative stress. The main aim of this review is to present as much detailed information as possible that is available on various neurodegenerative disorders and their connection with oxidative stress. A variety of therapeutic strategies designed to address these pathological processes are also described. For the future therapeutic direction, one specific pathway that involves the transcription factor nuclear factor erythroid 2-related factor 2 is receiving considerable attention.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".