The Role of Oxidative Stress in Huntington’s Disease: Are Antioxidants Good Therapeutic Candidates?
Bibliographic record
Abstract
Huntington's disease (HD) is the most common polyglutamine neurodegenerative disorder in humans, and is caused by a mutation of an unstable expansion of CAG repeats within the coding region of the HD gene, which expresses the protein huntingtin. Although abnormal protein is ubiquitously expressed throughout the organism, cell degeneration occurs mainly in the brain, and there, predominantly in the striatum and cortex. The mechanisms that account for this selective neuronal death are multifaceted in nature and several lines of evidence suggest that mitochondrial dysfunction, overproduction of reactive oxygen species (ROS) and oxidative stress (an imbalance between pro-oxidant and antioxidant systems resulting in oxidative damage to proteins, lipids and DNA) might play important roles. Over time, this can result in the death of the affected neuronal populations. In this review article we present an overview of the preclinical and clinical studies that have indicated a link between oxidative stress, neurodegeneration, and cell death in HD. We also discuss how changes in ROS production affect neuronal survival, highlighting the evidence for the use of antioxidants including essential fatty acids, coenzyme Q10, and creatine, as potential therapeutic strategies for the treatment of this devastating neurodegenerative disorder.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".