Role of Oxidative Stress and Antioxidants in Neurodegenerative Diseases
Bibliographic record
Abstract
Neurodegenerative diseases (NDD) are a group of illness with diverse clinical importance and etiologies. NDD include motor neuron disease such as amyotrophic lateral sclerosis (ALS), cerebellar disorders, Parkinson's disease (PD), Huntington's disease (HD), cortical destructive Alzheimer's disease (AD) and Schizophrenia. Numerous epidemiological and experimental studies provide many risk factors such as advanced age, genetic defects, abnormalities of antioxidant enzymes, excitotoxicity, cytoskeletal abnormalities, autoimmunity, mineral deficiencies, oxidative stress, metabolic toxicity, hypertension and other vascular disorders. Growing body of evidence implicates free radical toxicity, radical induced mutations and oxidative enzyme impairment and mitochondrial dysfunction due to congenital genetic defects in clinical manifestations of NDD. Accumulation of oxidative damage in neurons either primarily or secondarily may account for the increased incidence of NDD such as AD, ALS and stroke in aged populations. The molecular mechanisms of neuronal degeneration remain largely unknown and effective therapies are not currently available. Recent interest has focused on antioxidants such as carotenoids and in particular lycopene, a potent antioxidant in tomatoes and tomato products, flavonoids and vitamins as potentially useful agents in the management of human NDD. The pathobiology of neurodegenerative disorders with emphasis on genetic origin and its correlation with oxidative stress of neurodegenerative disorders will be reviewed and the reasons as to why brain constitutes a vulnerable site of oxidative damage will be discussed. The article will also discuss the potential free radical scavenger, mechanism of antioxidant action of lycopene and the need for the use of antioxidants in the prevention of NDD.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".