Alzheimer's Disease: Focus on the Neuroprotective Role of Melatonin
Bibliographic record
Abstract
Alzheimer’s disease (AD) is characterized by a progressive loss of memory and cognitive function, and by behavioural and sleep disturbances, including insomnia. The pathophysiology of AD has been attributed to oxidative stress-induced amyloid- β protein (A β ) deposition. Abnormal tau protein, mitochondrial dysfunction and protein hyper-phosphorylation have been demonstrated in neural tissues of AD patients. AD patients exhibit severe sleep-wake disturbances and these sleep disturbances are associated with rapid cognitive decline and memory impairment. Optimally effective management of AD patients will likely require a drug that can arrest A β - induced neurotoxic effects and can also restore the disturbed sleep-wake rhythm, with improvement in sleep quality. In this context, the pineal hormone melatonin has been demonstrated to be an effective antioxidant that can prevent A β - induced neurotoxic effects through a variety of mechanisms. Sleep deprivation itself produces many effects including oxidative damage, impaired mitochondrial function, neurodegenerative inflammation, altered proteosomal processing and abnormal activation of enzymes. In addition to treating the signs and symptoms of AD, treatment of sleep disturbances may also be necessary for preventing and arresting AD progression. Besides melatonin, a number of melatonergic agonists such as ramelteon, agomelatine and tasimelteon are now used clinically for treating insomnia and other sleep disorders. Their use may also be beneficial in treating Alzheimer’s disease. doi:10.4021/jnr93w
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".