Therapeutic potential of melatonin and its analogs in Parkinson’s disease: focus on sleep and neuroprotection
Bibliographic record
Abstract
Sleep disorders constitute major nonmotor features of Parkinson's disease (PD) that have a substantial effect on patients' quality of life and can be related to the progression of the neurodegenerative disease. They can also serve as preclinical markers for PD, as it is the case for rapid eye movement (REM)-associated sleep behavior disorder (RBD). Although the etiology of sleep disorders in PD remains undefined, the assessment of the components of the circadian system, including melatonin secretion, could give therapeutically valuable insight on their pathophysiopathology. Melatonin is a regulator of the sleep/wake cycle and also acts as an effective antioxidant and mitochondrial function protector. A reduction in the expression of melatonin MT(1) and MT(2) receptors has been documented in the substantia nigra of PD patients. The efficacy of melatonin for preventing neuronal cell death and for ameliorating PD symptoms has been demonstrated in animal models of PD employing neurotoxins. A small number of controlled trials indicate that melatonin is useful in treating disturbed sleep in PD, in particular RBD. Whether melatonin and the recently developed melatonergic agents (ramelteon, tasimelteon, agomelatine) have therapeutic potential in PD is also discussed.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".