Neurobiology of Sleep Disturbances in Neurodegenerative Disorders
Bibliographic record
Abstract
This review presents sleep disturbances and their underlying pathophysiology in three categories of neurodegenerative disorders namely tauopathies, synucleinopathies, and Huntington's disease (HD) and prion-related diseases. Sleep abnormalities are a major and early feature of neurodegenerative disorders, especially for synucleinopathies, HD and prion-related diseases, in which the sleep-related brainstem regions are severely altered and impaired sooner than in most of the tauopathies. In synucleinopathies, HD and prion-related diseases, specific sleep disturbances, different from those observed in tauopathies, are considered as core manifestations of the disease and in some cases, as preclinical signs. For this reason, the evaluation of sleep components in these neurodegenerative disorders may be useful to make a diagnosis and to assess the efficacy of pharmacotherapy. Since sleep disruption may occur early in the course of neurodegeneration, sleep disturbance may serve as groundwork to study the efficacy of neuroprotective agents to prevent or delay the development of a full-blown neurodegenerative disorder. The cause of sleep disturbances in neurodegenerative disorders may be attributed to several factors, including age-related modifications, symptoms of the disease, comorbid conditions and the neurodegenerative process itself.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".