Central and peripheral circadian clocks and their role in Alzheimer's disease
Bibliographic record
Abstract
Molecular and cellular oscillations constitute an internal clock that tracks the time of day and permits organisms to optimize their behaviour and metabolism to suit the daily demands they face. The workings of this internal clock become impaired with age. In this review, we discuss whether such age-related impairments in the circadian clock interact with age-related neurodegenerative disorders, such as Alzheimer's disease. Findings from mouse and fly models of Alzheimer's disease have accelerated our understanding of the interaction between neurodegeneration and circadian biology. These models show that neurodegeneration likely impairs circadian rhythms either by damaging the central clock or by blocking its communication with other brain areas and with peripheral tissues. The consequent sleep and metabolic deficits could enhance the susceptibility of the brain to further degenerative processes. Thus, circadian dysfunction might be both a cause and an effect of neurodegeneration. We also discuss the primary role of light in the entrainment of the central clock and describe important, alternative time signals, such as food, that play a role in entraining central and peripheral circadian clocks. Finally, we propose how these recent insights could inform efforts to develop novel therapeutic approaches to re-entrain arrhythmic individuals with neurodegenerative disease.
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".