Towards improving the prognosis of stroke through targeting the circadian clock system
Bibliographic record
Abstract
Rhythmicity of the circadian system is a 24-hour period, driven by transcription-translation feedback loops of circadian clock genes. The central circadian pacemaker in mammals is located in the hypothalamic suprachiasmatic nucleus (SCN), which controls peripheral circadian clocks. In general, most physiological processes are regulated by the circadian system, which is modulated by environmental cues such as exposure to light and/or dark, temperature, and the timing of sleep/wake and food intake. The chronic circadian disruption caused by shift work, jetlag, and/or irregular sleep-wake cycles has long-term health consequences. Its dysregulation contributes to the risk of psychiatric disorders, sleep abnormalities, hypothyroidism and hyperthyroidism, cancer, and obesity. A number of neurological conditions may be worsened by changes in the circadian clock via the SCN pacemaker. For stroke, different physiological activities such as sleep/wake cycles are disrupted due to alterations in circadian rhythms. Moreover, the immunological processes that affect the evolution and recovery processes of stroke are regulated by the circadian clock or core-clock genes. Thus, disrupted circadian rhythms may increase the severity and consequences of stroke, while readjustment of circadian clock machinery may accelerate recovery from stroke. In this manuscript, we discuss the relationship between stroke and circadian rhythms, particularly on stroke development and its recovery process. We focus on immunological and/or molecular processes linking stroke and the circadian system and suggest the circadian rhythm as a target for designing effective therapeutic strategies in stroke.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".