Cytokines and normal sleep
Bibliographic record
Abstract
PURPOSE OF REVIEW: Cytokines are mediators of immune system responses with multiple biologic actions on several target tissues. Over the past two decades, research has explored the interactions between cytokines and sleep mechanisms of the brain. This short review highlights selected findings that have advanced our understanding of the relation between cytokines and sleep. RECENT FINDINGS: A complex network of cytokines and their receptors exists in brain. Cytokines may either promote or inhibit sleep. Of cytokines studied thus far, evidence indicates that interleukin-1 and tumor necrosis factor play a role in the regulation of non-rapid eye movement sleep. Their sites of action for regulating such sleep likely include the hypothalamic preoptic area and the basal forebrain. Mechanisms of action include direct receptor-mediated effects on neurons and the synthesis and release of numerous transmitters, peptides, and hormones that lead to subsequent changes in sleep. Among others, the cascade of responses induced by cytokines that may lead to subsequent alterations in sleep includes alterations in nitric oxide synthesis and effects on neurohormonal systems such as growth hormone releasing hormone. The activation by cytokines of the hypothalamic-pituitary-adrenal axis also influences sleep. Studies suggest that there is a significant overlap between neurohormonal systems such as the somatotropic and hypothalamic-pituitary-adrenal axes and cytokines, particularly with regard to their effects on sleep-wake regulation. SUMMARY: There is increasing evidence of a role for cytokines in regulating spontaneous non-rapid eye movement sleep. The somatotropic hormonal system and hypothalamic-pituitary-adrenal axis mediate, in part, the effects of cytokines on sleep.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".