Dopaminergic Regulation of Sleep and Cataplexy in a Murine Model of Narcolepsy
Bibliographic record
Abstract
STUDY OBJECTIVES: To determine if the dopaminergic system modulates cataplexy, sleep attacks and sleep-wake behavior in narcoleptic mice. DESIGN: Hypocretin/orexin knockout (i.e., narcoleptic) and wild-type mice were administered amphetamine and specific dopamine receptor modulators to determine their effects on sleep, cataplexy and sleep attacks. PATIENTS OR PARTICIPANTS: Hypocretin knockout (n = 17) and wild-type mice (n = 21). INTERVENTIONS: Cataplexy, sleep attacks and sleep-wake behavior were identified using electroencephalogram, electromyogram and videography. These behaviors were monitored for 4 hours after an i.p. injection of saline, amphetamine and specific dopamine receptor modulators (D1- and D2-like receptor modulators). MEASUREMENTS AND RESULTS: Amphetamine (2 mg/kg), which increases brain dopamine levels, decreased sleep attacks and cataplexy by 61% and 67%, suggesting that dopamine transmission modulates such behaviors. Dopamine receptor modulation also had powerful effects on sleep attacks and cataplexy. Activation (SKF 38393; 20 mg/kg) and blockade (SCH 23390; 1 mg/kg) of D1-like receptors decreased and increased sleep attacks by 77% and 88%, without affecting cataplexy. Pharmacological activation of D2-like receptors (quinpirole; 0.5 mg/kg) increased cataplectic attacks by 172% and blockade of these receptors (eticlopride; 1 mg/kg) potently suppressed them by 97%. Manipulation of D2-like receptors did not affect sleep attacks. CONCLUSIONS: We show that the dopaminergic system plays a role in regulating both cataplexy and sleep attacks in narcoleptic mice. We found that cataplexy is modulated by a D2-like receptor mechanism, whereas dopamine modulates sleep attacks by a D1-like receptor mechanism. These results support a role for the dopamine system in regulating sleep attacks and cataplexy in a murine model of narcolepsy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".