Identification of the Mechanism Mediating Genioglossus Muscle Suppression in REM Sleep
Bibliographic record
Abstract
RATIONALE: Inhibition of pharyngeal motoneurons accompanies REM sleep and is a cause of hypoventilation and obstructive sleep apnea in humans. One explanation posits that the neurotransmitters glycine and γ-aminobutyric acid are responsible for REM sleep motor inhibition. However, blockade of that mechanism at cranial motor nuclei increases motor activity in all sleep-wake states, and least of all in REM sleep, arguing against it as a major mechanism of REM sleep pharyngeal motor inhibition. OBJECTIVES: To identify the mechanism of REM sleep inhibition at the hypoglossal motor pool. METHODS: Genioglossus and diaphragm activities were recorded in 34 rats across sleep-wake states. Microdialysis probes were implanted into the hypoglossal motor pool. MEASUREMENTS AND MAIN RESULTS: Here we show that muscarinic receptor antagonism at the hypoglossal motor pool prevents the inhibition of genioglossus activity throughout REM sleep; likewise, with G-protein-coupled inwardly rectifying potassium (GIRK) channel blockade. Importantly, the genioglossus activating effects of these interventions were largest in REM sleep and minimal or often absent in other sleep-wake states. Finally, we showed that muscarinic inhibition of the genioglossus is functionally linked to GIRK channel activation. CONCLUSIONS: We identify a powerful cholinergic-GIRK channel mechanism operating at the hypoglossal motor pool that has its largest inhibitory influence in REM sleep and minimal or no effects in other sleep-wake states. This mechanism is the major cause of REM sleep inhibition at a pharyngeal motor pool critical for effective breathing.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".