Endogenous Excitatory Drive Modulating Respiratory Muscle Activity across Sleep–Wake States
Bibliographic record
Abstract
RATIONALE: The concept of a tonic drive activating respiratory muscle in wakefulness but not sleep has been an important and enduring notion in respiratory medicine, not least because it is useful in modeling sleep effects on breathing and understanding the pathogenesis of sleep-related breathing disorders such as obstructive sleep apnea. However, a neurotransmitter substrate mediating respiratory muscle activation across sleep-wake states has not been identified. OBJECTIVES: We determined if alpha1 receptor antagonism at the hypoglossal motor nucleus (HMN) decreases genioglossus (GG) activity consistent with a role for an endogenous noradrenergic drive contributing to GG activation across sleep-wake states. We also determined if alpha1 receptor stimulation could counteract reduced endogenous noradrenergic drive and increase sleeping GG activity. METHODS: Thirty-five rats were implanted with electroencephalogram and neck electrodes to record sleep-wake states and GG and diaphragm electrodes for respiratory muscle recordings. Microdialysis probes were inserted into the HMN. MEASUREMENTS AND MAIN RESULTS: Microdialysis perfusion of the alpha1 receptor antagonist terazosin into the HMN significantly decreased GG activity in wakefulness and nonrapid eye movement (non-REM) sleep but not REM sleep. The alpha1 receptor agonist phenylephrine increased GG activity in wakefulness and sleep, but periods of motor inactivity persisted in REM sleep; there was no potentiating effect of combined alpha1 and 5-HT2 receptor stimulation. CONCLUSIONS: Identification of an endogenous noradrenergic drive contributing to GG activation in wakefulness and non-REM sleep, but not REM sleep, is important given the prevalence and clinical significance of sleep-induced hypoventilation and obstructive sleep apnea in humans and the potential for pharmacologic treatment.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".