Differential pharmacological and sex-specific effects of antimuscarinic agents at the hypoglossal motor nucleus in vivo in rats
Bibliographic record
Abstract
Successful cholinergic-noradrenergic pharmacotherapy for obstructive sleep apnea (OSA) is thought to be due to effects at the hypoglossal motor nucleus (HMN). Clinical efficacy varies with muscarinic-receptor (MR) subtype affinities. We hypothesized that oxybutynin (cholinergic agent in successful OSA pharmacotherapy) is an effective MR antagonist at the HMN and characterized its efficacy with other antagonists. We recorded tongue muscle activity of isoflurane anesthetized rats (121 males and 60 females, 7-13 per group across 13 protocols) in response to HMN microperfusion with MR antagonists with and without: (i) eserine-induced increased endogenous acetylcholine at the HMN and (ii) muscarine. Eserine-induced increased acetylcholine decreased tongue motor activity (p < 0.001) with lesser cholinergic suppression in females versus males (p = 0.017). Motor suppression was significantly attenuated by the MR antagonists atropine, oxybutynin, and omadacycline (MR2 antagonist), each p < 0.001, with similar residual activity between agents (p ≥ 0.089) suggesting similar efficacy at the HMN. Sex differences remained with atropine and oxybutynin (p < 0.001 to 0.05) but not omadacycline (p = 0.722). Muscarine at the HMN also decreased motor activity (p < 0.001) but this was not sex-specific (p = 0.849). These findings have translational relevance to antimuscarinic agents in OSA pharmacotherapy and understanding potential sex differences in HMN suppression with increased endogenous acetylcholine related to sparing nicotinic excitation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".