Contribution of the respiratory network to rhythm and motor output revealed by modulation of GIRK channels, somatostatin and neurokinin-1 receptors
Bibliographic record
Abstract
Breathing is generated by a respiratory network in the brainstem. At its core, a population of neurons expressing neurokinin-1 receptors (NK1R) and the peptide somatostatin (SST) form the preBötzinger Complex (preBötC), a site essential for the generation of breathing. PreBötC interneurons generate rhythm and follower neurons shape motor outputs by activating upper airway respiratory muscles. Since NK1R-expressing preBötC neurons are preferentially inhibited by μ-opioid receptors via activation of GIRK channels, NK1R stimulation may also involve GIRK channels. Hence, we identify the contribution of GIRK channels to rhythm, motor output and respiratory modulation by NK1Rs and SST. In adult rats, GIRK channels were identified in NK1R-expressing preBötC cells. Their activation decreased breathing rate and genioglossus muscle activity, an important upper airway muscle. NK1R activation increased rhythmic breathing and genioglossus muscle activity in wild-type mice, but not in mice lacking GIRK2 subunits (GIRK2(-/-)). Conversely, SST decreased rhythmic breathing via SST2 receptors, reduced genioglossus muscle activity likely through SST4 receptors, but did not involve GIRK channels. In summary, NK1R stimulation of rhythm and motor output involved GIRK channels, whereas SST inhibited rhythm and motor output via two SST receptor subtypes, therefore revealing separate circuits mediating rhythm and motor output.
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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".