Multiple Hypoxia-Independent Triggers of Upper Airway Long-Term Facilitation
Bibliographic record
Abstract
Abstract The respiratory control system can augment respiratory output following repetitive challenges. For example, repeated airway obstructions can trigger a form of respiratory memory that strengthens inspiratory activity of hypoglossal (XII) motoneurons. This augmentation in respiratory motor output is known as long-term facilitation (LTF) and can be elicited by repeated apneas or bouts of hypoxia. We demonstrate that LTF can be triggered in the absence of repeated apneas or hypoxia by intermittently stimulating locus coeruleus (LC) neurons, or through pharmacological activation of the neurotrophic machinery in XII motoneurons. We used pharmacological and optogenetic approaches to elicit LTF and show that this is mediated by α1-adrenergic receptor-binding at the XII motor pool. We also use optical LC inhibition to reaffirm the importance of the LC in mediating apnea-induced LTF. Lastly, we show that neurotrophic signaling agonists or antagonists applied to XII motoneurons can also be used to elicit or prevent LTF expression, respectively, and acts co-operatively with noradrenaline. These results suggest LTF can be triggered by multiple hypoxia-independent triggers and is mediated by the release of noradrenaline from the LC onto α1-adrenergic receptors on XII motoneurons to trigger plasticity via activation of neurotrophic signaling cascades.
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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) | 0.014 | 0.002 |
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".