Plasticity of Vagal Origin: Identification and Characterization of a Novel Form of Neural Plasticity in Respiratory Motor Control
Bibliographic record
Abstract
In anesthetized, spontaneously breathing adult Sprague Dawley rats I examined the mechanisms by which repeated obstructive apneas trigger a novel form of upper airway respiratory motor plasticity. Based on four specific research aims, the following conclusions were reached: 1. Repeated obstructive apneas elicited plasticity of upper airway motor outflow that was measured as a long-term (> 1 hour) enhancement of inspiratory genioglossus (tongue) muscle tone. Diaphragm muscle activity that served as an index of spinal motor outflow remained unchanged. Airway occlusions triggered upper airway motor plasticity via repeated modulation of vagally-mediated feedback. This form of plasticity required α1-noradrenergic receptor activation at the hypoglossal motor pool. 2. α1-noradrenergic receptor activation at the hypoglossal motor pool was required for both initiation and maintenance (after apneas) of apnea-induced upper airway motor plasticity. 3. Activation of neurotrophin-mediated signalling was necessary for eliciting apnea-induced upper airway motor plasticity. In fact, activation of neurotrophin cellular machinery in hypoglossal motoneurons in turn was sufficient for triggering long-lasting enhancements of genioglossus muscle tone. In addition, neurotrophin-induced motor plasticity requires persistent noradrenergic neuromodulation because it was rapidly reversed by antagonism of α1-noradrenergic receptors at the hypoglossal motor pool. This finding indicates that there exists a cooperative “cross-talk” between neurotrophic and noradrenergic-mediated mechanisms and that the two act synergistically in the manifestation of apnea-induced respiratory motor plasticity. 4. Sleep loss as experienced in disease conditions such as obstructive sleep apnea mitigated the expression of apnea-induced respiratory motor plasticity.
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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 | 0.001 |
| 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".