Endogenous Glutamatergic Control of Rhythmically Active Mammalian Respiratory Motoneurons In Vivo
Bibliographic record
Abstract
The transmission of rhythmic drive to respiratory motoneurons in vitro is critically dependent on glutamate acting primarily on non-NMDA receptors. We determined whether both non-NMDA and NMDA receptors contribute to respiratory drive transmission at respiratory motoneurons in the intact organism, both in the state of anesthesia and in the same animals during natural behaviors. Twenty-seven rats were implanted with electroencephalogram and neck electrodes to record sleep-wake states and genioglossus and diaphragm electrodes for respiratory muscle recordings. Microdialysis probes were inserted into the hypoglossal motor nucleus (HMN). Under anesthesia, non-NMDA or NMDA receptor antagonism significantly decreased respiratory-related genioglossus activity, indicating a contribution of each receptor to respiratory drive transmission at the HMN. However, despite the presence of respiratory-related genioglossus activity in the same rats across sleep-wake states, neither non-NMDA receptor antagonism at the HMN nor glutamate uptake inhibition had any effect on respiratory-related genioglossus activity. These results showed that, compared with anesthesia, respiratory drive transmission through the non-NMDA receptor is low in the behaving organism. In contrast, glutamate uptake inhibition increased tonic genioglossus activity in wakefulness and non-rapid-eye-movement sleep, indicating a functional endogenous glutamatergic modulation of tonic, but not respiratory, motor tone. Such an effect on tonic drive may contribute to the suppression of both tonic and respiratory-related genioglossus activity in wakefulness and sleep with NMDA receptor antagonism at the HMN. These data do not refute previous identification of a glutamatergic (mostly non-NMDA receptor activating) respiratory drive to hypoglossal motoneurons, but this mechanism is more prominent in anesthetized or in vitro preparations.
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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) | 0.000 | 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".