Muscarinic‐2 and orexin‐2 receptors on GABAergic and other neurons in the rat mesopontine tegmentum and their potential role in sleep–wake state control
Bibliographic record
Abstract
Acetylcholine (ACh) plays an important role in the promotion of paradoxical sleep (PS) with muscle atonia through the muscarinic-2 receptor (M2R) in the mesopontine tegmentum. Conversely, orexin (Orx or hypocretin) appears to be critical for the maintenance of waking with muscle tone through the orexin-2 (or hypocretin-B) receptor (Orx2R), which is lacking in dogs having narcolepsy with cataplexy. In dual-immunostained material viewed under fluorescence microscopy, we examined the presence and distribution of M2R or Orx2R labeling on all neuronal nuclei (NeuN)-stained neurons or on glutamic acid decarboxylase (GAD)-stained neurons through the mesopontine tegmentum. Applying stereological analysis, we determined that many neurons bear M2Rs on their membrane ( approximately 6,300), including relatively large, non-GABAergic cells, which predominate (>75%) in the oral and caudal pontine (PnO and PnC) reticular fields, and small, GABAergic cells ( approximately 2,800), which predominate (>80%) in the mesencephalic (Mes) reticular formation. Many neurons bear Orx2Rs on their membrane ( approximately 6,800), including relatively large, non-GABAergic cells, which predominate (>70%) through all reticular fields, and comparatively few GABAergic cells ( approximately 700). In triple-immunostained material viewed by confocal microscopy, many large neurons in PnO and PnC appear to bear both M2Rs and Orx2Rs on their membrane, indicating that ACh and Orx could exert opposing influences of inhibition vs. excitation on putative reticulo-spinal neurons and thus attenuate vs. facilitate activity and muscle tone. A few GABAergic cells bear both receptors and could as PS inhibitor neurons serve under these different influences to control PS effector neurons and accordingly gate PS and muscle atonia appropriately across sleep-wake states.
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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 | 0.001 | 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".