Nitric oxide activates hypoglossal motoneurons by cGMP‐dependent inhibition of TASK channels and cGMP‐independent activation of HCN channels
Bibliographic record
Abstract
Nitric oxide (NO) is an important signaling molecule; however mechanism(s) underlying NO modulation of motoneurons (MNs) remain obscure. Here, we used a combination of in vivo and in vitro recording techniques to examine NO modulation of MNs in the hypoglossal motor nucleus (HMN). Microperfusion of DEA (NO donor) into the HMN of anesthetized adult rats increased genioglossus muscle activity. In the brain slice, whole‐cell current‐clamp recordings from hypoglossal MNs show that exposure to DEA depolarized membrane potential and increased responsiveness to depolarizing current injections. Under voltage‐clamp conditions, we found that NO inhibited a Ba 2+ ‐sensitive background K + conductance and activated a Cs + ‐sensitive hyperpolarization‐activated inward current (Ih). The NO‐sensitive K + conductance exhibited properties similar to TWIK‐related acid‐sensitive K + (TASK) channels and was blocked by ODQ (soluble guanylyl cyclase antagonist) and KT5823 (PKG antagonist). In Ba 2+ , NO activated both the instantaneous (Iinst) and time‐dependent (Iss) components of Ih. Interestingly, at more hyperpolarized potentials NO preferentially increased Iinst, and this was retained in ODQ but blocked by a cysteine‐specific oxidant. These results suggest that NO activates hypoglossal MNs by cGMP‐dependent inhibition of a TASK‐like current and S‐nitrosylation‐ dependent activation of Ih.
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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".