Nitrergic modulation of neuronal excitability in the mouse hippocampus is mediated via regulation of Kv2 and voltage‐gated sodium channels
Bibliographic record
Abstract
Regulation of neuronal activity is a necessity for communication and information transmission. Many regulatory processes which have been studied provide a complex picture of how neurons can respond to permanently changing functional requirements. One such activity-dependent mechanism involves signaling mediated by nitric oxide (NO). Within the brain, NO is generated in response to neuronal NO synthase (nNOS) activation but NO-dependent pathways regulating neuronal excitability in the hippocampus remain to be fully elucidated. This study was set out to systematically assess the effects of NO on ion channel activities and intrinsic excitabilities of pyramidal neurons within the CA1 region of the mouse hippocampus. We characterized whole-cell potassium and sodium currents, both involved in action potential (AP) shaping and propagation and determined NO-mediated changes in excitabilities and AP waveforms. Our data describe a novel signaling by which NO, in a cGMP-independent manner, suppresses voltage-gated Kv2 potassium and voltage-gated sodium channel activities, thereby widening AP waveforms and reducing depolarization-induced AP firing rates. Our data show that glutathione, which possesses denitrosylating activity, is sufficient to prevent the observed nitrergic effects on potassium and sodium channels, whereas inhibition of cGMP signaling is also sufficient to abolish NO modulation of sodium currents. We propose that NO suppresses both ion channel activities via redox signaling and that an additional cGMP-mediated component is required to exert effects on sodium currents. Both mechanisms result in a dampened excitability and firing ability providing new data on nitrergic activities in the context of activity-dependent regulation of neuronal function following nNOS activation.
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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) | 0.001 | 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".