Dissecting the role of sodium currents in visceral sensory neurons in a model of chronic hyperexcitability using Na<sub>v</sub>1.8 and Na<sub>v</sub>1.9 null mice
Bibliographic record
Abstract
Tetrodotoxin-resistant (TTX-R) sodium currents have been proposed to underlie sensory neuronal hyperexcitability in acute inflammatory models, but their role in chronic models is unknown. Since no pharmacological tools to separate TTX-R currents are available, this study employs Na(v)1.8 and Na(v)1.9 null mice to evaluate these currents roles in a chronic hyperexcitability model after the resolution of an inflammatory insult. Transient jejunitis was induced by infection with Nippostrongylus brasiliensis (Nb) in Na(v)1.9 and Na(v)1.8 null, wild-type and naïve mice. Retrogradely labelled dorsal root ganglia (DRG) neurons were harvested on day 20-24 post-infection for patch clamp recording. Rheobase and action potential (AP) parameters were recorded as measures of excitability, and Na(v)1.9 and Na(v)1.8 currents were recorded. DRG neuronal excitability was significantly increased in post-infected mice compared to sham animals, despite the absence of ongoing inflammation (sham = 1.9 +/- 0.3, infected = 3.6 +/- 0.7 APs at 2x rheobase, P = 0.02). Hyperexcitability was associated with a significantly increased amplitude of TTX-R currents. Hyperexcitability was maintained in Na(v)1.9(-/-) mice, but hyperexcitability was absent and APs were blunted in Na(v)1.8(-/-) mice. This study identifies a critical role for Na(v)1.8 in chronic post-infectious visceral hyperexcitability, with no contribution from Na(v)1.9. Nb infection-induced hyperexcitability is not observed in Na(v)1.8(-/-) mice, but is still present in Na(v)1.9(-/-) mice. It is not clear whether hyperexcitability is due to a change in the function of Na(v)1.8 channels or a change in the number of Na(v)1.8 channels.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".