A novel Na<sub>v</sub>1.7 mutation producing carbamazepine‐responsive erythromelalgia
Bibliographic record
Abstract
OBJECTIVE: Human and animal studies have shown that Na(v)1.7 sodium channels, which are preferentially expressed within nociceptors and sympathetic neurons, play a major role in inflammatory and neuropathic pain. Inherited erythromelalgia (IEM) has been linked to gain-of-function mutations of Na(v)1.7. We now report a novel mutation (V400M) in a three-generation Canadian family in which pain is relieved by carbamazepine (CBZ). METHODS: We extracted genomic DNA from blood samples of eight members of the family, and the sequence of SCN9A coding exons was compared with the reference Na(v)1.7 complementary DNA. Wild-type Na(v)1.7 and V400M cell lines were then analyzed using whole-cell patch-clamp recording for changes in activation, deactivation, steady-state inactivation, and ramp currents. RESULTS: Whole-cell patch-clamp studies of V400M demonstrate changes in activation, deactivation, steady-state inactivation, and ramp currents that can produce dorsal root ganglia neuron hyperexcitability that underlies pain in these patients. We show that CBZ, at concentrations in the human therapeutic range, normalizes the voltage dependence of activation and inactivation of this inherited erythromelalgia mutation in Na(v)1.7 but does not affect these parameters in wild-type Na(v)1.7. INTERPRETATION: Our results demonstrate a normalizing effect of CBZ on mutant Na(v)1.7 channels in this kindred with CBZ-responsive inherited erythromelalgia. The selective effect of CBZ on the mutant Na(v)1.7 channel appears to explain the ameliorative response to treatment in this kindred. Our results suggest that functional expression and pharmacological studies may provide mechanistic insights into hereditary painful disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".