Differential modulation of Na<sub>v</sub>1.7 and Na<sub>v</sub>1.8 peripheral nerve sodium channels by the local anesthetic lidocaine
Bibliographic record
Abstract
1 Voltage-gated Na+ channels are transmembrane proteins that are essential for the propagation of action potentials in excitable cells. Nav1.7 and Nav1.8 dorsal root ganglion Na+ channels exhibit different kinetics and sensitivities to tetrodotoxin (TTX). We investigated the properties of both channels in the presence of lidocaine, a local anesthetic (LA) and class I anti-arrhythmic drug. 2 Nav1.7 and Nav1.8 Na+ channels were coexpressed with the beta1-subunit in Xenopus oocytes. Na+ currents were recorded using the two-microelectrode voltage-clamp technique. 3 Dose-response curves for both channels had different EC50 (dose producing 50% maximum current inhibition) (450 microm for Nav1.7 and 104 microm for Nav1.8). Lidocaine enhanced current decrease in a frequency-dependent manner. Steady-state inactivation of both channels was also affected by lidocaine, Nav1.7 being the most sensitive. Only the steady-state activation of Nav1.8 was affected while the entry of both channels into slow inactivation was affected by lidocaine, Nav1.8 being affected to a larger degree. 4 Although the channels share homology at DIV S6, the LA binding site, they differ in their sensitivity to lidocaine. Recent studies suggest that other residues on DI and DII known to influence lidocaine binding may explain the differences in affinities between Nav1.7 and Nav1.8 Na+ channels. 5 Understanding the properties of these channels and their pharmacology is of critical importance to developing drugs and finding effective therapies to treat chronic pain.
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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 | 0.001 | 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".