MrgD Activation Inhibits KCNQ/M-Currents and Contributes to Enhanced Neuronal Excitability
Bibliographic record
Abstract
The recently identified Mas-related gene (Mrg) family of G-protein-coupled receptors is expressed almost exclusively in dorsal root ganglion (DRG) neurons. The expression of one family member, MrgD, is even further confined to IB4+, nonpeptidergic, small-diameter nociceptors. Although the functional consequences of MrgD activation are not known, this expression profile provides intriguing potential for a role in pain sensation or modulation. In a recombinant cell line, we first assessed the functional significance of MrgD activation by coexpressing MrgD with the KCNQ2/3 potassium channel, a channel implicated in pain. Whole-cell voltage-clamp recordings revealed that bath application of the ligand for MrgD, beta-alanine, resulted in robust inhibition of KCNQ2/3 activity. Pharmacological blockade of G(i/o) and phospholipase C signaling revealed a partial and complete block of the response, respectively. We extended these observations to dissociated DRG neuron cultures by examining MrgD modulation of M-currents (carried primarily by KCNQ2/3). Here too, beta-alanine-induced activation of endogenous MrgD inhibited M-currents, but primarily via a pertussis toxin-sensitive pathway. Finally, we assessed the consequence of beta-alanine-induced activation of MrgD in phasic neurons. Phasic neurons that fired a single action potential (AP) before beta-alanine application fired multiple APs during beta-alanine exposure. In sum, we provide evidence for a novel interaction between MrgD and KCNQ/M-type potassium channels that contributes to an increase in excitability of DRG neurons and thus may enhance the signaling of primary afferent nociceptive neurons.
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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 | 0.001 |
| 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".