Differential Expression of Sodium Channel β Subunits in Dorsal Root Ganglion Sensory Neurons
Bibliographic record
Abstract
The small-diameter (<25 μm) and large-diameter (>30 μm) sensory neurons of the dorsal root ganglion (DRG) express distinct combinations of tetrodotoxin sensitive and tetrodotoxin-resistant Na(+) channels that underlie the unique electrical properties of these neurons. In vivo, these Na(+) channels are formed as complexes of pore-forming α and auxiliary β subunits. The goal of this study was to investigate the expression of β subunits in DRG sensory neurons. Quantitative single-cell RT-PCR revealed that β subunit mRNA is differentially expressed in small (β(2) and β(3)) and large (β(1) and β(2)) DRG neurons. This raises the possibility that β subunit availability and Na(+) channel composition and functional regulation may differ in these subpopulations of sensory neurons. To further explore these possibilities, we quantitatively compared the mRNA expression of the β subunit with that of Na(v)1.7, a TTX-sensitive Na(+) channel widely expressed in both small and large DRG neurons. Na(v)1.7 and β subunit mRNAs were significantly correlated in small (β(2) and β(3)) and large (β(1) and β(2)) DRG neurons, indicating that these subunits are coexpressed in the same populations. Co-immunoprecipitation and immunocytochemistry indicated that Na(v)1.7 formed stable complexes with the β(1)-β(3) subunits in vivo and that Na(v)1.7 and β(3) co-localized within the plasma membranes of small DRG neurons. Heterologous expression studies showed that β(3) induced a hyperpolarizing shift in Na(v)1.7 activation, whereas β(1) produced a depolarizing shift in inactivation and faster recovery. The data indicate that β(3) and β(1) subunits are preferentially expressed in small and large DRG neurons, respectively, and that these auxiliary subunits differentially regulate the gating properties of Na(v)1.7 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".