Nav1.6 promotes inflammation and neuronal degeneration in a mouse model of multiple sclerosis
Bibliographic record
Abstract
Abstract Background In multiple sclerosis (MS) and in the experimental autoimmune encephalomyelitis (EAE) model of MS, the Nav1.6 voltage-gated sodium (Nav) channel isoform has been implicated as a primary contributor to axonal degeneration. Following demyelination Nav1.6, which is normally co-localized with the Na+/Ca2+ exchanger (NCX) at the nodes of Ranvier, associates with β-APP, a marker of neural injury. The persistent influx of sodium through Nav1.6 is believed to reverse the function of NCX, resulting in an increased influx of damaging Ca2+ ions. However, direct evidence for the role of Nav1.6 in axonal degeneration is lacking. Methods In mice floxed for Scn8a, the gene that encodes the α subunit of Nav1.6, subjected to EAE we examined the effect of eliminating Nav1.6 from retinal ganglion cells (RGC) in one eye using an AAV vector harboring Cre and GFP, while using the contralateral either injected with AAV vector harboring GFP alone or non-targeted eye as control. Results In retinas, the expression of Rbpms, a marker for retinal ganglion cells, was found to be inversely correlated to the expression of Scn8a. Furthermore, the gene expression of the pro-inflammatory cytokines Il6 (IL-6) and Ifng (IFN-γ), and of the reactive gliosis marker Gfap (GFAP) were found to be reduced in targeted retinas. Optic nerves from targeted eyes were shown to have reduced macrophage infiltration and improved axonal health. Conclusion Taken together, our results are consistent with Nav1.6 promoting inflammation and contributing to axonal degeneration following demyelination.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".