Mice Heterozygous for the Sodium Channel Scn8a (Nav1.6) Have Reduced Inflammatory Responses During EAE and Following LPS Challenge
Bibliographic record
Abstract
Voltage gated sodium (Nav) channels contribute to axonal damage following demyelination in experimental autoimmune encephalomyelitis (EAE), a rodent model of multiple sclerosis (MS). The Nav1.6 isoform has been implicated as a primary contributor in this process. However, the role of Nav1.6 in immune processes, critical to the pathology of both MS and EAE, has not been extensively studied. EAE was induced with myelin oligodendrocyte (MOG35-55) peptide inScn8admu/+mice, which have reduced Nav1.6 levels.Scn8admu/+mice demonstrated improved motor capacity during the recovery and early chronic phases of EAE relative to wild-type animals. In the optic nerve, myeloid cell infiltration and the effects of EAE on the axonal ultrastructure were also significantly reduced inScn8admu/+mice. Analysis of innate immune parameters revealed reduced plasma IL-6 levels and decreased percentages of Gr-1high/CD11b+and Gr-1int/CD11b+myeloid cells in the blood during the chronic phase of EAE inScn8admu/+mice. Elevated levels of the anti-inflammatory cytokines IL-10, IL-13, and TGF-β1 were also observed in the brains of untreatedScn8admu/+mice. A lipopolysaccharide (LPS) model was used to further evaluate inflammatory responses.Scn8admu/+mice displayed reduced inflammation in response to LPS challenge. To further evaluate if this was an immune cell-intrinsic difference or the result of changes in the immune or hormonal environment, mast cells were derived from the bone marrow ofScn8admu/+mice. These mast cells also produced lower levels of IL-6, in response to LPS, compared with those from wild type mice. Our results demonstrate that in addition to its recognized impact on axonal damage, Nav1.6 impacts multiple aspects of the innate inflammatory response.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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".