Infection with murine gamma herpesvirus 68 modifies experimental autoimmune encephalomyelitis (101.1)
Bibliographic record
Abstract
Abstract Recent findings have identified Epstein-Barr virus (EBV) as a putative environmental trigger of multiple sclerosis (MS) but the mechanisms by which this virus causes MS remains elusive. We used murine gamma herpesvirus 68 (MγHV), the murine homolog to EBV, to examine how MγHV infection could aid in the enhancement of an autoimmune reaction against the CNS. C57Bl/6 mice were infected with MγHV and five weeks later, when the virus is cleared and has established latency, EAE was induced. Mice previously infected with MγHV developed a more severe EAE course showing both signs of paralysis and other neurological symptoms such as ataxia. MγHV EAE mice had higher levels of IFN-γ and TNF-α in the serum when compared to EAE mice and showed pronounced CD4 and CD8 T cell infiltrations both in the spinal cord and the brain parenchyma. On the other hand, CD4 T cells were less prominent in the brain parenchyma of uninfected EAE mice and CD8 T cells were absent. CD4 and CD8 T cells isolated from the CNS of MγHV EAE mice produced higher levels of IFN-γ accompanied by IL-17 suppression, whereas CD4 T cells isolated from the CNS of EAE mice produced high levels of IL-17 and lower IFN-γ levels. The absence of IL-17 production in infected mice suggests that the disease might be triggered by different T cell subsets than typical EAE. In conclusion, the ability of MγHV to elicit a more pathogenic T cell response could represent a new mechanism through which EBV triggers autoimmunity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".