Latent virus infection upregulates CD40 expression facilitating enhanced autoimmunity in a model of multiple sclerosis
Bibliographic record
Abstract
Epstein-Barr virus (EBV) has been identified as a putative environmental trigger of multiple sclerosis (MS) by multiple groups working worldwide. Previously, we reported that when experimental autoimmune encephalomyelitis (EAE) was induced in mice latently infected with murine γ-herpesvirus 68 (γHV-68), the murine homolog to EBV, a disease more reminiscent of MS developed. Specifically, MS-like lesions developed in the brain that included equal numbers of IFN-γ producing CD4(+) and CD8(+) T cells and demyelination, none of which is observed in MOG induced EAE. Herein, we demonstrate that this enhanced disease was dependent on the γHV-68 latent life cycle and was associated with STAT1 and CD40 upregulation on uninfected dendritic cells. Importantly, we also show that, during viral latency, the frequency of regulatory T cells is reduced via a CD40 dependent mechanism and this contributes towards a strong T helper 1 response that resolves in severe EAE disease pathology. Latent γ-herpesvirus infection established a long-lasting impact that enhances subsequent adaptive autoimmune responses.
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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".