Influence of Type I Interferons in Gammaherpesvirus-68 and Its Influence on EAE Enhancement
Bibliographic record
Abstract
Epstein-Barr virus (EBV) has been identified as a putative trigger of multiple sclerosis (MS). Previously, we reported that mice latently infected with murine gammaherpesvirus 68 (γHV-68), the murine homolog to EBV, and induced for experimental autoimmune encephalomyelitis (EAE), developed an enhanced disease more reminiscent of MS. These prior results showed that expression of CD40 on CD11b+CD11c+ cells in latently infected mice was required to prime the strong Th1 response driving disease as well as decreasing Treg frequencies in the periphery and CNS. Subsequent work demonstrated that transfer of B cells from latently infected mice was sufficient to enhance disease. Herein, we show that B cells from infected mice do not need type I IFN signaling to drive a strong Th1 response, yet are important in driving infiltration of the CNS by CD8+ T cells. Given the importance of type I IFNs in MS, we used IFNARko mice in order to determine if type I IFN signaling was important in the enhancement of EAE in latently infected mice. We found that while type I IFNs are important for the control of γHV-68 infection and maintenance of latency, they do not have a direct effect in the development of enhanced EAE.
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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".