Multiple Sclerosis-Like Symptoms in Mice Are Driven by Latent γHerpesvirus-68 Infected B Cells
Bibliographic record
Abstract
Multiple sclerosis (MS) is caused by a combination of genetic and environmental factors. It is believed that previous infection with Epstein Barr Virus (EBV) plays an important role in the development of MS. Previously, we developed a murine model where latent infection with gamma herpesvirus 68 (γHV-68), a murine homolog to EBV, enhanced the symptoms of experimental autoimmune encephalomyelitis (EAE), resulting in disease that more closely resembles MS in humans. Here, we explored the conditions that were necessary for EAE enhancement. We showed that latently infected CD19+IgD− B cells were capable of enhancing EAE symptoms when transferred from mice previously infected with γHV-68 into uninfected mice. We also observed a prevention of enhancement when B cells were depleted before infection. However, depletion after the establishment of latency only partially reduced EAE. This indicated the existence of a mechanism where B cells play an important role as antigen presenting cells (APCs) prior to EAE induction for the priming of Th1 cells. It is possible that these signals persist even after B cell depletion, strongly suggesting a paracrine signaling modulation of non-B cell APCs. These results strongly support the concept that EBV contributes to the development of autoimmunity and highlights the need for a vaccine against EBV that could limit or prevent multiple sclerosis development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.003 | 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".