Murine gammaherpesvirus68 drives demyelination in a novel model of MS, cuprizone autoimmune encephalomyelitis which may better represent disease initiation 2065
Bibliographic record
Abstract
Abstract Description Multiple sclerosis (MS) is an autoimmune disease and among the leading causes of disability in young adults. A primary animal model for studying MS, experimental autoimmune encephalomyelitis (EAE), relies on exogenous antigen and induces severe ascending paralysis in a number days. EAE represents an “outside in” disease model. Since the exogenous antigen is delivered peripherally, cells active against antigen migrate into the CNS and induce primary myelin loss. Increasing data suggest that MS displays qualities of an “inside out” model of diease where primary loss of oligodendrocytes precedes demyelination. Previous research in our lab showed Th1 skewing and more severe EAE in mice with latent murine gamma herpesvirus 68 (gHV68) infection. gHV68 is a murine homologue of EBV. EBV is strongly associated with MS pathology (Bjornevik et al. 2022) Curpizone autoimmune encephalomyelitis (CAE) (Caprariello et al. 2018), is another model of MS. In CAE, cuprizone chow is fed to mice to induce oligodendrocyte death, followed by an immune boost, resulting in inflammatory demyelination. Cuprizone leads to accumulated citrullinated myelin which is also overrepresented in MS (maybe linked to smoking). CAE represents an “inside out” disease model. Our lab found that latent gHV68 also increases demyelination in CAE and skews immune response toward a TH1 phenotype. CAE with gHV68 may provide a more accurate MS model by mimicking environmental triggers and better representing disease initiation Funding Sources Andrew Nord fellowship, University of British Columbia Topic Categories Basic Autoimmunity (BA)
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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 | 0.002 |
| 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".