A role for mast cells in EAE: W/Wv, Wsh, and CD34−/− mice are fully susceptible to disease induction using standard protocols (B92)
Bibliographic record
Abstract
Abstract EAE is a murine model of multiple sclerosis involving destruction of myelin by the immune system. Mast cells, known for a role in asthma and allergy, are reportedly required for EAE induction in mice. Our lab has reported that mature mast cells express the surface marker CD34. To further understand the role of mast cells in EAE, we utilized CD34−/− mice which have functional mast cells in the tissues, but are defective in their mobilization. We asked whether mast cells seeded in development were sufficient for EAE induction. Previous studies of mast cells in EAE used W/Wv mice, where reconstitution with WT-mast cells restored susceptibility to EAE. It was possible that CD34−/− mice were protected from EAE due to the decreased peripheral mobility of mast cells, or, seeding of CNS- or vascular-localized mast cells during development could be sufficient for their function. Here we compare clinical disease in WT, CD34−/−, W/Wv, and Wsh mice. We find CD34−/− mice are susceptible to induction of EAE, consistent with suggestions that mast cells act remotely in this model. Surprisingly, however, we also find both W/Wv and Wsh mice susceptible to disease in our hands. This result was confirmed by other laboratories. Interestingly, analysis of infiltrating leukocytes in the CD34−/− CNS shows increased mast cells vs. WT. We are now investigating whether inflammatory factors have bypassed the requirement for cKit on mast cells in 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".