IL-33–Stimulated Murine Mast Cells Polarize Alternatively Activated Macrophages, Which Suppress T Cells That Mediate Experimental Autoimmune Encephalomyelitis
Bibliographic record
Abstract
Abstract IL-33 is known to promote type 2 immune responses through ST2, a component of the IL-33R complex, expressed primarily on mast cells, Th2 cells, group 2 innate lymphoid cells and regulatory T cells, and to a lesser extent, on NK cells and Th1 cells. Consistent with previous studies, we found that IL-33 polarized alternatively activated macrophages (AAMΦ) in vivo. However, in vitro stimulation of murine bone marrow–derived or peritoneal macrophages with IL-33 failed to promote arginase activity or expression of YM-1 or Retnla, markers of AAMΦ. Furthermore, macrophages have low/no basal expression of ST2. This suggested that alternative activation of macrophages may involve an IL-33–responsive third-party cell. Because mast cells have the highest expression of ST2 relative to other leukocytes, we focused on this cell type. Coculture experiments showed that IL-33–stimulated mast cells polarized AAMΦ through production of soluble factors. IL-33–stimulated mast cells produced a range of cytokines, including IL-6 and IL-13. Mast cell–derived IL-13 was required for induction of AAMΦ, whereas mast cell–derived IL-6 enhanced macrophage responsiveness to IL-13 via upregulation of the IL-4Rα receptor. Furthermore, we found that AAMΦ polarized by IL-33–stimulated mast cells could suppress proliferation and IL-17 and IFN-γ production by T cells. Finally, we show that AAMΦ polarized by IL-33–stimulated mast cells attenuated the encephalitogenic function of T cells in the experimental autoimmune encephalomyelitis model. Our findings reveal that IL-33 can promote immunosuppressive responses by polarizing AAMΦ via mast cell–derived IL-6 and IL-13.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".