SHIP Represses Th2 Skewing by Inhibiting IL-4 Production from Basophils
Bibliographic record
Abstract
We report that SHIP(-/-) mice, compared to SHIP(+/+) mice, are Th2 skewed with elevated serum IgE and twice as many splenic CD4(+) Th2 cells that, when stimulated with anti-CD3, produce more IL-4 and less IFN-γ. Exploring the reason for this Th2 skewing, we found that freshly isolated SHIP(-/-) splenic and bone marrow basophils are present in elevated numbers and secrete far more IL-4 in response to IL-3 or to FcεRI stimulation than do WT basophils. These SHIP(-/-) basophils markedly skew wild-type macrophage colony stimulating factor-derived macrophages toward an M2 phenotype, stimulate OT-II CD4(+) Th cells to differentiate into Th2 cells, and trigger SHIP(+/+) B cells to become IgE-producing cells. All these effects are completely abrogated with neutralizing anti-IL-4 Ab. Exploring the cell signaling pathways responsible for hyperproduction of IL-4 by SHIP(-/-) basophils, we found that IL-3-induced activation of the PI3K pathway is significantly enhanced and that PI3K inhibitors, especially a p110α inhibitor, dramatically suppresses IL-4 production from these cells. In vivo studies, in which basophils were depleted from mast cell-deficient SHIP(+/+) and SHIP(-/-) mice, confirmed the central role that basophils play in the Th2 skewing of naive SHIP-deficient mice. Taken together, these studies demonstrate that SHIP is a potent negative regulator of IL-4 production from basophils and thus may be a novel therapeutic target for Th1- and Th2-related diseases.
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 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) | 0.000 | 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 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".