SHP2 protein-tyrosine phosphatase is a key regulator of mast cell signaling and development in mice (36.22)
Bibliographic record
Abstract
Abstract SH2 domain-containing phosphatase-2 (SHP2; also called PTPN11) is a positive effector of growth signaling pathways downstream of receptor tyrosine kinases and immune receptors. The development of conditional knockout mouse models for SHP2 has resulted in a better understanding of the role of SHP2 in adult tissues and cell types. In bone marrow-derived mast cells, recent studies have implicated SHP2 in functioning as a positive effector of growth signaling via Kit receptor tyrosine kinase, and TNFα production via the high affinity IgE receptor. In this study, we describe the use of transgenic mice expressing Cre recombinase in connective tissue mast cells (CTMCs) to generate a selective SHP2 knockout in CTMCs (MC-SHP2 KO). Compared to control mice lacking Cre, MC-SHP2 KO mice display a drastic reduction in mast cells within the peritoneum and skin. Previous studies have demonstrated the critical importance of Kit Y567 and Y719 signaling to Src family kinases/Gab2 and phosphatidylinositol 3’ kinase (PI3K) pathways for development of peritoneal and skin mast cells in mice. Thus, our results suggest that SHP2 plays a key role in signaling via the Src/Gab2/PI3K axis downstream of Kit during mast cell development in mice. In vitro differentiation assays for CTMCs are being investigated to further explore the molecular mechanisms by which SHP2 regulates mast cell development.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".