The Src-Like Adaptor Protein Regulates GM-CSFR Signaling and Monocytic Dendritic Cell Maturation
Bibliographic record
Abstract
GM-CSF is an important cytokine involved in myeloid differentiation and inflammatory processes. Signaling through the GM-CSFR also plays a critical role in the generation of monocyte-derived dendritic cells (DC). In this article, we report that the Src-like adaptor protein (SLAP) functions as a negative regulator of the GM-CSFR. In bone marrow-derived DC (BM-DC) lacking SLAP and the closely related SLAP2, downregulation of GM-CSFRβ is impaired, leading to enhanced phosphorylation of Jak2 and prolonged activation of Akt and Erk1/2 in response to GM-CSF stimulation. Compared with wild-type bone marrow, SLAP/SLAP2(-/-) bone marrow gave rise to similar numbers of CD11c(+) and CD11b(+) DC, but SLAP/SLAP2(-/-) BM-DC failed to acquire high levels of MHC class II, CD80, and CD86, indicating an impairment in maturation. Furthermore, MHC class II expression in SLAP/SLAP2(-/-) BM-DC was rescued by decreasing GM-CSF concentration, suggesting that enhanced GM-CSF signaling mediates the block in maturation. In addition, SLAP/SLAP2(-/-) BM-DC produced less IL-12 and TNF-α in response to LPS compared with controls and failed to stimulate T cells in an MLR. Ag-specific T cell activation assays showed that SLAP/SLAP2(-/-) BM-DC were less robust at inducing IFN-γ secretion by DO11.10 T cells. These results indicated that SLAP-mediated GM-CSFR regulation is important for the generation of functionally mature monocytic DC.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".