Protein Kinase C-δ Is a Negative Regulator of Antigen-Induced Mast Cell Degranulation
Bibliographic record
Abstract
Regulation of mast cell degranulation is dependent on the subtle interplay of cellular signaling proteins. The Src homology 2 (SH2) domain-containing inositol-5'-phosphatase (SHIP), which acts as the gatekeeper of degranulation, binds via both its SH2 domain and its phosphorylated NPXY motifs to the adapter protein Shc via the latter's phosphorylated tyrosines and phosphotyrosine-binding domain, respectively. This theoretically leaves Shc's SH2 domain available to bind proteins, which might be part of the SHIP/Shc complex. In a search for such proteins, protein kinase C-delta (PKC-delta) was found to coprecipitate in mast cells with Shc and to interact with Shc's SH2 domain following antigen or pervanadate stimulation. Phosphorylation of PKC-delta's Y(332), most likely by Lyn, was found to be responsible for PKC-delta's binding to Shc's SH2 domain. Using PKC-delta(-/-) bone marrow-derived mast cells (BMMCs), we found that the antigen-induced tyrosine phosphorylation of Shc was similar to that in wild-type (WT) BMMCs while that of SHIP was significantly increased. Moreover, increased translocation of PKC-delta to the membrane, as well as phosphorylation at T505, was observed in SHIP(-/-) BMMCs, demonstrating that while PKC-delta regulates SHIP phosphorylation, SHIP regulates PKC-delta localization and activation. Interestingly, stimulation of PKC-delta(-/-) BMMCs with suboptimal doses of antigen yielded a more sustained calcium mobilization and a significantly higher level of degranulation than that of WT cells. Altogether, our data suggest that PKC-delta is a negative regulator of antigen-induced mast cell degranulation.
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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 | 0.000 |
| 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 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".