Integration of DAG signaling systems mediated by PKC-dependent phosphorylation of RasGRP3
Bibliographic record
Abstract
Members of the RasGRP family of Ras activators have C1 domains that bind diacylglycerol (DAG) and DAG analogs such as the tumor-promoting phorbol esters. RasGRP members could be responsible for some of the DAG signaling processes that have previously been attributed to protein kinase C (PKC). We found that RasGRP3 is selectively expressed in B cells, suggesting that RasGRP3 might function downstream of the B-cell receptor (BCR). Indeed, stimulation of Ramos B cells with the DAG analog phorbol ester myristate (PMA) results in the association of RasGRP3 with the membrane fraction. However, we also made the unexpected observation that RasGRP3 is phosphorylated, coincident with Ras activation after stimulation. When inhibitors of PKC are present, Ras activation is attenuated, and this attenuation correlates with an inhibition of RasGRP3 phosphorylation. RasGRP3 is phosphorylated in vitro by PKC-theta and PKC-beta2. When ectopically coexpressed in HEK-293 cells, a dominant-activated mutant of PKC-theta phosphorylates RasGRP3 and enhances Ras-Erk signaling. These results provide the first indication for a functional interaction between a RasGRP family member and a dissimilar DAG binding protein. A convergent DAG signaling system could be important in fine-tuning Ras signaling during B-cell development or during the humoral immune response.
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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 | 0.001 |
| 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".