Expression of a catalytically inactive form of diacylglycerol kinase α induces sustained signaling through RasGRP
Bibliographic record
Abstract
Regulating the generation and clearance of lipid second messengers, such as diacylglycerol (DAG), is critical for the correct propagation of intracellular signaling pathways. DAGK type alpha acts as a negative modulator of the DAG levels generated during T cell activation, which is initiated by triggering of the endogenous T cell receptor (TCR), as well as by stimulation of an ectopically expressed human muscarinic type 1 receptor. Here we show that stimulation of either of these receptors causes rapid, transient membrane translocation of the recently discovered Ras guanyl nucleotide release protein (RasGRP), followed by activation of mitogen-activated protein kinase (MAPK). When cells expressing a catalytically inactive form of DAGKalpha were analyzed, however, similar agonist stimulation resulted in sustained signaling through RasGRP and MAPK. Biochemical analysis showed that expression of kinase-dead diacylglycerol kinase a (DGKalpha) led to a greater, more sustained, DAG accumulation following receptor stimulation. These results suggest that, in T cells, agonist-stimulated DAG generation is the key factor controlling activation of the Ras/MAPK signaling pathway through membrane translocation of RasGRP. Moreover, we demonstrate that through the modulation of the intracellular level of agonist-stimulated DAG, DGKalpha alters Ras activation and downstream signaling dramatically, a process of utmost importance for sound immunological function.
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 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".