Bibliographic record
Abstract
RasGRPs (guanine nucleotide releasing proteins) are a family of four GEFs (guanine nucleotide-exchange factors) (Ras GEFs) that positively regulate Ras and related small GTPases. RasGRP1 possesses a catalytic region consisting of a REM (Ras exchange motif) and a CDC25 (cell division cycle 25) domain. RasGRP1 also possesses a DAG (diacylglycerol)-binding C1 domain and a pair of EF hands that bind calcium. RasGRP1 is selectively expressed in lymphocytes as well as in some cells of the brain, kidney and skin. Functional analysis supports the hypothesis that RasGRP1 serves to couple TCR (T-cell receptor) stimulation and phospholipase C activation with Ras signalling. In B-cells, both RasGRP1 and RasGRP3 play a similar role downstream of the B-cell receptor. RasGRP2 acts on the Ras-related protein Rap and functions in platelet adhesion. RasGRP4 is expressed in mast cells and certain myeloid leukaemia cells. Membrane DAG regulates RasGRPs directly by recruitment to cellular membranes, as well as indirectly by protein kinase C-mediated phosphorylation. The properties of RasGRPs provide a novel view of Ras regulation in lymphocytes and explain several earlier observations. Many experimental results obtained with DAG analogues could be reviewed in light of these findings.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".