Interaction of Linker for Activation of T Cells with Multiple Adapter Proteins in Platelets Activated by the Glycoprotein VI-selective Ligand, Convulxin
Bibliographic record
Abstract
The snake venom toxin convulxin activates platelets through the collagen receptor glycoprotein VI (GPVI)/Fc receptor gamma-chain (FcR gamma-chain) complex leading to tyrosine phosphorylation and activation of the tyrosine Syk and phospholipase Cgamma2 (PLCgamma2). In the present study, we demonstrate that convulxin is a considerably more powerful agonist than collagen or the GPVI-selective collagen-related peptide (CRP). Confirmation that the response to convulxin is mediated solely via Syk was provided by studies on Syk-deficient platelets. The increase in phosphorylation of the FcR gamma-chain is associated with marked increases in tyrosine phosphorylation of downstream proteins including Syk, linker for activation of T cells (LAT), SLP-76, and PLCgamma2. The transmembrane adapter LAT coprecipitates with SLP-76 and PLCgamma2, as well as with a number of other adapter proteins, some of which have not been previously described in platelets, including Cbl, Grb2, Gads, and SKAP-HOM. Gads is constitutively associated with SLP-76 and is probably the protein bridging its association with LAT. There was no detectable association between Grb2 and SLP-76 in control or stimulated cells, suggesting that the interaction of LAT with Grb2 is present in a separate complex to that of LAT-Gads-SLP-76. These results show that the trimeric convulxin stimulates a much greater phosphorylation of the FcR gamma-chain and subsequent downstream responses relative to CRP and collagen, presumably because of its ability to cause a greater degree of cross-linking of GPVI. The adapter LAT appears to play a critical role in recruiting a number of other adapter proteins to the surface membrane in response to activation of GPVI, presumably at sites of glycolipid-enriched microdomains, enabling an organized signaling cascade that leads to platelet activation.
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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 | 0.000 |
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".