Essential Role of Protein Kinase Cδ in Platelet Signaling, αIIbβ3 Activation, and Thromboxane A2 Release
Bibliographic record
Abstract
The protein kinase C (PKC) family is an essential signaling mediator in platelet activation and aggregation. However, the relative importance of the major platelet PKC isoforms and their downstream effectors in platelet signaling and function remain unclear. Using isolated human platelets, we report that PKCdelta, but not PKCalpha or PKCbeta, is required for collagen-induced phospholipase C-dependent signaling, activation of alpha(IIb)beta(3), and platelet aggregation. Analysis of PKCdelta phosphorylation and translocation to the membrane following activation by both collagen and thrombin indicates that it is positively regulated by alpha(IIb)beta(3) outside-in signaling. Moreover, PKCdelta triggers activation of the mitogen-activated protein kinase-kinase (MEK)/extracellular-signal regulated kinase (ERK) and the p38 MAPK signaling. This leads to the subsequent release of thromboxane A(2), which is essential for collagen-induced but not thrombin-induced platelet activation and aggregation. This study adds new insight to the role of PKCs in platelet function, where PKCdelta signaling, via the MEK/ERK and p38 MAPK pathways, is required for the secretion of thromboxane A(2).
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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 | 0.000 |
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".