Proteomic identification of pleckstrin‐associated proteins in platelets: Possible interactions with actin
Bibliographic record
Abstract
Pleckstrin (plek)-null platelets from a knockout mouse have been shown to be defective in granule secretion, aggregation and actin polymerization. However, the mechanism of plek signaling is currently unknown. Therefore, we sought to identify plek-binding proteins in platelets by using GST pulldown assays and immunoprecipitation to isolate proteins from extracts of protein kinase C-activated or inhibited human platelets. Co-purified plek-binding proteins were resolved by SDS-PAGE and identified via nanospray quadruple TOF MS. Identified proteins may be involved in various cellular processes including cytoskeletal reorganization (moesin, radixin and alpha-actinin) and signal transduction (serum deprivation response protein, 17 beta-hydroxysteroid dehydrogenase 4 and factor XIIIA). Both platelet aggregation and/or secretion require actin polymerization. However, studies have shown no direct association between plek and actin. Based on our findings we propose indirect associations between plek and actin through 17 beta-hydroxysteroid dehydrogenase 4, alpha-actinin, moesin, radixin and factor XIIIA, which in turn suggest new roles for plek in platelet biology.
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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".