Grape Seed Extracts Inhibit Platelet Aggregation by Inhibiting Protein Tyrosine Phosphatase
Bibliographic record
Abstract
Platelets play an important role in various thrombotic diseases, including myocardial infarction. Because red wine consumption is inversely associated with death due to ischemic heart diseases, the effects of grape components on platelet function have been extensively investigated. Grape seed extracts (GSEs) reportedly inhibit platelet aggregation; however, the underlying mechanism has not been elucidated. We discovered that GSEs inhibit platelet aggregation induced by collagen and thrombin-receptor agonist peptide and increase basal levels of tyrosine phosphorylation, which was also observed in the presence of a protein tyrosine phosphatase (PTP) inhibitor. An in vitro phosphatase assay indicated that GSE dose dependently inhibited PTP-1B and Src homology 2 domain-containing phosphatase-1 activity, which positively regulates platelet aggregation. We propose that GSEs inhibit platelet aggregation by inhibiting tyrosine phosphatase activity. Moreover, we showed that GSE ingestion inhibited platelet aggregation in mice without enhancing tail bleeding, implying that GSE supplementation might be beneficial to prevention of thrombotic diseases.
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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".