Statins and Thrombin
Bibliographic record
Abstract
L-Mevalonic acid is the distant precursor of cholesterol, in contrast to cholesterol, L-mevalonic acid, its distant precursor gives rise to farnesyl and geranylgeranyl pyrophosphates in relatively few metabolic steps. These isoprenyl pyrophophates covalently conjugate with specific G-proteins and serve as membrane anchors enabling them to carry out their function. Although farnesyl-proteins may participate in signal transduction, geranylgeranyl-proteins (e.g., Rho GTP binding proteins) are well known to downregulate signaling pathways by inhibiting L-mevalonic acid synthesis. Such inhibitors include 3-hydroxy-3-methylglutaryl CoA reductase inhibitors, drugs (statins) and isoprenoids of dietary origins, where Rho protein activation appears to be necessary for cellular-mediated thrombin generation. Thrombin and other proteases (e.g., coagulation factor Xa, tryptase) upregulate protease-activated receptor (PAR) synthesis and PAR activation promotes synthesis and expression of other proteins [e.g., tissue factor (TF) and plasminogen activator inhibitor-1 (PAI-1)]. With the PAR-1 activating peptide SSFLRNP, we found that either cerivastatin or atorvastatin mitigated platelet stimulation in a time- and dose-dependent manner, as predicted if a statin-mediated Rho pathway is required. We also found that simvastatin decreased prothrombin fragments F1+2 in plasma from type 2 diabetics, demonstrating that statins downregulate thrombin generation. Thus, independent of cholesterol, statins and dietary isoprenoids behave as inhibitors of TF-dependent thrombin generation. Because thrombin has multiple physiological functions, the 20 pleiotropic effects reported for statins may reflect a common mechanism for downregulation of thrombin-mediated events, in particular at the cellular level.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".