Inhibition of protein geranylgeranylation induces apoptosis in synovial fibroblasts
Bibliographic record
Abstract
Statins, competitive inhibitors of hydroxymethylglutaryl-CoA reductase, have recently been shown to have a therapeutic effect in rheumatoid arthritis (RA). In RA, synovial fibroblasts in the synovial lining, are believed to be particularly important in the pathogenesis of disease because they recruit leukocytes into the synovium and secrete angiogenesis-promoting molecules and proteases that degrade extracellular matrix. In this study, we show a marked reduction in RA synovial fibroblast survival through the induction of apoptosis when the cells were cultured with statins. Simvastatin was more effective in RA synovial fibroblasts than atorvastatin, and both statins were more potent on tumor necrosis factor-alpha-induced cells. In contrast, in osteoarthritis synovial fibroblasts, neither the statin nor the activation state of the cell contributed to the efficacy of apoptosis induction. Viability of statin-treated cells could be rescued by geranylgeraniol but not by farnesol, suggesting a requirement for a geranylgeranylated protein for synovial fibroblast survival. Phase partitioning experiments confirmed that in the presence of statin, geranylgeranylated proteins are redistributed to the cytoplasm. siRNA experiments demonstrated a role for Rac1 in synovial fibroblast survival. Western blotting showed that the activated phosphorylated form of Akt, a protein previously implicated in RA synovial fibroblast survival, was decreased by about 75%. The results presented in this study lend further support to the importance of elevated pAkt levels to RA synovial fibroblast survival and suggest that statins might have a beneficial role in reducing the aberrant pAkt levels in patients with RA. The results may also partly explain the therapeutic effect of atorvastatin in patients with RA.
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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) | 0.001 | 0.001 |
| 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".