Arsenic Trioxide Induces Apoptosis of Fibroblast-like Synoviocytes and Represents Antiarthritis Effect in Experimental Model of Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: recent studies have demonstrated that rheumatoid arthritis (RA) fibroblast-like synoviocytes (FLS) proliferate as fiercely as tumor cells. Induction of apoptosis in RA FLS therefore provides a new approach for the inhibition of joint destruction. Arsenic trioxide (As(2)O(3)) was reported to be an effective apoptosis inducer in a variety of cell types. We investigated the possible effect of As(2)O(3) on apoptosis induction of RA FLS and the mechanisms involved in this process. METHODS: apoptosis was determined by flow cytometric analysis, terminal deoxynucleotide transferase-mediated dUTP nick end-labeling, and transmission electron microscopy. The activity and messenger RNA (mRNA) expression of nuclear factor-κB (NF-κB) was then detected by ELISA and real-time polymerase chain reaction, respectively. Activities of caspase-3 and caspase-8 were evaluated using luminogenic substrates. The effect of As(2)O(3) on the morphology of rats with collagen-induced arthritis was evaluated under a light microscope after H&E staining. RESULTS: as(2)O(3) significantly enhanced the apoptosis of RA FLS. It suppressed the DNA-binding activity and mRNA expression level of NF-κB, probably by inhibiting tumor necrosis factor-α-induced activation of NF-κB. As(2)O(3) treatment significantly increased the activity of both caspase-3 and caspase-8. Morphological analysis revealed histological recovery in the synovial membrane. Synovial hyperplasia and inflammation in the joints were effectively inhibited. CONCLUSION: as(2)O(3) represents an apoptotic effect on RA FLS through NF-κB signaling pathway, and this process is mediated by the activation of caspase cascade. Treatment with As(2)O(3) significantly improved the pathologic changes of collagen-induced arthritis and may have potential for treatment of 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".