Chemical Hypoxia Brings to Light Altered Autocrine Sphingosine‐1‐Phosphate Signalling in Rheumatoid Arthritis Synovial Fibroblasts
Bibliographic record
Abstract
Emerging evidence suggests a role for sphingosine-1-phosphate (S1P) in various aspects of rheumatoid arthritis (RA) pathogenesis. In this study we compared the effect of chemical hypoxia induced by cobalt chloride (CoCl2) on the expression of S1P metabolic enzymes and cytokine/chemokine secretion in normal fibroblast-like synoviocytes (FLS) and RAFLS. RAFLS incubated with CoCl2, but not S1P, produced less IL-8 and MCP-1 than normal FLS. Furthermore, incubation with the S1P2 and S1P3 receptor antagonists, JTE-013 and CAY10444, reduced CoCl2-mediated chemokine production in normal FLS but not in RAFLS. RAFLS showed lower levels of intracellular S1P and enhanced mRNA expression of S1P phosphatase 1 (SGPP1) and S1P lyase (SPL), the enzymes that are involved in intracellular S1P degradation, when compared to normal FLS. Incubation with CoCl2 decreased SGPP1 mRNA and protein and SPL mRNA as well. Inhibition of SPL enhanced CoCl2-mediated cytokine/chemokine release and restored autocrine activation of S1P2 and S1P3 receptors in RAFLS. The results suggest that the sphingolipid pathway regulating the intracellular levels of S1P is dysregulated in RAFLS and has a significant impact on cell autocrine activation by S1P. Altered sphingolipid metabolism in FLS from patients with advanced RA raises the issue of synovial cell burnout due to chronic inflammation.
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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".