Proinflammatory Cytokines Synergistically Enhance the Production of Chemokine Ligand 20 (CCL20) from Rheumatoid Fibroblast-like Synovial Cells <i>in vitro</i> and Serum CCL20 Is Reduced <i>in vivo</i> by Biologic Disease-modifying Antirheumatic Drugs
Bibliographic record
Abstract
OBJECTIVE: Chemokine ligand 20 (CCL20) is a selective ligand for chemokine receptor 6 (CCR6). We investigated, both in vitro and in vivo, whether CCL20 is critically involved in the disease process of rheumatoid arthritis (RA). METHODS: In vitro study investigated the effect of proinflammatory cytokines and biologic disease-modifying antirheumatic drugs (DMARD) on the production of CCL20 by rheumatoid fibroblast-like synovial cells (FLS). The in vivo role of CCL20 was studied by screening for serum CCL20 concentration in patients with RA during the therapeutic course of biologic DMARD, i.e., infliximab, etanercept, and tocilizumab. RESULTS: Spontaneous CCL20 production from rheumatoid FLS was minimal; however, its production was significantly stimulated by interleukin 1beta (IL-1beta), tumor necrosis factor-alpha (TNF-alpha), or IL-17. IL-1beta was the most potent for stimulating the production of CCL20. CCL20 production was synergistically augmented by a combination of IL-1beta, TNF-alpha, and IL-17. In contrast, interferon-gamma suppressed IL-1beta-induced CCL20 production. IL-6, in combination with soluble IL-6 receptor (sIL-6R), did not modulate CCL20 production, whereas IL-1beta-induced, TNF-alpha-induced, and IL-17-induced production were increased by IL-6. These production levels were clearly suppressed by biologic DMARD in vitro. Serum CCL20 was significantly higher in RA than in control subjects, and was clearly decreased by the treatment with infliximab, etanercept, and tocilizumab. CONCLUSION: Proinflammatory cytokines modulate the production of CCL20 from FLS. Our data suggest that therapeutic efficacy of biologic DMARD may result from the inhibition of CCL20 production in rheumatoid synovium.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".