Cytokine Secretion by Pathogen Recognition Receptor-stimulated Dendritic Cells in Rheumatoid Arthritis and Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: Interleukin 23 (IL-23) plays a major role in differentiation and survival of IL-17-secreting CD4+ Th17 cells. Having noted a higher frequency of Th17 cells in ankylosing spondylitis (AS) and rheumatoid arthritis (RA) than in healthy donors (HD), we investigated whether IL-23 secretion is increased in these conditions. METHODS: Monocyte-derived dendritic cells (moDC) were obtained from peripheral blood of 17 HD, 16 patients with RA, and 30 patients with AS, and stimulated with ligands for several pathogen recognition receptors. Messenger RNA (mRNA) expression and cytokine secretion were analyzed by real-time polymerase chain reaction and ELISA, respectively. RESULTS: The combination of ligands for Toll-like receptors (TLR) 7/8 and TLR3 led to synergistic secretion of both IL-23 and IL-12p70 from all subjects; similar synergy was seen with TLR2 ligands and curdlan. However, for both combinations, moDC from patients with RA produced significantly lower amounts of IL-23 than moDC from patients with AS; in contrast, IL-12p70 secretion did not differ. Similarly, tumor necrosis factor-α, IL-6, and IL-10 were secreted at comparable levels in all subjects, whereas CXCL8 and CCL3 production was actually enhanced in moDC of patients with RA. Equivalent levels of mRNA for both IL-23p19 and IL-12p35 subunits were found in moDC from all donors, suggesting posttranscriptional regulation of IL-23 production in RA. CONCLUSION: Our observations show that IL-23 production is decreased in RA and maintained in AS. Because increased numbers of CD4+IL-17+ T cells are seen in both diseases, these observations imply that there are different mechanisms underlying chronic inflammation in these 2 forms of inflammatory arthritis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".