Elevated Serum Interleukin 33 Is Associated with Autoantibody Production in Patients with Rheumatoid Arthritis
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Bibliographic record
Abstract
OBJECTIVE: Interleukin 33 (IL-33) is a novel cytokine involved in joint inflammation in animal models. We analyzed the expression of IL-33 in the serum and synovial fluid of patients with rheumatoid arthritis (RA) and investigated its possible pathophysiological importance. METHODS: The concentration of IL-33 was measured by ELISA in the serum of 223 patients with RA and 159 controls. Anticyclic citrullinated peptide, rheumatoid factor (RF)-IgA, and RF-IgG were tested by ELISA. Antikeratin antibody and antiperinuclear factor were tested by indirect immunofluorescence assay. Erythrocyte sedimentation rate, C-reactive protein, and immunoglobulins were measured by standard laboratory techniques. The association of IL-33 level with clinical and serologic features of RA was analyzed. We tested the change of IL-33 level following tumor necrosis factor (TNF-α) blockade therapy in 40 patients with RA. RESULTS: In contrast to almost no detectable IL-33 in osteoarthritis and healthy serum, IL-33 could be detected in 94 out of the 223 RA cases (42.2%). Serum IL-33 concentration was significantly higher in patients with RA than in control groups. The level of serum IL-33 decreased after anti-TNF treatment. The level of serum IL-33 was correlated with the production of IgM and RA-related autoantibodies including RF and anticitrullinated protein antibodies. However, no correlation was found between IL-33 concentration and acute-phase inflammation reactant or the score of the Disease Activity Index, suggesting a complex or indirect character of the link between IL-33 and the inflammation in RA. CONCLUSION: The level of IL-33 is abnormally elevated in RA serum. The elevation of serum IL-33 was at least partly attributed to excessive TNF-α in RA. IL-33 might be involved in the regulation of autoantibody production in RA.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it