Increased Levels of Interleukin 34 in Serum and Synovial Fluid Are Associated with Rheumatoid Factor and Anticyclic Citrullinated Peptide Antibody Titers in Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Interleukin 34 (IL-34) is a recently discovered cytokine that binds macrophage colony-stimulating factor (M-CSF) receptor. Rheumatoid arthritis (RA) is characterized by increased osteoclastogenesis. To identify the significance of IL-34 in RA, the IL-34 concentration was measured in serum and synovial fluid (SF). METHODS: IL-34 concentrations were measured in serum from patients with RA (n = 113), patients with osteoarthritis (OA; n = 56), and controls (n = 36), and in SF isolated from patients with RA (n = 36) or OA (n = 24). Correlations between serum IL-34 levels and clinical features in RA were assessed. The levels of IL-1β, IL-6, IL-17α, interferon-γ-induced protein 10, receptor activator of nuclear factor κB ligand (RANKL), and Dickkopf-1 were also measured. RESULTS: Patients with RA had a higher mean serum level of IL-34 than did patients with OA and controls (188.0 ± 550.3, 36.6 ± 38.0, and 49.1 ± 78.5 pg/ml, respectively). Similarly, SF IL-34 concentration was higher in patients with RA than in those with OA. IL-34 levels were positively associated with IL-6 levels in serum from patients with RA and OA. SF IL-34 concentration correlated significantly with IL-6 and RANKL levels only in RA. The serum level of IL-34 was not correlated with systemic osteoporosis and radiographic joint damage in RA. IL-34 levels in the serum from patients with RA were positively correlated with rheumatoid factor and anticyclic citrullinated peptide antibody titers (r = 0.282 and 0.491, respectively). CONCLUSION: Circulating IL-34 levels in RA correlated with autoantibody production. Further investigations of localized and systemic effects of IL-34 are warranted to elucidate RA pathogenesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".