Differences in the profiles of circulating levels of soluble tumor necrosis factor receptors and interleukin 1 receptor antagonist reflect the heterogeneity of the subgroups of juvenile rheumatoid arthritis.
Bibliographic record
Abstract
OBJECTIVE: To determine whether levels of soluble tumor necrosis factor receptor 55 (sTNFR55), sTNFR75, and interleukin 1 receptor antagonist (IL-1Ra) can differentiate different subtypes of juvenile rheumatoid arthritis (JRA), and to determine if the levels of these proteins correlate with disease activity. METHODS: Serum sTNFR (55 and 75) and IL-1Ra levels were measured by ELISA in 34 patients with JRA and these values were correlated with disease subtype and activity. RESULTS: Serum sTNFR55 levels were significantly elevated in patients with systemic onset JRA (SoJRA) (mean +/- 2 SD, 2.9 +/- 1.8 ng/ml) (p < or = 0.05) compared to rheumatoid factor positive (RF+) polyarticular JRA (2.1 +/- 0.6), RF-polyarticular JRA (1.5 +/- 0.6), and pauciarticular JRA (1.4 +/- 0.4). There was a trend for elevation of sTNFR75 levels in patients with SoJRA compared to other subtypes (p = 0.08). More patients had elevated levels of sTNFR75 than sTNFR55 (15 vs 7). This was true for all subsets (SoJRA 7 vs 5; polyarticular JRA 4 vs 2; and pauciarticular JRA 4 vs 0). In contrast to sTNFR, IL-1Ra levels were significantly elevated in RF+ polyarticular JRA compared to the other subgroups (p < or = 0.001). We found statistically significant Pearson correlations between (1) sTNFR75 and hemoglobin concentration: and (2) IL-1Ra and number of active joints and number of joints with effusions. CONCLUSION: The increased serum level of sTNF receptors in SoJRA suggests that TNF is likely more important than IL-1 in systemic inflammation and in particular in SoJRA. Conversely, IL-1 is likely more important in the inflammatory arthritis of JRA and in particular in the pathogenesis of RF+ polyarticular JRA. Our results suggest that cytokines have differing roles in JRA subtypes and likely reflect JRA subtype heterogeneity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".