Investigation of Complement-activating Pattern Recognition Molecules and Associated Enzymes as Possible Inflammatory Markers in Oligoarticular and Systemic Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: The complement system plays a crucial role in the pathogenesis of inflammatory processes. The lectin pathway of the complement system is activated through the recognition of pathogens by soluble pattern recognition molecules (PRM), i.e., mannan-binding lectin (MBL), collectin-LK, and the ficolins. PRM are reportedly correlated to disease activity in rheumatoid arthritis (RA). The aim was to evaluate the pathogenic role of PRM in juvenile idiopathic arthritis (JIA). METHODS: We measured MBL, M-ficolin, H-ficolin, MBL-associated serine proteases (MASP) 1, MASP-2, MASP-3, and 2 alternative splice products, MBL-associated protein (MAp) 44 and MAp19, in plasma and synovial fluid (SF) of children with persistent oligoarticular (n = 109 in plasma, n = 38 in SF) and systemic JIA (n = 19 in plasma, n = 11 in SF). The concentrations of the proteins were measured by in-house time-resolved immunofluorometric assays. RESULTS: We observed significantly higher levels of M-ficolin, MASP-1, MASP-2, and MASP-3 in plasma and SF from patients with systemic JIA compared with persistent oligoarticular JIA (p < 0.001). In paired samples of plasma and SF from 47 patients with oligoarticular and systemic JIA, we observed higher concentrations in plasma for both subtypes for 7 of the measured proteins while the reverse relationship was observed for MASP-3. M-ficolin and MASP-2 correlated to erythrocyte sedimentation rate, C-reactive protein, white blood cell count, and platelet count (p < 0.001). M-ficolin was in addition related to the number of active joints and inversely related to hemoglobin levels. CONCLUSION: Our results point to plasma M-ficolin and MASP-2 as inflammatory markers in JIA. The levels of all proteins are higher in plasma than in SF, except for MASP-3, indicating that MASP-3 may be produced locally in joints.
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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) | 0.001 | 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 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".