Kynurenic Acid in Synovial Fluid and Serum of Patients with Rheumatoid Arthritis, Spondyloarthropathy, and Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: Previously we demonstrated that kynurenic acid (KYNA), an endogenous metabolite of kynurenine, is present in the synovial fluid of patients with rheumatoid arthritis (RA). KYNA inhibits proliferation of synoviocytes in vitro. The goal of our study was to compare KYNA concentrations in synovial fluid and blood of patients with RA, inflammatory spondyloarthropathies (SpA), and osteoarthritis (OA). METHODS: Serum and synovial fluid samples were obtained from 189 patients with RA, 56 patients with SpA, and 32 patients with OA. KYNA was separated using a high-performance liquid chromatography system and measured fluorometrically. RESULTS: KYNA concentration in synovial fluid obtained from patients with RA and SpA was significantly lower than that in patients with OA (p < 0.05). The concentration of KYNA in serum of patients with RA, SpA, and OA did not differ among all groups studied. The positive correlation between KYNA content in synovial fluid and serum was found in patients with RA (p < 0.05). Univariate linear regression analysis demonstrated that fibrinogen was significantly associated with KYNA in synovial fluid (p < 0.05), and red blood cell counts, morning stiffness, and pain scores were significantly associated with KYNA level in serum (all p < 0.05). Multivariate regression analysis revealed correlation between the following independent variables: hemoglobin level, hematocrit, red blood cell count in conjunction with age and KYNA content in synovial fluid. A lack of correlation was observed between KYNA content in synovial fluid of patients with RA and other clinical and laboratory measures of disease activity. CONCLUSION: Our data show a local deficit of KYNA in inflammatory states.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".