Higher Circulating Concentration of Interleukin-38 in Patients with Knee Osteoarthritis: Its Association with Disease Severity
Bibliographic record
Abstract
Evidence showed that chronic inflammatory and immunopathological responses play a pivotal role in the development of osteoarthritis (OA). Interleukin-38 (IL-38) as a novel anti-inflammatory cytokine with influential modulatory properties on both innate and adaptive immune responses can be involved in the pathogenesis of OA. Therefore, this study aimed to measure the serum level of IL-38 in OA patients to clarify the positive or negative association with disease and its severity. Blood specimens were collected from two groups including 23newly-diagnosed OA patients and 22 healthy sex and age-matched subjects as a control group. Serum IL-38 quantities were measured using enzyme-linked immunosorbent assay (ELISA). Significantly higher IL-38 levels were detected in OA patients in comparison with the healthy group (265.78±41.27 pg/mL vs 44.23±6.04 pg/mL, p=0.0001). The IL-38 concentration in OA patients with Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores>40 and in OA patients with visual analog scale (VAS) scores >5 werehigher than those with WOMAC scores<40, and VASscores<5 (p=0.026 and p=0.035, respectively). The IL-38 levels in OA patients with body mass index (BMI)<25 were also significantly higher than in patients with BMI>25 (p=0.05). According to our findings, WOMAC, VAS, and BMI indices may influence the IL-38 serum levels in OA patients and it may be elevated in OA patients to modulate inflammatory responses in a compensatory manner.The patients with OA, especially those with more severe disease express higher serum amounts of IL-38. Accordingly, IL-38 may be considered as a valuable marker for OA.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".