Possible Involvement of Serum and Synovial Fluid Resistin in Knee Osteoarthritis: Cartilage Damage, Clinical, and Radiological Links
Bibliographic record
Abstract
BACKGROUND: Resistin is an adipocytokine associated with inflammation and insulin resistance. Recent studies have shown that resistin plays an important role in the pathogenesis and progression in osteoarthritis (OA) patients. The current study was aimed at investigating the relationship between resistin in serum and synovial fluid (SF) and disease severity in patients with knee osteoarthritis. METHOD: Seventy-four patients diagnosed with knee OA and 79 healthy controls receiving regular body check in our hospital were recruited in the study. The Noyes score method was used to assess articular cartilage damage arthroscopically. The symptomatic severity was evaluated according to the Western Ontario McMaster University Osteoarthritis (WOMAC) scores. The radiographic disease severity of OA was assessed by the Kellgren-Lawrence (K-L) grading system. The resistin levels in serum and SF were determined by enzyme-linked immunosorbent assay. Cartilage degradation marker CTX-II in SF was also examined. RESULTS: SF but not serum resistin levels are positively associated with Noyes scores, K-L grading scores WOMAC pain scores, physical functional scores and WOMAC total scores. In addition, SF resistin correlated positively with CTX-II. CONCLUSION: Resistin in SF might serve as a potential biomarker for reflecting the disease severity and cartilage degenerative extent of knee OA.
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 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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".