Synovial fluid alpha-melanocyte-stimulating hormone may act as a protective biomarker for primary knee osteoarthritis.
Bibliographic record
Abstract
OBJECTIVE: The current study was carried out to investigate the serum and synovial fluid (SF) alpha-melanocyte-stimulating hormone (α-MSH) levels in correlation with disease severity in primary knee osteoarthritis (OA). METHODS: This study comprised of 105 primary knee OA patients and 98 healthy controls. The radiographic severity was verified according to the Kellgren-Lawrence radiographic grading criteria. The symptomatic severity of knee OA was assessed by the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index. Serum α-MSH concentrations were measured by ELISA. The inflammation markers IL-6 and TNF-α, as well as cartilage damage markers MMP-3 (matrix metalloproteinase 3) and COMP (cartilage oligomeric matrix protein), were also measured. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value between α-MSH and other four markers with regard to the radiographic progression. RESULTS: SF α-MSH concentrations were negatively related to Kellgren-Lawrence grades and WOMAC index. SF α-MSH levels in knee OA patients were negatively associated with inflammation markers IL-6, TNF-α, and cartilage damage factors COMP and MMP-3. In addition, ROC analysis implied that attenuated α-MSH levels may serve as a favorable diagnostic marker for the radiographic progression. The difference of serum α-MSH concentration was not significant between knee OA patients and healthy controls. CONCLUSIONS: Reduced SF α-MSH expression may be a characteristic of OA patients. Attenuated α-MSH level in SF may serve as a potential biomarker for disease severity of knee OA, and further studies are needed to identify its potential application for monitoring the course of the disease and the efficacy of therapies in OA patients.
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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".