Plasma microRNA-320c as a Potential Biomarker for the Severity of Knee Osteoarthritis and Regulates cAMP Responsive Element Binding Protein 5 (CREB5) in Chondrocytes
Bibliographic record
Abstract
Objective: Osteoarthritis (OA) is a commonly known prevalent joint disease, with limited therapeutic methods. This study aimed to investigate the expression of plasma microRNA-320c (miR-320c) in patients with knee OA and to explore the clinical value and potential mechanism of miR-320c in knee OA. Methods: Forty knee OA patients and 20 healthy controls were enrolled. The levels of plasma miR-320c and plasma inflammatory cytokines were measured by real-time PCR or ELISA. Correlations of Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores and cytokine levels with the miR-320c expression level were evaluated by Pearson correlation analysis. Then, a receiver operating characteristic (ROC) curve was drawn to analyse the diagnostic value of miR-320c in OA. Finally, the interaction of miR-320c and cAMP responsive element binding protein 5 (CREB5) was determined using a luciferase reporter assay, and the effect of CREB5 on the cAMP pathway was assessed. Results: < 0.001) levels in patients with OA. ROC curve analysis demonstrated the relatively high diagnostic accuracy of plasma miR-320c for OA. Furthermore, the luciferase reporter assay results showed that miR-320c regulates CREB5 expression by binding to the CREB5 3'-untranslated region. Moreover, suppression of CREB5 significantly reduced the expression levels of c-fos and c-jun. Conclusion: Our results indicate that plasma miR-320c may serve as a potential novel predictor of the severity of knee OA and that miR-320c may play an important role in the pathogenesis of OA through inhibiting the cAMP pathway by targeting CREB5.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".