Unraveling the molecular landscape of osteoarthritis: A comprehensive review focused on the role of non-coding RNAs
Bibliographic record
Abstract
Osteoarthritis (OA) poses a significant global health challenge, with its prevalence anticipated to increase in the coming years. This review delves into the emerging molecular biomarkers in OA pathology, focusing on the roles of various molecules such as metabolites, noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Advances in omics technologies have transformed biomarker identification, enabling comprehensive analyses of the complex pathways involved in OA pathogenesis. Notably, ncRNAs, especially miRNAs and lncRNAs, exhibit dysregulated expression patterns in OA, presenting promising opportunities for diagnosis and therapy. Additionally, the intricate interplay between epigenetic modifications and OA progression highlights the regulatory role of epigenetics in gene expression dynamics. Genome-wide association studies have pinpointed key genes undergoing epigenetic changes, providing insights into the inflammatory processes and chondrocyte hypertrophy typical of OA. Understanding the molecular landscape of OA, including biomarkers and epigenetic mechanisms, holds significant potential for developing innovative diagnostic tools and therapeutic strategies for OA management.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".