The role of metabolomics in precision medicine of osteoarthritis: How far are we?
Bibliographic record
Abstract
Objectives: A narrative review on recent published studies of metabolomics in osteoarthritis (OA) with the focus on how the metabolomic findings help stratify OA patients in precision medicine. Design: A narrative review based on selected population-based metabolomics studies in OA. Results: studies, animal models. Thirty-two population-based metabolomic studies using either plasma/serum, synovial fluid, cartilage, or subchondral bone samples were reviewed. The most reported metabolic pathways to be involved in OA included energy metabolic pathways, arginine and proline metabolism, taurine and hypotaurine metabolism, and glycerophospholipid metabolism. Conclusions: While metabolomics of OA research is still in its infancy, the published data showed that metabolomics is a promising tool to help better understanding of pathogenesis of OA, classify OA patients into different endotypes, and develop precision medicine tools for OA management.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".