The role of adipose tissue secretion in the creation and pain level in osteoarthritis
Bibliographic record
Abstract
OBJECTIVES: With increasing evidence regarding the metabolic basis of osteoarthritis (OA), we studied the relationship between adipose tissue and OA. METHODS: This study is part of an OA registry in the eastern part of Fars Province, Iran. Overall, 150 patients with OA and 300 sex matched individuals were selected as a control group. They were compared regarding adipokine concentration (leptin, adiponectin, resistin and visfatin), anthropo-metric indices, the Western Ontario and McMaster universities arthritis index score (WOMAC). RESULTS: All adipokine levels were higher among OA patients (p<0.001). After adjusting for age, sex, and body mass index (BMI), adipokines showed a significant and positive association with OA (B: 14.12, B: 9.92, B: 24.71 and B: 12.29 for leptin, adiponectin, visfatin, and resistin, respectively; p<0.001). Except the adiponectin that had a negative relationship with BMI in the OA group (r=-0.570, p<0.001), other adipokines had positive relationships with BMI (r=0.781, p<0.001; r=0.530, p<0.001; r=0.549, p<0.001 for leptin, visfatin, and resistin, respectively). Only leptin and adiponectin levels were correlated with pain (B: 0.045, -0.079 and p<0.05). CONCLUSION: The present study shows that aside to the well-known role of mechanical stress in OA pathogenesis (weight load), leptin, adiponectin, visfatin, and resistin, which represent the adi-pose tissue independent on the weight, may play a chemical role in OA pathogenesis. In addition, leptin and adiponectin may be involved in the pain levels among patients with OA.
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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 | 0.001 |
| 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) | 0.001 | 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".