Short- and Long-Term Effectiveness of Supplementation with Non-Animal Chondroitin Sulphate on Inflammation, Oxidative Stress and Functional Status in Obese Subjects with Moderate Knee Osteoarthritis before and after Physical Stress: A Randomized, Double-Blind, Placebo-Controlled Trial
Bibliographic record
Abstract
It has recently been demonstrated that chronic supplementation with nonanimal chondroitin sulfate (nonanimal CS) in overweight subjects with knee osteoarthritis (OA) improves the function, pain and inflammation, but there are no studies of its effectiveness in an acute setting. In 48 obese subjects with moderate knee OA, we investigated the effectiveness of nonanimal CS supplementation for eight weeks on the inflammation, functional status, oxidative stress, cartilage catabolism markers, metabolic profile and body composition, by Dual-Energy X-ray Absorptiometry (DXA) at the baseline, after 15 days and at the end of the eight-week study. To evaluate the acute effectiveness on inflammation, 15-min cycle training sessions were done 15 days after the start of the study and at the end. C-reactive protein (CRP) was assayed in blood samples collected before and after the two cycling exercises. The 48 obese subjects (M and F, 20–50 years, body mass index (BMI) 30–35 kg/m2) were randomly assigned to an experimental group (N = 24, 600-mg tablet of nonanimal CS/day) or the control group (N = 24, placebo). The between-groups analysis of covariance showed a significant effect on the Western Ontario and McMaster Universities Arthritis index (WOMAC) scale (p = 0.000) and CRP (p = 0.022). For intra-group differences, the result was significant in the CS group for BMI, WOMAC, CRP, total cholesterol and Homeostasis Model Assessment (HOMA). In these obese adults with OA, nonanimal CS improved the inflammation, knee function, metabolic profile and body composition.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".