Protective effect of prebiotic and exercise intervention on knee health in a rat model of diet-induced obesity
Bibliographic record
Abstract
Obesity, and associated metabolic syndrome, have been identified as primary risk factors for the development of knee osteoarthritis (OA), representing nearly 60% of the OA patient population. In this study, we sought to determine the effects of prebiotic fibre supplementation, aerobic exercise, and the combination of the two interventions, on the development of metabolic knee osteoarthritis in a high-fat/high-sucrose (HFS) diet-induced rat model of obesity. Twelve-week-old male Sprague-Dawley rats were randomized into five groups: a non-exercising control group fed a standard chow diet, a non-exercising group fed a HFS diet, a non-exercising group fed a HFS diet combined with prebiotic fibre supplement, an exercise group fed a HFS diet, and an exercise group fed a HFS diet combined with prebiotic fibre supplement. Outcome measures included knee joint damage, percent body fat, insulin sensitivity, serum lipid profile, serum endotoxin, serum and synovial fluid cytokines and adipokines, and cecal microbiota. Prebiotic fibre supplementation, aerobic exercise, and the combination of the two interventions completely prevented knee joint damage that is otherwise observed in this rat model of obesity. Prevention of knee damage was associated with a normalization of insulin resistance, leptin levels, dyslipidemia, gut microbiota, and endotoxemia in the HFS-fed rats.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".