Prebiotic and Exercise Do Not Alter Knee Osteoarthritis in a Rat Model of Established Obesity
Bibliographic record
Abstract
OBJECTIVE: Metabolic disturbance is a known risk factor for cardiovascular disease and has been identified as a risk factor for the development of knee osteoarthritis. In this study, we sought to determine the effects of prebiotic fiber supplementation, aerobic exercise, and the combination of the 2 interventions, on the progression of knee osteoarthritis in a high-fat/high-sucrose diet-induced rat model of metabolic disturbance. DESIGN: Twelve-week-old male CD-Sprague-Dawley rats were either fed a standard chow diet, or a high-fat/high-sucrose diet. After 12 weeks on diets, rats consuming the high-fat/high-sucrose diet were randomized into 4 subgroups: a sedentary, an aerobic exercise, a prebiotic fiber supplementation, and an aerobic exercise combined with prebiotic fiber supplementation group. The aerobic exercise intervention consisted of a progressive treadmill training program for 12 weeks, while the prebiotic fiber was added to the high-fat/high-sucrose diet at a dose of 10% by weight for 12 weeks. Outcome measures included knee joint damage, body mass, percent body fat, bone mineral density, insulin sensitivity, and serum lipid profile. RESULTS: Aerobic exercise, or the combination of prebiotic fiber and aerobic exercise, improved select markers of metabolic disturbance, but not knee joint damage. However, these results need to be considered in view of the fact that the chow-fed rats had similar knee OA-like damage as the high-fat/high-sucrose-fed rats. CONCLUSION: Exercise or prebiotics did not increase joint damage and might be good strategies for populations with metabolic knee osteoarthritis to alleviate other health-related problems, such as diabetes or cardiovascular disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".