Response to diet‐induced obesity produces time‐dependent induction and progression of metabolic osteoarthritis in rat knees
Bibliographic record
Abstract
Obesity, and corresponding chronic-low grade inflammation, is associated with the onset and progression of knee OA. The origin of this inflammation is poorly understood. Here, the effect of high fat, high sucrose (HFS) diet induced obesity (DIO) on local (synovial fluid), and systemic (serum) inflammation is evaluated after a 12-week obesity induction and a further 16-week adaptation period. For 12-weeks of obesity induction, n = 40 DIO male Sprague-Dawley rats consumed a HFS diet while the control group (n = 14) remained on chow. DIO rats were allocated to prone (DIO-P, top 33% based on weight change) or resistant (DIO-R, bottom 33%) groups at 12-weeks. Animals were euthanized at 12- and after an additional 16-weeks on diet (28-weeks). At sacrifice, body composition and knee joints were collected and assessed. Synovial fluid and sera were profiled using cytokine array analysis. At 12-weeks, DIO-P animals demonstrated increased Modified Mankin scores compared to DIO-R and chow (p = 0.026), and DIO-R had higher Mankin scores compared to chow (p = 0.049). While numerous systemic and limited synovial fluid inflammatory markers were increased at 12-weeks in DIO animals compared to chow, by 28-weeks there were limited systemic differences but marked increases in local synovial fluid inflammatory marker concentrations. Metabolic OA may manifest from an initial systemic inflammatory disturbance. Twelve weeks of obesity induction leads to a unique inflammatory profile and induction of metabolic OA which is altered after a further 16-weeks of obesity and HFS diet intake, suggesting that obesity is a dynamic, progressive process. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:1010-1018, 2016.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".