Whole Blueberries Improve Pain, Functionality, Inflammation, and Cartilage Metabolism in Individuals with Symptomatic Knee Osteoarthritis (FS15-03-19)
Bibliographic record
Abstract
The purpose of this study was to examine the effect of freeze dried whole blueberry powder on pain, gait performance, joint flexibility, mobility, and serum and urine biomarkers of inflammation and cartilage metabolism in men and women aged 45–79 years old with symptomatic knee osteoarthritis (OA). In a randomized, double-blind control trial, a total of 63 adults with symptomatic knee OA, were randomized to either consume 40 grams freeze-dried blueberry powder (FDBP) (n = 33) or placebo powder (n = 30) daily for 4 months. Functionality and biomarkers of inflammation and cartilage metabolism were evaluated at baseline, 2 months and 4 months. Western Ontario McMaster Osteoarthritis Index (WOMAC) questionnaires were used to assess pain, and a GAITRite® electronic walkway was used to evaluate gait spatiotemporal parameters. Flexibility of the afflicted joint(s) were assessed via range of motion (ROM). Plasma was assessed for biomarkers such as glycoprotein-39 (YKL-40), insulin-like growth factor-1 (IGF-1), insulin-like growth factor-binding protein (IGFBP)-3, and interleukin (IL)-13. A total of 49 participants completed the study. WOMAC total score and sub-groups including pain, stiffness, and difficulty to perform daily activities decreased significantly in the FDBP group, while no changes of WOMAC total score and difficulty to perform daily activities were observed in the placebo group. Normal walking pace single support percentage for both limbs increased, while double support percentage for both limbs decreased in the FDBP group. ROM increased slightly for both knees in the FDBP treatment group. The FDBP group had an increasing trend in concentrations of IGF-1 with consistently stable concentrations of IGFBP-3, while the placebo group had declining concentrations of IGF-1 and increases in IGFBP-3 over the course of the study. The FDBP group had an overall decrease in the concentration of YKL-40. Also, an increasing trend for IL-13 was observed in the FDBP group. The findings of the study suggest that blueberries may have a positive effect on joint health by reducing pain, stiffness, and difficulty to perform daily activities, while improving gait performance, possibly improving ROM, and slowing down cartilage breakdown as reflected by the changes in the biomarkers. US Highbush Blueberry Council.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".