Modulation of Bone and Joint Biomarkers, Gut Microbiota, and Inflammation Status by Synbiotic Supplementation and Weight-Bearing Exercise: Human Study Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: There is strong evidence suggesting that prebiotics and probiotics regulate gut microbiota, reducing inflammation and thereby potentially improving bone health status. Similarly, mechanistic evidence suggests that either low-impact or high-impact weight-bearing exercises improve body composition and consequently increase bone mineral density in individuals with osteoporosis and osteoarthritis. OBJECTIVE: This study aims to investigate the effects of a synbiotic (probiotic+prebiotic) supplementation, an exercise intervention, or a combination of both on gut microbiota, inflammation, and bone biomarkers in postmenopausal women. METHODS: A total of 160 postmenopausal women from New Zealand will be recruited and randomized to one of four interventions or treatments for 12 weeks: control, synbiotic supplementation, exercise intervention, or synbiotic supplementation and exercise. The primary outcome measure is the bone and joint biomarkers at baseline and week 12, whereas the gut microbiota profile and inflammatory cytokine measurements will serve as the secondary outcome measures at baseline and week 12. Baseline data and exercise history will be used to assess, allocate, and stratify participants into treatment measures. RESULTS: Recruitment of participants will begin in September 2021, and the anticipated completion date is June 2022. CONCLUSIONS: To the best of our knowledge, this will be the first randomized controlled trial to analyze the effects of both a synbiotic supplement and an exercise intervention in postmenopausal women. On the basis of the results obtained, a combination of synbiotic supplements and exercise might serve as a noninvasive approach to manage and/or improve body composition and bone health in postmenopausal women. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12620000998943p; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380336&isClinicalTrial=False.
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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 | 0.038 | 0.032 |
| Meta-epidemiology (narrow) | 0.009 | 0.005 |
| Meta-epidemiology (broad) | 0.019 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.087 | 0.020 |
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".