Impact of a Powdered Meal Replacement on Metabolism and Gut Microbiota (PREMIUM) in individuals with excessive body weight: a study protocol for a randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Excess body weight is associated with a state of low-grade chronic inflammation and alterations of the gut microbiome. Powdered meal replacements (PMR) have been shown to be an effective strategy for weight management; however, their effect on inflammation and the gut microbiome remains unclear. The aim of this 12-week randomised control clinical trial is to investigate the effects of PMR consumption, here given as a soy-yoghurt-honey formula, on inflammation, gut microbiome and overall metabolism in individuals with excessive body weight. METHODS AND ANALYSIS: Healthy adults with excess body weight (n=88) are being recruited and randomly assigned to one of the following groups: (1) Control group (CON): maintaining usual diet for 12 weeks, or (2) PMR group: replacing morning and afternoon snacks daily with a PMR for 12 weeks. Participants are asked to maintain body weight throughout the study and fill out a journal with information about PMR consumption, body weight, food intake, appetite sensations and medications. Three study visits are required: baseline, week 6 and week 12. Outcome measures include systemic inflammatory biomarkers, gut microbiome composition, metabolic blood markers, host energy metabolism, body composition, appetite sensations and host gene expression profile. ETHICS AND DISSEMINATION: This research protocol was approved by the University of Alberta Ethics Board (Pro00070712) and adheres to the Canadian Tri-Council Policy statement on the use of human participants in research. Procedures and potential risks are fully discussed with participants. Study findings will be disseminated in peer-reviewed journals, conference presentations and social media. TRIAL REGISTRATION NUMBER: NCT03235804.
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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 | 0.034 | 0.031 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.062 | 0.013 |
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".