Impact of High-Fiber Diet on Gut Microbiome and Insulin Sensitivity in Individuals with Prediabetes: A Research Protocol
Bibliographic record
Abstract
Introduction: Approximately 537 million individuals globally are affected by type 2 diabetes (T2D), with projections of 780 million by 2045. T2D is a chronic condition characterized by insulin resistance or insufficient insulin production, leading to high blood sugar levels, because the body cannot use insulin effectively. The rise in the incidence and prevalence of prediabetes, where glucose levels are above normal range but below diabetes threshold, serves as a warning for T2D development. The interplay between the gut microbiome and host metabolic pathways has emerged as a critical area of research in understanding diabetes etiology. The gut microbiome’s role in modulating immune responses, influencing metabolic health, and potential to ease the progression of diabetes via a high-fiber diet have garnered significant interest. This research protocol proposes an experimental design to investigate the effect of a high-fiber diet on gut microbiome composition and insulin sensitivity in individuals with prediabetes. Methods: This randomized controlled trial will include 60 individuals with prediabetes, randomly assigned to either a high-fiber diet intervention group or a control group. Participants in the intervention group will follow a high-fiber diet for 12 weeks, while the control group will maintain their usual diet. Data collection will involve stool samples for gut microbiome analysis using 16S rRNA sequencing, dietary records, and blood samples for insulin sensitivity measures, including the oral glucose tolerance test (OGTT). Statistical analysis will compare pre- and post-intervention microbial composition and insulin sensitivity using paired t-tests. Results: We hypothesize that a high-fiber diet will increase the abundance of beneficial bacteria such as Akkermansia muciniphila, Roseburia, Faecalibacterium prausnitzii, and Bifidobacterium, which are known to improve insulin sensitivity by producing short-chain fatty acids (SCFAs). Concurrently, we also expect a decrease in potentially harmful bacteria, including Enterobacteriaceae and Bacteroides fragilis, which are associated with metabolic inflammation and insulin resistance. Conclusion: The results of this study will be analyzed to understand the relationship between dietary fiber intake and changes in gut microbiome and insulin sensitivity. The findings are expected to provide insights into the potential of dietary interventions for preventing and managing T2D.
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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 | 0.021 | 0.020 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.063 | 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".