Fiber and Prebiotic Interventions in Pediatric Inflammatory Bowel Disease: What Role Does the Gut Microbiome Play?
Bibliographic record
Abstract
The etiology of inflammatory bowel disease (IBD) is complex but is thought to be linked to an intricate interaction between the host's immune system, resident gut microbiome and environment, i.e., diet. One dietary component that has a major impact on IBD risk and disease management is fiber. Fiber intakes in pediatric IBD patients are suboptimal and often lower than in children without IBD. Fiber also has a significant impact on beneficially shaping gut microbiota composition and functional capacity. The impact is likely to be particularly important in IBD patients, where various studies have demonstrated that an imbalance in the gut microbiome, referred to as dysbiosis, occurs. Microbiome-targeted therapeutics, such as fiber and prebiotics, have the potential to restore the balance in the gut microbiome and enhance host gut health and clinical outcomes. Indeed, studies in adult IBD patients demonstrate that fiber and prebiotics positively alter the microbiome and improve disease course. To date, no studies have been conducted to evaluate the therapeutic potential of fiber and prebiotics in pediatric IBD patients. Consequently, pediatric IBD specific studies that focus on the benefits of fiber and prebiotics on gut microbiome composition and functional capacity and disease outcomes are required.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".