To Fiber or Not to Fiber: The Swinging Pendulum of Fiber Supplementation in Patients with Inflammatory Bowel Disease
Bibliographic record
Abstract
Evidence-based dietary guidance around dietary fiber in inflammatory bowel disease (IBD) has been limited owing to insufficient reproducibility in intervention trials. However, the pendulum has swung because of our increased understanding of the importance of fibers in maintaining a health-associated microbiome. Preliminary evidence suggests that dietary fiber can alter the gut microbiome, improve IBD symptoms, balance inflammation, and enhance health-related quality of life. Therefore, it is now more vital than ever to examine how fiber could be used as a therapeutic strategy to manage and prevent disease relapse. At present, there is limited knowledge about which fibers are optimal and in what form and quantity they should be consumed to benefit patients with IBD. Additionally, individual microbiomes play a strong role in determining the outcomes and necessitate a more personalized nutritional approach to implementing dietary changes, as dietary fiber may not be as benign as once thought in a dysbiotic microbiome. This review describes dietary fibers and their mechanism of action within the microbiome, details novel fiber sources, including resistant starches and polyphenols, and concludes with potential future directions in fiber research, including the move toward precision nutrition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".