Prebiotics in Chronic Intestinal Inflammation
Bibliographic record
Abstract
Prebiotics are nondigestible fermentable fibers that are reported to have health benefits for the host. Older as well as more recent studies show beneficial effects in experimental colitis and lately also in human inflammatory bowel diseases (IBD), such as Crohn's disease, ulcerative colitis, and chronic pouchitis. In this review we give an overview of the benefits of prebiotics in rodent IBD models and in IBD patients and discuss their possible protective mechanisms. Commensal intestinal bacteria induce and perpetuate chronic intestinal inflammation, whereas others are protective. However, most of the current medications are directed against the exaggerated proinflammatory immune response of the host, some of them toxic and costly. Feeding prebiotics changes the composition of the intestinal microflora toward more protective intestinal bacteria and alters systemic and mucosal immune responses of the host. Therapy for IBD targeting intestinal bacteria and their function is just emerging. Prebiotics have the promise to be relatively safe, inexpensive, and easy to administer. Unraveling their protective mechanisms will help to develop rational applications of prebiotics. However, the initial promising results with dietary prebiotics in preclinical trials as well as small studies in human IBD will need to be confirmed in large randomized controlled clinical trials.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".