Inflammatory bowel disease and immunonutrition: novel therapeutic approaches through modulation of diet and the gut microbiome
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the gastrointestinal tract, thought to at least in part reflect an aberrant immune response to gut bacteria. IBD is increasing in incidence, particularly in populations that have recently immigrated to western countries. This suggests that environmental factors are involved in its pathogenesis. We hypothesize that the increase in IBD rates might reflect the consumption of an unhealthy Western diet, containing excess calories and lacking in key nutritional factors, such as fibre and vitamin D. Several recent studies have determined that dietary factors can dramatically influence the activation of immune cells and the mediators they release through a process called immunonutrition. Moreover, dietary changes can profoundly affect the balance of beneficial versus pathogenic bacteria in the gut. This microbial imbalance can alter levels of microbiota-derived metabolites that in turn can influence innate and adaptive intestinal immune responses. If the diet-gut microbiome disease axis does indeed underpin much of the 'western' influence on the onset and progression of IBD, then tremendous opportunity exists for therapeutic changes in lifestyle, to modulate the gut microbiome and to correct immune imbalances in individuals with IBD. This review highlights four such therapeutic strategies - probiotics, prebiotics, vitamin D and caloric restriction - that have the potential to improve and add to current IBD treatment regimens.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".