Host immune interactions in chronic inflammatory gastrointestinal conditions
Bibliographic record
Abstract
PURPOSE OF REVIEW: We performed a literature review of the latest studies on the interactions between the host immune system and microbes in chronic intestinal inflammatory conditions. RECENT FINDINGS: The mechanisms leading to celiac disease (CeD) and inflammatory bowel disease (IBD), the most common chronic inflammatory gastrointestinal conditions, are complex. The intestinal homeostasis depends on the interactions between the microbiota, the intestinal mucosa and the host immune system. Failure to achieve or maintain equilibrium between a host and its microbiota has the potential to induce chronic conditions with an underlying inflammatory component. Mechanisms by which intestinal microbes trigger inflammation include the alteration of intestinal permeability, activation of the host immune system and digestion of dietary antigens with a consequent repercussion on tolerance to food. Therefore, therapies modulating gut microbiota, including diet, antibiotics, probiotics and faecal transplantation have a potential in CeD and IBD. Probiotics are effective to treat pouchitis and faecal transplant for ulcerative colitis, but the evidence is less clear in Crohn's disease or CeD. SUMMARY: Diverse regulatory mechanisms cooperate to maintain intestinal homeostasis, and a breakdown in these pathways may precipitate inflammation. The role of microbiota inducing immune dysfunction and inflammation supports the therapeutic rationale of manipulating microbiota to treat chronic inflammatory conditions.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".