Novel complementary strategies for the management of consistent gastrointestinal symptoms of Celiac disease
Bibliographic record
Abstract
Celiac disease (CD) is a chronic autoimmune disorder of the small intestine triggered by gluten consumption in genetically predisposed individuals. While a strict lifelong gluten-free diet (GFD) is the primary management strategy, adherence to GFD is challenging due to the ubiquity of gluten, risks of cross-contamination, and inferior nutrition. Additionally, many patients experience persistent gastrointestinal (GI) symptoms despite strict GFD compliance. Functional foods and nutraceuticals, known for their health benefits beyond basic nutrition, have shown potential in alleviating CD-related issues such as GI symptoms, gut dysbiosis, intestinal inflammation, gut barrier dysfunction, and associated nutritional deficits. This review explores the role of functional foods and nutraceuticals, including low FODMAP diets, anti-inflammatory diets, non-gluten cereals and pseudocereals, gluten sequestrants, probiotics, prebiotics, synbiotics, postbiotics, as well as digestive enzymes, transglutaminase 2 inhibitors, modified gluten products, and other emerging agents, as complementary strategies to enhance GFD efficacy and prevent or ameliorate persistent GI symptoms in CD patients. By synthesizing evidence from preclinical and clinical studies, the mechanisms and therapeutic potential of these interventions in addressing persistent symptoms in CD and related gluten disorders are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.005 | 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".