Connecting the Dots Between Inflammatory Bowel Disease and Metabolic Syndrome: A Focus on Gut-Derived Metabolites
Bibliographic record
Abstract
The role of the microbiome in health and disease has gained considerable attention and shed light on the etiology of complex diseases like inflammatory bowel disease (IBD) and metabolic syndrome (MetS). Since the microorganisms inhabiting the gut can confer either protective or harmful signals, understanding the functional network between the gut microbes and the host provides a comprehensive picture of health and disease status. In IBD, disruption of the gut barrier enhances microbe infiltration into the submucosae, which enhances the probability that gut-derived metabolites are translocated from the gut to the liver and pancreas. Considering inflammation and the gut microbiome can trigger intestinal barrier dysfunction, risk factors of metabolic diseases such as insulin resistance may have common roots with IBD. In this review, we focus on the overlap between IBD and MetS, and we explore the role of common metabolites in each disease in an attempt to connect a common origin, the gut microbiome and derived metabolites that affect the gut, liver and pancreas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".