Metabolite profiling in assessing ulcerative colitis activity: A systematic review
Bibliographic record
Abstract
Background: Ulcerative colitis (UC) is an immune-mediated chronic inflammatory condition of the colon, characterized by defects in the intestinal epithelial barrier, dysbiosis of the microbiota, and immune dysregulation. Metabolite profile has been widely and successfully used to characterize patient features in UC, as the development of metabolomics technology. Specific combinations of small metabolites can accurately depict the real-time pathological state of the body. Previous systematic reviews have focused on metabolite analysis between UC patients and healthy individuals, but have not systematically evaluated metabolite changes in different disease stages. This study focused on distinguish between patients in active and inactive phases, and even have the potential to predict changes in disease activity. Aim: To summarize the distinct metabolites between the active and remission phases in serum and colonic mucosa in patients with UC. Methods: A comprehensive literature search was conducted in PubMed, Embase, the Cochrane Library, Web of Science, WanFang Data, and China National Knowledge Infrastructure from 1995 to 2022. Studies were selected which included metabolomics detection on serum or mucosal samples from patients with active or remission phase UC. The disease activity was assessed by using the Mayo score, Ulcerative colitis activity index score, or Geboes score. The risk of bias was assessed using the Newcastle-Ottawa Scale. Results: Eleven articles (10 in English and 1 in Chinese) and 357 patients were included. Qualitative analysis was performed according to the classification of gas chromatography/mass spectrometry, liquid chromatography/mass spectrometry, or nuclear magnetic resonance. In the active period of UC, metabolites such as lipids, Amino acids showed a certain trend of change. Arachidonic acid showed specific upregulation in both serum and mucosal samples during the active stage in patients with UC. Conclusion: There exists an association between metabolite profile and disease activity in patients with UC. Especially in patients with active UC, the lipid metabolite (arachidonic acid) is highly expressed simultaneously in the serum and mucosa. This finding will identify small molecule biomarkers that may potentially replace colonoscopy in the assessment and prediction of UC disease activity in the future, which indicates a significant potential for biomarker development.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".