P0077 Identification of symbiote candidates for pouchitis in patients with ulcerative colitis
Bibliographic record
Abstract
Abstract Background Ulcerative colitis (UC) has been recognized as a life-long inflammatory disease. Although several novel treatments for UC has been developed, medication-uncontrollable UC patients require the surgical treatment. The surgical operation could improve the quality of life of the patients, but requires intensive medical following, because more than 40% develop to pouchitis. We have explored the symbiote candidates for Ileoanal pouch through comprehensive microbiome and metabolome analysis to prove the mechanism of pouchitis. Methods The fecal samples in patients with or without pouchitis were collected. 16S rRNA amplicon meta-analysis and metabolome analysis for 170 patients were performed. Results The alfa diversity in microbiome was significantly decreased with developing pouchitis. Several bacterial genera which include Lachnospiraceae, Bifidobacteriaceae, Prevotellaceae, Clostridiaceae, Ruminococcaceae, and Veillonellaceae were statistically reduced in correlation with inflammatory clinical score and were shown having significant relation with protective metabolites. In addition, the extent of decrease in these candidates was strikingly prominent in medication-refractory pouchitis. Additionally, some pouchitis revealed the increasing of Enterobacteriaceae, unclassified Lactobacillas, or Propionibacteriaceae. Conclusion Thus, our data show these bacterial taxa as symbiote candidates and could be attractive targets for maintenance of Ileal pouch in UC.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".