Mucosa-Associated Ileal Microbiota in New-Onset Pediatric Crohnʼs Disease
Bibliographic record
Abstract
BACKGROUND: The composition of the intestinal microbiome seems relevant to the pathogenesis of Crohn's disease (CD), with differences in both diversity and composition of the gut microbiota in patients with CD compared with healthy individuals. However, there are still conflicting reports on the importance of various bacterial taxa in the pathogenesis of CD. The aim of this study was to characterize the composition of mucosa-associated intestinal microbiota in newly diagnosed pediatric patients with CD. METHODS: Mucosa-associated bacteria were identified from ileal biopsy specimens obtained at colonoscopy of 10 patients with either ileal or ileocolonic new-onset CD and 15 controls without mucosal inflammation. Microbial composition was performed by profiling the 16S rDNA V6 region using Illumina sequencing. Samples were analyzed for differences in alpha/beta diversity and also for differentially abundant taxa. RESULTS: Alpha diversity did not differ between the controls and CD cases or between CD subjects with localized ileal disease compared with those with more extensive disease. Controls also did not clearly separate from patients with CD by principal coordinate analyses; however, 117 operational taxonomic units were found to be differentially abundant between the two groups. In particular, numerous operational taxonomic units associated with Faecalibacterium prausnitzii species were increased in children with CD. CONCLUSIONS: These findings contribute to emerging evidence regarding dysbiosis in pediatric CD, and provide additional evidence challenging the protective role of F. prausnitzii in CD.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".