Invasive potential of gut mucosa-derived fusobacterium nucleatum positively correlates with IBD status of the host
Bibliographic record
Abstract
BACKGROUND: Fusobacterium nucleatum is a heterogeneous oral pathogen that is also a common resident of the human gut mucosa. Given that some strains of F. nucleatum are known to be invasive and proinflammatory in the oral mucosa, we compared strains isolated from patients with inflammatory bowel disease (IBD) with strains isolated from healthy controls to determine 1) whether this species was more commonly associated with IBD patients; and 2) whether gut-derived F. nucleatum strains from IBD patients showed an increased capacity for invasion. METHODS: Biopsy material was obtained from 56 adult patients undergoing colonoscopy for colon cancer screening purposes or assessment of irritable bowel syndrome status (34 patients), or to assess for presence of gastrointestinal disease (i.e., IBD or indeterminate colitis, 22 patients). We enumerated Fusobacterium spp. strains isolated from human gut biopsy material in a blinded fashion, and then compared the virulence potential of a subset of F. nucleatum strains using an invasion assay in a Caco-2 model system. RESULTS: Fusobacterium spp. were isolated from 63.6% of patients with gastrointestinal disease compared to 26.5% of healthy controls (P = 0.01). In total, 69% of all Fusobacterium spp. recovered from patients were identified as F. nucleatum. F. nucleatum strains originating from inflamed biopsy tissue from IBD patients were significantly more invasive in a Caco-2 cell invasion assay than strains that were isolated from healthy tissue from either IBD patients or control patients (P < 0.05 to 0.001). CONCLUSIONS: This study indicates that colonization of the intestinal mucosa by highly invasive strains of F. nucleatum may be a useful biomarker for gastrointestinal disease.
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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 | 0.000 | 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) | 0.002 | 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".