Acute dextran sulfate sodium (DSS)‐induced colitis promotes gut microbial dysbiosis in mice
Bibliographic record
Abstract
UNLABELLED: The most widely used and characterized experimental model of ulcerative colitis (UC) is the epithelial erosion, dextran sulfate sodium (DSS)-induced colitis, which is developed by administration of DSS in drinking water. We investigated fecal and colonic mucosa microbial composition and functional changes in mice treated with DSS. C57Bl/6 mice received 5% DSS in drinking water for 5 days. Inflammation was evaluated clinically and by analysis of colonic tissue cytokine levels and C-reactive protein (CRP) in the serum. Colonic mucosa and fecal samples were used for DNA extraction and the V4 region of bacterial 16S rRNA gene was subjected to MiSeq Illumina sequencing. Alpha- and beta-diversities, and compositional differences at phylum and genus levels were determined, and bacterial functional pathways were predicted. DSS increased disease severity, serum CRP and cytokines IL-1β and IL-6, but decreased bacterial species richness, and shifted bacterial community composition. Bacteroides, Turicibacter, Escherichia, Clostridium, Enterobacteriaceae, Clostridiaceae, Bacteroidaceae, Bacteroidales, among other taxa were associated with DSS treatment in fecal and colonic samples. Also, DSS altered microbial functional pathways in both colonic mucosa and fecal samples. CONCLUSIONS: The development of colitis in DSS model was accompanied with reduced microbial diversity and dysbiosis of gut microbiota at lower taxonomical levels.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".