Intrarectal Instillation of Clostridium difficile Toxin A Triggers Colonic Inflammation and Tissue Damage: Development of a Novel and Efficient Mouse Model of Clostridium difficile Toxin Exposure
Bibliographic record
Abstract
Clostridium difficile, a major cause of hospital-acquired diarrhea, triggers disease through the release of two toxins, toxin A (TcdA) and toxin B (TcdB). These toxins disrupt the cytoskeleton of the intestinal epithelial cell, increasing intestinal permeability and triggering the release of inflammatory mediators resulting in intestinal injury and inflammation. The most prevalent animal model to study TcdA/TcdB-induced intestinal injury involves injecting toxin into the lumen of a surgically generated "ileal loop." This model is time-consuming and exhibits variability depending on the expertise of the surgeon. Furthermore, the target organ of C. difficile infection (CDI) in humans is the colon, not the ileum. In the current study, we describe a new model of CDI that involves intrarectal instillation of TcdA/TcdB into the mouse colon. The administration of TcdA/TcdB triggered colonic inflammation and neutrophil and macrophage infiltration as well as increased epithelial barrier permeability and intestinal epithelial cell death. The damage and inflammation triggered by TcdA/TcdB isolates from the VPI and 630 strains correlated with the concentration of TcdA and TcdB produced. TcdA/TcdB exposure increased the expression of a number of inflammatory mediators associated with human CDI, including interleukin-6 (IL-6), gamma interferon (IFN-γ), and IL-1β. Finally, we were able to demonstrate that TcdA was much more potent at inducing colonic injury than was TcdB but TcdB could act synergistically with TcdA to exacerbate injury. Taken together, our data indicate that the intrarectal murine model provides a robust and efficient system to examine the effects of TcdA/TcdB on the induction of inflammation and colonic tissue damage in the context of human CDI.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".