Induction of Inflammatory Bowel Disease Through Activation of Immune System Against Enteric Bacteria
Bibliographic record
Abstract
AIM: Current investigations have focused on mechanisms of inflammation in inflammatory bowel disease (IBD). The gut bacteria play an important role in the pathogenesis of IBD, however due to the complexity of gut microflora some skepticisms still remain. Most of currently animal models of colitis are mainly based on bowel mucosal damage which has some limitation in terms of dissimilarity to human IBD. In the present study, a new model based on defined bacterial infections has been developed and tested. METHODS: Seven groups of six rats were involved; normal, positive control which received trinitrobenzenesulfonic acid enema, Adjuvant + Ethanol 30% enema, Adjuvant + Ethanol 20% enema, Adjuvant + Ethanol 10% enema, Ethanol 30% enema and Adjuvant + Ethanol 30% enema which treated with 5/mg/kg/day infliximab. We administered two courses of Freund's complete adjuvant mixed with inactivated total enteric bacteria, then various percentages of ethanol enema used as a barrier breaker to expose the host immune system to its own flora. Colonic status was investigated two weeks after enemas. Macroscopic, histological and biochemical analyses were performed on samples. RESULTS: Ethanol 30% enema in vaccinated rats caused histological damage and resulted in a significant rise of TNF-α, IL-1, IL-17, myeloperoxidase activity, and oxidative stress biomarkers in comparison to Sham. CONCLUSION: This model is an immunogenic and reliable model, which demonstrates microscopic and macroscopic characteristics more similar to human IBD. These findings introduce a novel experimental IBD model and shed light on disease pathogenesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".