DNBS/TNBS Colitis Models: Providing Insights Into Inflammatory Bowel Disease and Effects of Dietary Fat
Bibliographic record
Abstract
Inflammatory Bowel Diseases (IBD), including Crohn's Disease and Ulcerative Colitis, have long been associated with a genetic basis, and more recently host immune responses to microbial and environmental agents. Dinitrobenzene sulfonic acid (DNBS)-induced colitis allows one to study the pathogenesis of IBD associated environmental triggers such as stress and diet, the effects of potential therapies, and the mechanisms underlying intestinal inflammation and mucosal injury. In this paper, we investigated the effects of dietary n-3 and n-6 fatty acids on the colonic mucosal inflammatory response to DNBS-induced colitis in rats. All rats were fed identical diets with the exception of different types of fatty acids [safflower oil (SO), canola oil (CO), or fish oil (FO)] for three weeks prior to exposure to intrarectal DNBS. Control rats given intrarectal ethanol continued gaining weight over the 5 day study, whereas, DNBS-treated rats fed lipid diets all lost weight with FO and CO fed rats demonstrating significant weight loss by 48 hr and rats fed SO by 72 hr. Weight gain resumed after 72 hr post DNBS, and by 5 days post DNBS, the FO group had a higher body weight than SO or CO groups. Colonic sections collected 5 days post DNBS-treatment showed focal ulceration, crypt destruction, goblet cell depletion, and mucosal infiltration of both acute and chronic inflammatory cells that differed in severity among diet groups. The SO fed group showed the most severe damage followed by the CO, and FO fed groups that showed the mildest degree of tissue injury. Similarly, colonic myeloperoxidase (MPO) activity, a marker of neutrophil activity was significantly higher in SO followed by CO fed rats, with FO fed rats having significantly lower MPO activity. These results demonstrate the use of DNBS-induced colitis, as outlined in this protocol, to determine the impact of diet in the pathogenesis of IBD.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".