MAG-EPA reduces severity of DSS-induced colitis in rats
Bibliographic record
Abstract
Ulcerative colitis (UC) is a chronic disease characterized by diffuse inflammation of the intestinal mucosa of the large bowel. Omega-3 (ω3) fatty acid supplementation has been associated with a decreased production of inflammatory cytokines involved in UC pathogenesis. The aim of this study was to determine the preventive and therapeutic potential of eicosapentaenoic acid monoglyceride (MAG-EPA) in an in vivo rats model of UC induced by dextran sulfate sodium (DSS). DSS rats were untreated or treated per os with MAG-EPA. Morphological, histological, and biochemical analyses were performed following MAG-EPA administrations. Morphological and histological analyses revealed that MAG-EPA pretreatment (12 days pre-DSS) and treatment (6 days post-DSS) exhibited strong activity in reducing severity of disease in DSS rats. Following MAG-EPA administrations, tissue levels of the proinflammatory cytokines TNF-α, IL-1β, and IL-6 were markedly lower compared with rats treated only with DSS. MAG-EPA per os administration decrease neutrophil infiltration in colon tissues, as depicted by myelohyperoxidase activity. Results also revealed a reduced activation of NF-κB pathways correlated with a decreased expression of COX-2 in colon homogenates derived from MAG-EPA-pretreated and treated rats. Tension measurements performed on colon tissues revealed that contractile responses to methacholine and relaxing effect induced by sodium nitroprusside were largely increased following MAG-EPA treatment. The combined treatment of MAG-EPA and vitamin E displayed an antagonistic effect on anti-inflammatory properties of MAG-EPA in DSS rats.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".