Effects of increase in fish oil intake on intestinal eicosanoids and inflammation in a mouse model of colitis
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel diseases (IBD) are chronic intestinal inflammatory diseases affecting about 1% of western populations. New eating behaviors might contribute to the global emergence of IBD. Although the immunoregulatory effects of omega-3 fatty acids have been well characterized in vitro, their role in IBD is controversial. METHODS: The aim of this study was to assess the impact of increased fish oil intake on colonic gene expression, eicosanoid metabolism and development of colitis in a mouse model of IBD. Rag-2 deficient mice were fed fish oil (FO) enriched in omega-3 fatty acids i.e. EPA and DHA or control diet for 4 weeks before colitis induction by adoptive transfer of naïve T cells and maintained in the same diet for 4 additional weeks. Onset of colitis was monitored by colonoscopy and further confirmed by immunological examinations. Whole genome expression profiling was made and eicosanoids were measured by HPLC-MS/MS in colonic samples. RESULTS: A significant reduction of colonic proinflammatory eicosanoids in FO fed mice compared to control was observed. However, neither alteration of colonic gene expression signature nor reduction in IBD scores was observed under FO diet. CONCLUSION: Thus, increased intake of dietary FO did not prevent experimental colitis.
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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) | 0.002 | 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".