Antagonizing Arachidonic Acid-Derived Eicosanoids Reduces Inflammatory Th17 and Th1 Cell-Mediated Inflammation and Colitis Severity
Bibliographic record
Abstract
During colitis, activation of two inflammatory T cell subsets, Th17 and Th1 cells, promotes ongoing intestinal inflammatory responses. n-6 polyunsaturated fatty acid- (PUFA-) derived eicosanoids, such as prostaglandin E2 (PGE2), promote Th17 cell-mediated inflammation, while n-3 PUFA antagonize both Th17 and Th1 cells and suppress PGE2 levels. We utilized two genetic mouse models, which differentially antagonize PGE2 levels, to examine the effect on Th17 cells and disease outcomes in trinitrobenzene sulfonic acid- (TNBS-) induced colitis. Fat-1 mice contain the ω3 desaturase gene from C. elegans and synthesize n-3 PUFA de novo, thereby reducing the biosynthesis of n-6 PUFA-derived eicosanoids. In contrast, Fads1 Null mice contain a disrupted Δ5 desaturase gene and produce lower levels of n-6 PUFA-derived eicosanoids. Compared to Wt littermates, Fat-1 and Fads1 Null mice exhibited a similar colitic phenotype characterized by reduced colonic mucosal inflammatory eicosanoid levels and mRNA expression of Th17 cell markers (IL-17A, RORγτ, and IL-23), decreased percentages of Th17 cells and, improved colon injury scores (P ≤ 0.05). Thus, during colitis, similar outcomes were obtained in two genetically distinct models, both of which antagonize PGE2 levels via different mechanisms. Our data highlight the critical impact of n-6 PUFA-derived eicosanoids in the promotion of Th17 cell-mediated colonic inflammation.
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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 | 0.002 |
| 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".