Intestinal responsiveness to experimental colitis in young rats is altered by maternal diet
Bibliographic record
Abstract
Increasing evidence suggests that fetal and neonatal nutrition impacts later health. Aims of the present study were to determine the effect of maternal dietary fat composition on intestinal phospholipid fatty acids and responsiveness to experimental colitis in suckling rat pups. Female rats were fed isocaloric diets varying only in fat composition throughout gestation and lactation. The oils used were high (8%) in n-3 [canola oil (18:3n-3)], n-6 (72%) [safflower oil (18:2n-6)], or n-9 (78%) [high oleic acid safflower oil (18:1n-9)] fatty acids, n = 6/group. Colitis was induced on postnatal day 15 by intrarectal 2,4-dinitrobenzene sulfonic acid (DNBS) administration with vehicle (50% ethanol) and procedure (0.9% saline) controls. Jejunal and colonic phospholipids and milk fatty acids were determined. The distal colon was assessed for macroscopic damage, histology, and MPO activity. The 18:2n-6 maternal diet increased n-6 fatty acids, whereas the 18:3n-3 diet increased n-3 fatty acids in milk and pup jejunal and colonic phospholipids. Maternal diet, milk, and pup intestinal n-6-to-n-3 fatty acid ratios increased significantly in order: high 18:3n-3 < high 18:1n-9 < high 18:2n-6. DNBS administration in pups in the high 18:2n-6 group led to severe colitis with higher colonic damage scores and MPO activity than in the 18:1n-9 and 18:3n-3 groups. High maternal dietary 18:3n-3 intake was associated with colonic damage scores and MPO activity, which were not significantly different from ethanol controls. We demonstrate that maternal dietary fat influences the composition of intestinal lipids and responsiveness to experimental colitis in nursing offspring.
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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) | 0.000 | 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 | 0.000 | 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".