The impact of exogenous vasoactive intestinal polypeptide on inflammatory responses and mRNA expression of tight junction genes in lambs fed a high-grain diet
Bibliographic record
Abstract
This study assessed the impact of administering vasoactive intestinal polypeptide (VIP) on inflammation and intestinal VIP and tight junction mRNA expression in lambs fed grain-based finishing diets. Sixteen wether lambs (69.6 ± 1.9 kg) were individually housed, adapted to a corn-based diet containing no forage, and randomly assigned to 2 treatment groups. Lambs were intraperitoneally injected every other day for 28 d with either saline (0.9% NaCl) with no VIP (n = 8; control) or saline with VIP (n = 8; 1.3 nmol/kg BW). Blood samples were collected weekly for analysis of cytokine concentrations, and on days 0 and 28 for lipopolysaccharide (LPS), and LPS-binding protein (LBP) concentrations. Upon completion of the treatment period, lambs were euthanized and gastrointestinal tissues, including rumen, jejunum, cecum, and colon samples, were collected for analysis of the expression of tight junction mRNA (claudin-1, claudin-4, occludin, and ZO-1), endogenous VIP, and VIP receptor (VPAC-1). No treatment effects (P ≥ 0.38) were observed for VIP and VPAC-1 mRNA expression in the colon. Supplementation with VIP did not influence (P ≥ 0.28) the expression of claudin-1, claudin-4, occludin, and ZO-1 tight junction mRNA in the rumen, jejunum, cecum, and colon. Lambs treated with VIP had greater (P ≤ 0.01) plasma concentrations of the anti-inflammatory cytokines, IL-10 and IL-36RA. There were treatment-by-day interactions observed (P ≤ 0.02) for concentrations of the pro-inflammatory cytokines, MIP-1α and MIP-1β. Lambs that did not receive VIP had greater serum concentrations of LPS (P = 0.05) than the lambs receiving VIP. These data suggest that VIP administration may not influence tight junction mRNA expression but may decrease LPS concentrations and thus inflammation in lambs fed a grain-based diet.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".