Supplemental Parenteral Vitamin E Into Conventional Soybean Lipid Emulsion Does Not Prevent Parenteral Nutrition–Associated Liver Disease in Full‐Term Neonatal Piglets
Bibliographic record
Abstract
BACKGROUND: Parenteral nutrition-associated liver disease (PNALD) continues to cause morbidity and mortality for neonates with intestinal failure. Lipid peroxidation is one potential etiological factor. This study was designed to test if supplementing vitamin E into conventional soy-based lipid would reduce the risk of PNALD. METHODS: Sixteen piglets, aged 2-5 days and weighing 1.8-2.5 kg, were randomized to parenteral nutrition (PN) with soy lipid (SO, n = 8) or the same lipid plus α-tocopherol, the most bioactive form of vitamin E (SO+E, n = 8). After 17 days, bile flow, liver chemistry, gene expression associated with bile acid metabolism, and bile acid composition were assessed. C-reactive protein (CRP) and oxidative stress markers, including plasma 8-isoprostane, were measured. All results were compared with a sow-reared control group (CON). RESULTS: Comparing PN-treated groups, SO vs SO+E mean bile flow (5.91 vs 5.54 µL/g liver; P = .83), serum bile acid concentration (39.2 vs 26.6 µmol/L; P = .12), and total bilirubin (35.2 vs 26.9 µmol/L; P = .56) were not different. Gene expression related to bile acid metabolism and bile composition was not different between PN groups. There was no difference in CRP (41.8 vs 36.8 µg/mL; P = .22) or in plasma 8-isoprostane (27.9 vs 26.1 pg/mL; P = .77). CONCLUSIONS: In term neonatal piglets, supplemental vitamin E did not prevent cholestasis. Additional vitamin E was not associated with reduced inflammation or oxidative stress. The benefit of supplementing vitamin E into conventional lipid, vs adding fish oil, to prevent early onset of PNALD requires further clarification.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".