Mixed Lipid, Fish Oil, and Soybean Oil Parenteral Lipids Impact Cholestasis, Hepatic Phytosterol, and Lipid Composition
Bibliographic record
Abstract
OBJECTIVES: In parenteral nutrition-dependent infants and children, intestinal failure (IF)-associated liver disease (IFALD) remains an important problem. A comparative study was undertaken of parenteral mixed lipid (ML), ω-3 predominant fish oil (FO), and ω-6 predominant soybean oil (SO) emulsions in regards to hepatic phytosterol, neutral lipid, fatty acid (FA) content, and the relationship to cholestasis in piglets. METHODS: Neonatal piglets received parenteral nutrition, varying in lipid dose (5 or 10 g· kg · day) and formulation: SO5 (n = 5), SO10 (n = 5), FO5 (n = 5), and ML10 (n = 5). On day 14, liver chemistry, bile flow, histology and neutral lipid staining were assessed. Hepatic triglyceride FA content was determined using thin layer and gas chromatography, and phytosterol content was assessed using gas chromatography-mass spectrometry. RESULTS: SO groups had higher prevalence of biochemical cholestasis (P < 0.04) and lower bile flow (P < 0.0001). Hepatic campesterol, stigmasterol, and β-sitosterol were highest in SO10 (P < 0.0001). Hepatic FA (P < 0.03) and ω-6/ω-3 FA ratio (P < 0.0001) were higher in the SO groups. Neutral lipid accumulation (P = 0.3) and liver histology (P = 0.16) were not different between groups. Univariate predictors of bile flow were: campesterol (r = -0.77, P = 0.001), β-sitosterol (r = -0.74, P = 0.002), stigmasterol (r = -0.74, P = 0.002), ω-6 FA (r = -0.72, P = 0.002), and ω-3 FA (r = 0.59, P = 0.02). Only campesterol independently predicted bile flow. CONCLUSIONS: ML and FO lipid emulsions reduce cholestasis in association with lowered hepatic phytosterol and lipid content. Lower hepatic phytosterol and ω-6 FA content, and higher ω-3 FA content are hepatoprotective. Multivariate analysis suggests reduced phytosterol accumulation may best explain the hepatoprotective effect of fish oil-containing lipids.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".