Parenteral Soy Oil and Fish Oil Emulsions
Bibliographic record
Abstract
BACKGROUND: Parenteral nutrition (PN)-associated liver disease (PNALD) remains a significant cause of morbidity and mortality for neonates dependent on PN. Total fat emulsion dose and composition, particularly the large amount of ω-6 long-chain polyunsaturated fatty acids in plant oils, have been proposed as risk factors for PNALD. We hypothesized restriction of the dose of emulsion would prevent PNALD, regardless of the composition, but growth could be compromised. METHODS: Using a neonatal piglet model, we compared conventional soy oil emulsion (Intralipid), dosed high (SO10, n = 8: 10 g/kg/d) and low (SO5, n = 6: 5 g/kg/d), with fish oil (Omegaven), dosed low (FO5, n = 8: 5 g/kg/d). Piglets were given isonitrogenous PN for 14 days. The normal range for all parameters was determined by measurement in equivalent aged sow-reared piglets. RESULTS: Bile flow was lower with high-dose Intralipid, outside the normal range, while higher for the other groups (SO10, 5.4 µg/g; SO5, 8.6 µg/g; FO5, 13.4 µg/g; P = .010; normal range, 6.5-12.2 µg/g). Total body weight was low in all treatment groups (SO10, 4.4 kg; SO5, 4.5 kg; FO5, 5.0 kg; P = .038; normal range, 5.2-7.3 kg). Brain weight was not different between groups (SO10, 40.3 g; SO5, 36.0 g; FO5, 36.6 g; P = .122; normal range, 41.8-51.4 g). Corrected for body weight, brain weight was lowest in the fish oil group (SO10, 9.3 g/kg; SO5, 8.0 g/kg; FO5, 7.3 g/kg; P < .001; normal range, 5.9-9.0 g/kg). CONCLUSION: Low-dose fat emulsions reduce the risk of developing PNALD. Further investigation of the risk to brain development in neonates exposed to dose restriction, particularly with fish oil, is required.
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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 | 0.001 |
| 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".