In parenteral nutrition–fed piglets, fatty acids vary by lipid emulsion and tissue sampled
Bibliographic record
Abstract
BACKGROUND: Children with intestinal failure without liver disease may be given soy-based lipid emulsion (SLE) or mixed lipid emulsion (MLE; containing soy, medium-chain triglyceride, olive, and/or fish oils). Both differ in essential fatty acid content: MLE has added arachidonic acid (AA) and docosahexaenoic acid (DHA). The aim of this study, in neonatal piglets, was to compare serum and tissue fatty acid composition when the emulsions were given at unrestricted doses. METHODS: We compared SLE (n = 15) and MLE (n = 15) at doses of 10-15 g/kg/day in parenteral nutrition (PN). On day 14 we collected serum and tissues. Using gas-liquid chromatography, percentage fatty acids were measured in serum, brain, and liver phospholipid. Comparisons were made to reference values from litter-matched controls (n = 8). RESULTS: Comparing median values, linoleic acid (LA) was lower for MLE vs SLE in serum (-27%), liver (-45%), and brain (-33%) (P < 0.001). AA was lower for MLE in serum (-25%), liver (-40%), and brain (-10%). DHA was higher for MLE in serum (+50%), liver (+200%), and brain (+10%). AA levels were lower for MLE vs control piglets in serum (-81%), liver (-63%), and brain (-9%). DHA levels were higher in serum (+41%), liver (+38%), and brain (+19%). CONCLUSION: This study in piglets has shown that, at unrestricted doses, MLE treatment is associated with low serum and tissue AA compared with SLE and healthy litter-matched controls. Although not yet proven, low tissue AA levels may have functional consequences, and these data support current practice avoiding MLE dose restriction.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".