Fatty acid composition in feeds and plasma of Canadian premature infants
Bibliographic record
Abstract
The objective of this exploratory study was to investigate how the fatty acid (FA) composition of different food sources for preterm infants including: breast milk (BM), formula (F), human milk fortifiers (HMFs) and total parenteral nutrition (TPN) impacted preterm infant's plasma FA. The associations between FA content of plasma with antioxidant enzyme activity and cognition were also evaluated. Methods Thirty‐two premature infants were included in this study. Five different feeds (BM, F, BM + F, BM + HMF and TPN) were provided. Foods and preterm infant plasma samples were collected at the same time on the same day biweekly where possible. Separation and identification of the plasma and food FA methyl esters were performed by gas‐liquid chromatography. Antioxidant enzymes were measured. The Bayley Scale of Infant Development version III was used to evaluate cognition. Results In food sources, BM contained significantly lower oleic acid (C18:1n9) (p<0.01), linoleic acid (C18:2n6) (p<0.01), a‐linoleic acid (C18:3n3) (p<0.01), arachidonic acid (AA) (C20:4n6) (p<0.05) and docosahexaenoic acid (DHA) (C22:6n3) (p<0.05) compared with the F. Palmitic acid (C16:0) was significantly higher (p<0.05) in the BM + HMF compared with the BM. Stearic acid (C18:0) was significantly higher (p<0.05) in the BM + F and BM + HMF compared with the BM. In the plasma lauric acid (C12:0) (p<0.05) and myristic acid (C14:0) (p<0.001) were higher in the BM fed babies compared to the F and TPN fed groups. Antioxidant enzymes, activities and cognition scores did not differ by feeding groups, however the study may not have been powered to detect these differences. Conclusion The type, and therefore quality, of fatty acids that are fed to premature infants is an important consideration as differences in feed fatty acids were seen in some plasma fatty acids in the study. Support or Funding Information CIHR
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".