Modulation of the Plasma Lipidomic Profile in Piglets Fed Polar Lipid-Rich Diets
Bibliographic record
Abstract
Background: Polar lipids from dairy are novel sources of energy that may replace other dietary lipids and impact plasma lipidomic profiles in piglets. This study evaluated the impact of feeding diets rich in polar lipids on the plasma lipidome of piglets during the weaning period. Material and Methods: Weaned male piglets (n = 240; 21 days of age; 6.3 ± 0.5 kg of BW) were blocked by initial weight and distributed into 48 pens of five animals each in a complete randomized block design with a 2 × 3 factorial arrangement of treatments as follows: a plant-based diet rich in neutral lipids from soybeans (24 pens; SD) or a polar lipid-rich diet by-product of cheese making (24 pens; PD) from weaning until the 21st day of the nursery phase. Within each diet group, animals received one of three milk replacers (MR; 0.5 L/d/animal) for the first 7 days after weaning: (1) commercial MR containing animal and coconut lipids (CO); (2) polar lipid-based MR (PO); or (3) soybean lipids-based MR (SO). Results: The PD diet group increased the plasma concentrations of sphingolipids, phospholipids, and cholesterol esters, but did not impact the concentrations of glycerolipids (GLs). Both the PO and CO milk replacers increased the plasma concentrations of ceramide, acyl-chain phosphatidyl choline, and cholesterol esters. The plasma concentrations of GLs containing 18-carbon fatty acids such as 18:0, 18:1, 18:2, and 18:3, were higher in SD, whereas GLs containing 16:0 and 20:3 were higher in PD. Conclusions: In summary, the diet lipid type significantly modulated the plasma lipid composition in piglets 7 days after weaning. The dietary inclusion of polar lipids in diets for growing pigs can modulate the plasma lipidomic profile, relative to plant-based diets rich in soybean lipids. Cost may be a major consideration when using these lipids in pig diets. Their health benefits need to be further characterized in other models of stress and inflammation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".