Exploring Increased Intestinal Lipid Absorption and Identifying Strategies to Improve Pork Quality in Low-Birth-Weight Swine
Bibliographic record
Abstract
Traditional swine production results in an increasing number of piglets born with low birth weight (LBW) due to intra-uterine competition and growth restriction. LBW piglets often have reduced growth rate compared with normal birth weight (NBW) littermates and can limit production return. We have previously established an LBW swine model of insulin resistance (IR) to study both complications of production as well as obesity-related dyslipidemia (FASEB 2019, PMID:31144992). LBW model exhibits increased intestinal lipid absorption and marbling in pork cuts under nutrition challenge. Additionally, there is emerging data on the nutritional benefits of full fat dairy on IR and associated impaired lipid metabolism. We sought to (1) investigate candidate mechanistic pathways responsible for increased intestinal lipid absorption in LBW swine; and (2) determine the effect of full fat dairy products on growth performance and pork quality in LBW swine. At 5 week of age, NBW piglets were randomly assigned to consume control or high fat (HF) diet; LBW piglets were randomly assigned to consume either HF diet or iso-caloric HF diet with 3 servings per 2000 kcal/day of full fat dairy products (HF + dairy). Five to eight piglets were allocated to each treatment group with a 7-week feeding period. Animals were euthanized at 12 week of age, and fasting blood, carcass and tissue samples were collected. CD36 protein expression was significantly higher in small intestine mucosal scrapings from LBW (0.90 ± 0.10) compared with NBW swine (0.50 ± 0.11) when fed a HF diet (p < 0.05). Adding dairy products significantly decreased subcutaneous fat depth (p < 0.05) and increased predicted lean yield % (p < 0.05), yet did not significantly change intestinal CD36 expression, pork quality (shear force, pH & color) or growth performance in HF-fed LBW swine. Data analysis is ongoing in order to assess the impact on lipid metabolism and pork marbling. Increased lipid absorption in response to a HF diet in an LBW swine model of IR is partially due to an increased intestinal expression of CD36. Dairy products potentially contribute to the greater lean yield %, which may improve the carcass grading index and compensate the economic loss in LBW swine. Agriculture Funding Consortium NSERC Discovery Program Dairy Farmers of Canada- Nutrition Research Program.
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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".