Health Benefits of Supplementing Nursery Pig Diets with Microalgae or Fish Oil
Bibliographic record
Abstract
Weaning stress can negatively impact a pig's performance; dietary supplementation with omega-3 polyunsaturated fatty acids (n-3 PUFA) reduces inflammatory stress and promotes nursery pig's health and growth. Fish oil (FO) is a major source of n-3 PUFA; however, microalgae (AL) may provide an alternative source of n-3 PUFA. The aim of this study was to assess the health benefits of supplementing a plant protein-based nursery diet with 3.12% AL or 1.25% FO providing equal total n-3 PUFA compared to a control (CON) diet. Seventy-two pigs were fed experimental diets for three weeks (phases 1 and 2), followed by a common standard diet for three weeks (phase 3). Following phase 2, 8 pigs per treatment underwent a lipopolysaccharide (LPS) immune stress challenge to assess the acute-phase response and 8 pigs per treatment were vaccinated with novel antigens to assess acquired immunity. No significant differences in piglets' growth were observed, despite decreased feed intake in FO piglets compared to AL piglets in phase 3. AL supplementation tended to reduce, and FO supplementation significantly reduced the LPS-induced fever response. The AL pigs had significantly reduced cortisol responses, increased cytokine concentrations, and increased chromogranin A concentrations compared to FO and CON pigs following LPS challenge. Results suggest that AL or FO supplementation in nursery diets differentially modulate the acute-phase response, possibly due to different n-3 PUFA profiles between the two ingredients.
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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".