Dietary α‐linolenic acid increases the n−3 PUFA content of sow's milk and the tissues of the suckling piglet
Bibliographic record
Abstract
alpha-Linolenic acid (18:3n-3) is a precursor to DHA (22:6n-3), which is essential for normal growth and development in the infant. This study was undertaken to assess how a raised 18:3n-3 intake in sows affects the n-3 PUFA content of the suckling piglet. Sows consumed a high-18:3n-3 or control diet (n-3 PUFA/n-6 PUFA, 0.5 vs. 0.05, respectively) for 10 d prior to parturition and for 14 d postpartum. Piglets suckled from their mothers until 14 d of age, when they were sacrificed. Sows consuming the high-18:3n-3 diet had 141% more 18:3n-3 and 86% more 22:6n-3 in their milk compared to control sows. There was no difference in the proximate composition of the piglets. The n-3/n-6 PUFA ratio was 82% higher in the milk of sows consuming the high-18:3n-3 diet compared to controls. Piglets suckling from sows consuming the high-18:3n-3 diet had 423% more 18:3n-3 in the carcass as well as a 460% higher n-3/n-6 PUFA ratio than controls. The piglets suckling from sows consuming the high-18:3n-3 diet had 333% more 18:3n-3 and 54% more 22:6n-3 in the liver, as well as a 114% higher n-3/n-6 ratio than control piglets. Piglets suckling from sows consuming a high-18:3n-3 diet also had 24% more 22:6n-3 and a 33% higher n-3/n-6 ratio in the brain compared to control piglets. A high 18:3n-3 intake in the sow increases not only the 18:3n-3 but also the 22:6n-3 content of sow's milk and the tissues of the suckling piglet.
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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 | 0.001 |
| 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".