Phenotypic and functional aspects of the neonatal immune system as related to the maternal dietary fatty acid supply of sows
Bibliographic record
Abstract
The maternal-fetal transfer and subsequent uptake of sow milk enriched with n-6- or n-3-polyunsaturated fatty acids may not only influence neonatal body fat but may also have an impact on the immune function of newborn piglets. Sows were fed a diet containing sunflower oil as n-6-source or oil from seal blubber with long chain polyunsaturated n-3-fatty acids during pregnancy and lactation. Sow serum was investigated during pregnancy and serum and milk during lactation; piglet serum and liver were investigated in the suckling period until day 19. Piglet leukocyte subpopulations were characterised by flow cytometry and leukocyte proliferation was tested after stimulation with mitogens. No differences were noted in performance. The serum and milk fatty acid status of the sows was markedly influenced by the diet. Eicosapentaenoic acid (20:5n-3), 22:5n-3 and 22:6n-3 were higher (p < 0.001) in serum and liver of piglets delivered from sows fed the seal blubber oil. Piglets at birth had lower lymphocyte counts (p < 0.01) than piglets 19 days after birth. However, no influence of feeding the different oil sources was noted on lymphocyte phenotyping and leukocyte proliferation test. The results of the present study show that the maternal diet affected the fatty acid status of neonates, but much more in the sucking period. Immunological traits were not affected, probably as the mononuclear cell lineage is too immature around birth. Effects of PUFA n-3 might only be seen at a later time point or in the polymorphonuclear cell lineage as they were dominating right after birth.
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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".