144 Pre-programming of the immune system to enhance immunological capacity of offspring
Bibliographic record
Abstract
Livestock experience different forms of immune system stimulation (ISS) during their production cycle including microbial infection, vaccination, and tissue trauma. The release of pro-inflammatory cytokines during ISS activates the hypothalamic-pituitary-adrenal (HPA) axis or “stress axis”, which regulates metabolism and the immune response during ISS to restore physiological homeostasis. When ISS occurs during pregnancy, it can later cause programming of the immature fetal neuroendocrine-immune system. It is hypothesized that this plasticity in neuroendocrine-immune programming allows the fetus to adapt to its post-natal environment; however, risk of adulthood disease may also increase if the newborn is not appropriately matched to its novel environment. Bacterial lipopolysaccharide (LPS) endotoxin is an ISS that is commonly used by immunologists to simulate and study the host response to bacterial infection. When LPS was administered to sheep and pigs during late pregnancy, and the dams were consuming diets containing different n3 and n6 polyunsaturated fatty acid (PUFA) profiles, we observed long-term changes to various offspring health-related phenotypes. This presentation will highlight the immunological changes that were observed, and the health implications of these changes will be discussed.
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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) | 0.003 | 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".