Rearing environment affects development of the immune system in neonates
Bibliographic record
Abstract
Early-life exposure to appropriate microbial flora drives expansion and development of an efficient immune system. Aberrant development results in increased likelihood of allergic disease or increased susceptibility to infection. Thus, factors affecting microbial colonization may also affect the direction of immune responses in later life. There is a need for a manipulable animal model of environmental influences on the development of microbiota and the immune system during early life. We assessed the effects of rearing under low- (farm, sow) and high-hygiene (isolator, milk formula) conditions on intestinal microbiota and immune development in neonatal piglets, because they can be removed from the mother in the first 24 h for rearing under controlled conditions and, due to placental structure, neither antibody nor antigen is transferred in utero. Microbiota in both groups was similar between 2 and 5 days. However, by 12-28 days, piglets reared on the mother had more diverse flora than siblings reared in isolators. Dendritic cells accumulated in the intestinal mucosa in both groups, but more rapidly in isolator piglets. Importantly, the minority of 2-5-day-old farm piglets whose microbiota resembled that of an older (12-28-day-old) pig also accumulated dendritic cells earlier than the other farm-reared piglets. Consistent with dendritic cell control of T cell function, the effects on T cells occurred at later time-points, and mucosal T cells from high-hygiene, isolator pigs made less interleukin (IL)-4 while systemic T cells made more IL-2. Neonatal piglets may be a valuable model for studies of the effects of interaction between microbiota and immune development on allergy.
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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 | 0.001 |
| 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".