The importance of the timing of microbial signals for perinatal immune system development
Bibliographic record
Abstract
Background: Development and maturation of the immune system begin in utero and continue throughout the neonatal period. Both the maternal and neonatal gut microbiome influence immune development, but the relative importance of the prenatal and postnatal periods is unclear. Methods: In the present study, we characterized immune cell populations in mice in which the timing of microbiome colonization was strictly controlled using gnotobiotic methodology. Results: Compared to conventional (CONV) mice, germ-free (GF) mice conventionalized at birth (EC mice) showed few differences in immune cell populations in adulthood, explaining only 2.36% of the variation in immune phenotypes. In contrast, delaying conventionalization to the fourth week of life (DC mice) affected seven splenic immune cell populations in adulthood, including dendritic cells and regulatory T cells (Tregs), explaining 29.01% of the variation in immune phenotypes. Early life treatment of DC mice with Limosilactobacillus reuteri restored splenic dendritic cells and Tregs to levels observed in EC mice, and there were strain-specific effects on splenic CD4+ T cells, CD8+ T cells, and CD11c+ F4/80+ mononuclear phagocytes. Conclusion: This work demonstrates that the early postnatal period, compared to the prenatal period, is relatively more important for microbial signals to influence immune development in mice. Our findings further show that targeted microbial treatments in early life can redress adverse effects on immune development caused by the delayed acquisition of the neonatal gut microbiome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".