Intestinal Microbial Diversity during Early-Life Colonization Shapes Long-Term IgE Levels
Bibliographic record
Abstract
Microbial exposure following birth profoundly impacts mammalian immune system development. Microbiota alterations are associated with increased incidence of allergic and autoimmune disorders with elevated serum IgE as a hallmark. The previously reported abnormally high serum IgE levels in germ-free mice suggests that immunoregulatory signals from microbiota are required to control basal IgE levels. We report that germ-free mice and those with low-diversity microbiota develop elevated serum IgE levels in early life. B cells in neonatal germ-free mice undergo isotype switching to IgE at mucosal sites in a CD4 T-cell- and IL-4-dependent manner. A critical level of microbial diversity following birth is required in order to inhibit IgE induction. Elevated IgE levels in germ-free mice lead to increased mast-cell-surface-bound IgE and exaggerated oral-induced systemic anaphylaxis. Thus, appropriate intestinal microbial stimuli during early life are critical for inducing an immunoregulatory network that protects from induction of IgE at mucosal sites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".