Toll-like receptor 2 impacts the development of oral tolerance in mouse pups via a milk-dependent mechanism
Bibliographic record
Abstract
Background The role of breast-feeding in the development of oral tolerance and allergic diseases is controversial, which could be related to variability in milk components. Toll-like receptor 2 (TLR2) is an innate immune receptor implicated in regulating allergic disease development. Objectives We examined whether deficiency of maternal TLR2 affects the normal development of oral tolerance and related immune parameters during lactation in a mouse model. Methods Heterozygous TLR2 +/– pups from wild-type (WT) or TLR2 –/– dams were fed either by their biologic dam or a dam of the alternate genotype. Development of oral tolerance to ovalbumin, levels of tolerogenic CD103 + dendritic cells, and regulatory T (Treg) cells, as well as intestinal permeability, were evaluated in these pups. The levels of key immune mediators in milk from TLR2 –/– and WT mothers were also examined. Results Heterozygous TLR2 +/– pups that were born to and nursed by TLR2 –/– dams exhibited impaired oral tolerance. This was prevented by cross-fostering onto WT (TLR2 +/+ ) dams. Impairments included selective elevation in anti-ovalbumin IgE in plasma following immunization, reduced numbers of tolerogenic dendritic cells and Treg cells in the intestinal tract, and increased intestinal permeability. TLR2 deficiency also affected milk content of insulin-like growth factor-1, IFN-γ, IL-6, and IL-13. Conclusion Our results underline a critical role for TLR2 in regulating milk components that are essential for development of oral tolerance in early life and demonstrate the importance of considering the immune status of nursing mothers in studies of immune development and responses.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".