Toll‐like receptor 2 activators modulate oral tolerance in mice
Bibliographic record
Abstract
BACKGROUND: Toll-like receptor 2 (TLR2) is a widely expressed pattern recognition receptor critical for innate immunity. TLR2 is also a key regulator of mucosal immunity implicated in the development of allergic disease. TLR2 activators are found in many common foods, but the role of TLR2 in oral tolerance and allergic sensitization to foods is not well understood. OBJECTIVE: The purpose of this study was to evaluate the impacts of TLR2 expression and TLR2 activation on oral tolerance to food antigens in a murine model. METHODS: Mice were fed ovalbumin (OVA) or peanut butter with or without the addition of low doses of TLR2 activators Pam3 CSK4 or FSL-1. Oral tolerance was assessed by analysing antibody responses after a systemic antigen challenge. OVA-specific Tregs were assessed in the Peyer's patches, mesenteric lymph nodes, and spleen in wild-type and TLR2(-/-) mice. Low-dose Pam3 CSK4 was also tested as an oral adjuvant. RESULTS: Oral tolerance was successfully induced in both wild-type and TLR2(-/-) recipient mice, with an associated regulatory T-cell response. Oral TLR2 activation, with low-dose Pam3 CSK4 or FSL-1, during oral antigen exposure was found to alter oral tolerance and was associated with the development of substantial IgE and IgA responses to foods upon systemic challenge. Low-dose oral Pam3 CSK4 treatment also selectively enhanced antigen-specific IgA responses to oral antigen exposure. CONCLUSIONS AND CLINICAL RELEVANCE: TLR2 is not necessary for oral tolerance induction, but oral TLR2 activation modulates humoral IgE and IgA responses during tolerance development. Low-dose Pam3 CSK4 is also an effective oral adjuvant that selectively enhances IgA production. These observations are pertinent to the optimization of oral allergen immunotherapy and oral vaccine development.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
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 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".