Investigating the Roles of Mast Cells and Innate Activators in Oral Tolerance
Bibliographic record
Abstract
Oral tolerance is the state of immunologic non-responsiveness that is established following oral antigen consumption. Failures of oral tolerance can result in food allergy. The mechanisms regulating oral tolerance are not well understood, but similar mechanisms may control tolerance to foods and commensal microbes in the intestine. The specific roles of many pattern recognition receptors (PRRs) and innate cells have not been examined in the context of oral tolerance. Mast cells are innate sentinel cells positioned at mucosal surfaces, and have been identified as key regulators of peripheral tolerance to allografts. Toll-like receptor 2 (TLR2) is a PRR involved in bacterial responses and the regulation of intestinal inflammation. We evaluated the impact of mast cells, TLR2, immunoglobulin E (IgE)-mediated mast cell activation, TLR2 activation, and histamine receptor blockade in the development of oral tolerance in mice. Models of tolerance to ovalbumin, peanut butter, and cow’s milk were established. Oral tolerance was assessed in wild type, TLR2-deficient, or mast cell-deficient mice and was measured primarily by analysis of antigen-specific antibody levels after a systemic antigen challenge. The development of antigen-specific Tregs was also assessed. We observed that neither mast cells nor TLR2 were necessary for oral tolerance induction. Moreover, IgE-mediated mast cell activation and antihistamine treatment did not significantly alter oral tolerance induction. TLR2 activators, notably Pam3CSK4, were administered orally concurrent with food antigen and were found to impair oral tolerance to a later systemic antigen challenge. When Pam3CSK4 was administered as an oral adjuvant with ovalbumin, a profound selective enhancement of the IgA response to oral challenge was observed. These results highlight an important differential regulation of oral tolerance by TLR2. Oral TLR2 activation selectively promotes IgA responses to antigen upon repeated oral challenge but prevents the maintenance of oral tolerance upon a systemic challenge. Taken together these results suggest that mast cells are not essential regulators of oral tolerance, but TLR2 is involved in regulating IgA and IgE responses during oral and systemic challenges. These findings inform mechanisms of commensal tolerance and have implications for the potential therapeutic manipulation of oral tolerance to foods.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".