Proteinase-activated receptor-2 activation participates in allergic sensitization to house dust mite allergens in a murine model
Bibliographic record
Abstract
BACKGROUND: Many aeroallergens contain proteinase activity and are able to induce allergic sensitization when presented to mucosal surfaces. Some of these allergens activate proteinase-activated receptor-2 (PAR2 ). OBJECTIVE: To determine the role of PAR2 activation in a murine house dust mite (HDM) allergy model. METHODS: We sensitized and challenged PAR2 -deficient mice with HDM, and examined allergic outcomes compared to wild-type animals. To focus on the role of PAR2 in allergic sensitization, we administered a PAR2 blocking antibody to wild-type animals during the sensitization phase and examined the outcomes immediately after sensitization or following subsequent allergen challenge. RESULTS: We found PAR2 -deficient mice sensitized and challenged with HDM failed to develop airway inflammation, did not produce HDM-specific IgG1 and had less IL-4 mRNA in the lungs than wild-type animals. Prevention of PAR2 activation during sensitization in wild-type mice diminished the levels of Th2 mediators, including IL-4, IL-5 and IL-13, in the lungs. Blocking PAR2 during the sensitization phase also led to decreased manifestations of allergic disease, including airway hyperresponsiveness (AHR) and airway inflammation following subsequent allergen challenge. HDM-induced proliferation of splenocytes obtained from animals sensitized in the presence of PAR2 antibody was reduced relative to those that did not receive antibody. The effect of PAR2 blockade could be transferred to naïve mice through splenic CD4(+) T cells from sensitized mice. CONCLUSIONS AND CLINICAL RELEVANCE: PAR2 activation plays a key role during the sensitization phase of our HDM allergy model, leading to increased lung cytokine production and augmented lung reactivity. PAR2 activation is a common mechanism for sensitization to a wide variety of allergens and is therefore a potential pharmacological target to prevent allergy.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".