Investigating the Systemic Effects of Cat Allergen-Induced Allergic Rhinitis
Bibliographic record
Abstract
8.5 million cats live in Canada, approximately in every third household. However, one in five Canadians is allergic to cats, often in combination with other allergic diseases. To date, only symptomatic treatments are available for cat allergies, but no prevention or cure. To improve treatment options for cat-allergic individuals, we need to better understand the mechanisms underlying this common cause of rhinitis. While clinical data provide important insights into immunological phenotypes and symptom severity, preclinical models allow for dissection of the immune response throughout the whole organism, and across a long timespan. Notably, the main effector cells mediating allergic rhinitis –eosinophilic granulocytes– derive from hematopoietic stem cells (HSCs). HSCs reside within bone marrow (BM) –a location far from the nose as primary site of the allergy. Based on previous studies on respiratory infections, we hypothesize that sensitization to cat allergens in the nose initiates HSC activation and expansion in the BM. These HSCs produce eosinophils that are epigenetically programmed for rapid and strong reaction upon allergen encounter, perpetuating allergic sensitization. We have established a preclinical model for cat allergen-induced rhinitis in which wild-type C57BL/6 mice are intranasally exposed to cat dander, mimicking human sensitization. Similar to our clinical study, eosinophils increase in the nasal mucosa upon cat allergen exposure in mice. We are now testing the systemic changes occurring throughout allergic sensitization and challenge. Specifically, we will analyze immune cell and HSC populations in lung, blood, and BM by flow cytometry. We will compare the phenotypes of these cells with effector eosinophils in the nose during allergen exposure. Using mice for the investigation of cat allergy enables us to trace eosinophil migration and systemic distribution of these potent allergy-promoting cells. These insights are fundamental to determining novel intervention foci, and to understanding how cat allergy links with other allergic diseases.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".