Allergen-Specific B Cell Quantity Is Similar in Allergic and Nonallergic Individuals, Whereas Allergen-Specific T Cells May Be Increased in Allergic Individuals
Bibliographic record
Abstract
Abstract Allergen-specific IgE production is a hallmark of allergic asthma, rhinitis or eczema. Theoretically this could be due to a high number of allergen-specific B cells, a high number of allergen-specific T cells helping allergen-specific B cells to differentiate into IgE plasma cells, or other mechanisms. In this study, we compared the number of allergenspecific B cells and T helper (Th) cells in 41 patients with allergic asthma/rhinitis/eczema (allergic individuals) and 34 nonallergic individuals. Allergen-specific B and Th cells were enumerated by culturing CFSE-loaded blood mononuclear cells for 7 days with allergen (cat, dog, D.pteronyssimus, Timothy or birch), and determining by flow cytometry the number of B or Th cells that had proliferated (diluted CFSE). The quantities of B cells specific for each of the 5 allergens were similar in individuals allergic to the allergen (per skin prick test result) compared to nonallergic individuals. The quantity of Timothy-specific Th cells was 3-times higher in Timothy-allergic individuals compared to nonallergic individuals (p=0.023). In contrast, the quantity of cat-specific Th cells was similar in cat-allergic and nonallergic individuals. The quantities of dog, D.pteronyssimus and birch-specific Th cells were slightly higher in dog, D.pteronyssiumus and birch-allergic compared to nonallergic individuals. No significant change in the number of allergen specific B and Th cells was found when blood drawn from the same individual at different time points was compared for 3 allergic and 3 non-allergic individuals. We conclude that for some allergens (eg, Timothy), a high number of allergen-specific Th cells, but not B cells, may play a role in the pathogenesis of allergic asthma/rhinitis/eczema. For other allergens (eg, cat), the pathogenesis may be different.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".