BCR analysis of single-sorted, putative IgE <sup>+</sup> memory B cells in food allergy: <i>an ephemeral existence?</i>
Bibliographic record
Abstract
Abstract Immunoglobulin (Ig) E is the critical effector molecule in allergic reactions. Consequently, research efforts to understand the biology of IgE-expressing cells is of paramount importance. In particular, the role of IgE + memory B cells (MBCs) in the perpetuation of allergic reactivity has been the subject of intense research. Studies in mice have convincingly established that IgE + B cells are rare and transient and, therefore, an unlikely candidate to maintain allergic disease. In contrast, IgE + MBCs have been detected by flow cytometry in the sputum and peripheral blood of humans and have been proposed as a clinical marker of allergic disease. We established a method to genetically validate, at the single-cell level, the putative IgE + MBCs identified by flow cytometry from humans. We, then used this information to develop an enhanced flow cytometry protocol that more accurately identifies bona fide IgE + MBCs. We found that IgE + MBCs were detected in some patients with atopic dermatitis, but at a frequency that was ~100 times lower than previously reported. We also found that IgE + MBCs were undetectable in PBMCs from peanut allergic patients. These findings provide tools to identify bona fide IgE + MBCs, demonstrate their extreme rarity in circulation and are consistent with the lack of a central role for IgE + MBCs in the maintenance of allergic sensitivity. One Sentence Summary The frequency of IgE + MBCs in the peripheral circulation of humans is orders of magnitude lower than previously reported and comparable between allergic and healthy donors, which cautions about the clinical utility of their assessment.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".