Allergic Reactivity and Memory Occur Independently of Sequential Switching Through <scp>IgG1</scp>
Bibliographic record
Abstract
Allergic reactions to foods are primarily driven by allergen-binding immunoglobulin (Ig)E antibodies. IgE-expressing cells can be generated through direct switching from IgM to IgE or a sequential class switching pathway where activated B cells first switch to an intermediary isotype, most frequently IgG1, and then to IgE. It has been proposed that sequential class switch recombination is involved in augmenting the severity of allergic reactions, generating high affinity IgE, differentiation of IgE plasma cells, and in holding the memory of IgE responses. We directly tested these possibilities by comparing the allergic immunity of wild-type and IgG1-deficient (hMT) mice. We found that sequential switching through IgG1 was not required to maintain the binding capacity of IgE nor for its ability to promote degranulation and elicit anaphylaxis against bona fide food allergens. Furthermore, the absence of sequential switching modestly impacted IgE affinity and clinical reactivity against hapten antigens, suggesting that the nature of the antigen impacts the requirement for sequential switching. At a cellular level, the capacity to undergo sequential switching through IgG1 provided no competitive advantage for subsequent IgE expression among germinal center B cells or plasma cells. Furthermore, the recall of allergic immunity at memory timepoints was preserved in the absence of sequential switching through IgG1, a finding that corresponded with intact type 2 memory B cell polarization. Together, these data demonstrate that sequential switching through IgG1 is redundant in sensitization, anaphylaxis, and the persistence of allergy, ultimately revealing that IgE derived from any switching source should be targeted by novel therapeutics seeking to ameliorate allergic diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".