Sequential class switching is required for the generation of high affinity IgE antibodies
Bibliographic record
Abstract
IgE antibodies with high affinity for their antigens can be stably cross-linked at low concentrations by trace amounts of antigen, whereas IgE antibodies with low affinity bind their antigens weakly. In this study, we find that there are two distinct pathways to generate high and low affinity IgE. High affinity IgE is generated through sequential class switching (μ→γ→ε) in which an intermediary IgG phase is necessary for the affinity maturation of the IgE response, where the IgE inherits somatic hypermutations and high affinity from the IgG1 phase. In contrast, low affinity IgE is generated through direct class switching (μ→ε) and is much less mutated. Mice deficient in IgG1 production cannot produce high affinity IgE, even after repeated immunizations. We demonstrate that a small amount of high affinity IgE can cause anaphylaxis and is pathogenic. Low affinity IgE competes with high affinity IgE for binding to Fcε receptors and prevents anaphylaxis and is thus beneficial.
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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 | 0.001 |
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".