IgE-producing cells on the move: CCR2 is a key regulator of IgE <sup>+</sup> plasma cell migration
Bibliographic record
Abstract
Abstract Background Immunoglobulin E (IgE) plays a fundamental role in the pathogenesis of allergic disease, including asthma. The IgE-producing plasma cells (PCs) are thought to persist indefinitely, providing a sustained source of allergen-specific IgE. Although these cells can accumulate in the bone marrow (BM), after prolonged allergen exposure, their frequency remains remarkably low, and the mechanisms that regulate their migration are poorly understood. Objective To investigate the chemokine receptor profile and the migration potential of the human IgE-producing cells. Methods Tonsil B cells were stimulated with IL-4 and anti-CD40 to induce class switching to IgE and IgG1. The chemokine receptor profile of IgE + and IgG1 + switched cells was determined using flow cytometry and migration towards relevant chemokines was quantified using transwell chemotaxis assays. Chemokine expression was also validated by re-analysis of a published single cell RNA sequencing (scRNAseq) dataset of PCs isolated from nasal polyps (NP) of patients with allergic fungal rhinosinusitis. Results IgE ⁺ PCs exhibit significantly reduced expression of the BM-homing chemokine receptor CXCR4 and impaired migration towards its ligand, CXCL12. While IgE + PCs can upregulate CCR10 and respond to its ligand, CCL28, this behaviour is similar to IgG1 + PCs. Strikingly, however, IgE ⁺ PCs selectively upregulate CCR2 and migrate robustly towards its ligand CCL2. Re-analysis of NP scRNAseq data confirmed that IgE ⁺ PCs express significantly higher levels of CCR2 compared with PCs of all other isotypes. Conclusions These findings identify CCR2 as a key regulator of IgE ⁺ PC migration and provide insights into their homing preferences that may shape the nature of the IgE responses.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".