Reciprocal activation of B cells and group 2 innate lymphoid cells
Bibliographic record
Abstract
Abstract B cells can be activated at peripheral sites in chronic inflammatory disease, but the mechanisms that drive this, especially in humans, are unclear. We have reported elevated frequencies of Epstein-Barr virus-induced molecule 2 (EBI2) expressing B cells in tissues from patients with chronic airway inflammation. EBI2 is a marker of extrafollicular plasmablasts, which are activated antibody-secreting cells (ASC). We sought to determine the mechanisms of extrafollicular B cell activation during chronic airway inflammation. ELISpot was used to determine ASC frequency in cells from inflamed nasal tissue or control tonsil tissue. B cells, T cells, and group 2 innate lymphoid cells (ILC2) were isolated from peripheral blood, and B cells were co-cultured with group 2 innate lymphoid cells (ILC2) or T cells. EBI2 expression was assessed by flow cytometry, and gene expression changes were assessed by single cell RNA-seq. Inflamed nasal tissue had a higher frequency of ASC compared to tonsil (p<0.05). The majority of the ASC were contained in the EBI2+ B cell subset in nasal and tonsil tissues. Co-culture of B cells and ILC2 significantly increased the frequency of EBI2+ B cells (p<0.01). B cells co-cultured with ILC2 expressed significantly higher levels of CCL17, CCL22, and FceR2 (>5 fold), compared to freshly isolated B cells, or B cells co-cultured with T cells. ILC2 co-cultured with B cells had significantly increased expression of IL-5, IL-13, and IL-2Ra (>7 fold) compared to freshly isolated ILC2. Our data suggest that not only can ILC2 directly activate B cells, but B cells can also enhance ILC2 function. These findings provide new insights into mechanisms that B cells may play in chronic inflammatory disease.
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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 | 0.001 | 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 | 0.001 |
| 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".