Chronic upper airway inflammation is characterized by an extrafollicular B cell response and elevated antibody production in humans (HUM1P.260)
Bibliographic record
Abstract
Abstract Chronic rhinosinusitis (CRS) is an upper airway disease that affects 30 million Americans and a subgroup of CRS patients also has nasal polyps (CRSwNP). In CRSwNP patients, inflamed sinus tissues can be removed as part of treatment, which provides a unique model system to investigate mechanisms of human mucosal inflammation. We have previously reported local elevations in NP of B cells, antibodies (Ab), and expression of Epstein-Barr virus-Induced protein 2 (EBI2), a marker of extrafollicular plasma cells (PC). To characterize the mechanisms mediating these responses, we assessed B cells from fresh tissue (d0) or after 4 days of culture (d4) from NP, uncinate tissue (UT) or tonsils from CRS and control subjects by flow cytometry. We measured Ab production by multiplex array and assessed formation of B cell follicles by immunohistochemistry. We assessed the Ab repertoire by DNA deep sequencing and by analysis of Ab genes from single cells. We found that NP uniquely supported the accumulation of PC (p<0.01) and Ab production (p<0.05) in vitro. Plasmablasts (PB) and PC were Ki67+, and EBI2 expression was highest on PB. We found no evidence for increased B cell follicles in NP compared to control UT (n>10/group). Ab from NP had fewer CDR3 mutations than Ab from UT (p<0.05), but more mutations than Ab from peripheral blood (p<0.05). These data suggest that there is a strong extrafollicular B cell response in NP that may drive Ab production during chronic airway inflammation.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".