SεSμ and SεSγ Switch Circles in Human Nasal Mucosa Following Ex Vivo Allergen Challenge: Evidence for Direct as Well as Sequential Class Switch Recombination
Bibliographic record
Abstract
B cells switch to IgE under the influence of IL-4, IL-13, and CD40 costimulation through a multistep process involving epsilon germline transcription and class switch recombination. Classically, switching has been considered an event restricted to lymphoid tissues; however, epsilon germline transcripts (I(initiator)epsilon RNA) have been observed within lung, sinus, and nasal tissue of individuals with asthma, sinusitis, and rhinitis. Furthermore, nasal mucosal tissue from allergic rhinitics produces epsilon germline transcripts following ex vivo allergen challenge. Collectively, these studies raised the possibility that switching to IgE may occur locally, at sites of allergic inflammation. Although epsilon germline transcripts are considered necessary to target the IgE locus, it is class switch recombination that ultimately leads to de novo IgE production. In this study, we demonstrate that S epsilon S mu DNA switch circles (products of class switch recombination) as well as I epsilon and C epsilon RNA are produced within nasal tissue from allergic individuals following ex vivo allergen challenge. epsilon germline transcription was inhibited when tissue was cultured with a combination of allergen and neutralizing Abs against IL-4 and IL-13, indicating that de novo cytokine production mediated the isotype switch. We also show allergen-induced appearance of S epsilon S gamma DNA switch circles and up-regulation of C gamma 4 mRNA, illustrating that sequential switching to IgE also occurred. This work strongly suggests that B cells residing within the nasal mucosa undergo switching to IgE in the context of a local immune response to allergen.
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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) | 0.001 | 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 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".