Engagement of CD153 (CD30 Ligand) by CD30+ T Cells Inhibits Class Switch DNA Recombination and Antibody Production in Human IgD+ IgM+ B Cells
Bibliographic record
Abstract
CD153 (CD30 ligand) is a member of the TNF ligand/cytokine family expressed on the surface of human B cells. Upon exposure to IL-4, a critical Ig class switch-inducing cytokine, Ag-activated T cells express CD30, the CD153 receptor. The observation that dysregulated IgG, IgA, and/or IgE production is often associated with up-regulation of T cell CD30 prompted us to test the hypothesis that engagement of B cell CD153 by T cell CD30 modulates Ig class switching. In this study, we show that IgD+ IgM+ B cells up-regulate CD153 in the presence of CD154 (CD40 ligand), IL-4, and B cell Ag receptor engagement. In these cells, CD153 engagement by an agonistic anti-CD153 mAb or T cell CD30 inhibits S mu-->Sgamma, Smu-->Salpha, and S mu-->Sepsilon class switch DNA recombination (CSR). This inhibition is associated with decreased TNFR-associated factor-2 binding to CD40, decreased NF-kappaB binding to the CD40-responsive element of the Cgamma3 promoter, decreased Igamma3-Cgamma3 germline gene transcription, and decreased expression of Ku70, Ku80, DNA protein kinase, switch-associated protein-70, and Msh2 CSR-associated transcripts. In addition, CD153 engagement inhibits IgG, IgA, and IgE production, and this effect is associated with reduced levels of B lymphocyte maturation protein-1 transcripts, and increased binding of B cell-specific activation protein to the Ig 3' enhancer. These findings suggest that CD30+ T cells modulate CSR as well as IgG, IgA, and IgE production by inducing reverse signaling through B cell CD153.
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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".