Antibody-Independent Function of Human B Cells Contributes to Antifungal T Cell Responses
Bibliographic record
Abstract
Abstract Fungal infections (e.g., Candida albicans) can manifest as serious medical illnesses, especially in the elderly and immune-compromised hosts. T cells are important for Candida control. Whether and how B cells are involved in antifungal immunity has been less clear. Although patients with agammaglobulinemia exhibit normal antifungal immunity, increased fungal infections are reported following B cell–depleting therapy, together pointing to Ab-independent roles of B cells in controlling such infections. To test how human B cells may contribute to fungal-associated human T cell responses, we developed a novel Ag-specific human T cell/B cell in vitro coculture system and found that human B cells could induce C. albicans–associated, MHC class II–restricted responses of naive T cells. Activated B cells significantly enhanced C. albicans–mediated Th1 and Th17 T cell responses, which were both strongly induced by CD80/CD86 costimulation. IL-6+GM-CSF+ B cells were the major responding B cell subpopulation to C. albicans and provided efficient costimulatory signals to the T cells. In vivo B cell depletion in humans resulted in reduced C. albicans–associated T responses. Of note, the decreased Th17, but not Th1, responses could be reversed by soluble factors from B cells prior to depletion, in an IL-6–dependent manner. Taken together, our results implicate an Ab-independent cytokine-defined B cell role in human antifungal T cell responses. These findings may be particularly relevant given the prospects of chronic B cell depletion therapy use in lymphoma and autoimmune disease, as patients age and are exposed to serial combination therapies.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".