Inflammation enhances the vaccination potential of CD40‐activated B cells in mice
Bibliographic record
Abstract
Vaccination with antigen‐pulsed CD40‐activated B (CD40‐B) cells can efficiently lead to the in vivo differentiation of naive CD8+ T cells into fully functional effectors. In contrast to bone marrow‐derived dendritic cell (BMDC) vaccination, CD40‐B cell priming does not allow for memory CD8+ T‐cell generation but the reason for this deficiency is unknown. Here, we show that compared to BMDCs, murine CD40‐B cells induce lower expression of several genes regulated by T‐cell receptor signaling, costimulation, and inflammation (signals 1–3) in mouse T cells. The reduced provision of signals 1 and 2 by CD40‐B cells can be explained by a reduction in the quality and duration of the interactions with naive CD8+ T cells as compared to BMDCs. Furthermore, CD40‐B cells produce less inflammatory mediators, such as IL‐12 and type I interferon, and increasing inflammation by coadministration of polyriboinosinic‐polyribocytidylic acid with CD40‐B‐cell immunization allowed for the generation of long‐lived and functional CD8+ memory T cells. In conclusion, it is possible to manipulate CD40‐B‐cell vaccination to promote the formation of long‐lived functional CD8+ memory T cells, a key step before translating the use of CD40‐B cells for therapeutic vaccination.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".