Costimulatory ligand 4-1BBL (CD137L) as an efficient adjuvant for human antiviral cytotoxic T cell responses
Bibliographic record
Abstract
Effective adjuvants capable of inducing strong cytotoxic T cell responses in humans are lacking. In this study, we tested 4-1BBL as an adjuvant for activation of human memory antiviral CD8 T cell responses ex vivo. A recombinant replication-defective 4-1BBL adenovirus was used to convert autologous monocytes into efficient antigen-presenting cells after overnight incubation, bypassing the need to generate dendritic cells. Together with viral peptides, 4-1BBL led to robust memory responses of human Epstein-Barr virus- and influenza virus-specific cytotoxic T cells, with expansion of peptide-specific CD8 effector cells; up-regulation of Bcl-x(L), granzyme A, and perforin; enhanced cytotoxic activity; and increased cytokine production. The response was significant even at a 100-fold lower peptide dose, compared with responses obtained with control adenovirus. Adenovirus-delivered B7.1 also expanded and activated virus-specific CD8 T cells, but 4-1BBL was more effective in driving the T cells toward a more fully differentiated CD27(-) effector state. Thus, 4-1BBL is a promising adjuvant for human memory CD8 T cells and will likely be most effective in the boost phase of a prime-boost strategy.
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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 | 0.001 | 0.001 |
| 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".