4-1BB costimulation following mRNA vaccination improves CD8 T cell responses
Bibliographic record
Abstract
Abstract mRNA vaccines have received full FDA approval to prevent COVID-19, and are being explored for multiple infectious diseases as well as cancer. While they have shown high efficacy at preventing severe disease caused by SARS-CoV-2, waning immunity has motivated the development of improved mRNA vaccine regimens. 4-1BB (also known as CD137) is a costimulatory receptor that has been shown to be important for T cell responses following viral infections and cancer. We asked whether triggering 4-1BB costimulation with agonistic antibodies could improve immune responses elicited by mRNA vaccines in C57BL/6 mice. Here, we show that triggering 4-1BB costimulation at the time of mRNA vaccination impairs CD8 T cell responses, whereas triggering 4-1BB costimulation after day 4 of mRNA vaccination improves CD8 T cell immune responses. These data demonstrate time-dependent effects of 4-1BB costimulation on cellular responses elicited by mRNA vaccines, and suggest that delayed provision of 4-1BB costimulation could offer immunologic benefits following mRNA vaccination. This work was supported by a DP2 New Innovator Award to P.P.M. This work was supported by a DP2 New Innovator Award to P.P.M.
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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) | 0.003 | 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".