Targeting CD40 enhances antibody- and CD8-mediated protection against respiratory syncytial virus infection
Bibliographic record
Abstract
Abstract Respiratory Syncytial Virus (RSV) infects almost all children under the age of one and is the leading cause of hospitalization among infants. It also causes high rates of infection in the elderly and immunocompromised patient populations. Despite several decades of research with dozens of candidate vaccines being vigorously evaluated in pre-clinical and clinical studies, there is no licensed vaccine available to date. A clinical trial conducted in the early 1960s testing a formaldehyde-inactivated RSV (FIRSV) vaccine resulted in enhanced respiratory disease, following subsequent RSV infection, leading to hospitalization of 80% of the participants and 2 deaths. Since then, other forms of RSV vaccine have also been found to induce enhanced disease in preclinical animal studies. Here, we aimed to develop a vaccine that can effectively protect mice from RSV infection and help identify facets of FIRSV-induced enhanced disease. In this study, BALB/c mice were immunized with an adenoviral vector containing the RSV fusion protein (F) fused with CD40 ligand where the CD40 ligand serves two vital functions as a molecular adjuvant and an antigen-targeting molecule. In contrast to the FIRSV vaccine, the vectored vaccine effectively protected animals against RSV without inducing enhanced respiratory disease. This protection involved a robust induction of neutralizing antibodies and memory CD8 T cells, which were not observed in the FIRSV group. Finally, the vectored vaccine was able to elicit long-lasting protection against RSV, which was mediated by increased levels of effector memory CD8 T cell 3 months post-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 | 0.000 | 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) | 0.001 | 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".