Novel Plant Virus-Based Vaccine Induces Protective Cytotoxic T-Lymphocyte-Mediated Antiviral Immunity through Dendritic Cell Maturation
Bibliographic record
Abstract
Currently used vaccines protect mainly through the production of neutralizing antibodies. However, antibodies confer little or no protection for a majority of chronic viral infections that require active involvement of cytotoxic T lymphocytes (CTLs). Virus-like particles (VLPs) have been shown to be efficient inducers of cell-mediated immune responses, but administration of an adjuvant is generally required. We recently reported the generation of a novel VLP system exploiting the self-assembly property of the papaya mosaic virus (PapMV) coat protein. We show here that uptake of PapMV-like particles by murine splenic dendritic cells (DCs) in vivo leads to their maturation, suggesting that they possess intrinsic adjuvant-like properties. DCs pulsed with PapMV-like particles displaying the lymphocytic choriomeningitis virus (LCMV) p33 immunodominant CTL epitope (PapMV-p33) efficiently process and cross-present the viral epitope to p33-specific transgenic T cells. Importantly, the CTL epitope is also properly processed and presented in vivo, since immunization of p33-specific T-cell receptor transgenic mice with PapMV-p33 induces the activation of large numbers of specific CTLs. C57BL/6 mice immunized with PapMV-p33 VLPs in the absence of adjuvant develop p33-specific effector CTLs that rapidly expand following LCMV challenge and protect vaccinated mice against LCMV infection in a dose-dependent manner. These results demonstrate the efficiency of this novel plant virus-based vaccination platform in inducing DC maturation leading to protective CTL responses.
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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) | 0.000 | 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 | 0.000 |
| 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".