Homologous and Heterologous Vaccination Regimens with mRNA and rVSV Platforms Induce Potent Immune Responses Against SFTSV Glycoprotein
Bibliographic record
Abstract
BACKGROUND: Severe fever with thrombocytopenia syndrome virus (SFTSV) is a highly pathogenic bunyavirus with a high case-fatality ratio for which there is no approved vaccine. Studies have assessed different vaccine technologies. However, few studies have yet assessed the immunogenicity of heterologous prime-boost regimens. METHODS: Here, we compare a lipid nanoparticle (LNP)-encapsulated nucleoside-modified mRNA-based vaccine encoding the SFTSV glycoproteins, Gn and Gc, to our recently described recombinant VSV SFTSV (rVSV-SFTSV) vaccine in single dose, homologous, and heterologous prime-boost regimens in mice. RESULTS: We show that all regimens protect from pathogenic SFTSV challenge and elicit strong long-lasting antibody responses. Furthermore, strong cellular immunity is elicited by mRNA-LNP immunizations and by heterologous immunization with an rVSV-SFTSV prime and mRNA-LNP boost. Cellular responses robustly polarized towards a type 1 response, characterized by high levels of IFNγ, TNFα, and IL-2. Immunization with mRNA led to a mixed type 1/type 2 immune response, as determined by antibody isotypes IgG1 and IgG2c. We found that homologous immunization leads to stronger antibody responses while heterologous immunization drives a slightly stronger cellular response. CONCLUSIONS: Taken together, the vaccine platforms described here represent strong vaccine candidates for further development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".