A Pvs25 mRNA vaccine induces complete and durable transmission-blocking immunity to Plasmodium vivax
Bibliographic record
Abstract
Plasmodium vivax (P. vivax) is the major malaria parasite outside of Africa and no vaccine is available against it. A vaccine that interrupts parasite transmission (transmission-blocking vaccine, TBV) is considered highly desirable to reduce the spread of P. vivax and to accelerate its elimination. However, the development of a TBV against this pathogen has been hampered by the inability to culture the parasite as well as the low immunogenicity of the vaccines developed to date. Pvs25 is the most advanced TBV antigen candidate for P. vivax. However, in previous phase I clinical trials, TBV vaccines based on Pvs25 yielded low antibody responses or had unacceptable safety profiles. As the nucleoside-modified mRNA-lipid nanoparticle (mRNA-LNP) vaccine platform proved to be safe and effective in humans, we generated and tested mRNA-LNP vaccines encoding several versions of Pvs25 in mice. We found that in a prime-boost vaccination schedule, all Pvs25 mRNA-LNP vaccines elicited robust antigen-specific antibody responses. Furthermore, when compared with a Pvs25 recombinant protein vaccine formulated with Montanide ISA-51 adjuvant, the full-length Pvs25 mRNA-LNP vaccine induced a stronger and longer-lasting functional immunity. Seven months after the second vaccination, vaccine-induced antibodies retained the ability to fully block P. vivax transmission in direct membrane feeding assays, whereas the blocking activity induced by the protein/ISA-51 vaccine dropped significantly. Taken together, we report on mRNA vaccines targeting P. vivax and demonstrate that Pvs25 mRNA-LNP outperformed an adjuvanted Pvs25 protein vaccine suggesting that it is a promising candidate for further testing in non-human primates.
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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".