Messenger RNA expressing PfCSP induces functional, protective immune responses against malaria in mice
Bibliographic record
Abstract
Human malaria affects the vast majority of the world's population with the Plasmodium falciparum species causing the highest rates of morbidity and mortality. With no licensed vaccine and leading candidates achieving suboptimal protection in the field, the need for an effective immunoprophylactic option continues to motivate the malaria research community to explore alternative technologies. Recent advances in the mRNA discipline have elevated the long-neglected platform to the forefront of infectious disease research. As the immunodominant coat protein of the invasive stage of the malaria parasite, circumsporozoite protein (PfCSP) was selected as the antigen of choice to assess the immunogenic and protective potential of an mRNA malaria vaccine. In mammalian cell transfection experiments, PfCSP mRNA was well expressed and cell associated. In the transition to an in vivo murine model, lipid nanoparticle (LNP) encapsulation was applied to protect and deliver the mRNA to the cell translation machinery and supply adjuvant activity. The immunogenic effect of an array of factors was explored, such as formulation, dose, number, and interval of immunizations. PfCSP mRNA-LNP achieved sterile protection against infection with two P. berghei PfCSP transgenic parasite strains, with mRNA dose and vaccination interval having a greater effect on outcome. This investigation serves as the assessment of pre-erythrocytic malaria, PfCSP mRNA vaccine candidate resulting in sterile protection, with numerous factors affecting protective efficacy, making it a compelling candidate for further investigation.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".