iDC-targeting PfCSP mRNA vaccine confers superior protection against Plasmodium compared to conventional mRNA
Bibliographic record
Abstract
Malaria resurgence in 2022 saw 249 million clinical cases and 608,000 deaths, mostly in children under five. The WHO-approved circumsporozoite protein (CSP)-targeting vaccines, RTS,S and R21, remain limited in availability. Strong humoral responses are crucial for sporozoite neutralization before hepatocyte infection, yet first-generation vaccines provide suboptimal protection, necessitating improved strategies. With the success of mRNA-LNP vaccines against COVID-19, there is interest in leveraging this approach to malaria. Here, we developed a novel chemokine fusion mRNA vaccine targeting immature dendritic cells (iDC) to enhance immunity against P. falciparum CSP (PfCSP). Mice immunized with MIP3α-CSP mRNA-LNP exhibited stronger CD4 + T cell responses and higher anti-NANP6 antibody titers than conventional CSP mRNA-LNP. Importantly, upon P. berghei PfCSP transgenic sporozoite challenge, MIP3α-CSP mRNA provided significantly greater protection from liver infection, strongly associated with multifunctional CD4 + T cells and anti-NANP6 titers. This study underscores iDC targeting as a promising strategy to enhance malaria vaccine efficacy.
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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".