50-Fold Adjuvant and 20-Fold Antigen Vaccine Dose Sparing from Nanoliposome Display of a Stabilized Malarial Protein Antigen
Bibliographic record
Abstract
Displaying soluble vaccine protein antigens onto the surface of adjuvanted nanoliposomes can enhance the magnitude of elicited antibody responses. In this study, we examine this approach with respect to dose sparing, for not only the antigen component but also the adjuvant dose in the vaccine. Using a structurally stabilized Pfs48/45 derived malarial protein as a model antigen, we confirmed the protein rapidly displayed on the surface of immunogenic liposomes containing cobalt porphyrin phospholipid (CoPoP; for antigen display via His-tag interaction) along with the immunostimulatory adjuvants monophosphoryl lipid A (MPLA) and QS-21. Mice were immunized with a fixed protein antigen dose with varying adjuvant doses to estimate the extent of adjuvant sparing. In mice vaccinated at a fixed protein antigen dose, liposome-bound Pfs48/45 achieved superior antibody IgG titers compared to the soluble (nonbound) form at all assessed adjuvant doses, reflecting MPLA and QS-21 adjuvant dose sparing of at least 50-fold. The primary driver of adjuvant sparing in these conditions was presentation of the antigen in a nanoparticle format, and potent responses were achieved even without co-delivery of antigen and adjuvant within the same particle, provided that adjuvant and liposome-displayed antigen were co-administered to the same injection site. By keeping the adjuvant dose fixed and varying the antigen dose in a comparable experimental design, ∼20-fold antigen dose sparing was observed with liposome display. This case study illustrates the potential of antigen-display nanotechnologies, such as CoPoP nanoliposomes, to achieve substantial adjuvant and antigen dose sparing, which could theoretically facilitate the deployment of future vaccines.
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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) | 0.001 | 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 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".