PfCSP-ferritin nanoparticle malaria vaccine antigen formulated with aluminum-salt and CpG 1018® adjuvants: Preformulation characterization, antigen-adjuvant interactions, and mouse immunogenicity studies
Bibliographic record
Abstract
Circumsporozite protein (CSP), the most abundant surface protein in parasitic Plasmodium falciparum (Pf) sporozoite and an attractive target for malaria vaccine design, has been shown to induce protective humoral response in humans. In this work, we characterized and formulated a promising recombinant PfCSP immunogen (155) candidate consisting of two PfCSP epitopes (i.e. junction, NANP repeat) fused to H. pylori apoferritin forming a 24-mer nanoparticle. In addition, two N-linked glycans were engineered to mitigate possible anti-apoferritin immune responses, and a universal T-cell epitope was included to further enhance immunogenicity. Physicochemical characterization of the 155 antigen was performed including primary structure, post-translational modifications, conformational stability, and particle size. A competitive ELISA was developed to assess antigen binding to a PfCSP-specific mAb. The in vitro antigenicity of the 155 antigen was measured upon formulation with adjuvants, including aluminum-salts (i.e. AlhydrogelTM, Adju-PhosTM) and the TLR-9 agonist CpG 1018®, when freshly combined and after storage at different temperatures over 3 months. The in vivo immunological impact of various adjuvanted formulations of the 155 antigen was investigated in mice. The results support the formulation of 155 with AlhydrogelTM + CpG 1018® adjuvants as a promising recombinant malaria vaccine candidate from both a pharmaceutical and immunological perspective.
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 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) | 0.000 | 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 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".