Pre-clinical evaluation of a P. berghei-based whole-sporozoite malaria vaccine candidate
Bibliographic record
Abstract
Abstract Whole-sporozoite vaccination/immunization induces high levels of protective immunity in both rodent models of malaria and in humans. Recently, we generated a transgenic line of the rodent malaria parasiteP. berghei(Pb) that expresses theP. falciparum(Pf) circumsporozoite protein (PfCS), and showed that this parasite line (PbVac) was capable of (1) infecting and developing in human hepatocytes but not in human erythrocytes, and (2) inducing neutralizing antibodies against the humanPfparasite. Here, we analyzedPbVac in detail and developed tools necessary for its use in clinical studies. A microbiological contaminant-free Master Cell Bank ofPbVac parasites was generated through a process of cyclic propagation and clonal expansion in mice and mosquitoes and was genetically characterized. A highly sensitive qRT-PCR-based method was established that enablesPbVac parasite detection and quantification at low parasite densities in vivo. This method was employed in a biodistribution study in a rabbit model, revealing that the parasite is only present at the site of administration and in the liver up to 48 h post infection and is no longer detectable at any site 10 days after administration. An extensive toxicology investigation carried out in rabbits further showed the absence ofPbVac-related toxicity. In vivo drug sensitivity assays employing rodent models of infection showed that both the liver and the blood stage forms ofPbVac were completely eliminated by Malarone®treatment. Collectively, our pre-clinical safety assessment demonstrates thatPbVac possesses all characteristics necessary to advance into clinical evaluation.
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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 | 0.001 | 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".