Induction of Strain-Transcending Immunity against<i>Plasmodium chabaudi adami</i>Malaria with a Multiepitope DNA Vaccine
Bibliographic record
Abstract
A major goal of current malaria vaccine programs is to develop multivalent vaccines that will protect humans against the many heterologous malaria strains that circulate in endemic areas. We describe a multiepitope DNA vaccine, derived from a genomic Plasmodium chabaudi adami DS DNA expression library of 30,000 plasmids, which induces strain-transcending immunity in mice against challenge with P. c. adami DK. Segregation of this library and DNA sequence analysis identified vaccine subpools encoding open reading frames (ORFs)/peptides of >9 amino acids [aa] (the V9+ pool, 303 plasmids) and >50 aa (V50+ pool, 56 plasmids), respectively. The V9+ and V50+ plasmid vaccine subpools significantly cross-protected mice against heterologous P. c. adami DK challenge, and protection correlated with the induction of both specific gamma interferon production by splenic cells and opsonizing antibodies. Bioinformatic analysis showed that 22 of the V50+ ORFs were polypeptides conserved among three or more Plasmodium spp., 13 of which are predicted hypothetical proteins. Twenty-nine of these ORFs are orthologues of predicted Plasmodium falciparum sequences known to be expressed in the blood stage, suggesting that this vaccine pool encodes multiple blood-stage antigens. The results have implications for malaria vaccine design by providing proof-of-principle that significant strain-transcending immunity can be induced using multiepitope blood-stage DNA vaccines and suggest that both cellular responses and opsonizing antibodies are necessary for optimal protection against P. c. adami.
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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 | 0.001 | 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 | 0.001 |
| 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 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".