Sm‐p80–Based DNA Vaccine Provides Baboons with Levels of Protection against<i>Schistosoma</i><i>mansoni</i>Infection Comparable to Those Achieved by the Irradiated Cercarial Vaccine
Bibliographic record
Abstract
To date, no vaccine is available to prevent human schistosomiasis. We have targeted a protein of Schistosoma mansoni that plays an important role in the surface membrane renewal process, a mechanism widely believed to be utilized by the parasite as an immune evasion strategy. Sm-p80 antigen is a promising vaccine target because of its documented immunogenicity, protective efficacy, and antifecundity effects observed in both experimental murine and nonhuman primate models of this infectious disease. In the present study, we report that, in a vector approved for human use (VR1020), an Sm-p80-based DNA vaccine formulation confers a 46% reduction in the worm burden in a baboon (Papio anubis) model. Baboons vaccinated with Sm-p80-VR1020 had a 28% decrease in egg production after challenge with the infectious parasite. Sm-p80-VR1020 vaccine elicited robust immune responses to specific antigen Sm-p80, including immunoglobulin (Ig) G, its subtypes IgG1 and IgG2, and IgA and IgM in vaccinated animals. When stimulated in vitro with recombinant Sm-p80, peripheral blood mononuclear cells and splenocytes from baboons vaccinated with Sm-p80-VR1020 produced considerably higher levels of T helper 1 response-enhancing cytokines (interleukin [IL]-2 and interferon-gamma) than T helper 2 (Th2) response-enhancing cytokines (IL-4 and IL-10). Peripheral blood mononuclear cells produced a significantly higher number of spot-forming units for interferon-gamma than for IL-4 in enzyme-linked immunosorbent spot assays. A mixed T helper 1/T helper 2 type of humoral and T cell responses was generated after immunization with Sm-p80-VR1020. These findings again highlight the potential of Sm-p80 as a promising vaccine candidate for schistosomiasis.
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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) | 0.001 | 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) | 0.002 | 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".