Immunization with a tri-antigen syphilis vaccine significantly attenuates chancre development, reduces bacterial load, and inhibits dissemination of Treponema pallidum
Bibliographic record
Abstract
Syphilis continues to be a significant public health concern worldwide. The disease is endemic in many low- and middle-income countries, and rates have risen sharply in high-income countries over the last decade. The continued prevalence of infectious and congenital syphilis worldwide highlights the need for the development of an effective syphilis vaccine to complement public health measures for syphilis control. The complex, multi-stage course of syphilis infection necessitates a holistic approach to the development of an effective vaccine, in which immunization prevents both the localized stage of infection (typified by the highly infectious chancre) and the disseminated stages of infection (typified by the secondary rash, neurosyphilis, and destructive tertiary lesions, as well as congenital syphilis). Inhibiting development of the infectious chancre would reduce transmission thus providing community- level protection, while preventing dissemination would provide individual-level protection by reducing serious sequelae and may also provide community level protection by reducing shedding during secondary syphilis. In the current study we build upon prior investigations which demonstrated that immunizations with individual, well characterized T. pallidum TprK, TprC, and Tp0751 peptides elicits partial protection against infection in the animal model. Specifically, we show here that immunization with a TprC/TprK/Tp0751 tri-antigen cocktail protects animals from progressive syphilis lesions and substantially inhibits dissemination of the infection.
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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) | 0.000 | 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) | 0.001 | 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".