Adjuvanted Schistosoma mansoni-Cathepsin B With Sulfated Lactosyl Archaeol Archaeosomes or AddaVax™ Provides Protection in a Pre-Clinical Schistosomiasis Model
Bibliographic record
Abstract
Schistosomiasis threatens 800 million people worldwide. Chronic pathology manifests as hepatosplenomegaly, and intestinal schistosomiasis caused by Schistosoma mansoni can lead to liver fibrosis, cirrhosis, and blood in the stool. To assist the only FDA approved drug, praziquantel, in parasite elimination, the development of a vaccine would be of high value. S. mansoni Cathepsin B (SmCB) is a well documented vaccine target for intestinal schistosomiasis. Herein, we test the increased efficacy and immunogenicity of S. mansoni Cathepsin B (SmCB) when combined with sulfated lactosyl archaeol (SLA) archaeosomes or AddaVax™ (a squalene based oil-in-water emulsion). Both vaccine formulations resulted in robust humoral and cell mediated immune responses. Impressively, both formulations were able to reduce parasite burden greater than 40% (WHO standard) with AddaVax™ reaching 86.8%. Additionally, SmCB with both adjuvants were able to reduce granuloma size and the amount of larval parasite hatched from feces which would reduce transmission. Our data support SmCB as a target for S. mansoni vaccination; especially when used in an adjuvanted formulation.
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 | 0.001 |
| 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".