Immunological and Toxicological Assessment of Triterpenoid Saponins Bearing Lewis‐X‐ and QS‐21‐Based Trisaccharides
Bibliographic record
Abstract
The search for safer and more effective vaccine adjuvants has intensified in recent years, with triterpenoid saponins like QS-21 and its analogues emerging as promising candidates. We report the synthesis of a novel QS-21 analogue featuring betulinic acid as aglycone, a lupane-type triterpenoid with low toxicity derived from white birch bark. Two convergent synthetic routes, involving different protecting groups and glycosyl donors (bromide and trichloroacetimidate), were optimized to construct the QS-21-based linear trisaccharide motif critical for adjuvant activity. This strategy also enabled efficient preparation of the structurally similar echinocystic acid analogue reported by Gin. The immunological and toxicological profiles of these chimeric saponins, along with Lewis-X-containing and rhamnose-modified derivatives, were evaluated in C57BL/6 wild-type and hDC-SIGN transgenic mice. While the synthetic saponins exhibited low toxicity in vitro and in vivo, replacing echinocystic acid with betulinic acid reduced immunogenicity when tested with ovalbumin as a model antigen compared to alhydrogel and QS-21. These findings provide a foundation for developing saponin-based adjuvants and demonstrate the utility of advanced glycosylation strategies for synthesizing complex unnatural triterpenoid saponins.
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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 | 0.000 |
| 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 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".