Melioidosis patient serum-reactive synthetic tetrasaccharides bearing the predominant epitopes of<i>Burkholderia pseudomallei</i>and<i>Burkholderia mallei</i>O-antigens
Bibliographic record
Abstract
Melioidosis and glanders, respectively caused by the Gram-negative bacteria Burkholderia pseudomallei (Bp) and Burkholderia mallei (Bm), are considered as urgent public health issues in developing countries and potential bioterrorism agents. Bp and Bm lipopolysaccharides (LPS) have been identified as attractive vaccine candidates for the development of prophylactic measures against melioidosis and glanders. Bp and Bm express structurally similar LPSs wherein the O-antigen (OAg) portion consists of a heteropolymer whose repeating unit is a disaccharide composed of d-glucose and 6-deoxy-l-talose residues, the latter being diversely acetylated and methylated. Herein we report the synthesis of two tetrasaccharides mimicking the main substitution epitopes of Bp and Bm LPS OAgs. The assembly of the tetrasaccharides was achieved using a sequential glycosylation strategy while relying on the late-stage epimerization of the inner rhamnose into a 6-deoxy-l-talose residue. We show that these synthetic compounds strongly react with culture-confirmed Thai melioidosis patient serum and closely mimic the antigenicity of native Bp OAg. Our results suggest that these tetrasaccharides could be suitable candidates for the development of vaccines and/or diagnostic tools against melioidosis and glanders.
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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) | 0.001 | 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".