Chemical Synthesis and Immunological Evaluation of the Inner Core Oligosaccharide of Francisella tularensis
Bibliographic record
Abstract
Francisella tularensis, which is a Gram negative bacterium that causes tularemia, has been classified by the Center for Disease Control and Prevention (CDC) as a category A bioweapon. The development of vaccines, immunotherapeutics, and diagnostics for F. tularensis requires a detailed knowledge of the saccharide structures that can be recognized by protective antibodies. We have synthesized the inner core region of the lipopolysaccharide (LPS) of F. tularensis to probe antigenic responses elicited by a live and subunit vaccine. The successful preparation of the target compound relied on the use of a disaccharide which was modified by the orthogonal protecting groups diethylisopropylsilyl (DEIPS), 2-naphthylmethyl (Nap), allyl ether (All), and levulinoyl (Lev) ester. The ability to remove the protecting groups in different orders made it possible to establish the optimal glycosylations sequence to prepare a highly crowded 1,2,3-cis configured branching point. A variety of different methods were exploited to control anomeric selectivities of the glycosylations. A comparison of the (1)H NMR spectra of isolated material and the synthetic derivative confirmed the reported structural assignment of the inner core oligosaccharide of F. tularensis . The observation that immunizations with LPS lead to antibody responses to the inner core saccharides provides an impetus to further explore this compound as a vaccine candidate.
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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".