Anomerization of N-Acetylglucosamine Glycosides Promoted by Dibromomethane and Dimethylformamide
Bibliographic record
Abstract
In previous quests to synthesize fragments of tumor-associated carbohydrate antigens (TACAs), we determined that bromoalkyl β glycosides of N-acetylglucosamine were labile and incompatible with some of the synthetic conditions required for the preparation of oligosaccharides. While N-acetylglucosamine chloroalkyl β glycosides are common intermediates for oligosaccharide synthesis, they exhibit poor yields upon subsequent reactions used to introduce the oxyamine required for further conjugation. Thus, we looked to synthesize these TACAs using chloroalkyl β glycosides and substitute the chlorine for bromine at a later synthetic stage. Upon substitution of the bromine for chlorine using sodium bromide in a dibromomethane (DBM) dimethylformamide (DMF) mixture, we observed the unexpected anomerization of the N-acetylglucosamine β glycosides, yielding up to 90% of the α glycosides. We describe our studies of this unexpected anomerization and report on how the anomeric ratios can be controlled experimentally. Interestingly, we also report the anomerization of alkyl β glycosides of N-acetylglucosamine in a mixture of DBM and DMF without sodium bromide. Further studies are being conducted to determine the mechanism of this anomerization and the scope of this reaction.
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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".