Synthesis of the H-type 1 and Lewis B antigens as 6-aminohexyl glycosides
Bibliographic record
Abstract
The LebLea heptasaccharide is a tumor-associated carbohydrate antigen that was isolated from the human colonic adenocarcinoma cell line Colo205 and is a good target for the development of anti-cancer immunotherapeutics. However, it displays on its reducing end the Leb tetrasaccharide: α-l-Fuc p-(1→2)-β-d-Gal p-(1→3)-[α-l-Fuc p-(1→4)]-d-GlcNAc p and the H-type 1 (H-1 antigen) trisaccharide: α-l-Fuc p-(1→2)-β-d-Gal p-(1→3)-d-GlcNAc p that are also found on noncancerous tissues. To discover analogues or fragments of LebLea that could be used as immunotherapeutics while not triggering immune responses against Leb and the H-1 antigen, we have synthesized the Leb tetrasaccharide hexyl glycoside and the Leb and H-1 antigens aminohexyl glycosides to be used in ELISA experiments. We describe an improved preparation of the 6- O-benzyl-2,3,4-tri- O-acetyl-α-d-galactopyranosyl bromide in neutral conditions and demonstrate the importance of appropriately “matching” the reactivity of acceptors with that of glycosyl donors. Mono- and di-fucosylation of a disaccharide diol acceptor with per-benzylated thioethyl fucoside activated in situ with bromine and under halide ion catalysis is described and our results are compared to literature reports. We observed that our fucosylation reactions required higher equivalents of fucosyl donor and extended reaction times than previously reported. We propose that the protecting groups on the galactosyl unit led to a reduced reactivity of the acceptor. The protected intermediates were converted to 6-azido hexyl glycosides and submitted to dissolving metal conditions to give 6-aminohexyl glycosides. We also prepared the n-hexyl tetrasaccharide glycoside Leb that will be used as a soluble antigen in competitive ELISA experiments.
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) | 0.002 | 0.001 |
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".