Fucosylation in prokaryotes and eukaryotes
Bibliographic record
Abstract
Fucosylated carbohydrate structures are involved in a variety of biological and pathological processes in eukaryotic organisms including tissue development, angiogenesis, fertilization, cell adhesion, inflammation, and tumor metastasis. In contrast, fucosylation appears less common in prokaryotic organisms and has been suggested to be involved in molecular mimicry, adhesion, colonization, and modulating the host immune response. Fucosyltransferases (FucTs), present in both eukaryotic and prokaryotic organisms, are the enzymes responsible for the catalysis of fucose transfer from donor guanosine-diphosphate fucose to various acceptor molecules including oligosaccharides, glycoproteins, and glycolipids. To date, several subfamilies of mammalian FucTs have been well characterized; these enzymes are therefore delineated and used as models. Non-mammalian FucTs that possess different domain construction or display distinctive acceptor substrate specificity are highlighted. It is noteworthy that the glycoconjugates from plants and schistosomes contain some unusual fucose linkages, suggesting the presence of novel FucT subfamilies as yet to be characterized. Despite the very low sequence homology, striking functional similarity is exhibited between mammalian and Helicobacter pylori alpha1,3/4 FucTs, implying that these enzymes likely share a conserved mechanistic and structural basis for fucose transfer; such conserved functional features might also exist when comparing other FucT subfamilies from different origins. Fucosyltranferases are promising tools used in synthesis of fucosylated oligosaccharides and glycoconjugates, which show great potential in the treatment of infectious and inflammatory diseases and tumor metastasis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".