Structural advances of Siglecs: insight into synthetic glycan ligands for immunomodulation
Bibliographic record
Abstract
Sialic acid-binding immunoglobulin-like lectins (Siglecs) are transmembrane proteins of the immunoglobulin (Ig) superfamily predominantly expressed on the cells of our immune system. Siglecs recognize sialic acid via their terminal V-set domain. In mammals, sialic acid-terminated glycolipids and glycoproteins are the ligands of Siglecs, and the monomeric affinity of Siglecs for their sialic acid-containing ligands is weak. Significant efforts have been devoted toward the development of chemically modified sialoside ligands to target Siglecs with higher affinity and selectivity. In this review we discuss natural and synthetic sialoside ligands for each human Siglec, emphasizing the ligand binding determinants uncovered from recent advances in protein structural information. Potential therapeutic applications of these ligands are also discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".