Advances in understanding and exploiting Siglec–glycan interactions
Bibliographic record
Abstract
Sialic-acid-binding immunoglobulin-type lectins (Siglecs) are a family of cell-surface immunomodulatory receptors that recognize sialic-acid-containing glycans. The majority of Siglecs have an inhibitory motif in their intercellular domain and can regulate the cellular activation of immune cells. Importantly, the immunomodulatory role of Siglecs is regulated by engagement with distinct sialoglycan ligands. However, there are still many unanswered questions about the precise ligand(s) recognized by individual Siglec family members. New tools and approaches to study Siglec-ligand interactions are rapidly filling this knowledge gap. This review provides an overview of recent advances in discovering Siglec ligands as well as the development of approaches to modulate the function of Siglecs. In both aspects, chemical biology approaches are emphasized with a discussion on how these are complementing biochemical and genetic strategies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".