Bifunctional CD22 Ligands Use Multimeric Immunoglobulins as Protein Scaffolds in Assembly of Immune Complexes on B Cells
Bibliographic record
Abstract
CD22 is a B cell-specific sialic acid-binding immunoglobulin-like lectin (Siglec) whose function as a regulator of B cell signaling is modulated by its interaction with glycan ligands bearing the sequence NeuAc alpha2-6Gal. To date, only highly multivalent polymeric ligands (n = 450) have achieved sufficient avidity to bind to CD22 on native B cells. Here we demonstrate that a synthetic bifunctional molecule comprising a ligand of CD22 linked to an antigen (nitrophenol; NP) can use a monoclonal anti-NP IgM as a decavalent protein scaffold to efficiently drive assembly of IgM-CD22 complexes on the surface of native B cells. Surprisingly, anti-NP antibodies of lower valency, IgA (n = 4) and IgG (n = 2), were also found to drive complex formation, though with lower avidity. Ligands bearing alternate linkers of variable length and structure were constructed to establish the importance of a minimal length requirement, and versatility in the structural requirement. We show that the ligand drives assembly of IgM complexes exclusively on the surface of B cells and not other classes of white blood cells that do not express CD22, which lends itself to the possibility of targeting B cells in certain hematopoietic malignancies.
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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".