Cutting Edge: CD43 Functions as a T Cell Counterreceptor for the Macrophage Adhesion Receptor Sialoadhesin (Siglec-1)
Bibliographic record
Abstract
Sialoadhesin (Siglec-1) is a macrophage-restricted sialic acid-binding receptor that mediates interactions with hemopoietic cells, including lymphocytes. In this study, we identify sialoadhesin counterreceptors on T lymphocytes. Several major glycoproteins (85, 130, 240 kDa) were precipitated by sialoadhesin-Fc fusion proteins from a murine T cell line (TK-1). Binding of sialoadhesin to these glycoproteins was sialic acid dependent and was abolished by mutation of a critical residue (R97A) of the sialic acid binding site in the membrane distal Ig-like domain of sialoadhesin. The 130- and 240-kDa sialoadhesin-binding glycoproteins were identified as the sialomucins CD43 and P-selectin glycoprotein ligand 1 (CD162), respectively. CD43 expressed in COS cells supported increased binding to immobilized sialoadhesin. Finally, sialoadhesin bound different glycoforms of CD43 expressed in Chinese hamster ovary cells, including unbranched (core 1) and branched (core 2) O:-linked glycans, that are normally found on CD43 in resting and activated T cells, respectively. These results identify CD43 as a T cell counterreceptor for sialoadhesin and suggest that in addition to its anti-adhesive role CD43 may promote cell-cell interactions.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".