Identification and Characterization of S2V, a Novel Putative Siglec That Contains Two V Set Ig-like Domains and Recruits Protein-tyrosine Phosphatases SHPs
Bibliographic record
Abstract
We describe the molecular cloning and characterization of S2V, a novel sialic acid binding immunoglobulin-like lectin. The cDNA of S2V encodes a type 1 transmembrane protein with four extracellular immunoglobulin-like (Ig-like) domains and a cytoplasmic tail bearing a typical immunoreceptor tyrosine-based inhibitory motif (ITIM) and an ITIM-like motif. A unique feature of S2V is the presence of two V-set Ig-like domains responsible for the binding to sialic acid, whereas all other known siglecs possess only one. S2V is predominantly expressed in macrophage. In vivo S2V was tyrosine-phosphorylated when co-expressed with exogenous c-Src kinase. Upon tyrosine phosphorylation, S2V recruits both Src homology 2 (SH2) domain-containing protein-tyrosine phosphatases SHP-1 and SHP-2, two important inhibitory regulators of immunoreceptor signal transduction. These findings suggest that S2V is involved in the negative regulation of the signaling in macrophage by functioning as an inhibitory receptor. When expressed in COS-7 cells, S2V was able to mediate sialic acid-dependent binding to human red blood cells, suggesting that S2V may function through cell-cell interaction.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".