mSiglec-E, a novel mouse CD33-related siglec (sialic acid-binding immunoglobulin-like lectin) that recruits Src homology 2 (SH2)-domain-containing protein tyrosine phosphatases SHP-1 and SHP-2
Bibliographic record
Abstract
The sialic acid-binding immunoglobulin-like lectins (siglecs) represent a recently defined distinct subset of the immunoglobulin superfamily. By using the Src homology 2 (SH2)-domain-containing protein tyrosine phosphatase SHP-1 as bait in a yeast two-hybrid screen, we have identified a new member of the mouse siglec family, mSiglec-E. The mSiglec-E cDNA encodes a protein of 467 amino acids that contains three extracellular immunoglobulin-like domains, a transmembrane region and a cytoplasmic tail bearing two immunoreceptor tyrosine-based inhibitory motifs (ITIMs). mSiglec-E is highly expressed in mouse spleen, a tissue rich in leucocytes. The ITIMs of mSiglec-E can recruit SHP-1 and SHP-2, two inhibitory regulators of immunoreceptor signal transduction. This suggests that the function of mSiglec-E is probably an involvement in haematopoietic cells and the immune system as an inhibitory receptor. When expressed in COS-7 cells, mSiglec-E was able to mediate sialic acid-dependent binding to human red blood cells, suggesting that mSiglec-E may function through cell–cell interactions. In comparison with the known members of the siglec family, mSiglec-E exhibits a high degree of sequence similarity to both human siglec-7 and siglec-9. The gene encoding mSiglec-E is localized in the same chromosome as that encoding mouse CD33. Phylogenetic analysis reveals that neither mouse mSiglec-E nor CD33 shows a clear relationship with any human siglecs so far identified.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".