Allelic Variation in the Ectodomain of the Inhibitory Ly-49G2 Receptor Alters Its Specificity for Allogeneic and Xenogeneic Ligands
Bibliographic record
Abstract
The Ly-49 multigene receptor family regulates mouse NK cell functions. A number of Ly-49 genes exhibit allelic variation, but the functional significance of allelic differences in extracellular domains of Ly-49 receptors regarding ligand specificity is largely unknown. Amino acid differences exist in the extracellular domains of the B6 and BALB/c allele products of the inhibitory Ly-49G receptor. We constructed chimeric Ly-49 receptors consisting of common cytoplasmic and transmembrane regions of the activating Ly-49W receptor fused with the ectodomains of the B6 and BALB/c alleles of Ly-49G. Expression of these chimeras in the RNK-16 rat NK cell line allowed us to study the specificity of inhibitory receptor ectodomains as they stimulated NK lytic activity. We found that the ectodomain of the BALB/c allele of Ly-49G recognizes both H-2D(d) and D(k) class I MHC alleles, whereas the ectodomain of the B6 allele of Ly-49G recognizes D(d), and not D(k). The specificity for D(k) as well as D(d) of the wild-type Ly-49G(BALB/c) allele product was confirmed with RNK-16 transfectants of this inhibitory receptor. Furthermore, the ectodomain of the Ly-49G(BALB/c) allele recognizes a distinct repertoire of xenogeneic ligands that only partially overlaps with that recognized by Ly-49G(B6). Our results indicate that allelic variation in Ly-49 extracellular domains can have functional significance by altering Ly-49 receptor specificity for mouse class I MHC and xenogeneic ligands.
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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 | 0.001 |
| 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".