Reciprocal Transfer of Class I MHC Allele Specificity between Activating Ly-49P and Ly-49W Receptors by Exchange of β4–β5 Loop Residues
Bibliographic record
Abstract
Receptors of the Ly-49 multigene family regulate rodent NK cell functions. Ly-49Rs are highly polymorphic and exist in either activating or inhibitory forms. Examples of both Ly-49 receptor types have been shown to recognize class I MHC ligands. Ly-49Rs can distinguish between class I alleles, but the molecular basis of this discrimination is unknown. Two activating receptors, Ly-49P and Ly-49W, differ in class I recognition, recognizing H-2D(d), or H-2D(d) and D(k), respectively. In this report, we demonstrate that specificity for H-2D(k) can be transferred from Ly-49W to Ly-49P by substituting 3 aa predicted to reside in the beta4-beta5 loop of Ly-49W into Ly-49P. Replacement of these same residues of Ly-49W with corresponding residues in Ly-49P eliminates H-2D(k) recognition while still preserving H-2D(d) recognition. Further mutagenesis indicates that all 3 aa facilitate optimal class I specificity exchange. These results provide the first evidence for a specific site on Ly-49Rs, the beta4-beta5 loop, in determining class I MHC allele specificity.
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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 | 0.001 |
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".