Ly49 receptors: evolution, genetic diversity, and impact on immunity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Natural killer (NK) cells express cell surface receptors that recognize class I major histocompatibility complex (MHC-I) molecules to distinguish between healthy and unhealthy cells. The multigenic and polymorphic nature of the MHC-I genes has influenced the convergent evolution of similarly polymorphic and diversified NK cell receptor families: the C-type lectin-like Ly49 receptors in mice, and the killer cell immunoglobulin-like receptors (KIRs) in humans. Although structurally distinct, both receptor families have similar functions in terms of MHC-I recognition and downstream signal transduction, and they regulate multiple aspects of NK cell biology during development and after maturation as fully differentiated and functionally competent cells. The Ly49 gene locus has undergone rapid, lineage-specific expansions and contractions resulting in multiple distinct haplotypes of variable gene number, allelic diversity, and MHC-I ligand specificity. This in turn has influenced the type and degree of Ly49 receptor expression on NK cells, and their contribution to immunity in different mouse strains. In this review, we have attempted to describe the evolutionary processes that have shaped strain-specific Ly49 receptor repertoires, and their impact on NK cell functions during health and disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.015 |
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 it