Molecular and Genetic Basis for Strain-Dependent NK1.1 Alloreactivity of Mouse NK Cells
Bibliographic record
Abstract
NK1.1 alloantigen expression can be used to define NK cells in certain mouse strains, such as B6 (NKR-P1C) and SJL (NKR-P1B). However, BALB/c NK cells do not react with the anti-NK1.1 mAb, PK136. To investigate the NK1.1(-) phenotype of BALB/c NK cells, we have undertaken NK1.1 epitope mapping and genomic analysis of the BALB/c Nkrp1 region. Bacterial artificial chromosome library analysis reveals that, unlike the Ly49 region, the Nkrp1-Ocil/Clr region displays limited genetic divergence between B6 and BALB/c mice. In fact, significant divergence is confined to the Nkrp1b and Nkrp1c genes. Strikingly, the B6 Nkrp1d gene appears to represent a divergent allele of the Nkrp1b gene in BALB/c mice and other strains. Importantly, BALB/c NK cells express abundant and functional Nkrp1 transcripts, and the BALB/c NKR-P1B receptor functionally binds Ocil/Clr-b ligand. However, the BALB/c NKR-P1B/C sequences differ from those of the known NK1.1 alloantigens, and epitope mapping demonstrates that directed mutation of a single amino acid in the NKR-P1B(BALB) protein confers NK1.1 reactivity. Thus, PK136 mAb recognizes, in part, a distal C-terminal epitope present in NKR-P1B(Sw/SJL) and NKR-P1C(B6), but absent in NKR-P1A/D/F(B6) and NKR-P1B/C(BALB). Allelic divergence of the Nkrp1b/c gene products and limited divergence of the BALB/c Nkrp1-Ocil/Clr region explain a longstanding confusion regarding the strain-specific NK1.1 alloantigen reactivity of mouse NK cells.
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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 | 0.000 | 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 | 0.000 |
| 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 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".