Acquisition of MHC-Specific Receptors on Murine Natural Killer Cells
Bibliographic record
Abstract
NK cells in adult mice express two families of MHC class I-specific receptors, namely, Ly49 and CD94/NKG2. Co-expression of these receptors in various combinations generates diverse receptor repertoires. The expression of individual receptors is mostly stochastic and independent of each other. NK cells acquire the receptors as they develop from progenitors in the bone marrow in adult mice. In vivo as well as in vitro studies have shown that the acquisition of the receptors is ordered and regulated by the host MHC class I. Developing NK cells first acquire CD94/NKG2 and subsequently various Ly49 receptors in an ordered manner. Unlike adult NK cells, most fetal and neonatal NK cells express CD94/NKG2 but not Ly49. During the first several weeks after birth, NK cells expressing various Ly49 receptors slowly accumulate, while CD94/NKG2+ NK cells decrease to approximately 50% of the population. The acquisition of NK receptors following hematopoietic stem cell transplantation is also a slow and apparently preprogrammed process, mimicking the ontogeny, regardless of whether stem cells from fetal liver or adult bone marrow are used as donors. The regulation of the transcription of individual receptor genes is rather complex, since two promoters have been identified for the genes encoding Ly49 and CD94.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".