Origins of natural killer cell memory: special creation or adaptive evolution
Bibliographic record
Abstract
The few initial formative studies describing non-specific and apparently spontaneous activity of natural killer (NK) cells have since multiplied into thousands of scientific reports defining their unique capacities and means of regulation. Characterization of the array of receptors that govern NK cell education and activation revealed an unexpected relationship with the major histocompatibility molecules that NK cells originally became well known for ignoring. Proceeding true to form, NK cells continue to up-end archetypal understanding of their ever-expanding capabilities. Discovery that the NK cell repertoire is extremely diverse and can be reshaped by particular viruses into unique subsets of adaptive NK cells challenges, or at least broadens, the definition of immunological memory. This review provides an overview of studies identifying adaptive NK cells, addressing the origins of NK cell memory and introducing the heretical concept of NK cells with extensive antigenic specificity. Whether these newly apparent properties reflect adaptive utilization of known NK cell attributes and receptors or a specially creative allocation from an undefined receptor array remains to be fully determined.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".