A novel antibody combination to identify KIR2DS2<sup>high</sup> natural killer cells in KIR2DL3/L2/S2 heterozygous donors
Bibliographic record
Abstract
The killer cell immunoglobulin-like receptor (KIR) KIR2DS2 induces natural killer (NK) cell activation upon ligation and in genetic studies is associated with protection against certain cancers and viral infections. One of the difficulties in understanding KIR2DS2 has been that ligands have been hard to define. In part, this is because the high sequence homology between KIR2DS2 and KIR2DL3/KIR2DL2 has made it difficult to make antibodies that specifically detect NK cells expressing KIR2DS2. Using transfected NK cell line (NKL) cells and primary human samples, we report the identification of a novel antibody combination which allows identification of NK cells with relatively high expression of KIR2DS2. This separation is sufficient to examine primary human NK cell activation in response to KIR2DS2 specific ligands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".