Bibliographic record
Abstract
Abstract Leukocyte immunoglobulin-like receptor B-1 (LILRB-1) is an inhibitory receptor of the immunoglobulin super family expressed on a subset of natural killer (NK) cells. LILRB-1 binds a wide range of classical and non-classical MHC class I molecules, and a glycoprotein product of the human cytomegalovirus (HCMV), UL18. UL18 is a structural homolog of MHC class I expressed on the surface of infected cells. The two most distal domains of LILRB-1, denoted as D1 and D2, are the main contributors at the interaction interface of LILRB-1 with its ligands. Four non-synonymous polymorphisms within D1 and D2 domains produce LILRB-1’s natural variants. Interestingly, these variants have shown different expression and binding trends on NK cells and were suggested to affect susceptibility to HCMV infection in a cohort of kidney transplant recipients. Differences in the interaction of different LILRB-1 variants with their ligands such as, classical (HLA-Cw15) and non-classical MHC class I ligands (HLA-G) as well as UL18 have are assessed using a flowcytometry based binding assay and confirmed with functional assays. Our experiments show a trend of tight binding range of most LILRB-1 variants with HLA-G. However, the strength of binding is more variant with other classical MHC class I ligands, showing a constant trend based on the protein introduced by each of the four non-synonymous polymorphisms in different genotypes. Such findings may highlight an evolutionary pressure to maintain a relatively constant interaction of LILRB-1 with HLA-G, which is expressed on fetal trophoblasts to maintain maternal tolerance.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".