Critical role of natural killer cells in the rejection of human hepatocytes after xenotransplantation into immunodeficient mice
Bibliographic record
Abstract
The severe combined immunodeficiency/albumin linked-urokinase type plasminogen activator (SCID/Alb-uPA) human liver chimeric mouse model has added a new dimension to studies of liver based human diseases and has important potential for study of human hepatic drug metabolism. However, it remains unclear if natural killer (NK) cell in SCID/Alb-uPA mice has an important negative impact on engraftment and expansion of human hepatocytes after transplantation. Here, we explore the role of mouse NK cells in the rejection of transplanted human hepatocytes in SCID/Alb-uPA mice. We assessed NK cell activity in vivo, using (125)I-iodo-2'-deoxyuridine incorporation assay. Low serum human alpha-1 antitrypsin (hAAT, <10 microg/ml) recipients, representing graft failure, showed resistance to engraftment of MHC class I knockout marrow (indicating high NK cell activity), while NK cell-depleted low hAAT recipients and high hAAT (>100 microg/ml) recipients accepted MHC class I knockout marrow, indicating a correlation between low NK cell activity, in vivo, and high level human hepatocyte engraftment. We also showed that higher level engraftment of human hepatocytes was achieved in both NK cell-depleted SCID/Alb-uPA mice and Rag2(-/-)gammac(-/-)/Alb-uPA (T,B and NK cell deficient) mice compared with untreated SCID/Alb-uPA mice. These results support a critical role for mouse NK cells in the rejection of human hepatocytes xenotransplanted to immunodeficient mice.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".