Induction of Human Blood Group A Antigen Expression on Mouse Cells, Using Lentiviral Gene Transduction
Bibliographic record
Abstract
Fan and colleagues at the University of Alberta develop a lentiviral-based gene transfer system that can be used to induce human histo-blood group antigens on mouse cells. They demonstrate that this vector can be used in vivo to induce human A antigen expression in mouse liver. The authors suggest that this gene transfer strategy can be used to develop a small animal model of the human ABO histo-blood system. The ABO histo-blood group system is the most important antigen system in transplantation medicine, yet no small animal model of the ABO system exists. To determine the feasibility of developing a murine model, we previously subcloned the human α-1,2-fucosyltransferase (H-transferase, EC 2.4.1.69) cDNA and the human α-1,3-N-acetylgalactosaminyltransferase (A-transferase, EC 2.4.1.40) cDNA into lentiviral vectors to study their ability to induce human histo-blood group A antigen expression on mouse cells. Herein we investigated the optimal conditions for human A and H antigen expression in murine cells. We determined that transduction of a bicistronic lentiviral vector (LvEF1-AH-trs) resulted in the expression of A antigen in a mouse endothelial cell line. We also studied the in vivo utility of this vector to induce human A antigen expression in mouse liver. After intrahepatic injection of LvEF1-AH-trs, A antigen expression was observed on hepatocytes as detected by immunohistochemistry and real-time RT-PCR. In human group A erythrocyte-sensitized mice, A antigen expression in the liver was associated with tissue damage, and deposition of antibody and complement. These results suggest that this gene transfer strategy can be used to simulate the human ABO blood group system in a murine model. This model will facilitate progress in the development of interventions for ABO-incompatible transplantation and transfusion scenarios, which are difficult to develop in clinical or large animal settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".