Sustained Engraftment of Cryopreserved Human Bone Marrow CD34 <sup>+</sup> Cells in Young Adult NSG Mice
Bibliographic record
Abstract
Hematopoietic stem cells (HSCs) are defined by their ability to repopulate the bone marrow of myeloablative conditioned and/or (lethally) irradiated recipients. To study the repopulating potential of human HSCs, murine models have been developed that rely on the use of immunodeficient mice that allow engraftment of human cells. The NSG xenograft model has emerged as the current standard for this purpose allowing for engraftment and study of human T cells. Here, we describe adaptations to the original NSG xenograft model that can be readily implemented. These adaptations encompass use of adult mice instead of newborns and a short ex vivo culture. This protocol results in robust and reproducible high levels of lympho-myeloid engraftment. Immunization of recipient mice with relevant antigen resulted in specific antibody formation, showing that both T cells and B cells were functional. In addition, bone marrow cells from primary recipients exhibited repopulating ability following transplantation into secondary recipients. Similar results were obtained with cryopreserved human bone marrow samples, thus circumventing the need for fresh cells and allowing the use of patient derived bio-bank samples. Our findings have implications for use of this model in fundamental stem cell research, immunological studies in vivo and preclinical evaluations for HSC transplantation, expansion, and genetic modification.
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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) | 0.001 | 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".