Increased Engraftment of Human Short Term Repopulating Hematopoietic Cells in NOD/SCID/IL2rγnull Mice by Lentiviral Expression of NUP98-HOXA10HD
Bibliographic record
Abstract
Techniques to expand human hematopoietic stem cells ex-vivo could be beneficial to the fields of clinical hematopoietic stem cell transplantation and gene therapy targeted at hematopoietic stem cells. NUP98-HOXA10HD is a relatively newly discovered fusion gene that in mouse transplant experiments has been shown to increase numbers of hematopoietic stem cells. We evaluated whether this fusion gene could be used to expand engrafting human primitive CD34+ cells in an immunodeficient mouse model. Gene transfer was achieved using a lentiviral based vector. The engraftment of mobilized peripheral blood human CD34+ cells grown in culture for one week after gene transfer was evaluated 3-4 months after transplant and found to be 2-3 fold higher in the NUP98-HOXA10HD groups as compared to controls. These data suggest an expansive effect at least at the short term human repopulating cell level. Further evaluation in long term repopulating models and investment in a NUP98-HOXA10HD protein seems worthy of consideration. Additionally, the results here provide strong impetus to utilize NUP98-HOXA10HD as a tool to search for underlying genes and pathways involved in hematopoietic stem cell expansion that can be enhanced and have an even more potent expansive effect.
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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) | 0.002 | 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".