Human Progenitor Cells Rapidly Mobilized by AMD3100 Repopulate NOD/SCID Mice with Increased Frequency in Comparison to Cells from the Same Donor Mobilized by Granulocyte Colony Stimulating Factor
Bibliographic record
Abstract
AMD3100 inhibits the interaction between SDF-1 and CXCR4, and rapidly mobilizes hematopoietic progenitors for clinical transplantation. However, the repopulating function of human cells mobilized with AMD3100 has not been characterized in comparison to cells mobilized with granulocyte-colony stimulating factor (G-CSF) in the same donor. Therefore, healthy donors were leukapheresed 4 hours after injection with AMD3100; after 10 days of drug clearance the same donor was mobilized with G-CSF, allowing a paired comparison of repopulation by mobilized cells. Transplantation of mononuclear cells (MNC) or purified CD34(+) cells was compared at limiting dilution into NOD/SCID mice. Human AMD3100-mobilized MNC possessed enhanced repopulating frequency in comparison to G-CSF-mobilized MNC from paired donors, and purified CD34(+) progenitors were at least as efficient as the G-CSF mobilized cells. The frequencies of NOD/SCID repopulating cells (SRC) were 1 SRC in 8.7 x 10(6) AMD3100-mobilized MNC compared to 1 SRC in 29.0 x 10(6) G-CSF-mobilized MNC, and 1 SRC in 1.2 x 10(5) AMD3100-mobilized CD34(+) cells compared to 1 SRC in 1.8 x 10(5) G-CSF-mobilized CD34(+) cells. Hematopoietic differentiation of transplanted progenitors was similar after AMD3100 or G-CSF-mobilization. Thus, AMD3100 mobilized peripheral blood represents a rapidly obtained, highly repopulating source of hematopoietic progenitors for clinical transplantation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".