Ex vivo treatment of proliferating human cord blood stem cells with stroma-derived factor–1 enhances their ability to engraft NOD/SCID mice
Bibliographic record
Abstract
Ex vivo proliferation of hematopoietic stem cells (HSCs) is important for cellular and gene therapy but is limited by the observation that HSCs do not engraft as they transit S/G(2)/M. Recently identified candidate inhibitors of human HSC cycling are transforming growth factor-beta(1) (TGF-beta(1)) and stroma-derived factor-1 (SDF-1). To determine the ability of these factors to alter the transplantability of human HSCs proliferating in vitro, lin(-) cord blood cells were first cultured for 96 hours in serum-free medium containing Flt3 ligand, Steel factor, interleukin-3, interleukin-6, and granulocyte colony-stimulating factor. These cells were then transferred to medium containing Steel factor and thrombopoietin with or without SDF-1 and/or TGF-beta(1) for 48 hours. Exposure to SDF-1 but not TGF-beta(1) significantly increased (> 2-fold) the recovery of HSCs able to repopulate nonobese diabetic/severe combined immunodeficiency mice. These results suggest new strategies for improving the engraftment activity of HSCs stimulated to proliferate ex vivo.
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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".