The Inherent Differentiation Program of Short-Term Hematopoietic Repopulating Cells Changes During Human Ontogeny
Bibliographic record
Abstract
Human umbilical cord blood (CB) could be an attractive source of hematopoietic repopulating cells for clinical stem cell therapy because of its accessibility and low propensity for unwanted immune reaction against the host. However, CB recipients suffer from severely delayed and often chronically deficient platelet recovery of unknown cause. Here we show that human short-term repopulating cells (STRCs), which predominantly carry early hematopoietic reconstitution after transplantation, display an intrinsically fixed differentiation program in vivo that changes during ontogeny. Compared to adult sources of hematopoietic cells, CB myeloidrestricted STRC-M showed a markedly reduced megakaryocytic and erythroid cell output in the quantitative xenotransplantation of human short-term hematopoiesis in NOD/SCID-beta2m(-/-) mice. This output in vivo was not altered by pre-treating CB cells before transplantation with growth factors that effectively stimulate megakaryocytopoiesis in vitro. Moreover, injecting mice with granulocyte colony-stimulating factor did not affect the differentiation of human STRC. These findings demonstrate that the differentiation capacity of human STRCs is developmentally regulated by mechanisms inaccessible to currently available hematopoietic growth factors, and explain why thrombopoiesis is deficient in clinical CB 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) | 0.000 | 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) | 0.001 | 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".