Derivation and Characterization of Hematopoietic Cells From Human Embryonic Stem Cells
Bibliographic record
Abstract
In vitro, the aggregation of pluripotent human embryonic stem cells (hESC) into cell clusters termed embryoid bodies (EB) allows for the spontaneous differentiation of hESC into progeny representing endoderm, mesoderm, and ectoderm lineages. During human EB (hEB) differentiation, stochastic emergence of hematopoietic cells can be enhanced by a combination of hematopoietic cytokines and the ventral mesoderm inducer bone morphogenetic protein (BMP)-4. Dependent on the presence of hematopoietic cytokines and BMP-4, vascular endothelial growth factor (VEGF-A165) selectively promotes erythropoietic development toward the primitive lineage. The effects of VEGF-A165 can be augmented by erythropoietin (EPO). Hematopoietic cells are derived from a rare subpopulation of hemogenic precursors during hEB development. These hemogenic precursors lack CD45, but express PECAM-1, Flk-1, and VE-cadherin (hereinafter CD45(neg)PFV) and are solely responsible for hematopoietic cell fate. Human ESC-derived hematopoietic cells have similar colony and cellular morphologies to those derived from committed adult hematopoietic tissues, and also show repopulating capacity in immune deficient mice after intrabone marrow transplantation. In this chapter, we describe methods that have been successfully applied in our laboratory, including (1) generation of hematopoietic cells by EB formation; (2) augmentation of hematopoiesis by use of hematopoietic cytokines and BMP-4; (3) promotion of erythropoietic development by addition of VEGF-A165 and EPO; (4) isolation of CD45(neg)PFV hemogenic precursors and generation of hematopoietic cells from these precursors; and (5) characterization of hESC-derived hematopoietic cells in vitro and in 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".