Novel roles for Notch, Wnt and Hedgehog in hematopoesis derived from human pluripotent stem cells
Bibliographic record
Abstract
Human pluripotent stem cells (PSCs) derived from a number of different sources, including reprogrammed adult somatic cells, provide a powerful cellular system to study signaling pathways implicated in cell fate decisions, and generate new sources of cells for regenerative medicine. To realize this potential, it is essential to control the direction and efficiency of human PSC differentiation. Although Notch, Wnt and Hedgehog (HH) signaling pathways have been implicated in the self-renewal/proliferation of hematopoietic stem/progenitor cells, both in vitro and in vivo, their roles in differentiation processes remain poorly explored. This review describes the role(s) of these pathways in the adult and embryonic hematopoietic system of mice and humans, with a particular emphasis on our recent studies on the hematopoietic development of human embryonic stem cells (hESCs). Understanding the individual and collective contributions of Notch, Wnt and HH signaling to the initial development of hematopoiesis is critical for achieving successful ex vivo expansion and differentiation of hematopoietic stem cells (HSCs) from human PSCs that will retain bona fide function comparable to adult-derived HSCs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".