Signal control of hematopoietic stem cell fate: Wnt, Notch, and Hedgehog as the usual suspects
Bibliographic record
Abstract
PURPOSE OF REVIEW: Hematopoietic homeostasis depends on appropriate self-renewal and differentiation capacity of hematopoietic stem cells. The characterization of the key extracellular signals that integrate with intracellular molecular machinery to regulate hematopoietic stem cells fate choice is crucial to move toward hematopoietic stem cell clinical application. RECENT FINDINGS: Several factors have been described as positive and negative regulators of hematopoietic stem cell self-renewal and differentiation. Most of the hematopoietic cytokines studied promote either survival or differentiation or both in hematopoietic stem cells ex vivo, whereas morphogens (Wnt, Notch, and Hedgehog) may signify a class of hematopoietic stem cell regulators that support expansion of the hematopoietic stem cell pool by a combination of survival and induced self-renewal. SUMMARY: Although Wnt, Notch, and Hedgehog signaling pathways have been implicated in self-renewal and proliferation in vivo, modulation of these pathways alone does not result in substantive expansion of hematopoietic stem cells ex vivo. In addition to these signaling pathways, Bcl-2 family members may have an important role in inducing survival in hematopoietic stem cells both in vivo and ex vivo. Understanding the complex relationship between these unique signaling pathways is essential to achieve successful ex-vivo expansion toward enhanced hematopoietic stem cell transplantation-based therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".