Improved hematopoietic differentiation of human pluripotent stem cells via estrogen receptor signaling pathway
Bibliographic record
Abstract
BACKGROUND: Aside from its importance in reproduction, estrogen (E2) is known to regulate the proliferation and differentiation of hematopoietic stem cells in rodents. However, the regulatory role of E2 in human hematopoietic system has not been investigated. The purpose of this study is to investigate the effect of E2 on hematopoietic differentiation using human pluripotent stem cells (hPSCs). RESULTS: E2 improved hematopoietic differentiation of hPSCs via estrogen receptor alpha (ER-α)-dependent pathway. During hematopoietic differentiation of hPSCs, ER-α is persistently maintained and hematopoietic phenotypes (CD34 and CD45) were exclusively detected in ER-α positive cells. Interestingly, continuous E2 signaling is required to promote hematopoietic output from hPSCs. Supplementation of E2 or an ER-α selective agonist significantly increased the number of hemangioblasts and hematopoietic progenitors, and subsequent erythropoiesis, whereas ER-β selective agonist did not. Furthermore, ICI 182,780 (ER antagonist) completely abrogated the E2-induced hematopoietic augmentation. Not only from hPSCs but also from human umbilical cord bloods, does E2 signaling potentiate hematopoietic development, suggesting universal function of E2 on hematopoiesis. CONCLUSIONS: Our study identifies E2 as positive regulator of human hematopoiesis and suggests that endocrine factors such as E2 influence the behavior of hematopoietic stem cells in various physiological conditions.
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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".