VEGF-A165 augments erythropoietic development from human embryonic stem cells
Bibliographic record
Abstract
Combinations of hematopoietic cytokines and the ventral mesoderm inducer BMP-4 have recently been shown to augment hematopoietic cell fate of human embryonic stem cells (hESCs) during embryoid body (EB) development. However, factors capable of regulating lineage commitment of hESC-derived hematopoiesis have yet to be reported. Here we show that vascular endothelial growth factor (VEGF-A165) selectively promotes erythropoietic development from hESCs. Effects of VEGF-A165 were dependent on the presence of hematopoietic cytokines and BMP-4, and could be augmented by addition of erythropoietin (EPO). Treatment of human EBs with VEGF-A165 increased the frequency of cells coexpressing CD34 and the VEGF-A165 receptor KDR, as well as cells expressing erythroid markers. Although fetal/adult globins were unaffected, VEGF-A165 induced the expression of embryonic zeta (zeta) and epsilon (epsilon) globins, and was accompanied by expression of the hematopoietic transcription factor SCL/Tal-1. In addition to promoting erythropoietic differentiation from hESCs, the presence of VEGF-A165 enhanced the in vitro self-renewal potential of primitive hematopoietic cells capable of erythroid progenitor capacity. Our study demonstrates a role for VEGF-A165 during erythropoiesis of differentiating hESCs, thereby providing the first evidence for a factor capable of regulating hematopoietic lineage development of hESCs.
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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".