Retroviral transduction of hematopoietic cells differentiated from human embryonic stem cell-derived CD45negPFV hemogenic precursors
Bibliographic record
Abstract
Human embryonic stem cells (hESCs) provide a unique opportunity to study molecular mechanisms that regulate specification of the hematopoietic lineage in the human. Exploitation of this model using transgenic strategies depends on the ability to target cells of the hematopoietic lineage effectively and establish stable transgene expression. Here, a recently defined subpopulation of endothelial-like precursors derived from hESCs that is exclusively responsible for hematopoietic cell fate (CD45(neg)PFV) is shown to express GALVR-1 receptor and be efficiently transduced with GALV-pseudotyped retrovirus. Retroviral transduction, measured by enhanced green fluorescent protein, of hESC-derived CD45(+) cells differentiated from isolated CD45(neg)PFV precursors was 26.5 +/- 13% with 5.6 +/- 4% of these cells coexpressing CD34. An average of 17.5% of clonogenic hematopoietic progenitors derived from CD45(neg)PFV precursors expressed the retroviral transgene. Addition of serum to cultures after retroviral exposure supported transgene expression in resulting hematopoietic cells derived from hemogenic CD45(neg)PFV precursors. Our study represents the first report to demonstrate that retroviral transduction systems, similar to those used currently in clinical gene therapy protocols, are capable of efficient transduction of hematopoietic progenitors derived from 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".