Inability of Human Induced Pluripotent Stem Cell-Hematopoietic Derivatives to Downregulate MicroRNAs In Vivo Reveals a Block in Xenograft Hematopoietic Regeneration
Bibliographic record
Abstract
Hematopoietic stem cells (HSCs) can regenerate the entire hematopoietic system in vivo, providing the most relevant criteria to measure candidate HSCs derived from human embryonic stem cell (hESC) or induced pluripotent stem cell (hiPSC) sources. Here we show that, unlike primitive hematopoietic cells derived from hESCs, phenotypically identical cells derived from hiPSC are more permissive to graft the bone marrow of xenotransplantation recipients. Despite establishment of bone marrow graft, hiPSC-derived cells fail to demonstrate hematopoietic differentiation in vivo. However, once removed from recipient bone marrow, hiPSC-derived grafts were capable of in vitro multilineage hematopoietic differentiation, indicating that xenograft imparts a restriction to in vivo hematopoietic progression. This failure to regenerate multilineage hematopoiesis in vivo was attributed to the inability to downregulate key microRNAs involved in hematopoiesis. Based on these analyses, our study indicates that hiPSCs provide a beneficial source of pluripotent stem cell-derived hematopoietic cells for transplantation compared with hESCs. Since use of the human-mouse xenograft models prevents detection of putative hiPSC-derived HSCs, we suggest that new preclinical models should be explored to fully evaluate cells generated from hiPSC sources.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".