The Tumorigenic Potential of Human Pluripotent Stem Cells
Bibliographic record
Abstract
Human pluripotent stem cells (hPSCs) are currently evaluated for clinical applications due to their proliferation and differentiation capacities, raising the need to both assess and enhance, the safety of hPSC-based treatments. Distinct molecular features contribute to the tumorigenicity of hPSCs, manifested in the formation of teratoma tumors upon transplantation in vivo. Prolonged in vitro culturing of hPSCs can enhance selection for specific genetic aberrations, either at the chromosome or gene level. Some of these aberrations are tightly linked to human tumor pathology and increase the tumorigenic aggressiveness of the abnormal cells. In this perspective, we describe major tumor-associated risk factors entailed in hPSC-based therapy, and present precautionary and safety measures relevant for the development and application of such 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 | 0.001 | 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 | 0.001 | 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".