Ultrasensitive and rapid quantification of rare tumorigenic stem cells in hPSC-derived cardiomyocyte populations
Bibliographic record
Abstract
The ability to detect rare human pluripotent stem cells (hPSCs) in differentiated populations is critical for safeguarding the clinical translation of cell therapy, as these undifferentiated cells have the capacity to form teratomas in vivo. The detection of hPSCs must be performed using an approach compatible with traceable manufacturing of therapeutic cell products. Here, we report a novel microfluidic approach, stem cell quantitative cytometry (SCQC), for the quantification of rare hPSCs in hPSC-derived cardiomyocyte (CM) populations. This approach enables the ultrasensitive capture, profiling, and enumeration of trace levels of hPSCs labeled with magnetic nanoparticles in a low-cost, manufacturable microfluidic chip. We deploy SCQC to assess the tumorigenic risk of hPSC-derived CM populations in vivo. In addition, we isolate rare hPSCs from the differentiated populations using SCQC and characterize their pluripotency.
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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 | 0.000 | 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) | 0.000 | 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".