Reversible Lineage-Specific Priming of Human Embryonic Stem Cells Can Be Exploited to Optimize the Yield of Differentiated Cells
Bibliographic record
Abstract
The clinical use of human embryonic stem cells (hESCs) requires efficient cellular expansion that must be paired with an ability to generate specialized progeny through differentiation. Self-renewal and differentiation are deemed inherent hallmarks of hESCs and a growing body of evidence suggests that initial culture conditions dictate these two aspects of hESC behavior. Here, we reveal that defined culture conditions using commercial mTeSR1 media augment the expansion of hESCs and enhance their capacity for neural differentiation at the expense of hematopoietic lineage competency without affecting pluripotency. This culture-induced modification was shown to be reversible, as culture in mouse embryonic fibroblast-conditioned media (MEF-CM) in subsequent passages allowed mTeSR1-expanded hESCs to re-establish hematopoietic differentiation potential. Optimal yield of hematopoietic cells can be achieved by expansion in mTeSR1 followed by a recovery period in MEF-CM. Furthermore, the lineage propensity to hematopoietic and neural cell types could be predicted via analysis of surrogate markers expressed by hESCs cultured in mTeSR1 versus MEF-CM, thereby circumventing laborious in vitro differentiation assays. Our study reveals that hESCs exist in a range of functional states and balance expansion with differentiation potential, which can be modulated by culture conditions in a predictive and quantitative manner.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".