Expansion and long-term maintenance of induced pluripotent stem cells in stirred suspension bioreactors
Bibliographic record
Abstract
Induced pluripotent stem cells (iPSCs) can provide an important source of cells for the next-generation of cell therapies in regenerative medicine, in part due to their similarity to embryonic stem cells (ESCs). Patient-specific iPSCs represent an opportunity for autologous cell therapies that are not restricted by immunological, ethical and technical obstacles. One of the technical hurdles that must be overcome before iPSCs can be clinically implemented is the scalable, reproducible production of iPSCs and their differentiated progeny. All of the iPSC lines established thus far have been generated and expanded with static tissue culture protocols, which are time-consuming and suffer from batch-to-batch variability. Alternatively, stirred suspension bioreactors propose several benefits and their homogeneous culture environment facilitates the large-scale expansion required for clinical studies at less cost. We have previously developed protocols for expanding murine and human ESCs as undifferentiated aggregates in stirred suspension bioreactors. The resulting cells were karyotypically normal, expressed pluripotency markers and could be differentiated into all three germ lineages, both in vitro and in vivo. In this study, we demonstrate that stirred suspension bioreactors yield 58-fold expansion of undifferentiated pluripotent iPSCs over 4 days. In vitro differentiation into cartilage, bone and cardiomyocytes lineages, in addition to in vivo teratoma formation, further confirmed the existence of fully functional and undifferentiated pluripotent iPSC aggregates following long-term passaging. Stirred suspension bioreactor culture represents an efficient process for the large-scale expansion and maintenance of iPSCs, which is an important first step in their clinical application.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".