Shear‐Controlled Single‐Step Mouse Embryonic Stem Cell Expansion and Embryoid Body–Based Differentiation
Bibliographic record
Abstract
To facilitate the exploitation of embryonic stem cells (ESCs) and ESC-derived cells, scale-up of cell production and optimization of culture conditions are necessary. Conventional ESC culture methods are impractical for large-scale cell production and lack robust microenvironmental control. We developed two stirred-suspension culture systems for the propagation of undifferentiated ESCs--microcarrier and aggregate cultures--and compared them with tissue-culture flask and Petri dish controls. ESCs cultured on glass microcarriers had population doubling times (approximately 14-17 hours) comparable to tissue-culture flask controls. ESC growth could be elicited in shear-controlled stirred-suspension culture, with population doubling times ranging between 24 and 39 hours at 100 rpm impeller speed. Upon removal of leukemia inhibitory factor, the size-controlled ESC aggregates developed into embryoid bodies (EBs) capable of multilineage differentiation. A comprehensive analysis of ESC developmental potential, including flow cytometry for Oct-4, SSEA-1, and E-cadherinprotein expression, reverse transcription-polymerase chain reaction for Flk-1, HNF3-beta, MHC, and Sox-1 gene expression, and EB differentiation analysis, demonstrated that the suspension-cultured ESCs retained the developmental potential of the starting cell population. Analysis of E-cadherin-/- and E-cadherin+/- cells using both systems provided insight into the mechanisms behind the role of cell aggregation control, which is fundamental to these observations. These cell-culture tools should prove useful for both the production of ESCs and ESC-derived cells and for investigations into adhesion, survival, and differentiation phenomena during ESC propagation and differentiation.
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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 | 0.000 | 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 | 0.001 |
| 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".