Efficiency of embryoid body formation and hematopoietic development from embryonic stem cells in different culture systems
Bibliographic record
Abstract
Embryonic stem (ES) cells have tremendous potential as a cell source for cell-based therapies. Realization of that potential will depend on our ability to understand and manipulate the factors that influence cell fate decisions and to develop scalable methods of cell production. We compared four standard ES cell differentiation culture systems by measuring aspects of embryoid body (EB) formation efficiency and cell proliferation, and by tracking development of a specific differentiated tissue type-blood-using functional (colony-forming cell) and phenotypic (Flk-1 and CD34 expression) assays. We report that individual murine ES cells form EBs with an efficiency of 42 +/- 9%, but this value is rarely obtained because of EB aggregation-a process whereby two or more individual ES cells or EBs fuse to form a single, larger cell aggregate. Regardless of whether EBs were generated from a single ES cell in methylcellulose or liquid suspension culture, or aggregates of ES cells in hanging drop culture, they grew to a similar maximum cell number of 28,000 +/- 9,000 cells per EB. Among the three methods for EB generation in suspension culture there were no differences in the kinetics or frequency of hematopoietic development. Thus, initiating EBs with a single ES cell and preventing EB aggregation should allow for maximum yield of differentiated cells in the EB system. EB differentiation cultures were also compared to attached differentiation culture using the same outputs. Attached colonies were not similarly limited in cell number; however, hematopoietic development in attached culture was impaired. The percentage of early Flk-1 and CD34 expressing cells was dramatically lower than in EBs cultured in suspension, whereas hematopoietic colony formation was almost completely inhibited. These results provide a foundation for development of efficient, scalable bioprocesses for ES cell differentiation, and inform novel methods for the production of hematopoietic tissues.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".