Umbilical Cord Tissue as a Source of Young Cells for the Derivation of Induced Pluripotent Stem Cells Using Non-Integrating Episomal Vectors and Feeder-Free Conditions
Bibliographic record
Abstract
The clinical application of induced pluripotent stem cells (iPSC) needs to balance the use of an autologous source that would be a perfect match for the patient against any safety or efficacy issues that might arise with using cells from an older patient or donor. Drs. Takahashi and Yamanaka and the Office of Cellular and Tissue-based Products (PMDA), Japan, have had concerns over the existence of accumulated DNA mutations in the cells of older donors and the possibility of long-term negative effects. To mitigate the risk, they have chosen to partner with the Umbilical Cord (UC) banks in Japan to source allogeneic-matched donor cells. Production of iPSCs from UC blood cells (UCB) has been successful; however, reprogramming blood cells requires cell enrichment with columns or flow cytometry and specialized growth media. These requirements add to the cost of production and increase the manipulation of the cells, which complicates the regulatory approval process. Alternatively, umbilical cord tissue mesenchymal stromal cells (CT-MSCs) have the same advantage as UCB cells of being a source of young donor cells. Crucially, CT-MSCs are easier and less expensive to harvest and grow compared to UCB cells. Here, we demonstrate that CT-MSCs can be easily isolated without expensive enzymatic treatment or columns and reprogramed well using episomal vectors, which allow for the removal of the reprogramming factors after a few passages. Together the data indicates that CT-MSCs are a viable source of donor cells for the production of clinical-grade, patient matched iPSCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".