Culture and <i>in vitro</i> hepatogenic differentiation of placenta‐derived stem cells, using placental extract as an alternative to serum
Bibliographic record
Abstract
OBJECTIVES: Translational research using adult stem cells derived from various tissues has been highlighted in cell-based therapy. However, there are many limitations to using conventional culture systems of adult stem cells for clinically applicability, including limited combinations of cytokines and use of nutrients derived from animals. Here, we have investigated the effects of placental extract (PE) for culture of placenta-derived stem cells (PDSCs) as well as their potential for hepatogenic differentiation. MATERIALS AND METHODS: Placental extract, extracted using water-soluble methods, was used as a supplement for culture of PDSCs. Cell viability was determined using the MTT assay, and cytokine assay was performed using Luminex assay kit. Gene expression, indocyanine green (ICG) up-take, PAS (Periodic Acid-Schiff) staining and urea production were also analysed. RESULTS: The placental extract contained several types of cytokine and chemokine essential for maintenance and differentiation of stem cells. Expression of stemness markers in PDSCs cultured with PE is no different from that of PDSCs cultured with foetal bovine serum (FBS). After hepatogenic differentiation, expression patterns for hepatocyte-specific markers in PDSCs cultured with PE were consistent and potential for hepatogenic differentiation of PDSCs cultured with PE was similar to that of PDSCs cultured with FBS, as shown by PAS staining and urea production assays. CONCLUSIONS: Our findings revealed that placental extract could be used as a new component for culture of adult stem cells, as well as for development of human-based medium, in translational research for regenerative medicine.
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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) | 0.001 | 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) | 0.001 | 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".