Comparison of Synthetic Media Designed for Expansion of Adipose-Derived Mesenchymal Stromal Cells
Bibliographic record
Abstract
Mesenchymal stromal cells (MSCs) are multipotent cells that can differentiate into various cell types, such as osteoblasts, myocytes, and adipocytes. This characteristic makes the cells a useful tool in developing new therapies for a number of common maladies and diseases. The utilization of animal-derived growth serum, such as fetal bovine serum (FBS), for the expansion of MSCs has traditionally been used for cell culture. However, in clinical applications, animal-derived products present limitations and safety concerns for the recipient, as exposure to animal (xeno-) antigens and infectious agents is possible. Multiple synthetic, xeno-free media have been developed to combat these limitations of animal-derived growth serum and have the potential to be used in ex vivo MSC expansion for clinical use. The goal of this study was to determine if xeno-free media are adequate to significantly and efficiently expand MSCs derived from adipose tissue. MSCs were cultured in both standard FBS-containing as well as xeno-free media. The media were compared for cell yield, viability, and phenotypic expression via flow cytometry and directed differentiation. The xeno-free media that were tested were StemMACS MSC Expansion Media (Miltenyi Biotec, Bergisch Gladbach, Germany), PLTMax Human Platelet Lysate (Sigma-Aldrich, St. Louis, MO, USA), and MesenCult-hPL media (Stemcell Technologies, Vancouver, BC, Canada). All xeno-free media showed promise as a feasible replacement for animal-derived growth serums. The xeno-free media expanded MSCs more quickly than the FBS-containing medium and also showed great similarity in cell viability and phenotypic expression. In fact, each xeno-free media produced a greater viable cell yield than the standard FBS-containing medium.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".