Comparison of Human Serum with Fetal Bovine Serum for Expansion and Differentiation of Human Synovial MSC: Potential Feasibility for Clinical Applications
Bibliographic record
Abstract
The aim of this study was to evaluate the effect of human serum (HS) on growth and differentiation capacity of human synovium-derived mesenchymal stem cells (MSC) in comparison to cells grown in fetal bovine serum (FBS). Human MSCs were isolated from the synovium of knee joints of three donors and the cells were cultured individually in varying concentrations of allogenic HS or FBS. Bovine MSCs were isolated from synovium and cultured in the same manner. Cell proliferation was assessed by the tetrazolium assay after passage 3. The capacity for chondrogenic and osteogenic differentiation was investigated in specific media followed by 1,9-dimethylmethylene blue assay and alcian blue staining, or by alizarin red staining, respectively. Human MSCs proliferated significantly more rapidly in the presence of HS than with equivalent levels of FBS. Chondrogenic or osteogenic differentiation occurred to nearly identical levels in HS or FBS. The results of this study indicate that HS is superior for the culture of human MSCs compared with FBS in terms of cellular expandability, without losing chondrogenic or osteogenic differentiation capacity. Coupled with the advantage in eliminating the potential risk accompanied with the use of xeno-derived materials, pooled, well-characterized HS could be a useful reagent to promote cellular expansion for clinical synovial stem cell-based therapy.
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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 | 0.001 |
| 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) | 0.001 | 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".