The Effect of Serial Passaging on the Proliferation and Differentiation of Bovine Adipose-Derived Stem Cells
Bibliographic record
Abstract
Adipose-derived stem cells (ASCs) represent an excellent cell source for the development of regenerative therapies for a broad variety of tissue disorders. Commonly, in vitro expansion is necessary to obtain sufficient cell populations for research purposes and clinical applications. Although it has been demonstrated that human ASCs can maintain their adipogenic, chondrogenic and osteogenic potential in long-term culture (up to 15 passages), it is not guaranteed that a satisfactory level of differentiation is achievable in later passages. In this study, we investigated the self-renewal and multilineage differentiation capacity of bovine ASCs, isolated from the interdigital fat pad, and explored how serial passaging influences the cells. A proliferation study examined the changes in growth kinetics from passage 1 to 5, and multilineage (adipogenesis, chondrogenesis and osteogenesis) differentiation studies were conducted to compare the potential between passage 2 (P2) and passage 5 (P5). From the proliferation study, a statistically significant change in the doubling time did not appear until P5. In the differentiation study, both P2 and P5 ASCs could be stimulated to undergo multilineage differentiation under specific culturing conditions. However, adipogenic and chondrogenic cultures showed significantly lower levels of differentiation in the P5-induced cultures. In contrast, P5-induced osteogenic cultures had higher alkaline phosphatase enzyme activity than P2-induced cultures, suggesting an increase in the osteogenic response with serial passaging. Overall, bovine ASCs are capable of self-renewal and multilineage differentiation; however, long-term in vitro expansion has a negative effect on adipogenic and chondrogenic differentiation, while potentially favoring osteogenesis.
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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 | 0.001 |
| 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 | 0.001 |
| 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".