Seeding cells directly into a new medium subjects the cells to stress due to certain differences in medium formulation. As a result, it seems necessary for cells to be adapted to a new medium, in order to save the properties of the cells and to achieve reliable results from the tests. The MC3T3 osteoblastic cell line is recommended to be cultured in Alpha Minimum Essential Medium (α-MEM). However, Dulbecco's Modified Eagle's medium (DMEM) is widely used for its culture. Therefore, in the present paper, two sequential methodologies were applied to adapt the MC3T3 cells to DMEM. In sequential adaptation 1, 10 vol.% DMEM was added to the original medium every day, while in sequential adaptation 2, the old medium was changed to a new medium having 20 vol.% higher DMEM content after each passage. Cells were monitored and compared to direct cell adaptation, while they were growing. The results showed that in the direct cell adaptation, increase in the number of cells was very slow. In contrast, the two sequential adaptation processes were more efficient where sequential adaptation 2 resulted in a higher number of cells in fewer days; 88 % greater than sequential adaptation 1 when it was believed that the cells were adapted. Furthermore, the statistical analysis was conducted by stepwise regression analysis and mathematical models were provided, which can predict the number of cells by day of culture.

中文翻译：

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使MC3T3细胞系适应Dulbecco的改良Eagle培养基。

由于培养基配方的某些差异，将细胞直接播种到新培养基中会使细胞承受压力。结果，似乎有必要使细胞适应新的培养基，以保存细胞的特性并从测试中获得可靠的结果。建议将MC3T3成骨细胞系培养在Alpha最低必需培养基（α-MEM）中。但是，Dulbecco的改良Eagle培养基（DMEM）被广泛用于其培养。因此，在本文中，应用了两种顺序方法来使MC3T3细胞适应DMEM。在连续适应1中，每天向原始培养基中添加10％（体积）的DMEM，而在连续适应2中，在每次传代后，将旧培养基更换为DMEM含量高20％（体积）的新培养基。监测细胞并在其生长期间将其与直接细胞适应进行比较。结果表明，在直接细胞适应中，细胞数量的增加非常缓慢。相比之下，两个顺序适应过程效率更高，其中顺序适应2在较短的时间内导致了更多的细胞数量；当认为细胞已适应时，比顺序适应1大88％。此外，通过逐步回归分析进行统计分析，并提供数学模型，该模型可以预测培养日的细胞数量。这两个顺序适应过程效率更高，其中顺序适应2在较少的几天内产生了更多的细胞；当认为细胞已适应时，比顺序适应1大88％。此外，通过逐步回归分析进行统计分析并提供数学模型，该模型可以预测培养日的细胞数量。这两个顺序适应过程效率更高，其中顺序适应2在较少的几天内产生了更多的细胞；当认为细胞已适应时，比顺序适应1大88％。此外，通过逐步回归分析进行统计分析，并提供数学模型，该模型可以预测培养日的细胞数量。