Influences on induction and maturation of mouse bone marrow-derived dendritic cells by varying combinations of cytokines / 中华微生物学和免疫学杂志

Objective To investigate the influences of culture conditions on the in vitro induction and maturation of dendritic cells by using different combinations of cytokines. -ethods Mouse bone mar-row cells were isolated and cultured in media containing varying combinations of cytokines, including granu-locyte-macrophage colony stimulating factor (GM-CSF), interleukin-4 (IL-4) and fms-like tyrosine kinase 3 ligand (Flt3L). After cultured at 37℃ for seven days, the attached bone marrow cells were collected and stained by fluorescence-labeled monoclonal antibodies (McAb) against CD11c, MHCⅡ and CD86 for flow cytometry analysis. In the parallel group, LPS was added on day 5 to a final concentration of 1μg/ml for DC maturation analysis by flow cytometry. Results In group Flt3L (20 ng/ml)/GM-CSF (20 ng/ml)/IL-4 (10 ng/ml), 90％ of bone marrow cells were CD11c-positive. Flt3L (100 ng/ml) could induce 88％ of bone marrow cells to express CD11c. Bone marrow cells positive for MHCⅡ accounted for 35. 4％ and 36. 1％ in group Flt3L/GM-CSF/IL-4 and group Flt3L/GM-CSF, where both Flt3L and GM-CSF were used at a concentration of 20 ng/ml. After LPS stimulation, the positive rates of MHCⅡ in group Flt3L/GM-CSF/IL-4 and group Flt3L/GM-CSF were 58. 1％ and 59. 6％, which increased by 22. 7％ and 23. 5％, re-spectively. The percentages of CD86-positive bone marrow cells were 7. 1％ and 5. 5％ in group Flt3L/GM-CSF/IL-4 and group Flt3L/GM-CSF. Bone marrow cells positive for CD86 grew by 7. 1％ and 6. 2％ in group Flt3L (20 ng/ml) and group GM-CSF/IL-4 after LPS stimulation. Conclusions Flt3L and GM-CSF probably dominated the differentiation and maturation of bone marrow-derived dendritic cells with a synergis-tic effect. Combined usage of Flt3L and GM-CSF at the concentration of 20 ng/ml would be an optimal proto-col for DC research.

Practice and application of big data in biomedical research / 中华医学科研管理杂志

With the growing awearness of Big data and its application in economic,social and scientific fields,this paper analyzed the impact and challenges big data has brought to the field of biomedical research,and put forward suggestion of improving applications of big data in biomedical research.