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The recruitment of bone marrow CD34- mesenchymal stem- and progenitor cells (MSC) and their subsequent differentiation into distinct tissues is the precondition for in situ tissue engineering. The objective of this study was to determine the entire chemokine receptor expression profile of human MSC and to investigate their chemotactic response to the selected chemokines CCL2, CXCL8 and CXCL12. Human MSC were isolated from iliac crest bone marrow aspirates and showed a homogeneous population presenting a typical MSC-related cell surface antigen profile (CD14-, CD34-, CD44+, CD45-, CD166+, SH-2+). The expression profile of all 18 chemokine receptors was determined by real-time PCR and immunohistochemistry. Both methods consistently demonstrated that MSC express CC, CXC, C and CX(3)C receptors. Gene expression and immunohistochemical analysis documented that MSC express chemokine receptors CCR2, CCR8, CXCR1, CXCR2 and CXCR3. A dose-dependent chemotactic activity of CXCR4 and CXCR1/CXCR2 ligands CXCL12 and CXCL8 (interleukin-8) was demonstrated using a 96-well chemotaxis assay. In contrast, the CCR2 ligand CCL2 (monocyte chemoattractant protein-1, MCP-1) did not recruited human MSC. In conclusion, we report that the chemokine receptor expression profile of human MSC is much broader than known before. Furthermore, for the first time, we demonstrate that human MSC migrate upon stimulation with CXCL8 but not CCL2. In combination with already known data on MSC recruitment and differentiation these are promising results towards in situ regenerative medicine approaches based on guiding of MSC to sites of degenerated tissues.

SummaryData analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed.

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