Shear stress induces osteogenic differentiation of human mesenchymal stem cells

Aim: To determine whether fluid flow-induced shear stress affects the differentiation of bone marrow-derived human mesenchymal stem cells (hMSCs) into osteogenic cells. Materials & methods: hMSCs cultured with or without osteogenic differentiation medium were exposed to fluid flow-induced shear stress and analyzed for alkaline phosphatase activity and expression of osteogenic genes. Results: Immediately following shear stress, alkaline phosphatase activity in osteogenic medium was significantly increased. At days 4 and 8 of culture the mRNA expression of bone morphogenetic protein-2 and osteopontin was significantly higher in hMSCs subjected to shear stress than those cultured in static conditions. However, hMSCs cultured in osteogenic differentiation medium were less responsive in gene expression of alkaline phosphatase and bone morphogenetic protein-2. Conclusion: These data demonstrate that shear stress stimulates hMSCs towards an osteoblastic phenotype in the absence of chemical induction, suggesting that certain mechanical stresses may serve as an alternative to chemical stimulation of stem cell differentiation

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Curiethérapie à débit pulsé des carcinomes du col utérin (expérience du Centre Oscar Lambret 1995-2003)

LILLE2-BU Santé-Recherche (593502101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF