TGFβ(1 )activates c-Jun and Erk1 via α(V)β(6 )integrin

Transforming growth factor β (TGFβ) plays an important role in animal development and many cellular processes. A variety of cellular functions that are required for tumor metastasis are controlled by integrins, a family of cell adhesion receptors. Overexpression of α(V)β(6 )integrin is associated with lymph node metastasis of gastric carcinomas. It has been demonstrated that a full TGFβ(1 )signal requires both α(V)β(6 )integrin and SMAD pathway. TGFβ(1 )binds to α(V)β(6 )via the DLXXL motif, a freely accessible amino acid sequence in the mature form of TGFβ(1). Binding of mature TGFβ(1 )to α(V)β(6 )leads to immobilization and tyrosine phosphorylation of proteins, which are associated with focal adhesions, a hallmark of integrin-mediated signal transduction. Here, we show that binding of mature TGFβ(1 )recruits the mitogen-activated protein kinase kinase kinase 1 (MEKK1), a mediator of c-Jun activation, and the extracellular signaling-regulated kinase-1 (Erk1) to focal adhesions. In addition, the p21-activated kinase 1 (PAK1) is associated with focal adhesions and differentially phosphorylated upon TGFβ(1 )stimulation. We conclude that TGFβ(1 )activates c-Jun via the MEKK1/p38 MAP kinase pathway and influences cytoskeletal organization. These finding may provide a link between TGFβ(1 )and the metastatic behavior of cancers

Tuning the memory dependence of vapour deposited metallic glasses

Peer ReviewedPostprint (published version

Exploring knowledge transfer configuration profiles in global operations

This research looks to integrate network configuration and knowledge transfer (KT) approaches. The developed framework was tested using an in-depth case study involving three manufacturing networks at different stages of maturity. Current and future knowledge transfer configuration profiles and supporting KT mechanisms for each network are presented and discussed

Considerations in the Calculation of Vertical Velocity in Three-Dimensional Circulation Models

The vertical velocity, w, in three-dimensional circulation models is typically computed from the three-dimensional continuity equation assuming that the depth-varying horizontal velocity field was calculated earlier in the solution sequence. Computing w in this way appears to require the solution of an over-determined system since the continuity equation is first order, yet w must satisfy two boundary conditions (one at the free surface and one at the bottom). At least three methods have been previously proposed to compute w: (i) the “traditional” method that solves the continuity equation with the bottom boundary condition and ignores the free surface boundary condition, (ii) a “vertical derivative” method that solves the vertical derivative of the continuity equation using both boundary conditions and (iii) an “adjoint” approach that minimizes a cost functional comprised of residuals in the continuity equation and in both boundary conditions. The latter solution is equivalent to the "traditional" solution plus a correction that increases linearly over the depth and is proportional to the misfit between the "traditional" solution at the surface and the surface boundary condition. In this paper we show that the "vertical derivative" method yields inaccurate and physically inconsistent results if it is discretized as has been previously proposed. However, if properly discretized the "vertical derivative" method is equivalent to the “adjoint” method if the cost function is weighted to exactly satisfy the boundary conditions. Furthermore, if the horizontal flow field satisfies the depth-integrated continuity equation locally, one of the boundary conditions is redundant and w obtained from the "traditional" method should match the free surface boundary condition. In this case, the “traditional,” “adjoint” and properly discretized “vertical derivative” approaches yield the same results for w. If the horizontal flow field is not locally mass conserving, the mass conservation error is transferred into the solution for w. This is particularly important for models that do not guarantee local mass conservation, such as some finite element models