High-frequency analysis of the efficiency of a local approximate DtN2 boundary condition for prolate spheroidal-shaped boundaries

The performance of the second-order local approximate DtN boundary condition suggested in [4] is investigated analytically when employed for solving high-frequency exterior Helmholtz problems with elongated scatterers. This study is performed using a domain-based formulation and assuming the scatterer and the exterior artificial boundary to be prolate spheroid. The analysis proves that, in the high-frequency regime, the reflected waves at the artificial boundary decay faster than 1/(ka)15/8, where k is the wavenumber and a is the semi-major axis of this boundary. Numerical results are presented to illustrate the accuracy and the efficiency of the proposed absorbing boundary condition, and to provide guidelines for satisfactory performance

Exponential decay of high-order spurious prolate spheroidal modes induced by a local approximate dtn exterior boundary condition

We investigate analytically the asymptotic behavior of high-order spurious prolate spheroidal modes induced by a second-order local approximate DtN absorbing boundary condition (DtN2) when employed for solving high-frequency acoustic scattering problems. We prove that these reflected modes decay exponentially in the high frequency regime. This theoretical result demonstrates the great potential of the considered absorbing boundary condition for solving efficiently exterior high-frequency Helmholtz problems. In addition, this exponential decay proves the superiority of DtN2 over the widely used Bayliss-Gunsburger-Turkel absorbing boundary condition

Identification of O-Linked Glycoproteins Binding to the Lectin Helix pomatia Agglutinin as Markers of Metastatic Colorectal Cancer

Background Protein glycosylation is an important post-translational modification shown to be altered in all tumour types studied to date. Mucin glycoproteins have been established as important carriers of O-linked glycans but other glycoproteins exhibiting altered glycosylation repertoires have yet to be identified but offer potential as biomarkers for metastatic cancer. Methodology In this study a glycoproteomic approach was used to identify glycoproteins exhibiting alterations in glycosylation in colorectal cancer and to evaluate the changes in O-linked glycosylation in the context of the p53 and KRAS (codon 12/13) mutation status. Affinity purification with the carbohydrate binding protein from Helix pomatia agglutinin (HPA) was coupled to 2-dimensional gel electrophoresis with mass spectrometry to enable the identification of low abundance O-linked glycoproteins from human colorectal cancer specimens. Results Aberrant O-linked glycosylation was observed to be an early event that occurred irrespective of the p53 and KRAS status and correlating with metastatic colorectal cancer. Affinity purification using the lectin HPA followed by proteomic analysis revealed annexin 4, annexin 5 and CLCA1 to be increased in the metastatic colorectal cancer specimens. The results were validated using a further independent set of specimens and this showed a significant association between the staining score for annexin 4 and HPA and the time to metastasis; independently (annexin A4: Chi square 11.45, P = 0.0007; HPA: Chi square 9.065, P = 0.0026) and in combination (annexin 4 and HPA combined: Chi square 13.47; P = 0.0002). Conclusion Glycoproteins showing changes in O-linked glycosylation in metastatic colorectal cancer have been identified. The glycosylation changes were independent of p53 and KRAS status. These proteins offer potential for further exploration as biomarkers and potential targets for metastatic colorectal cancer

Cellular glycosylation affects Herceptin binding and sensitivity of breast cancer cells to doxorubicin and growth factors

Alterations in protein glycosylation are a key feature of oncogenesis and have been shown to affect cancer cell behaviour perturbing cell adhesion, favouring cell migration and metastasis. This study investigated the effect of N-linked glycosylation on the binding of Herceptin to HER2 protein in breast cancer and on the sensitivity of cancer cells to the chemotherapeutic agent doxorubicin (DXR) and growth factors (EGF and IGF-1). The interaction between Herceptin and recombinant HER2 protein and cancer cell surfaces (on-rate/off-rate) was assessed using a quartz crystal microbalance biosensor revealing an increase in the accessibility of HER2 to Herceptin following deglycosylation of cell membrane proteins (deglycosylated cells Bmax: 6.83 Hz; glycosylated cells Bmax: 7.35 Hz). The sensitivity of cells to DXR and to growth factors was evaluated using an MTT assay. Maintenance of SKBR-3 cells in tunicamycin (an inhibitor of N-linked glycosylation) resulted in an increase in sensitivity to DXR (0.1 µM DXR P<0.001) and a decrease in sensitivity to IGF-1 alone and to IGF-1 supplemented with EGF (P<0.001). This report illustrates the importance of N-linked glycosylation in modulating the response of cancer cells to chemotherapeutic and biological treatments and highlights the potential of glycosylation inhibitors as future combination treatments for breast cancer

Approximation of surfaces with fault(s) and/or rapidly varying data, using a segmentation process, Dm-splines and the finite element method

In many problems of geophysical interest, one has to deal with data that exhibit complex fault structures. This occurs, for instance, when describing the topography of seafloor surfaces, mountain ranges, volcanoes, islands, or the shape of geological entities, as well as when dealing with reservoir characterization and modelling. In all these circumstances, due to the presence of large and rapid variations in the data, attempting a fitting using conventional approximation methods necessarily leads to instability phenomena or undesirable oscillations which can locally and even globally hinder the approximation. As will be shown in this paper, the right approach to get a good approximant consists, in effect, in applying first a segmentation process to precisely define the locations of large variations and faults, and exploiting then a discrete approximation technique. To perform the segmentation step, we propose a quasi-automatic algorithm that uses a level set method to obtain from the given (gridded or scattered) Lagrange data several patches delimited by large gradients (or faults). Then, with the knowledge of the location of the discontinuities of the surface, we generate a triangular mesh (which takes into account the identified set of discontinuities) on which a Dm-spline approximant is constructed. To show the efficiency of this technique, we will present the results obtained by its application to synthetic datasets as well as real gridded datasets in Oceanography and Geosciences