Simultaneous blockade of AP-1 and phosphatidylinositol 3-kinase pathway in non-small cell lung cancer cells

c-Jun is a major constituent of AP-1 transcription factor that transduces multiple mitogen growth signals, and it is frequently overexpressed in non-small cell lung cancers (NSCLCs). Earlier, we showed that blocking AP-1 by the overexpression of a c-Jun dominant-negative mutant, TAM67, inhibited NSCLC cell growth. The phosphatidylinositol 3-kinase (PI3K)/Akt signal transduction pathway is important in transformation, proliferation, survival and metastasis of NSCLC cells. In this study, we used NCI-H1299 Tet-on clone cells that express TAM67 under the control of inducible promoter to determine the effects of inhibition of AP-1 and PI3K on cell growth. The PI3K inhibitor, LY294002, produced a dose-dependent inhibition of growth in H1299 cells and that inhibition was enhanced by TAM67. TAM67 increased dephosphorylation of Akt induced by LY294002 and reduced the TPA response element DNA-binding of phosphorylated c-Jun. TAM67 increased G1 cell cycle blockade induced by LY294002, which was partially associated with cyclin A decrease and p27Kip1 accumulation. Furthermore, TAM67 and LY294002 act, at least additively, to inhibit anchorage-independent growth of the H1299 cells. These results suggest that AP-1 and PI3K/Akt pathways play an essential role in the growth of some NSCLC cells

Transient receptor potential canonical 4 and 5 proteins as targets in cancer therapeutics

Novel approaches towards cancer therapy are urgently needed. One approach might be to target ion channels mediating Ca²+ entry because of the critical roles played by Ca²+ in many cell types, including cancer cells. There are several types of these ion channels, but here we address those formed by assembly of transient receptor potential canonical (TRPC) proteins, particularly those which involve two closely related members of the family: TRPC4 and TRPC5. We focus on these proteins because recent studies point to roles in important aspects of cancer: drug resistance, transmission of drug resistance through extracellular vesicles, tumour vascularisation, and evoked cancer cell death by the TRPC4/5 channel activator (−)-englerin A. We conclude that further research is both justified and necessary before these proteins can be considered as strong targets for anti-cancer cell drug discovery programmes. It is nevertheless already apparent that inhibitors of the channels would be unlikely to cause significant adverse effects, but, rather, have other effects which may be beneficial in the context of cancer and chemotherapy, potentially including suppression of innate fear, visceral pain and pathological cardiac remodelling

Acoustic full-waveform inversion in the frequency domain

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A parallel algorithm for 2D visco-acoustic frequency-domain full-waveform inversion: application to a dense OBS data set

We present a distributed-memory parallel algorithm for 2D visco-acoustic full-waveform inversion of wide-angle seismic data. Our code is written in fortran90 and use MPI for parallelism. The algorithm was applied to real wide-angle data set recorded by 100 OBSs with a 1-km spacing in the eastern-Nankai trough (Japan) to image the deep structure of the subduction zone. Full-waveform inversion is applied sequentially to discrete frequencies by proceeding from the low to the high frequencies. The inverse problem is solved with a classic gradient method. Full-waveform modeling is performed with a frequency-domain finite-difference method. In the frequency-domain, solving the wave equation requires resolution of a large unsymmetric system of linear equations. We use the massively parallel direct solver MUMPS (http://www.enseeiht.fr/irit/apo/MUMPS) for distributed-memory computer to solve this system. The MUMPS solver is based on a multifrontal method for the parallel factorization. The MUMPS algorithm is subdivided in 3 main steps: a symbolic analysis step that performs re-ordering of the matrix coefficients to minimize the fill-in of the matrix during the subsequent factorization and an estimation of the assembly tree of the matrix. Second, the factorization is performed with dynamic scheduling to accomodate numerical pivoting and provides the LU factors distributed over all the processors. Third, the resolution is performed for multiple sources. To compute the gradient of the cost function, 2 simulations per shot are required (one to compute the forward wavefield and one to back-propagate residuals). The multi-source resolutions can be performed in parallel with MUMPS. In the end, each processor stores in core a sub-domain of all the solutions. These distributed solutions can be exploited to compute in parallel the gradient of the cost function. Since the gradient of the cost function is a weighted stack of the shot and residual solutions of MUMPS, each processor computes the corresponding sub-domain of the gradient. In the end, the gradient is centralized on the master processor using a collective communation. The gradient is scaled by the diagonal elements of the Hessian matrix. This scaling is computed only once per frequency before the first iteration of the inversion. Estimation of the diagonal terms of the Hessian requires performing one simulation per non redondant shot and receiver position. The same strategy that the one used for the gradient is used to compute the diagonal Hessian in parallel. This algorithm was applied to a dense wide-angle data set recorded by 100 OBSs in the eastern Nankai trough, offshore Japan. Thirteen frequencies ranging from 3 and 15 Hz were inverted. Tweny iterations per frequency were computed leading to 260 tomographic velocity models of increasing resolution. The velocity model dimensions are 105 km x 25 km corresponding to a finite-difference grid of 4201 x 1001 grid with a 25-m grid interval. The number of shot was 1005 and the number of inverted OBS gathers was 93. The inversion requires 20 days on 6 32-bits bi-processor nodes with 4 Gbytes of RAM memory per node when only the LU factorization is performed in parallel. Preliminary estimations of the time required to perform the inversion with the fully-parallelized code is 6 and 4 days using 20 and 50 processors respectively

Frequency-domain full-waveform modeling using a hybrid direct-iterative solver based on a parallel domain decomposition method: A tool for 3D full-waveform inversion?

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Frequency-domain Acoustic Wave Modeling Using a Hybrid Direct-iterative Solver Based on a Domain Decomposition Method

International audienceDesigning an efficient modeling tool is a key point for large 3D frequency-domain full-waveform inversion problems. We present a frequency-domain acoustic wave modeling using a hybrid direct-iterative solver based on a parallel domain decomposition method and Schur complement approach. The main interest of mixing solvers is to overcome the huge memory complexity of direct solvers while partially preserving efficient multi-RHS simulations and mitigating the iteration count in iterative solvers. To improve the convergence rate of the iterative solver, a preconditioning based on an additive Schwartz approach is used. Discretization of the Helmholtz equation is based on a parsimonious finite-difference method but the domain decomposition method could apply to any numerical scheme such as finite-element or finite-volume methods and to any media such as elastic, anisotropic ones ... To asses the efficiency of the hybrid approach, we computed simulations in the 2D Marmousi II and 3D SEG/EAGE Overthrust model, and compared results with that of a direct solver. ..

3D Acoustic Frequency-domain Full Waveform Tomography (FWT) - An Application on SEG/EAGE Overthrust Velocity Model

International audienceThree-dimensional quantitative seismic imaging in complex environments such those involving deepwater, thrust belts, sub-salt and sub-basalt structures is one of the main challenges of seismic exploration such that hydrocarbon exploitation. We present a 3D frequency-domain full waveform tomography (FWT) algorithm suited for wide-aperture seismic data. We aim to develop high-resolution P-wave velocity models at low frequencies. The inverse problem based on a classic gradient method consists of the successive inversion of few increasing frequencies. This defines a multiresolution imaging scheme and allows us to manage compact data volume. The code is fully parallelized and avoids disk swapping by keeping in core the foward-problem solutions in distributed format. We present two validations of our algorithm with the SEG/EAGE Overthrust model. The main structures were well imaged with a spatial resolution in accordance with the inverted frequencies. Further work is required to [i] perform more representative applications on larger computational platforms, [ii] assess the sensitivity of 3D FWT to the starting model and to the acquisition geometry and [iii] Investigate less demanding strategies to perform the forward problem in the frequency domain such that hybrid direct/iterative solver based on domain decomposition method. ..