Learn More
The amyloid precursor protein (APP) plays a central role in Alzheimer's disease, but its physiological function and that of its mammalian paralogs, the amyloid precursor-like proteins 1 and 2 (APLPs), is still poorly understood. APP has been proposed to form dimers, a process that could promote cell adhesion via trans-dimerization. We investigated the(More)
Progressive neurodegeneration and decline of cognitive functions are major hallmarks of Alzheimer disease (AD). Neurodegeneration in AD correlates with dysfunction of diverse signal transduction mechanisms, such as the G-protein-stimulated phosphoinositide hydrolysis mediated by Galphaq/11. We report here that impaired Galphaq/11-stimulated signaling in(More)
Many G protein-coupled receptors form dimers in cells. However, underlying mechanisms are barely understood. We report here that intracellular factor XIIIA transglutaminase crosslinks agonist-induced AT1 receptor homodimers via glutamine315 in the carboxyl-terminal tail of the AT1 receptor. The crosslinked dimers displayed enhanced signaling and(More)
In this paper we show additional properties of the limit of the sequence produced by the subspace correction algorithm proposed by Fornasier and Schönlieb [24] for L 2 /T V-minimization problems. Inspired by the work of Vonesch and Unser [34], we adapt and specify this algorithm to the case of an orthogonal wavelet space decomposition and for deblurring(More)
The amyloid precursor protein (APP) is a type I transmembrane protein of unknown physiological function. Its soluble secreted form (sAPP) shows similarities with growth factors and increases the in vitro proliferation of embryonic neural stem cells. As neurogenesis is an ongoing process in the adult mammalian brain, we have investigated a role for sAPP in(More)
In this paper we are concerned with the analysis of convergent sequential and parallel overlapping domain decomposition methods for the minimization of func-tionals formed by a discrepancy term with respect to the data and a total variation constraint. To our knowledge, this is the first successful attempt of addressing such a strategy for the nonlinear,(More)
We present several domain decomposition algorithms for sequential and parallel minimization of functionals formed by a discrepancy term with respect to data and total variation constraints. The convergence properties of the algorithms are analyzed. We provide several numerical experiments, showing the successful application of the algorithms for the(More)
Computational problems of large-scale appearing in biomedical imaging, astronomy, art restoration, and data analysis are gaining recently a lot of attention due to better hardware , higher dimensionality of images and data sets, more parameters to be measured, and an increasing number of data acquired. In the last couple of years non-smooth minimization(More)