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© 2015 The Authors.Desminopathies belong to a family of muscle disorders called myofibrillar myopathies that are caused by Desmin mutations and lead to protein aggregates in muscle fibers. To date, the initial pathological steps of desminopathies and the impact of desmin aggregates in the genesis of the disease are unclear. Using live, high-resolution microscopy, we show that Desmin loss of function and Desmin aggregates promote skeletal muscle defects and alter heart biomechanics. In addition, we show that the calcium dynamics associated with heart contraction are impaired and are associated with sarcoplasmic reticulum dilatation as well as abnormal subcellular distribution of Ryanodine receptors. Our results demonstrate that desminopathies are associated with perturbed excitation-contraction coupling machinery and that aggregates are more detrimental than Desmin loss of function. Additionally, we show that pharmacological inhibition of aggregate formation and Desmin knockdown revert these phenotypes. Our data suggest alternative therapeutic approaches and further our understanding of the molecular determinants modulating Desmin aggregate formation. Desminopathies are myopathies and cardiomyopathies associated with Desmin mutations leading to protein aggregates. Ramspacher et al. demonstrate that altered Desmin function or expression affect the EC coupling machinery and calcium dynamics. They show that aggregates are more toxic than the loss of function and can be rescued by knockdown and pharmacological treatment.

Discretization of continuous (analog) convolution operators by direct sampling of the convolution kernel and use of fast Fourier transforms is highly efficient. However, it assumes the input and output signals are band-limited, a condition rarely met in practice, where signals have finite support or abrupt edges and sampling is nonideal. Here, we propose to approximate signals in analog, shift-invariant function spaces, which do not need to be band-limited, resulting in discrete coefficients for which we derive discrete convolution kernels that accurately model the analog convolution operator while taking into account nonideal sampling devices (such as finite fill-factor cameras). This approach retains the efficiency of direct sampling but not its limiting assumption. We propose fast forward and inverse algorithms that handle finite-length, periodic, and mirror-symmetric signals with rational sampling rates. We provide explicit convolution kernels for computing coherent wave propagation in the context of digital holography. When compared to band-limited methods in simulations, our method leads to fewer reconstruction artifacts when signals have sharp edges or when using nonideal sampling devices. © 2013 Optical Society of America.

3D deconvolution in optical wide eld microscopy aims at recovering optical sections through thick objects. Acquiring data from multiple, mutually-tilted directions helps ll the missing cone of information in the optical transfer function, which normally renders the deconvolution problem particularly ill-posed. Here, we propose a fast-converging iterative deconvolution method for multi-angle deconvolution microscopy. Specically, we formulate the imaging problem using a lter-bank structure, and present a multi-channel variation of a thresholded Landweber deconvolution algorithm with wavelet-sparsity regularization. Decomposition of the minimization problem into subband-dependent terms ensures fast convergence. We demonstrate the applicability of the algorithm via simulation results.

We present an algorithm to spatially register two volumetric datasets related via a rigid-body transform and degraded by an anisotropic point-spread-function (PSF). Registration is necessary, for example, when fusing data in multi-view microscopy. Automatic algorithms that only rely on maximizing pixel similarity, without accounting for the anisotropic image formation process, provide poor results in such applications. We propose to solve this problem by re-blurring the reference and test data with transformed forms of the PSF, in order to make them comparable, before minimizing the mean squared intensity difference between them. Our approach extends the pyramid-based sub-pixel registration algorithm proposed by Thevenaz et al., 1998, that employs an improved form of the Marquardt-Levenberg algorithm. We show, via simulations, that our method is more accurate than the conventional approach that does not account for the PSF. We demonstrate our algorithm in practice by registering multi-view volumes of a zebrafish larva acquired using a wide-field microscope.