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Vibrio cholerae (V. cholerae), the etiological agent of cholera, uses cholera toxin (CT) to cause severe diarrheal disease. Cholera is still a significant cause of mortality worldwide with about half of all cholera cases and deaths occurring in children under five. Owing to the lack of cost-effective vaccination and poor vaccine efficacy in children, there is a need for alternative preventative and therapeutic strategies. Recent advances in our knowledge of the interplay between CT-induced disease and host-pathogen metabolism have opened the door for investigating how modulation of intestinal metabolism by V. cholerae during disease impacts host intestinal immunity, the gut microbiota, and pathogen-phage interactions. In this review article, we examine recent progress in our understanding of host-pathogen interactions during V. cholerae infection and discuss future work deciphering how modulation of gut metabolism during cholera intersects these processes to enable successful fecal-oral transmission of the pathogen., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Published by Elsevier Ltd.)

Here, we describe the embryonic central nervous system expression of 5,000 GAL4 lines made using molecularly defined cis-regulatory DNA inserted into a single attP genomic location. We document and annotate the patterns in early embryos when neurogenesis is at its peak, and in older embryos where there is maximal neuronal diversity and the first neural circuits are established. We note expression in other tissues, such as the lateral body wall (muscle, sensory neurons, and trachea) and viscera. Companion papers report on the adult brain and larval imaginal discs, and the integrated data sets are available online (http://www.janelia.org/gal4-gen1). This collection of embryonically expressed GAL4 lines will be valuable for determining neuronal morphology and function. The 1,862 lines expressed in small subsets of neurons (<20/segment) will be especially valuable for characterizing interneuronal diversity and function, because although interneurons comprise the majority of all central nervous system neurons, their gene expression profile and function remain virtually unexplored., (Copyright © 2012 The Authors. Published by Elsevier Inc. All rights reserved.)

Three-dimensional Oximetric Electron Paramagnetic Resonance Imaging using the Single Point Imaging modality generates unpaired spin density and oxygen images that can readily distinguish between normal and tumor tissues in small animals. It is also possible with fast imaging to track the changes in tissue oxygenation in response to the oxygen content in the breathing air. However, this involves dealing with gigabytes of data for each 3D oximetric imaging experiment involving digital band pass filtering and background noise subtraction, followed by 3D Fourier reconstruction. This process is rather slow in a conventional uniprocessor system. This paper presents a parallelization framework using OpenMP runtime support and parallel MATLAB to execute such computationally intensive programs. The Intel compiler is used to develop a parallel C++ code based on OpenMP. The code is executed on four Dual-Core AMD Opteron shared memory processors, to reduce the computational burden of the filtration task significantly. The results show that the parallel code for filtration has achieved a speed up factor of 46.66 as against the equivalent serial MATLAB code. In addition, a parallel MATLAB code has been developed to perform 3D Fourier reconstruction. Speedup factors of 4.57 and 4.25 have been achieved during the reconstruction process and oximetry computation, for a data set with 23 x 23 x 23 gradient steps. The execution time has been computed for both the serial and parallel implementations using different dimensions of the data and presented for comparison. The reported system has been designed to be easily accessible even from low-cost personal computers through local internet (NIHnet). The experimental results demonstrate that the parallel computing provides a source of high computational power to obtain biophysical parameters from 3D EPR oximetric imaging, almost in real-time.