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      Small-angle X-ray scattering characteristics of mouse brain: Planar imaging measurements and tomographic imaging simulations

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      PLoS ONE
      Public Library of Science

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          Abstract

          Small-angle x-ray scattering (SAXS) imaging can differentiate tissue types based on their nanoscale molecular structure. However, characterization of the coherent scattering cross-section profile of relevant tissues is needed to optimally design SAXS imaging techniques for a variety of biomedical applications. Reported measured nervous tissue x-ray scattering cross sections under a synchrotron source have had limited agreement. We report a set of x-ray cross-section measurements obtained from planar SAXS imaging of 1 mm thick mouse brain (APP/PS1 wild-type) coronal slices using an 8 keV laboratory x-ray source. Two characteristic peaks were found at 0.96 and 1.60 nm −1 attributed to myelin. The peak intensities varied by location in the slice. We found that regions of gray matter, white matter, and corpus callosum could be segmented by their increasing intensities of myelin peaks respectively. Measured small-angle x-ray scattering cross sections were then used to define brain tissue scattering properties in a GPU-accelerated Monte Carlo simulation of SAXS computed tomography (CT) using a higher monochromatic x-ray energy (20 keV) to study design trade-offs for noninvasive in vivo SAXS imaging on a small-animal head including radiation dose, signal-to-noise ratio (SNR), and the effect of skull presence on the previous two metrics. Simulation results show the estimated total dose to the mouse head for a single SAXS-CT slice was 149.4 mGy. The pixel SNR was approximately 30.8 for white matter material whether or not a skull was present. In this early-stage proof-of-principle work, we have demonstrated our brain cross-section data and simulation tools can be used to assess optimal instrument parameters for dedicated small-animal SAXS-CT prototypes.

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          A diversity of assembly mechanisms of a generic amyloid fold.

          Protein misfolding and amyloid assembly have long been recognized as being responsible for many devastating human diseases. Recent findings indicate that amyloid assemblies may facilitate crucial biological processes from bacteria to mammals. This review focuses on the mechanistic understanding of amyloid formation, including the transformation of initially innocuous proteins into oligomers and fibrils. The result is a competing folding and assembly energy landscape, which contains a number of routes by which the polypeptide chain can convert its primary sequence into functional structures, dysfunctional assemblies, or epigenetic entities that provide both threats and opportunities in the evolution of life. Copyright © 2011 Elsevier Inc. All rights reserved.
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            Glassy Carbon as an Absolute Intensity Calibration Standard for Small-Angle Scattering

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              Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit.

              It is a known fact that Monte Carlo simulations of radiation transport are computationally intensive and may require long computing times. The authors introduce a new paradigm for the acceleration of Monte Carlo simulations: The use of a graphics processing unit (GPU) as the main computing device instead of a central processing unit (CPU). A GPU-based Monte Carlo code that simulates photon transport in a voxelized geometry with the accurate physics models from PENELOPE has been developed using the CUDATM programming model (NVIDIA Corporation, Santa Clara, CA). An outline of the new code and a sample x-ray imaging simulation with an anthropomorphic phantom are presented. A remarkable 27-fold speed up factor was obtained using a GPU compared to a single core CPU. The reported results show that GPUs are currently a good alternative to CPUs for the simulation of radiation transport. Since the performance of GPUs is currently increasing at a faster pace than that of CPUs, the advantages of GPU-based software are likely to be more pronounced in the future.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ResourcesRole: Software
                Role: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2017
                31 October 2017
                : 12
                : 10
                : e0186451
                Affiliations
                [1 ] Fischell Department of Bioengineering, University of Maryland, College Park, MD, 20742, United States of America
                [2 ] Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, CDRH/USFDA, Silver Spring, Maryland 20993, United States of America
                Massey University, NEW ZEALAND
                Author notes

                Competing Interests: The authors have declared that no competing interests exists.

                Author information
                http://orcid.org/0000-0002-1695-2271
                Article
                PONE-D-17-23490
                10.1371/journal.pone.0186451
                5663376
                29088259
                d08c2607-895f-4c14-ae39-191e45056582

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 20 June 2017
                : 2 October 2017
                Page count
                Figures: 7, Tables: 2, Pages: 14
                Funding
                M.C. acknowledges funding by the Fischell Fellowship in Biomedical Engineering at University of Maryland and was also supported by an appointment to the Research Participation Program at the Center for Devices and Radiological Health (CDRH) administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and the U.S. Food and Drug Administration (FDA). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Physical Sciences
                Physics
                Scattering
                Small-Angle Scattering
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Skeleton
                Skull
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Skeleton
                Skull
                Research and Analysis Methods
                Imaging Techniques
                Neuroimaging
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Bone Imaging
                X-Ray Radiography
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Bone Imaging
                X-Ray Radiography
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Bone Imaging
                X-Ray Radiography
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                X-Ray Radiography
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                X-Ray Radiography
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                X-Ray Radiography
                Biology and Life Sciences
                Anatomy
                Nervous System
                Central Nervous System
                Medicine and Health Sciences
                Anatomy
                Nervous System
                Central Nervous System
                Research and analysis methods
                Mathematical and statistical techniques
                Statistical methods
                Monte Carlo method
                Physical sciences
                Mathematics
                Statistics (mathematics)
                Statistical methods
                Monte Carlo method
                Research and Analysis Methods
                Imaging Techniques
                Research and Analysis Methods
                Imaging Techniques
                Neuroimaging
                Computed Axial Tomography
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Computed Axial Tomography
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Tomography
                Computed Axial Tomography
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Tomography
                Computed Axial Tomography
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Tomography
                Computed Axial Tomography
                Custom metadata
                Data are available from DIDSR github repository for all researchers. https://github.com/DIDSR/SAXS_data.

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