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      Ceramide analog [ 18F]F-HPA-12 detects sphingolipid disbalance in the brain of Alzheimer’s disease transgenic mice by functioning as a metabolic probe

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          Abstract

          The metabolism of ceramides is deregulated in the brain of Alzheimer’s disease (AD) patients and is associated with apolipoprotein (APO) APOE4 and amyloid-β pathology. However, how the ceramide metabolism changes over time in AD, in vivo, remains unknown. Distribution and metabolism of [ 18F]F-HPA-12, a radio-fluorinated version of the ceramide analog N-(3-hydroxy-1-hydroxymethyl-3-phenylpropyl) dodecanamide, was investigated in the brain of AD transgenic mouse models (FAD) on an APOE4 or APOE3 genetic background, by positron emission tomography and by gamma counter. We found that FAD mice displayed a higher uptake of [ 18F]F-HPA-12 in the brain, independently from the APOE4 or APOE3 genetic background. FAD mice could be distinguished from littermate control animals with a sensitivity of 85.7% and a specificity of 87.5%, by gamma counter measurements. Metabolic analysis of [ 18F]F-HPA-12 in the brain suggested that the tracer is degraded less efficiently in the FAD mice. Furthermore, the radioactive signal registered in the hippocampus correlated with an increase of Cer d18:1/20:2 levels measured in the same brain region by mass spectrometry. Our data gives additional proof that ceramide metabolism is different in FAD mice compared to controls. Ceramide analogs like HPA-12 may function as metabolic probes to study ceramide disbalance in the brain.

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          Most cited references55

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          NIH Image to ImageJ: 25 years of image analysis

          For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine.

            The clinical performance of a laboratory test can be described in terms of diagnostic accuracy, or the ability to correctly classify subjects into clinically relevant subgroups. Diagnostic accuracy refers to the quality of the information provided by the classification device and should be distinguished from the usefulness, or actual practical value, of the information. Receiver-operating characteristic (ROC) plots provide a pure index of accuracy by demonstrating the limits of a test's ability to discriminate between alternative states of health over the complete spectrum of operating conditions. Furthermore, ROC plots occupy a central or unifying position in the process of assessing and using diagnostic tools. Once the plot is generated, a user can readily go on to many other activities such as performing quantitative ROC analysis and comparisons of tests, using likelihood ratio to revise the probability of disease in individual subjects, selecting decision thresholds, using logistic-regression analysis, using discriminant-function analysis, or incorporating the tool into a clinical strategy by using decision analysis.
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              Intraneuronal beta-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer's disease mutations: potential factors in amyloid plaque formation.

              Mutations in the genes for amyloid precursor protein (APP) and presenilins (PS1, PS2) increase production of beta-amyloid 42 (Abeta42) and cause familial Alzheimer's disease (FAD). Transgenic mice that express FAD mutant APP and PS1 overproduce Abeta42 and exhibit amyloid plaque pathology similar to that found in AD, but most transgenic models develop plaques slowly. To accelerate plaque development and investigate the effects of very high cerebral Abeta42 levels, we generated APP/PS1 double transgenic mice that coexpress five FAD mutations (5XFAD mice) and additively increase Abeta42 production. 5XFAD mice generate Abeta42 almost exclusively and rapidly accumulate massive cerebral Abeta42 levels. Amyloid deposition (and gliosis) begins at 2 months and reaches a very large burden, especially in subiculum and deep cortical layers. Intraneuronal Abeta42 accumulates in 5XFAD brain starting at 1.5 months of age (before plaques form), is aggregated (as determined by thioflavin S staining), and occurs within neuron soma and neurites. Some amyloid deposits originate within morphologically abnormal neuron soma that contain intraneuronal Abeta. Synaptic markers synaptophysin, syntaxin, and postsynaptic density-95 decrease with age in 5XFAD brain, and large pyramidal neurons in cortical layer 5 and subiculum are lost. In addition, levels of the activation subunit of cyclin-dependent kinase 5, p25, are elevated significantly at 9 months in 5XFAD brain, although an upward trend is observed by 3 months of age, before significant neurodegeneration or neuron loss. Finally, 5XFAD mice have impaired memory in the Y-maze. Thus, 5XFAD mice rapidly recapitulate major features of AD amyloid pathology and may be useful models of intraneuronal Abeta42-induced neurodegeneration and amyloid plaque formation.
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                Author and article information

                Contributors
                p.martinez@maastrichtuniversity.nl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                9 November 2020
                9 November 2020
                2020
                : 10
                : 19354
                Affiliations
                [1 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, , Maastricht University, ; Universiteitssingel 50, 6229ER Maastricht, The Netherlands
                [2 ]GRID grid.266539.d, ISNI 0000 0004 1936 8438, Department of Physiology, , University of Kentucky College of Medicine, ; Lexington, KY USA
                [3 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, NUTRIM, School for Nutrition and Translational Research in Metabolism, , Maastricht University, ; Maastricht, The Netherlands
                [4 ]GRID grid.412966.e, ISNI 0000 0004 0480 1382, Department of Nuclear Medicine and Radiology, , MUMC+, ; Maastricht, The Netherlands
                [5 ]Division of Nuclear Medicine, Uniklinikum Aachen, Aachen, Germany
                [6 ]GRID grid.440789.6, ISNI 0000 0001 2226 7046, Department of Organic Chemistry, , Slovak University of Technology, ; Radlinského 9, 81237 Bratislava, Slovak Republic
                [7 ]GRID grid.484519.5, Department of Molecular Cell Biology and Immunology, Amsterdam Neuroscience, , Amsterdam UMC, ; Amsterdam, The Netherlands
                [8 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Internal Medicine, Laboratory Vascular Medicine, , Erasmus MC University Medical Center, ; Rotterdam, The Netherlands
                [9 ]GRID grid.10388.32, ISNI 0000 0001 2240 3300, Department of Neurology, University Hospital Bonn, , University of Bonn, ; Bonn, Germany
                [10 ]GRID grid.5596.f, ISNI 0000 0001 0668 7884, Laboratory of Protein Phosphorylation and Proteomics, , KU Leuven, ; Leuven, Belgium
                [11 ]GRID grid.5596.f, ISNI 0000 0001 0668 7884, Laboratory of Lipid Metabolism and Cancer, , KU Leuven, ; Leuven, Belgium
                [12 ]GRID grid.413837.a, ISNI 0000 0004 0419 5749, Veterans Affairs Medical Center, ; Lexington, KY 40502 USA
                Article
                76335
                10.1038/s41598-020-76335-4
                7652882
                33168861
                c8900261-49a5-4841-84ab-4537728f5043
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 June 2020
                : 22 October 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001826, ZonMw;
                Award ID: 7330598117
                Award ID: 733050105
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000009, Foundation for the National Institutes of Health;
                Award ID: R01AG034389
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000738, U.S. Department of Veterans Affairs;
                Award ID: VA I01BX003643
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100010969, Alzheimer Nederland;
                Award ID: 14545
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                neurodegeneration,alzheimer's disease,lipidomics,nuclear chemistry
                Uncategorized
                neurodegeneration, alzheimer's disease, lipidomics, nuclear chemistry

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