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      Untargeted metabolomics unveil alterations of biomembranes permeability in human HaCaT keratinocytes upon 60 GHz millimeter-wave exposure

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          Abstract

          A joint metabolomic and lipidomic workflow is used to account for a potential effect of millimeter waves (MMW) around 60 GHz on biological tissues. For this purpose, HaCaT human keratinocytes were exposed at 60.4 GHz with an incident power density of 20 mW/cm², this value corresponding to the upper local exposure limit for general public in the context of a wide scale deployment of MMW technologies and devices. After a 24h-exposure, endo- and extracellular extracts were recovered to be submitted to an integrative UPLC-Q-Exactive metabolomic and lipidomic workflow. R-XCMS data processing and subsequent statistical treatment led to emphasize a limited number of altered features in lipidomic sequences and in intracellular metabolomic analyses, whatever the ionization mode ( i.e 0 to 6 dysregulated features). Conversely, important dysregulations could be reported in extracellular metabolomic profiles with 111 and 99 frames being altered upon MMW exposure in positive and negative polarities, respectively. This unexpected extent of modifications can hardly stem from the mild changes that could be reported throughout transcriptomics studies, leading us to hypothesize that MMW might alter the permeability of cell membranes, as reported elsewhere.

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          CAMERA: an integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry data sets.

          Liquid chromatography coupled to mass spectrometry is routinely used for metabolomics experiments. In contrast to the fairly routine and automated data acquisition steps, subsequent compound annotation and identification require extensive manual analysis and thus form a major bottleneck in data interpretation. Here we present CAMERA, a Bioconductor package integrating algorithms to extract compound spectra, annotate isotope and adduct peaks, and propose the accurate compound mass even in highly complex data. To evaluate the algorithms, we compared the annotation of CAMERA against a manually defined annotation for a mixture of known compounds spiked into a complex matrix at different concentrations. CAMERA successfully extracted accurate masses for 89.7% and 90.3% of the annotatable compounds in positive and negative ion modes, respectively. Furthermore, we present a novel annotation approach that combines spectral information of data acquired in opposite ion modes to further improve the annotation rate. We demonstrate the utility of CAMERA in two different, easily adoptable plant metabolomics experiments, where the application of CAMERA drastically reduced the amount of manual analysis. © 2011 American Chemical Society
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            Mechanisms of cell membrane electropermeabilization: a minireview of our present (lack of ?) knowledge.

            Cell electropulsation is routinely used in cell Biology for protein, RNA or DNA transfer. Its clinical applications are under development for targeted drug delivery and gene therapy. Nevertheless, the molecular mechanisms supporting the induction of permeabilizing defects in the membrane assemblies remain poorly understood. This minireview describes the present state of the investigations concerning the different steps in the reversible electropermeabilization process. The different hypotheses, which were proposed to give a molecular description of the membrane events, are critically discussed. Other possibilities are then given. The need for more basic research on the associated loss of cohesion of the membrane appears as a conclusion.
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              Current practice of liquid chromatography-mass spectrometry in metabolomics and metabonomics.

              Based on publication and citation numbers liquid chromatography (LC-MS) has become the major analytical technology in the field of global metabolite profiling. This dominance reflects significant investments from both the research community and instrument manufacturers. Here an overview of the approaches taken for LC-MS-based metabolomics research is given, describing critical steps in the realisation of such studies: study design and its needs, specific technological problems to be addressed and major obstacles in data treatment and biomarker identification. The current state of the art for LC-MS-based analysis in metabonomics/metabolomics is described including recent developments in liquid chromatography, mass spectrometry and data treatment as these are applied in metabolomics underlining the challenges, limitations and prospects for metabolomics research. Examples of the application of metabolite profiling in the life sciences focusing on disease biomarker discovery are highlighted. In addition, new developments and future prospects are described. Copyright © 2013 Elsevier B.V. All rights reserved.
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                Author and article information

                Contributors
                david.rondeau@univ-rennes1.fr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 June 2019
                27 June 2019
                2019
                : 9
                : 9343
                Affiliations
                [1 ]ISNI 0000 0001 2191 9284, GRID grid.410368.8, Univ Rennes, CNRS, IETR (Institut d’Électronique et de Télécommunication de Rennes), UMR 6164, ; F-35000 Rennes, France
                [2 ]ISNI 0000 0001 2191 9284, GRID grid.410368.8, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) – UMR_S 1085, ; F-35000 Rennes, France
                [3 ]ISNI 0000 0001 2188 0893, GRID grid.6289.5, Département de Chimie, , Université de Bretagne Occidentale, 6 avenue Victor Le Gorgeu, ; 29238 Brest, Cedex France
                Author information
                http://orcid.org/0000-0001-8101-3839
                http://orcid.org/0000-0001-5326-5916
                Article
                45662
                10.1038/s41598-019-45662-6
                6597695
                31249327
                9aee37fa-a462-4eaa-b23a-9684b0f757d0
                © The Author(s) 2019

                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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 April 2018
                : 30 May 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100007546, Agence Nationale de Sécurité Sanitaire de l'Alimentation, de l'Environnement et du Travail (ANSES);
                Award ID: BEMAM n° EST-2014/2 RF/012
                Award Recipient :
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                © The Author(s) 2019

                Uncategorized
                metabolomics,diagnostic markers
                Uncategorized
                metabolomics, diagnostic markers

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