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Georgiadis M, Menzel M, Reuter JA, Born DE, Kovacevich SR, Alvarez D, Taghavi HM, Schroeter A, Rudin M, Gao Z, Guizar-Sicairos M, Weiss TM, Axer M, Rajkovic I, Zeineh MM. Imaging crossing fibers in mouse, pig, monkey, and human brain using small-angle X-ray scattering. Acta Biomater 2023; 164:317-331. [PMID: 37098400 PMCID: PMC10811447 DOI: 10.1016/j.actbio.2023.04.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/15/2023] [Accepted: 04/18/2023] [Indexed: 04/27/2023]
Abstract
Myelinated axons (nerve fibers) efficiently transmit signals throughout the brain via action potentials. Multiple methods that are sensitive to axon orientations, from microscopy to magnetic resonance imaging, aim to reconstruct the brain's structural connectome. As billions of nerve fibers traverse the brain with various possible geometries at each point, resolving fiber crossings is necessary to generate accurate structural connectivity maps. However, doing so with specificity is a challenging task because signals originating from oriented fibers can be influenced by brain (micro)structures unrelated to myelinated axons. X-ray scattering can specifically probe myelinated axons due to the periodicity of the myelin sheath, which yields distinct peaks in the scattering pattern. Here, we show that small-angle X-ray scattering (SAXS) can be used to detect myelinated, axon-specific fiber crossings. We first demonstrate the capability using strips of human corpus callosum to create artificial double- and triple-crossing fiber geometries, and we then apply the method in mouse, pig, vervet monkey, and human brains. We compare results to polarized light imaging (3D-PLI), tracer experiments, and to outputs from diffusion MRI that sometimes fails to detect crossings. Given its specificity, capability of 3-dimensional sampling and high resolution, SAXS could serve as a ground truth for validating fiber orientations derived using diffusion MRI as well as microscopy-based methods. STATEMENT OF SIGNIFICANCE: To study how the nerve fibers in our brain are interconnected, scientists need to visualize their trajectories, which often cross one another. Here, we show the unique capacity of small-angle X-ray scattering (SAXS) to study these fiber crossings without use of labeling, taking advantage of SAXS's specificity to myelin - the insulating sheath that is wrapped around nerve fibers. We use SAXS to detect double and triple crossing fibers and unveil intricate crossings in mouse, pig, vervet monkey, and human brains. This non-destructive method can uncover complex fiber trajectories and validate other less specific imaging methods (e.g., MRI or microscopy), towards accurate mapping of neuronal connectivity in the animal and human brain.
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Affiliation(s)
- Marios Georgiadis
- Department of Radiology, Stanford School of Medicine, Stanford, CA, USA; Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.
| | - Miriam Menzel
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH, Jülich 52425, Germany; Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
| | - Jan A Reuter
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH, Jülich 52425, Germany
| | - Donald E Born
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA
| | | | - Dario Alvarez
- Department of Radiology, Stanford School of Medicine, Stanford, CA, USA
| | | | - Aileen Schroeter
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Markus Rudin
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Zirui Gao
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | | | - Thomas M Weiss
- SLAC National Accelerator Laboratory, Stanford Synchrotron Radiation Lightsource, USA
| | - Markus Axer
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH, Jülich 52425, Germany
| | - Ivan Rajkovic
- SLAC National Accelerator Laboratory, Stanford Synchrotron Radiation Lightsource, USA
| | - Michael M Zeineh
- Department of Radiology, Stanford School of Medicine, Stanford, CA, USA
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Grandjean J, Desrosiers-Gregoire G, Anckaerts C, Angeles-Valdez D, Ayad F, Barrière DA, Blockx I, Bortel A, Broadwater M, Cardoso BM, Célestine M, Chavez-Negrete JE, Choi S, Christiaen E, Clavijo P, Colon-Perez L, Cramer S, Daniele T, Dempsey E, Diao Y, Doelemeyer A, Dopfel D, Dvořáková L, Falfán-Melgoza C, Fernandes FF, Fowler CF, Fuentes-Ibañez A, Garin CM, Gelderman E, Golden CEM, Guo CCG, Henckens MJAG, Hennessy LA, Herman P, Hofwijks N, Horien C, Ionescu TM, Jones J, Kaesser J, Kim E, Lambers H, Lazari A, Lee SH, Lillywhite A, Liu Y, Liu YY, López-Castro A, López-Gil X, Ma Z, MacNicol E, Madularu D, Mandino F, Marciano S, McAuslan MJ, McCunn P, McIntosh A, Meng X, Meyer-Baese L, Missault S, Moro F, Naessens DMP, Nava-Gomez LJ, Nonaka H, Ortiz JJ, Paasonen J, Peeters LM, Pereira M, Perez PD, Pompilus M, Prior M, Rakhmatullin R, Reimann HM, Reinwald J, Del Rio RT, Rivera-Olvera A, Ruiz-Pérez D, Russo G, Rutten TJ, Ryoke R, Sack M, Salvan P, Sanganahalli BG, Schroeter A, Seewoo BJ, Selingue E, Seuwen A, Shi B, Sirmpilatze N, Smith JAB, Smith C, Sobczak F, Stenroos PJ, Straathof M, Strobelt S, Sumiyoshi A, Takahashi K, Torres-García ME, Tudela R, van den Berg M, van der Marel K, van Hout ATB, Vertullo R, Vidal B, Vrooman RM, Wang VX, Wank I, Watson DJG, Yin T, Zhang Y, Zurbruegg S, Achard S, Alcauter S, Auer DP, Barbier EL, Baudewig J, Beckmann CF, Beckmann N, Becq GJPC, Blezer ELA, Bolbos R, Boretius S, Bouvard S, Budinger E, Buxbaum JD, Cash D, Chapman V, Chuang KH, Ciobanu L, Coolen BF, Dalley JW, Dhenain M, Dijkhuizen RM, Esteban O, Faber C, Febo M, Feindel KW, Forloni G, Fouquet J, Garza-Villarreal EA, Gass N, Glennon JC, Gozzi A, Gröhn O, Harkin A, Heerschap A, Helluy X, Herfert K, Heuser A, Homberg JR, Houwing DJ, Hyder F, Ielacqua GD, Jelescu IO, Johansen-Berg H, Kaneko G, Kawashima R, Keilholz SD, Keliris GA, Kelly C, Kerskens C, Khokhar JY, Kind PC, Langlois JB, Lerch JP, López-Hidalgo MA, Manahan-Vaughan D, Marchand F, Mars RB, Marsella G, Micotti E, Muñoz-Moreno E, Near J, Niendorf T, Otte WM, Pais-Roldán P, Pan WJ, Prado-Alcalá RA, Quirarte GL, Rodger J, Rosenow T, Sampaio-Baptista C, Sartorius A, Sawiak SJ, Scheenen TWJ, Shemesh N, Shih YYI, Shmuel A, Soria G, Stoop R, Thompson GJ, Till SM, Todd N, Van Der Linden A, van der Toorn A, van Tilborg GAF, Vanhove C, Veltien A, Verhoye M, Wachsmuth L, Weber-Fahr W, Wenk P, Yu X, Zerbi V, Zhang N, Zhang BB, Zimmer L, Devenyi GA, Chakravarty MM, Hess A. Author Correction: A consensus protocol for functional connectivity analysis in the rat brain. Nat Neurosci 2023:10.1038/s41593-023-01328-1. [PMID: 37072562 DOI: 10.1038/s41593-023-01328-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands.
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Gabriel Desrosiers-Gregoire
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Cynthia Anckaerts
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Diego Angeles-Valdez
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Fadi Ayad
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - David A Barrière
- UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction, Physiologie de la reproduction et des comportements, Centre de recherche INRAE de Nouzilly, Tours, France
| | - Ines Blockx
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Aleksandra Bortel
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Margaret Broadwater
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Beatriz M Cardoso
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marina Célestine
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Jorge E Chavez-Negrete
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Sangcheon Choi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Emma Christiaen
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Perrin Clavijo
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Luis Colon-Perez
- Department of Pharmacology & Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Samuel Cramer
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Tolomeo Daniele
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Elaine Dempsey
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Yujian Diao
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arno Doelemeyer
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - David Dopfel
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lenka Dvořáková
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Claudia Falfán-Melgoza
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Francisca F Fernandes
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Caitlin F Fowler
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Antonio Fuentes-Ibañez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Clément M Garin
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Eveline Gelderman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Carla E M Golden
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Chao C G Guo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Marloes J A G Henckens
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Department of Neuroscience and Pharmacology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lauren A Hennessy
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Peter Herman
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Nita Hofwijks
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Corey Horien
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Tudor M Ionescu
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Jolyon Jones
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Johannes Kaesser
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Eugene Kim
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Henriette Lambers
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Alberto Lazari
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lillywhite
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Yikang Liu
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Yanyan Y Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Alejandra López-Castro
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Xavier López-Gil
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Zilu Ma
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Eilidh MacNicol
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Dan Madularu
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Center for Translational Neuroimaging, Northeastern University, Boston, MA, USA
| | - Francesca Mandino
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Sabina Marciano
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Matthew J McAuslan
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Patrick McCunn
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Alison McIntosh
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Xianzong Meng
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Lisa Meyer-Baese
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Stephan Missault
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Federico Moro
- Laboratory of Acute Brain Injury and Therapeutic Strategies, Department of NeuroscienceIstituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Daphne M P Naessens
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura J Nava-Gomez
- Facultad de Medicina, Universidad Autónoma de Querétaro, Querétaro, México
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Hiroi Nonaka
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Juan J Ortiz
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jaakko Paasonen
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Lore M Peeters
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mickaël Pereira
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Pablo D Perez
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Marjory Pompilus
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Malcolm Prior
- School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Henning M Reimann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Jonathan Reinwald
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rodrigo Triana Del Rio
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | | | - Gabriele Russo
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
| | - Tobias J Rutten
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Rie Ryoke
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Markus Sack
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Piergiorgio Salvan
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Basavaraju G Sanganahalli
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bhedita J Seewoo
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | | | - Aline Seuwen
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bowen Shi
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Joanna A B Smith
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Corrie Smith
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Filip Sobczak
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Petteri J Stenroos
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Milou Straathof
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Sandra Strobelt
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Akira Sumiyoshi
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Kengo Takahashi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Maria E Torres-García
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Raul Tudela
- Group of Biomedical Imaging, Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), University of Barcelona, Barcelona, Spain
| | - Monica van den Berg
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Kajo van der Marel
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Aran T B van Hout
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Roberta Vertullo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Benjamin Vidal
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Roël M Vrooman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Victora X Wang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Isabel Wank
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - David J G Watson
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Ting Yin
- Animal Imaging and Technology Section, Center for Biomedical Imaging, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | - Yongzhi Zhang
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Sophie Achard
- Inria, University Grenoble Alpes, CNRS, Grenoble, France
| | - Sarael Alcauter
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Dorothee P Auer
- School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emmanuel L Barbier
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Christian F Beckmann
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nicolau Beckmann
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | | | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Sandrine Bouvard
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Eike Budinger
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Joseph D Buxbaum
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Diana Cash
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Victoria Chapman
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Kai-Hsiang Chuang
- Queensland Brain Institute and Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | | | - Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeffrey W Dalley
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Marc Dhenain
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Oscar Esteban
- Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Cornelius Faber
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Marcelo Febo
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Kirk W Feindel
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | - Gianluigi Forloni
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Jérémie Fouquet
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Natalia Gass
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Jeffrey C Glennon
- Conway Institute of Biomedical and Biomolecular Sciences, School of Medicine, University College Dublin, Dublin, Ireland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Olli Gröhn
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Andrew Harkin
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Arend Heerschap
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Xavier Helluy
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Kristina Herfert
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Arnd Heuser
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Judith R Homberg
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Danielle J Houwing
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Fahmeed Hyder
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | | | - Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Heidi Johansen-Berg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gen Kaneko
- School of Arts & Sciences, University of Houston-Victoria, Victoria, TX, USA
| | - Ryuta Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Shella D Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Georgios A Keliris
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Clare Kelly
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Christian Kerskens
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Trinity Centre for Biomedical Engineering, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jibran Y Khokhar
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Peter C Kind
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Brain Development and Repair, Institute for Stem Cell Biology and Regenerative Medicine, Bangalore, India
| | | | - Jason P Lerch
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- Department of Medical Biophysics, University of Toronto, Toronto, QC, Canada
| | - Monica A López-Hidalgo
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | | | - Fabien Marchand
- Université Clermont Auvergne, Inserm U1107 Neuro-Dol, Pharmacologie Fondamentale et Clinique de la Douleur, Clermont-Ferrand, France
| | - Rogier B Mars
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gerardo Marsella
- Animal Care Unit, Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Edoardo Micotti
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Emma Muñoz-Moreno
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Jamie Near
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, QC, Canada
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Willem M Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Patricia Pais-Roldán
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Medical Imaging Physics (INM-4), Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich, Germany
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Roberto A Prado-Alcalá
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Gina L Quirarte
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jennifer Rodger
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Tim Rosenow
- Centre for Microscopy, Characterisation and Analysis, University of Western Australia, Crawley, WA, Australia
| | - Cassandra Sampaio-Baptista
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Alexander Sartorius
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephen J Sawiak
- Translational Neuroimaging Laboratory, Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Tom W J Scheenen
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany
| | - Noam Shemesh
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amir Shmuel
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Physiology, McGill University, Montreal, QC, Canada
| | - Guadalupe Soria
- Laboratory of Surgical Neuroanatomy, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Ron Stoop
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | | | - Sally M Till
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Nick Todd
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Annemie Van Der Linden
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Annette van der Toorn
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Geralda A F van Tilborg
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Christian Vanhove
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Andor Veltien
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marleen Verhoye
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Lydia Wachsmuth
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang Weber-Fahr
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Patricia Wenk
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Xin Yu
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, Lausanne, Switzerland
- Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Nanyin Zhang
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Baogui B Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Luc Zimmer
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
- CERMEP - Imagerie du vivant, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
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Grandjean J, Desrosiers-Gregoire G, Anckaerts C, Angeles-Valdez D, Ayad F, Barrière DA, Blockx I, Bortel A, Broadwater M, Cardoso BM, Célestine M, Chavez-Negrete JE, Choi S, Christiaen E, Clavijo P, Colon-Perez L, Cramer S, Daniele T, Dempsey E, Diao Y, Doelemeyer A, Dopfel D, Dvořáková L, Falfán-Melgoza C, Fernandes FF, Fowler CF, Fuentes-Ibañez A, Garin CM, Gelderman E, Golden CEM, Guo CCG, Henckens MJAG, Hennessy LA, Herman P, Hofwijks N, Horien C, Ionescu TM, Jones J, Kaesser J, Kim E, Lambers H, Lazari A, Lee SH, Lillywhite A, Liu Y, Liu YY, López-Castro A, López-Gil X, Ma Z, MacNicol E, Madularu D, Mandino F, Marciano S, McAuslan MJ, McCunn P, McIntosh A, Meng X, Meyer-Baese L, Missault S, Moro F, Naessens DMP, Nava-Gomez LJ, Nonaka H, Ortiz JJ, Paasonen J, Peeters LM, Pereira M, Perez PD, Pompilus M, Prior M, Rakhmatullin R, Reimann HM, Reinwald J, Del Rio RT, Rivera-Olvera A, Ruiz-Pérez D, Russo G, Rutten TJ, Ryoke R, Sack M, Salvan P, Sanganahalli BG, Schroeter A, Seewoo BJ, Selingue E, Seuwen A, Shi B, Sirmpilatze N, Smith JAB, Smith C, Sobczak F, Stenroos PJ, Straathof M, Strobelt S, Sumiyoshi A, Takahashi K, Torres-García ME, Tudela R, van den Berg M, van der Marel K, van Hout ATB, Vertullo R, Vidal B, Vrooman RM, Wang VX, Wank I, Watson DJG, Yin T, Zhang Y, Zurbruegg S, Achard S, Alcauter S, Auer DP, Barbier EL, Baudewig J, Beckmann CF, Beckmann N, Becq GJPC, Blezer ELA, Bolbos R, Boretius S, Bouvard S, Budinger E, Buxbaum JD, Cash D, Chapman V, Chuang KH, Ciobanu L, Coolen BF, Dalley JW, Dhenain M, Dijkhuizen RM, Esteban O, Faber C, Febo M, Feindel KW, Forloni G, Fouquet J, Garza-Villarreal EA, Gass N, Glennon JC, Gozzi A, Gröhn O, Harkin A, Heerschap A, Helluy X, Herfert K, Heuser A, Homberg JR, Houwing DJ, Hyder F, Ielacqua GD, Jelescu IO, Johansen-Berg H, Kaneko G, Kawashima R, Keilholz SD, Keliris GA, Kelly C, Kerskens C, Khokhar JY, Kind PC, Langlois JB, Lerch JP, López-Hidalgo MA, Manahan-Vaughan D, Marchand F, Mars RB, Marsella G, Micotti E, Muñoz-Moreno E, Near J, Niendorf T, Otte WM, Pais-Roldán P, Pan WJ, Prado-Alcalá RA, Quirarte GL, Rodger J, Rosenow T, Sampaio-Baptista C, Sartorius A, Sawiak SJ, Scheenen TWJ, Shemesh N, Shih YYI, Shmuel A, Soria G, Stoop R, Thompson GJ, Till SM, Todd N, Van Der Linden A, van der Toorn A, van Tilborg GAF, Vanhove C, Veltien A, Verhoye M, Wachsmuth L, Weber-Fahr W, Wenk P, Yu X, Zerbi V, Zhang N, Zhang BB, Zimmer L, Devenyi GA, Chakravarty MM, Hess A. A consensus protocol for functional connectivity analysis in the rat brain. Nat Neurosci 2023; 26:673-681. [PMID: 36973511 PMCID: PMC10493189 DOI: 10.1038/s41593-023-01286-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 02/15/2023] [Indexed: 03/29/2023]
Abstract
Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.
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Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands.
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Gabriel Desrosiers-Gregoire
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Cynthia Anckaerts
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Diego Angeles-Valdez
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Fadi Ayad
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - David A Barrière
- UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction, Physiologie de la reproduction et des comportements, Centre de recherche INRAE de Nouzilly, Tours, France
| | - Ines Blockx
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Aleksandra Bortel
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Margaret Broadwater
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Beatriz M Cardoso
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marina Célestine
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Jorge E Chavez-Negrete
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Sangcheon Choi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Emma Christiaen
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Perrin Clavijo
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Luis Colon-Perez
- Department of Pharmacology & Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Samuel Cramer
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Tolomeo Daniele
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Elaine Dempsey
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Yujian Diao
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arno Doelemeyer
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - David Dopfel
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lenka Dvořáková
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Claudia Falfán-Melgoza
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Francisca F Fernandes
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Caitlin F Fowler
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Antonio Fuentes-Ibañez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Clément M Garin
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Eveline Gelderman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Carla E M Golden
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Chao C G Guo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Marloes J A G Henckens
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Department of Neuroscience and Pharmacology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lauren A Hennessy
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Peter Herman
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Nita Hofwijks
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Corey Horien
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Tudor M Ionescu
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Jolyon Jones
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Johannes Kaesser
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Eugene Kim
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Henriette Lambers
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Alberto Lazari
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lillywhite
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Yikang Liu
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Yanyan Y Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Alejandra López-Castro
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Xavier López-Gil
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Zilu Ma
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Eilidh MacNicol
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Dan Madularu
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Center for Translational Neuroimaging, Northeastern University, Boston, MA, USA
| | - Francesca Mandino
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Sabina Marciano
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Matthew J McAuslan
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Patrick McCunn
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Alison McIntosh
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Xianzong Meng
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Lisa Meyer-Baese
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Stephan Missault
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Federico Moro
- Laboratory of Acute Brain Injury and Therapeutic Strategies, Department of NeuroscienceIstituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Daphne M P Naessens
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura J Nava-Gomez
- Facultad de Medicina, Universidad Autónoma de Querétaro, Querétaro, México
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Hiroi Nonaka
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Juan J Ortiz
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jaakko Paasonen
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Lore M Peeters
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mickaël Pereira
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Pablo D Perez
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Marjory Pompilus
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Malcolm Prior
- School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Henning M Reimann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Jonathan Reinwald
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rodrigo Triana Del Rio
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | | | - Gabriele Russo
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
| | - Tobias J Rutten
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Rie Ryoke
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Markus Sack
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Piergiorgio Salvan
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Basavaraju G Sanganahalli
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bhedita J Seewoo
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | | | - Aline Seuwen
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bowen Shi
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Joanna A B Smith
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Corrie Smith
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Filip Sobczak
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Petteri J Stenroos
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Milou Straathof
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Sandra Strobelt
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Akira Sumiyoshi
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Kengo Takahashi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Maria E Torres-García
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Raul Tudela
- Group of Biomedical Imaging, Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), University of Barcelona, Barcelona, Spain
| | - Monica van den Berg
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Kajo van der Marel
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Aran T B van Hout
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Roberta Vertullo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Benjamin Vidal
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Roël M Vrooman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Victora X Wang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Isabel Wank
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - David J G Watson
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Ting Yin
- Animal Imaging and Technology Section, Center for Biomedical Imaging, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | - Yongzhi Zhang
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Sophie Achard
- Inria, University Grenoble Alpes, CNRS, Grenoble, France
| | - Sarael Alcauter
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Dorothee P Auer
- School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emmanuel L Barbier
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Christian F Beckmann
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nicolau Beckmann
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | | | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Sandrine Bouvard
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Eike Budinger
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Joseph D Buxbaum
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Diana Cash
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Victoria Chapman
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Kai-Hsiang Chuang
- Queensland Brain Institute and Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | | | - Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeffrey W Dalley
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Marc Dhenain
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Oscar Esteban
- Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Cornelius Faber
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Marcelo Febo
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Kirk W Feindel
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | - Gianluigi Forloni
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Jérémie Fouquet
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Natalia Gass
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Jeffrey C Glennon
- Conway Institute of Biomedical and Biomolecular Sciences, School of Medicine, University College Dublin, Dublin, Ireland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Olli Gröhn
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Andrew Harkin
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Arend Heerschap
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Xavier Helluy
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Kristina Herfert
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Arnd Heuser
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Judith R Homberg
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Danielle J Houwing
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Fahmeed Hyder
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | | | - Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Heidi Johansen-Berg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gen Kaneko
- School of Arts & Sciences, University of Houston-Victoria, Victoria, TX, USA
| | - Ryuta Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Shella D Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Georgios A Keliris
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Clare Kelly
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Christian Kerskens
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Trinity Centre for Biomedical Engineering, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jibran Y Khokhar
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Peter C Kind
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Brain Development and Repair, Institute for Stem Cell Biology and Regenerative Medicine, Bangalore, India
| | | | - Jason P Lerch
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- Department of Medical Biophysics, University of Toronto, Toronto, QC, Canada
| | - Monica A López-Hidalgo
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | | | - Fabien Marchand
- Université Clermont Auvergne, Inserm U1107 Neuro-Dol, Pharmacologie Fondamentale et Clinique de la Douleur, Clermont-Ferrand, France
| | - Rogier B Mars
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gerardo Marsella
- Animal Care Unit, Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Edoardo Micotti
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Emma Muñoz-Moreno
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Jamie Near
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, QC, Canada
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Willem M Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Patricia Pais-Roldán
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Medical Imaging Physics (INM-4), Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich, Germany
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Roberto A Prado-Alcalá
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Gina L Quirarte
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jennifer Rodger
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Tim Rosenow
- Centre for Microscopy, Characterisation and Analysis, University of Western Australia, Crawley, WA, Australia
| | - Cassandra Sampaio-Baptista
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Alexander Sartorius
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephen J Sawiak
- Translational Neuroimaging Laboratory, Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Tom W J Scheenen
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany
| | - Noam Shemesh
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amir Shmuel
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Physiology, McGill University, Montreal, QC, Canada
| | - Guadalupe Soria
- Laboratory of Surgical Neuroanatomy, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Ron Stoop
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | | | - Sally M Till
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Nick Todd
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Annemie Van Der Linden
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Annette van der Toorn
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Geralda A F van Tilborg
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Christian Vanhove
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Andor Veltien
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marleen Verhoye
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Lydia Wachsmuth
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang Weber-Fahr
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Patricia Wenk
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Xin Yu
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, Lausanne, Switzerland
- Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Nanyin Zhang
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Baogui B Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Luc Zimmer
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
- CERMEP - Imagerie du vivant, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
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Ioanas HI, Schlegel F, Skachokova Z, Schroeter A, Husak T, Rudin M. Hybrid fiber optic-fMRI for multimodal cell-specific recording and manipulation of neural activity in rodents. Neurophotonics 2022; 9:032206. [PMID: 35355657 PMCID: PMC8936941 DOI: 10.1117/1.nph.9.3.032206] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 01/19/2022] [Indexed: 05/08/2023]
Abstract
Significance: Multiscale imaging holds particular relevance to neuroscience, where it helps integrate the cellular and molecular biological scale, which is most accessible to interventions, with holistic organ-level evaluations, most relevant with respect to function. Being inextricably interdisciplinary, multiscale imaging benefits substantially from incremental technology adoption, and a detailed overview of the state-of-the-art is vital to an informed application of imaging methods. Aim: In this article, we lay out the background and methodological aspects of multimodal approaches combining functional magnetic resonance imaging (fMRI) with simultaneous optical measurement or stimulation. Approach: We focus on optical techniques as these allow, in conjunction with genetically encoded proteins (e.g. calcium indicators or optical signal transducers), unprecedented read-out and control specificity for individual cell-types during fMRI experiments, while leveraging non-interfering modalities. Results: A variety of different solutions for optical/fMRI methods has been reported ranging from bulk fluorescence recordings via fiber photometry to high resolution microscopy. In particular, the plethora of optogenetic tools has enabled the transformation of stimulus-evoked fMRI into a cell biological interrogation method. We discuss the capabilities and limitations of these genetically encoded molecular tools in the study of brain phenomena of great methodological and neuropsychiatric interest-such as neurovascular coupling (NVC) and neuronal network mapping. We provide a methodological description of this interdisciplinary field of study, and focus in particular on the limitations of the widely used blood oxygen level dependent (BOLD) signal and how multimodal readouts can shed light on the contributions arising from neurons, astrocytes, or the vasculature. Conclusion: We conclude that information from multiple signaling pathways must be incorporated in future forward models of the BOLD response to prevent erroneous conclusions when using fMRI as a surrogate measure for neural activity. Further, we highlight the potential of direct neuronal stimulation via genetically defined brain networks towards advancing neurophysiological understanding and better estimating effective connectivity.
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Affiliation(s)
- Horea-Ioan Ioanas
- University of Zurich Institute for Biomedical Engineering, ETH, Zürich, Switzerland
- Massachusetts Institute of Technology, Department of Biological Engineering, Cambridge, Massachusetts, United States
- Dartmouth College, Center for Open Neuroscience, Hanover, New Hampshire, United States
- Address all correspondence to Markus Rudin, ; Horea-Ioan Ioanas,
| | - Felix Schlegel
- University of Zurich Institute for Biomedical Engineering, ETH, Zürich, Switzerland
| | - Zhiva Skachokova
- University of Zurich Institute for Biomedical Engineering, ETH, Zürich, Switzerland
| | - Aileen Schroeter
- University of Zurich Institute for Biomedical Engineering, ETH, Zürich, Switzerland
- University of Zurich, USZ Innovation Hub, Zurich, Switzerland
| | - Tetiana Husak
- Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, Cambridge, Massachusetts, United States
| | - Markus Rudin
- University of Zurich Institute for Biomedical Engineering, ETH, Zürich, Switzerland
- The LOOP Zurich, Zurich, Switzerland
- Address all correspondence to Markus Rudin, ; Horea-Ioan Ioanas,
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5
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Steiner AR, Rousseau-Blass F, Schroeter A, Hartnack S, Bettschart-Wolfensberger R. Systematic Review: Anesthetic Protocols and Management as Confounders in Rodent Blood Oxygen Level Dependent Functional Magnetic Resonance Imaging (BOLD fMRI)-Part B: Effects of Anesthetic Agents, Doses and Timing. Animals (Basel) 2021; 11:ani11010199. [PMID: 33467584 PMCID: PMC7830239 DOI: 10.3390/ani11010199] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/17/2020] [Accepted: 12/29/2020] [Indexed: 02/07/2023] Open
Abstract
Simple Summary To understand brain function in rats and mice functional magnetic resonance imaging of the brain is used. With this type of “brain scan” regional changes in blood flow and oxygen consumption are measured as an indirect surrogate for activity of brain regions. Animals are often anesthetized for the experiments to prevent stress and blurred images due to movement. However, anesthesia may alter the measurements, as blood flow within the brain is differently affected by different anesthetics, and anesthetics also directly affect brain function. Consequently, results obtained under one anesthetic protocol may not be comparable with those obtained under another, and/or not representative for awake animals and humans. We have systematically searched the existing literature for studies analyzing the effects of different anesthesia methods or studies that compared anesthetized and awake animals. Most studies reported that anesthetic agents, doses and timing had an effect on functional magnetic resonance imaging results. To obtain results which promote our understanding of brain function, it is therefore essential that a standard for anesthetic protocols for functional magnetic resonance is defined and their impact is well characterized. Abstract In rodent models the use of functional magnetic resonance imaging (fMRI) under anesthesia is common. The anesthetic protocol might influence fMRI readouts either directly or via changes in physiological parameters. As long as those factors cannot be objectively quantified, the scientific validity of fMRI in rodents is impaired. In the present systematic review, literature analyzing in rats and mice the influence of anesthesia regimes and concurrent physiological functions on blood oxygen level dependent (BOLD) fMRI results was investigated. Studies from four databases that were searched were selected following pre-defined criteria. Two separate articles publish the results; the herewith presented article includes the analyses of 83 studies. Most studies found differences in BOLD fMRI readouts with different anesthesia drugs and dose rates, time points of imaging or when awake status was compared to anesthetized animals. To obtain scientifically valid, reproducible results from rodent fMRI studies, stable levels of anesthesia with agents suitable for the model under investigation as well as known and objectively quantifiable effects on readouts are, thus, mandatory. Further studies should establish dose ranges for standardized anesthetic protocols and determine time windows for imaging during which influence of anesthesia on readout is objectively quantifiable.
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Affiliation(s)
- Aline R. Steiner
- Section of Anaesthesiology, Department of Clinical and Diagnostic Services, Vetsuisse Faculty, University of Zurich, 8057 Zurich, Switzerland;
- Correspondence:
| | - Frédérik Rousseau-Blass
- Department of Clinical Sciences, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC J2S 2M2, Canada;
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, 8093 Zurich, Switzerland;
| | - Sonja Hartnack
- Section of Epidemiology, Vetsuisse Faculty, University of Zurich, 8057 Zurich, Switzerland;
| | - Regula Bettschart-Wolfensberger
- Section of Anaesthesiology, Department of Clinical and Diagnostic Services, Vetsuisse Faculty, University of Zurich, 8057 Zurich, Switzerland;
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6
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Steiner AR, Rousseau-Blass F, Schroeter A, Hartnack S, Bettschart-Wolfensberger R. Systematic Review: Anaesthetic Protocols and Management as Confounders in Rodent Blood Oxygen Level Dependent Functional Magnetic Resonance Imaging (BOLD fMRI)-Part A: Effects of Changes in Physiological Parameters. Front Neurosci 2020; 14:577119. [PMID: 33192261 PMCID: PMC7646331 DOI: 10.3389/fnins.2020.577119] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Accepted: 09/10/2020] [Indexed: 12/09/2022] Open
Abstract
Background: To understand brain function in health and disease, functional magnetic resonance imaging (fMRI) is widely used in rodent models. Because animals need to be immobilised for image acquisition, fMRI is commonly performed under anaesthesia. The choice of anaesthetic protocols and may affect fMRI readouts, either directly or via changing physiological balance, and thereby threaten the scientific validity of fMRI in rodents. Methods: The present study systematically reviewed the literature investigating the influence of different anaesthesia regimes and changes in physiological parameters as confounders of blood oxygen level dependent (BOLD) fMRI in rats and mice. Four databases were searched, studies selected according to pre-defined criteria, and risk of bias assessed for each study. Results are reported in two separate articles; this part of the review focuses on effects of changes in physiological parameters. Results: A total of 121 publications was included, of which 49 addressed effects of changes in physiological parameters. Risk of bias was high in all included studies. Blood oxygenation [arterial partial pressure of oxygen (paO2)], ventilation [arterial partial pressure of carbon dioxide (paCO2)] and arterial blood pressure affected BOLD fMRI readouts across various experimental paradigms. Conclusions: Blood oxygenation, ventilation and arterial blood pressure should be monitored and maintained at stable physiological levels throughout experiments. Appropriate anaesthetic management and monitoring are crucial to obtain scientifically valid, reproducible results from fMRI studies in rodent models.
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Affiliation(s)
- Aline R. Steiner
- Section of Anaesthesiology, Department of Clinical and Diagnostic Services, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland
| | - Frédérik Rousseau-Blass
- Department of Clinical Sciences, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Sonja Hartnack
- Section of Epidemiology, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland
| | - Regula Bettschart-Wolfensberger
- Section of Anaesthesiology, Department of Clinical and Diagnostic Services, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland
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7
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Veys K, Fan Z, Ghobrial M, Bouché A, García-Caballero M, Vriens K, Conchinha NV, Seuwen A, Schlegel F, Gorski T, Crabbé M, Gilardoni P, Ardicoglu R, Schaffenrath J, Casteels C, De Smet G, Smolders I, Van Laere K, Abel ED, Fendt SM, Schroeter A, Kalucka J, Cantelmo AR, Wälchli T, Keller A, Carmeliet P, De Bock K. Role of the GLUT1 Glucose Transporter in Postnatal CNS Angiogenesis and Blood-Brain Barrier Integrity. Circ Res 2020; 127:466-482. [PMID: 32404031 PMCID: PMC7386868 DOI: 10.1161/circresaha.119.316463] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Supplemental Digital Content is available in the text. Rationale: Endothelial cells (ECs) are highly glycolytic and generate the majority of their energy via the breakdown of glucose to lactate. At the same time, a main role of ECs is to allow the transport of glucose to the surrounding tissues. GLUT1 (glucose transporter isoform 1/Slc2a1) is highly expressed in ECs of the central nervous system (CNS) and is often implicated in blood-brain barrier (BBB) dysfunction, but whether and how GLUT1 controls EC metabolism and function is poorly understood. Objective: We evaluated the role of GLUT1 in endothelial metabolism and function during postnatal CNS development as well as at the adult BBB. Methods and Results: Inhibition of GLUT1 decreases EC glucose uptake and glycolysis, leading to energy depletion and the activation of the cellular energy sensor AMPK (AMP-activated protein kinase), and decreases EC proliferation without affecting migration. Deletion of GLUT1 from the developing postnatal retinal endothelium reduces retinal EC proliferation and lowers vascular outgrowth, without affecting the number of tip cells. In contrast, in the brain, we observed a lower number of tip cells in addition to reduced brain EC proliferation, indicating that within the CNS, organotypic differences in EC metabolism exist. Interestingly, when ECs become quiescent, endothelial glycolysis is repressed, and GLUT1 expression increases in a Notch-dependent fashion. GLUT1 deletion from quiescent adult ECs leads to severe seizures, accompanied by neuronal loss and CNS inflammation. Strikingly, this does not coincide with BBB leakiness, altered expression of genes crucial for BBB barrier functioning nor reduced vascular function. Instead, we found a selective activation of inflammatory and extracellular matrix related gene sets. Conclusions: GLUT1 is the main glucose transporter in ECs and becomes uncoupled from glycolysis during quiescence in a Notch-dependent manner. It is crucial for developmental CNS angiogenesis and adult CNS homeostasis but does not affect BBB barrier function.
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Affiliation(s)
- Koen Veys
- From the Laboratory of Angiogenesis and Vascular Metabolism, Department of Oncology (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), KU Leuven.,Laboratory of Angiogenesis and Vascular Metabolism (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), Center for Cancer Biology, VIB, Leuven
| | - Zheng Fan
- Laboratory of Exercise and Health, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETHZ) Zurich (Z.F., M.G., T.G., P.G., R.A., K.D.B.)
| | - Moheb Ghobrial
- Laboratory of Exercise and Health, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETHZ) Zurich (Z.F., M.G., T.G., P.G., R.A., K.D.B.).,Group of CNS Angiogenesis and Neurovascular Link, Neuroscience Center Zurich, University of Zurich (UZH) and ETHZ and Division of Neurosurgery, USZ, Zurich (M.G., T.W.)
| | - Ann Bouché
- From the Laboratory of Angiogenesis and Vascular Metabolism, Department of Oncology (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), KU Leuven.,Laboratory of Angiogenesis and Vascular Metabolism (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), Center for Cancer Biology, VIB, Leuven
| | - Melissa García-Caballero
- From the Laboratory of Angiogenesis and Vascular Metabolism, Department of Oncology (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), KU Leuven.,Laboratory of Angiogenesis and Vascular Metabolism (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), Center for Cancer Biology, VIB, Leuven
| | - Kim Vriens
- Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology (K. Vriens, S.-M.F.), KU Leuven.,Laboratory of Cellular Metabolism and Metabolic Regulation (K. Vriens, S.-M.F.), Center for Cancer Biology, VIB, Leuven
| | - Nadine Vasconcelos Conchinha
- From the Laboratory of Angiogenesis and Vascular Metabolism, Department of Oncology (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), KU Leuven.,Laboratory of Angiogenesis and Vascular Metabolism (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), Center for Cancer Biology, VIB, Leuven
| | - Aline Seuwen
- Institute for Biomedical Engineering (A. Seuwen, F.S., A. Schroeter), UZH/ETHZ, Zurich, Switzerland.,Institute of Pharmacology and Toxicology, UZH, Zurich, Switzerland (A. Seuwen, F.S., A. Schroeter)
| | - Felix Schlegel
- Institute for Biomedical Engineering (A. Seuwen, F.S., A. Schroeter), UZH/ETHZ, Zurich, Switzerland.,Institute of Pharmacology and Toxicology, UZH, Zurich, Switzerland (A. Seuwen, F.S., A. Schroeter)
| | - Tatiane Gorski
- Laboratory of Exercise and Health, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETHZ) Zurich (Z.F., M.G., T.G., P.G., R.A., K.D.B.)
| | - Melissa Crabbé
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, University Hospitals Leuven, Belgium (M.C., C.C., K.V.L.).,Molecular Small Animal Imaging Centre, KU Leuven (M.C., C.C., K.V.L.)
| | - Paola Gilardoni
- Laboratory of Exercise and Health, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETHZ) Zurich (Z.F., M.G., T.G., P.G., R.A., K.D.B.)
| | - Raphaela Ardicoglu
- Laboratory of Exercise and Health, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETHZ) Zurich (Z.F., M.G., T.G., P.G., R.A., K.D.B.)
| | - Johanna Schaffenrath
- Neuroscience Center Zurich (J.S., A.K.), UZH/ETHZ, Zurich, Switzerland.,Department of Neurosurgery, Clinical Neurocentre, USZ, Zurich (J.S., A.K.)
| | - Cindy Casteels
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, University Hospitals Leuven, Belgium (M.C., C.C., K.V.L.).,Molecular Small Animal Imaging Centre, KU Leuven (M.C., C.C., K.V.L.)
| | - Gino De Smet
- Department of Pharmaceutical Chemistry, Drug Analysis and Drug Information, Center for Neurosciences, Vrije Universiteit Brussel (G.D.S., I.S.)
| | - Ilse Smolders
- Department of Pharmaceutical Chemistry, Drug Analysis and Drug Information, Center for Neurosciences, Vrije Universiteit Brussel (G.D.S., I.S.)
| | - Koen Van Laere
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, University Hospitals Leuven, Belgium (M.C., C.C., K.V.L.).,Molecular Small Animal Imaging Centre, KU Leuven (M.C., C.C., K.V.L.)
| | - E Dale Abel
- Laboratory of Exercise and Health, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETHZ) Zurich (Z.F., M.G., T.G., P.G., R.A., K.D.B.).,Fraternal Order of Eagles Diabetes Research Center (E.D.A.), University of Iowa.,Division of Endocrinology and Metabolism, Carver College of Medicine (E.D.A.), University of Iowa
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology (K. Vriens, S.-M.F.), KU Leuven.,Laboratory of Cellular Metabolism and Metabolic Regulation (K. Vriens, S.-M.F.), Center for Cancer Biology, VIB, Leuven
| | - Aileen Schroeter
- Institute for Biomedical Engineering (A. Seuwen, F.S., A. Schroeter), UZH/ETHZ, Zurich, Switzerland.,Institute of Pharmacology and Toxicology, UZH, Zurich, Switzerland (A. Seuwen, F.S., A. Schroeter)
| | - Joanna Kalucka
- From the Laboratory of Angiogenesis and Vascular Metabolism, Department of Oncology (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), KU Leuven.,Laboratory of Angiogenesis and Vascular Metabolism (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), Center for Cancer Biology, VIB, Leuven.,Aarhus Institute of advanced studies (AIAS) and Department of Biomedicine, Aarhus University (J.K.)
| | - Anna Rita Cantelmo
- From the Laboratory of Angiogenesis and Vascular Metabolism, Department of Oncology (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), KU Leuven.,Laboratory of Angiogenesis and Vascular Metabolism (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), Center for Cancer Biology, VIB, Leuven.,Université de Lille, INSERM U1003, Physiologie Cellulaire, France (A.R.C.)
| | - Thomas Wälchli
- Group of CNS Angiogenesis and Neurovascular Link, Neuroscience Center Zurich, University of Zurich (UZH) and ETHZ and Division of Neurosurgery, USZ, Zurich (M.G., T.W.).,Group of Brain Vasculature and Neurovascular Unit, Department of Clinical Neurosciences, University Hospital Geneva (T.W.).,Department of Fundamental Neurobiology, Krembil Research Institute (T.W.), Toronto Western Hospital, University Health Network, University of Toronto.,Division of Neurosurgery, Department of Surgery (T.W.), Toronto Western Hospital, University Health Network, University of Toronto
| | - Annika Keller
- Neuroscience Center Zurich (J.S., A.K.), UZH/ETHZ, Zurich, Switzerland.,Department of Neurosurgery, Clinical Neurocentre, USZ, Zurich (J.S., A.K.)
| | - Peter Carmeliet
- From the Laboratory of Angiogenesis and Vascular Metabolism, Department of Oncology (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), KU Leuven.,Laboratory of Angiogenesis and Vascular Metabolism (K. Veys, A.B., M.G.-C., N.V.C., J.K., A.R.C., P.C.), Center for Cancer Biology, VIB, Leuven
| | - Katrien De Bock
- Laboratory of Exercise and Health, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETHZ) Zurich (Z.F., M.G., T.G., P.G., R.A., K.D.B.)
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8
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Wahl AS, Erlebach E, Brattoli B, Büchler U, Kaiser J, Ineichen BV, Mosberger AC, Schneeberger S, Imobersteg S, Wieckhorst M, Stirn M, Schroeter A, Ommer B, Schwab ME. Early reduced behavioral activity induced by large strokes affects the efficiency of enriched environment in rats. J Cereb Blood Flow Metab 2019; 39:2022-2034. [PMID: 29768943 PMCID: PMC6775586 DOI: 10.1177/0271678x18777661] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The majority of stroke patients develop post-stroke fatigue, a symptom which impairs motivation and diminishes the success of rehabilitative interventions. We show that large cortical strokes acutely reduce activity levels in rats for 1-2 weeks as a physiological response paralleled by signs of systemic inflammation. Rats were exposed early (1-2 weeks) or late (3-4 weeks after stroke) to an individually monitored enriched environment to stimulate self-controlled high-intensity sensorimotor training. A group of animals received Anti-Nogo antibodies for the first two weeks after stroke, a neuronal growth promoting immunotherapy already in clinical trials. Early exposure to the enriched environment resulted in poor outcome: Training intensity was correlated to enhanced systemic inflammation and functional impairment. In contrast, animals starting intense sensorimotor training two weeks after stroke preceded by the immunotherapy revealed better recovery with functional outcome positively correlated to the training intensity and the extent of re-innervation of the stroke denervated cervical hemi-cord. Our results suggest stroke-induced fatigue as a biological purposeful reaction of the organism during neuronal remodeling, enabling new circuit formation which will then be stabilized or pruned in the subsequent rehabilitative training phase. However, intense training too early may lead to wrong connections and is thus less effective.
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Affiliation(s)
- Anna-Sophia Wahl
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.,Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Eva Erlebach
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Biagio Brattoli
- Computer Vision Group, Interdisciplinary Center for Scientific Computing (IWR), University of Heidelberg, Heidelberg, Germany
| | - Uta Büchler
- Computer Vision Group, Interdisciplinary Center for Scientific Computing (IWR), University of Heidelberg, Heidelberg, Germany
| | - Julia Kaiser
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Benjamin V Ineichen
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Alice C Mosberger
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Shirin Schneeberger
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Stefan Imobersteg
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Martin Wieckhorst
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Martina Stirn
- Clinical Laboratory, University of Zurich, Zurich, Switzerland
| | - Aileen Schroeter
- Institute for Biomedical Imaging, ETH Zurich, Zurich, Switzerland
| | - Bjoern Ommer
- Computer Vision Group, Interdisciplinary Center for Scientific Computing (IWR), University of Heidelberg, Heidelberg, Germany
| | - Martin E Schwab
- Brain Research Institute, University of Zurich, Zurich, Switzerland.,Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
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9
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Georgiadis M, Schroeter A, Gao Z, Guizar-Sicairos M, Novikov DS, Fieremans E, Rudin M. Retrieving neuronal orientations using 3D scanning SAXS and comparison with diffusion MRI. Neuroimage 2019; 204:116214. [PMID: 31568873 DOI: 10.1016/j.neuroimage.2019.116214] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2019] [Revised: 09/06/2019] [Accepted: 09/18/2019] [Indexed: 01/08/2023] Open
Abstract
While diffusion MRI (dMRI) is currently the method of choice to non-invasively probe tissue microstructure and study structural connectivity in the brain, its spatial resolution is limited and its results need structural validation. Current ex vivo methods employed to provide 3D fiber orientations have limitations, including tissue-distorting sample preparation, small field of view or inability to quantify 3D fiber orientation distributions. 3D fiber orientation in tissue sections can be obtained from 3D scanning small-angle X-ray scattering (3D sSAXS) by analyzing the anisotropy of scattering signals. Here we adapt the 3D sSAXS method for use in brain tissue, exploiting the high sensitivity of the SAXS signal to the ordered molecular structure of myelin. We extend the characterization of anisotropy from vectors to tensors, employ the Funk-Radon-Transform for converting scattering information to real space fiber orientations, and demonstrate the feasibility of the method in thin sections of mouse brain with minimal sample preparation. We obtain a second rank tensor representing the fiber orientation distribution function (fODF) for every voxel, thereby generating fODF maps. Finally, we illustrate the potential of 3D sSAXS by comparing the result with diffusion MRI fiber orientations in the same mouse brain. We show a remarkably good correspondence, considering the orthogonality of the two methods, i.e. the different physical processes underlying the two signals. 3D sSAXS can serve as validation method for microstructural MRI, and can provide novel microstructural insights for the nervous system, given the method's orthogonality to dMRI, high sensitivity to myelin sheath's orientation and abundance, and the possibility to extract myelin-specific signal and to perform micrometer-resolution scanning.
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Affiliation(s)
- Marios Georgiadis
- Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland; Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, USA; Department of Radiology, Stanford Medicine, USA.
| | - Aileen Schroeter
- Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland
| | - Zirui Gao
- Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland; Paul Scherrer Institute, Villigen, Switzerland
| | | | - Dmitry S Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, USA
| | - Markus Rudin
- Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland; Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
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10
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Zerbi V, Markicevic M, Gasparini F, Schroeter A, Rudin M, Wenderoth N. Inhibiting mGluR5 activity by AFQ056/Mavoglurant rescues circuit-specific functional connectivity in Fmr1 knockout mice. Neuroimage 2019; 191:392-402. [DOI: 10.1016/j.neuroimage.2019.02.051] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 02/11/2019] [Accepted: 02/19/2019] [Indexed: 12/12/2022] Open
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11
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Bukhari Q, Schroeter A, Rudin M. Increasing isoflurane dose reduces homotopic correlation and functional segregation of brain networks in mice as revealed by resting-state fMRI. Sci Rep 2018; 8:10591. [PMID: 30002419 PMCID: PMC6043584 DOI: 10.1038/s41598-018-28766-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Accepted: 06/26/2018] [Indexed: 11/23/2022] Open
Abstract
Effects of anesthetics on brain functional networks are not fully understood. In this work, we investigated functional brain networks derived from resting-state fMRI data obtained under different doses of isoflurane in mice using stationary and dynamic functional connectivity (dFC) analysis. Stationary network analysis using FSL Nets revealed a modular structure of functional networks, which could be segregated into a lateral cortical, an associative cortical network, elements of the prefrontal network, a subcortical network, and a thalamic network. Increasing isoflurane dose led to a loss of functional connectivity between the bilateral cortical regions. In addition, dFC analysis revealed a dominance of dynamic functional states (dFS) exhibiting modular structure in mice anesthetized with a low dose of isoflurane, while at high isoflurane levels dFS showing widespread unstructured correlation displayed highest weights. This indicates that spatial segregation across brain functional networks is lost with increasing dose of the anesthetic drug used. To what extent this indicates a state of deep anesthesia remains to be shown. Combining the results of stationary and dynamic FC analysis indicates that increasing isoflurane levels leads to loss of modular network organization, which includes loss of the strong bilateral interactions between homotopic brain areas.
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Affiliation(s)
- Q Bukhari
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - A Schroeter
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - M Rudin
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland. .,Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
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12
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Schlegel F, Sych Y, Schroeter A, Stobart J, Weber B, Helmchen F, Rudin M. Fiber-optic implant for simultaneous fluorescence-based calcium recordings and BOLD fMRI in mice. Nat Protoc 2018; 13:840-855. [PMID: 29599439 DOI: 10.1038/nprot.2018.003] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Despite the growing popularity of blood oxygen level-dependent (BOLD) functional MRI (fMRI), understanding of its underlying principles is still limited. This protocol describes a technique for simultaneous measurement of neural activity using fluorescent calcium indicators together with the corresponding hemodynamic BOLD fMRI response in the mouse brain. Our early work using small-molecule fluorophores in rats gave encouraging results but was limited to acute measurements using synthetic dyes. Our latest procedure combines fMRI with optical detection of cell-type-specific virally delivered GCaMP6, a genetically encoded calcium indicator (GECI). GCaMP6 fluorescence, which increases upon calcium binding, is collected by a chronically implanted optical fiber, allowing longitudinal studies in mice. The chronic implant, placed horizontally on the skull, has an angulated tip that reflects light into the brain and is connected via fiber optics to a remote optical setup. The technique allows access to the neocortex and does not require adaptations of commercial MRI hardware. The hybrid approach permits fiber-optic calcium recordings with simultaneous artifact-free BOLD fMRI with full brain coverage and 1-s temporal resolution using standard gradient-echo echo-planar imaging (GE-EPI) sequences. The method provides robust, cell-type-specific readouts to link neural activity to BOLD signals, as emonstrated for task-free ('resting-state') conditions and in response to hind-paw stimulation. These results highlight the power of fiber photometry combined with fMRI, which we aim to further advance in this protocol. The approach can be easily adapted to study other molecular processes using suitable fluorescent indicators.
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Affiliation(s)
- Felix Schlegel
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.,Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Yaroslav Sych
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zurich, Switzerland
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Jillian Stobart
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.,Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Bruno Weber
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.,Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Fritjof Helmchen
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.,Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zurich, Switzerland
| | - Markus Rudin
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.,Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.,Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
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13
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Schroeter A, Grandjean J, Schlegel F, Saab BJ, Rudin M. Contributions of structural connectivity and cerebrovascular parameters to functional magnetic resonance imaging signals in mice at rest and during sensory paw stimulation. J Cereb Blood Flow Metab 2017; 37:2368-2382. [PMID: 27596833 PMCID: PMC5531337 DOI: 10.1177/0271678x16666292] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Previously, we reported widespread bilateral increases in stimulus-evoked functional magnetic resonance imaging signals in mouse brain to unilateral sensory paw stimulation. We attributed the pattern to arousal-related cardiovascular changes overruling cerebral autoregulation thereby masking specific signal changes elicited by local neuronal activity. To rule out the possibility that interhemispheric neuronal communication might contribute to bilateral functional magnetic resonance imaging responses, we compared stimulus-evoked functional magnetic resonance imaging responses to unilateral hindpaw stimulation in acallosal I/LnJ, C57BL/6, and BALB/c mice. We found bilateral blood-oxygenation-level dependent signal changes in all three strains, ruling out a dominant contribution of transcallosal communication as reason for bilaterality. Analysis of functional connectivity derived from resting-state functional magnetic resonance imaging, revealed that bilateral cortical functional connectivity is largely abolished in I/LnJ animals. Cortical functional connectivity in all strains correlated with structural connectivity in corpus callosum as revealed by diffusion tensor imaging. Given the profound influence of systemic hemodynamics on stimulus-evoked functional magnetic resonance imaging outcomes, we evaluated whether functional connectivity data might be affected by cerebrovascular parameters, i.e. baseline cerebral blood volume, vascular reactivity, and reserve. We found that effects of cerebral hemodynamics on functional connectivity are largely outweighed by dominating contributions of structural connectivity. In contrast, contributions of transcallosal interhemispheric communication to the occurrence of ipsilateral functional magnetic resonance imaging response of equal amplitude to unilateral stimuli seem negligible.
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Affiliation(s)
- Aileen Schroeter
- 1 Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,2 Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland
| | - Joanes Grandjean
- 1 Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,2 Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland
| | - Felix Schlegel
- 1 Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,2 Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland
| | - Bechara J Saab
- 2 Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland.,3 Preclinical Laboratory for Translational Research into Affective Disorders, University of Zurich Hospital for Psychiatry, Zurich, Switzerland
| | - Markus Rudin
- 1 Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,2 Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland.,4 Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
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Bukhari Q, Schroeter A, Cole DM, Rudin M. Resting State fMRI in Mice Reveals Anesthesia Specific Signatures of Brain Functional Networks and Their Interactions. Front Neural Circuits 2017; 11:5. [PMID: 28217085 PMCID: PMC5289996 DOI: 10.3389/fncir.2017.00005] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Accepted: 01/16/2017] [Indexed: 01/29/2023] Open
Abstract
fMRI studies in mice typically require the use of anesthetics. Yet, it is known that anesthesia alters responses to stimuli or functional networks at rest. In this work, we have used Dual Regression analysis Network Modeling to investigate the effects of two commonly used anesthetics, isoflurane and medetomidine, on rs-fMRI derived functional networks, and in particular to what extent anesthesia affected the interaction within and between these networks. Experimental data have been used from a previous study (Grandjean et al., 2014). We applied multivariate ICA analysis and Dual Regression to infer the differences in functional connectivity between isoflurane- and medetomidine-anesthetized mice. Further network analysis was performed to investigate within- and between-network connectivity differences between these anesthetic regimens. The results revealed five major networks in the mouse brain: lateral cortical, associative cortical, default mode, subcortical, and thalamic network. The anesthesia regime had a profound effect both on within- and between-network interactions. Under isoflurane anesthesia predominantly intra- and inter-cortical interactions have been observed, with only minor interactions involving subcortical structures and in particular attenuated cortico-thalamic connectivity. In contrast, medetomidine-anesthetized mice displayed subcortical functional connectivity including interactions between cortical and thalamic ICA components. Combining the two anesthetics at low dose resulted in network interaction that constituted the superposition of the interaction observed for each anesthetic alone. The study demonstrated that network modeling is a promising tool for analyzing the brain functional architecture in mice and comparing alterations therein caused by different physiological or pathological states. Understanding the differential effects of anesthetics on brain networks and their interaction is essential when interpreting fMRI data recorded under specific physiological and pathological conditions.
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Affiliation(s)
- Qasim Bukhari
- Institute of Biomedical Engineering, University of Zurich and ETH Zurich Zurich, Switzerland
| | - Aileen Schroeter
- Institute of Biomedical Engineering, University of Zurich and ETH Zurich Zurich, Switzerland
| | - David M Cole
- Institute of Biomedical Engineering, University of Zurich and ETH ZurichZurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of PsychiatryZurich, Switzerland
| | - Markus Rudin
- Institute of Biomedical Engineering, University of Zurich and ETH ZurichZurich, Switzerland; Institute of Pharmacology and Toxicology, University of ZurichZurich, Switzerland
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Sahlholm K, Ielacqua GD, Xu J, Jones LA, Schlegel F, Mach RH, Rudin M, Schroeter A. The role of beta-arrestin2 in shaping fMRI BOLD responses to dopaminergic stimulation. Psychopharmacology (Berl) 2017; 234:2019-2030. [PMID: 28382543 PMCID: PMC5486931 DOI: 10.1007/s00213-017-4609-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Accepted: 03/18/2017] [Indexed: 01/11/2023]
Abstract
RATIONALE The dopamine D2 receptor (D2R) couples to inhibitory Gi/o proteins and is targeted by antipsychotic and antiparkinsonian drugs. Beta-arrestin2 binds to the intracellular regions of the agonist-occupied D2R to terminate G protein activation and promote internalization, but also to initiate downstream signaling cascades which have been implicated in psychosis. Functional magnetic resonance imaging (fMRI) has proven valuable for measuring dopamine receptor-mediated changes in neuronal activity, and might enable beta-arrestin2 function to be studied in vivo. OBJECTIVES The present study examined fMRI blood oxygenation level dependent (BOLD) signal changes elicited by a dopamine agonist in wild-type (WT) and beta-arrestin2 knockout (KO) mice, to investigate whether genetic deletion of beta-arrestin2 prolongs or otherwise modifies D2R-dependent responses. METHODS fMRI BOLD data were acquired on a 9.4 T system. During scans, animals received 0.2 mg/kg apomorphine, i.v. In a subset of experiments, animals were pretreated with 2 mg/kg of the D2R antagonist, eticlopride. RESULTS Following apomorphine administration, BOLD signal decreases were observed in caudate/putamen of WT and KO animals. The time course of response decay in caudate/putamen was significantly slower in KO vs. WT animals. In cingulate cortex, an initial BOLD signal decrease was followed by a positive response component in WT but not in KO animals. Eticlopride pretreatment significantly reduced apomorphine-induced BOLD signal changes. CONCLUSIONS The prolonged striatal response decay rates in KO animals might reflect impaired D2R desensitization, consistent with the known function of beta-arrestin2. Furthermore, the apomorphine-induced positive response component in cingulate cortex may depend on beta-arrestin2 signaling downstream of D2R.
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Affiliation(s)
- Kristoffer Sahlholm
- Institute for Biomedical Engineering, University and ETH Zurich, Wolfgang-Pauli-Str. 27, 8093, Zurich, Switzerland. .,Department of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, St. Louis, MO, 63110, USA. .,Department of Neuroscience, Karolinska Institutet, Retzius väg 8, SE-171 77, Stockholm, Sweden.
| | - Giovanna D. Ielacqua
- 0000 0001 2156 2780grid.5801.cInstitute for Biomedical Engineering, University and ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland
| | - Jinbin Xu
- 0000 0001 2355 7002grid.4367.6Department of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, St. Louis, MO 63110 USA
| | - Lynne A. Jones
- 0000 0001 2355 7002grid.4367.6Department of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, St. Louis, MO 63110 USA
| | - Felix Schlegel
- 0000 0001 2156 2780grid.5801.cInstitute for Biomedical Engineering, University and ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland
| | - Robert H. Mach
- 0000 0004 1936 8972grid.25879.31Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 231 S. 34th St, Philadelphia, PA 19104 USA
| | - Markus Rudin
- 0000 0001 2156 2780grid.5801.cInstitute for Biomedical Engineering, University and ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland ,0000 0001 2156 2780grid.5801.cNeuroscience Center Zurich, University and ETH Zurich, Winterthurer-Str. 190, 8057 Zurich, Switzerland ,0000 0004 1937 0650grid.7400.3Institute of Pharmacology and Toxicology, University of Zurich, Winterthurer-Str. 190, 8057 Zurich, Switzerland
| | - Aileen Schroeter
- 0000 0001 2156 2780grid.5801.cInstitute for Biomedical Engineering, University and ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland ,0000 0001 2156 2780grid.5801.cNeuroscience Center Zurich, University and ETH Zurich, Winterthurer-Str. 190, 8057 Zurich, Switzerland
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16
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Mueller J, Oliveira J, Barker R, Trapp M, Schroeter A, Brezesinski G, Neubert R. The effect of urea and taurine as hydrophilic penetration enhancers on stratum corneum lipid models. Biochimica et Biophysica Acta (BBA) - Biomembranes 2016; 1858:2006-2018. [DOI: 10.1016/j.bbamem.2016.05.010] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Revised: 05/08/2016] [Accepted: 05/13/2016] [Indexed: 10/21/2022]
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17
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Seuwen A, Schroeter A, Grandjean J, Rudin M. Metabolic changes assessed by MRS accurately reflect brain function during drug-induced epilepsy in mice in contrast to fMRI-based hemodynamic readouts. Neuroimage 2015; 120:55-63. [DOI: 10.1016/j.neuroimage.2015.07.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2015] [Revised: 05/29/2015] [Accepted: 07/02/2015] [Indexed: 12/21/2022] Open
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18
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Grandjean J, Schroeter A, Batata I, Rudin M. Optimization of anesthesia protocol for resting-state fMRI in mice based on differential effects of anesthetics on functional connectivity patterns. Neuroimage 2014; 102 Pt 2:838-47. [PMID: 25175535 DOI: 10.1016/j.neuroimage.2014.08.043] [Citation(s) in RCA: 203] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2014] [Revised: 08/13/2014] [Accepted: 08/21/2014] [Indexed: 10/24/2022] Open
Abstract
Resting state-fMRI (rs-fMRI) in mice allows studying mechanisms underlying functional connectivity (FC) as well as alterations of FC occurring in murine models of neurological diseases. Mouse fMRI experiments are typically carried out under anesthesia to minimize animal movement and potential distress during examination. Yet, anesthesia inevitably affects FC patterns. Such effects have to be understood for proper interpretation of data. We have compared the influence of four commonly used anesthetics on rs-fMRI. Rs-fMRI data acquired under isoflurane, propofol, and urethane presented similar patterns when accounting for anesthesia depth. FC maps displayed bilateral correlation with respect to cortical seeds, but no significant inter-hemispheric striatal connectivity. In contrast, for medetomidine, we detected bilateral striatal but compromised inter-hemispheric cortical connectivity. The spatiotemporal patterns of the rs-fMRI signal have been rationalized considering anesthesia depth and pharmacodynamic properties of the anesthetics. Our results bridge the results from different studies from the burgeoning field of mouse rs-fMRI and offer a framework for understanding the influences of anesthetics on FC patterns. Utilizing this information, we suggest the combined use of medetomidine and isoflurane representing the two proposed classes of anesthetics; the combination of low doses of the two anesthetics retained strong correlations both within cortical and subcortical structures, without the potential seizure-inducing effects of medetomidine, rendering this regimen an attractive anesthesia for rs-fMRI in mice.
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Affiliation(s)
- Joanes Grandjean
- Institute for Biomedical Engineering, University and ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland; Neuroscience Center Zurich, University and ETH Zurich, Winterthurer-Str. 190, 8057 Zurich, Switzerland
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland; Neuroscience Center Zurich, University and ETH Zurich, Winterthurer-Str. 190, 8057 Zurich, Switzerland
| | - Imene Batata
- Institute for Biomedical Engineering, University and ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland
| | - Markus Rudin
- Institute for Biomedical Engineering, University and ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland; Neuroscience Center Zurich, University and ETH Zurich, Winterthurer-Str. 190, 8057 Zurich, Switzerland; Institute of Pharmacology and Toxicology, University of Zurich, Winterthurer-Str. 190, 8057 Zurich, Switzerland.
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19
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Azoitei ML, Ban YA, Kalyuzhny O, Guenaga J, Schroeter A, Porter J, Wyatt R, Schief WR. Computational design of protein antigens that interact with the CDR H3 loop of HIV broadly neutralizing antibody 2F5. Proteins 2014; 82:2770-82. [PMID: 25043744 DOI: 10.1002/prot.24641] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2014] [Revised: 06/07/2014] [Accepted: 06/18/2014] [Indexed: 11/06/2022]
Abstract
Rational design of proteins with novel binding specificities and increased affinity is one of the major goals of computational protein design. Epitope-scaffolds are a new class of antigens engineered by transplanting viral epitopes of predefined structure to protein scaffolds, or by building protein scaffolds around such epitopes. Epitope-scaffolds are of interest as vaccine components to attempt to elicit neutralizing antibodies targeting the specified epitope. In this study we developed a new computational protocol, MultiGraft Interface, that transplants epitopes but also designs additional scaffold features outside the epitope to enhance antibody-binding specificity and potentially influence the specificity of elicited antibodies. We employed MultiGraft Interface to engineer novel epitope-scaffolds that display the known epitope of human immunodeficiency virus 1 (HIV-1) neutralizing antibody 2F5 and that also interact with the functionally important CDR H3 antibody loop. MultiGraft Interface generated an epitope-scaffold that bound 2F5 with subnanomolar affinity (K(D) = 400 pM) and that interacted with the antibody CDR H3 loop through computationally designed contacts. Substantial structural modifications were necessary to engineer this antigen, with the 2F5 epitope replacing a helix in the native scaffold and with 15% of the native scaffold sequence being modified in the design stage. This epitope-scaffold represents a successful example of rational protein backbone engineering and protein-protein interface design and could prove useful in the field of HIV vaccine design. MultiGraft Interface can be generally applied to engineer novel binding partners with altered specificity and optimized affinity.
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Affiliation(s)
- M L Azoitei
- Department of Biochemistry, University of Washington, Seattle, Washington, 98195
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20
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Mach H, Hecker M, Hill I, Schroeter A, Mach F. Physiologische Bedeutung der „Stringent Control“ bei Escherichia coli unter extremen Hungerbedingungen / Stringent Control and Starvation Survival in Escherichia coli. ACTA ACUST UNITED AC 2014. [DOI: 10.1515/znc-1989-9-1024] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The viability of three isogenic relA+/relA strain pairs of Escherichia coli (CP78/CP79; NF 161/ NF162; CP 107/CP 143) was studied during prolonged starvation for amino acids, glucose or phosphate. After amino acid limitation we found a prolonged viability of all relA+ strains which synthesized ppGpp. We suggest that some ppGpp-mediated pleiotropic effects of the stringent response (e.g. glykogen accumulation, enhanced protein turnover) might be involved in this prolongation of survival. After glucose or phosphate starvation there was no difference in the relA+/relA strains either in the ppGpp content or in the survival.
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Affiliation(s)
- H. Mach
- Sektion Biologie der Ernst-Moritz-Arndt-Universität, L.-Jahn-Straße 15, D D R -2200 Greifswald, Deutsche Demokratische Republik
| | - M. Hecker
- Sektion Biologie der Ernst-Moritz-Arndt-Universität, L.-Jahn-Straße 15, D D R -2200 Greifswald, Deutsche Demokratische Republik
| | - I. Hill
- Sektion Biologie der Ernst-Moritz-Arndt-Universität, L.-Jahn-Straße 15, D D R -2200 Greifswald, Deutsche Demokratische Republik
| | - A. Schroeter
- Sektion Biologie der Ernst-Moritz-Arndt-Universität, L.-Jahn-Straße 15, D D R -2200 Greifswald, Deutsche Demokratische Republik
| | - F. Mach
- Sektion Biologie der Ernst-Moritz-Arndt-Universität, L.-Jahn-Straße 15, D D R -2200 Greifswald, Deutsche Demokratische Republik
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21
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Tenhagen BA, Vossenkuhl B, Käsbohrer A, Alt K, Kraushaar B, Guerra B, Schroeter A, Fetsch A. Methicillin-resistant Staphylococcus aureus in cattle food chains - prevalence, diversity, and antimicrobial resistance in Germany. J Anim Sci 2014; 92:2741-51. [PMID: 24778337 DOI: 10.2527/jas.2014-7665] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Livestock-associated methicillin-resistant Staphylococcus aureus (MRSA) have been found in various farm animal species throughout the world. It was the objective of this study to estimate the prevalence of MRSA in different cattle food chains (milk, beef, and veal) in Germany, to analyze the MRSA diversity along each food chain and to compare the characteristics of the different subtypes. Samples were collected between 2009 and 2012 from dairy herds (bulk tank milk), veal herds (dust from the stables), veal calves, and beef cattle at slaughter (nasal swabs) and carcasses of veal calves (surface cuts) and beef as well as veal at retail. Sampling was proportionally distributed over the country according to the cattle population (on-farm sampling), slaughterhouse capacity (abattoir samples), and the human population (meat at retail). Methicillin-resistant S. aureus were isolated using harmonized methods from all sample types and populations investigated. The highest proportion of positive samples was found in nasal swabs from veal calves at slaughter in 2012 (144/320; 45.0%) and the lowest rate in bulk tank milk in 2009 (14/388; 4.1%). Most isolates, irrespective of the origin, were from spa types t011 and t034. Both have been assigned to the clonal complex (CC) 398. Few isolates (15/632; 2.4%) were from spa types not associated with the CC398. Spa-type patterns were similar along individual food chains but differed between food chains. Antimicrobial resistance patterns differed between isolates from the different food chains and spa types. Isolates from the veal chain displayed the highest resistance rates. We conclude that there is substantial diversity in the MRSA prevalence across different cattle production sectors.
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Affiliation(s)
- B-A Tenhagen
- Federal Institute for Risk Assessment (BfR), Department Biological Safety, 10589 Berlin, Germany Robert Koch Institute, Berlin, Germany
| | - B Vossenkuhl
- Federal Institute for Risk Assessment (BfR), Department Biological Safety, 10589 Berlin, Germany Robert Koch Institute, Berlin, Germany
| | - A Käsbohrer
- Federal Institute for Risk Assessment (BfR), Department Biological Safety, 10589 Berlin, Germany Robert Koch Institute, Berlin, Germany
| | - K Alt
- Robert Koch Institute, Berlin, Germany
| | - B Kraushaar
- Federal Institute for Risk Assessment (BfR), Department Biological Safety, 10589 Berlin, Germany Robert Koch Institute, Berlin, Germany
| | - B Guerra
- Federal Institute for Risk Assessment (BfR), Department Biological Safety, 10589 Berlin, Germany Robert Koch Institute, Berlin, Germany
| | - A Schroeter
- Federal Institute for Risk Assessment (BfR), Department Biological Safety, 10589 Berlin, Germany Robert Koch Institute, Berlin, Germany
| | - A Fetsch
- Federal Institute for Risk Assessment (BfR), Department Biological Safety, 10589 Berlin, Germany Robert Koch Institute, Berlin, Germany
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22
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Kempf A, Montani L, Petrinovic MM, Schroeter A, Weinmann O, Patrignani A, Schwab ME. Upregulation of axon guidance molecules in the adult central nervous system of Nogo-A knockout mice restricts neuronal growth and regeneration. Eur J Neurosci 2013; 38:3567-79. [DOI: 10.1111/ejn.12357] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2013] [Revised: 08/14/2013] [Accepted: 08/15/2013] [Indexed: 02/02/2023]
Affiliation(s)
- Anissa Kempf
- Department of Health Sciences and Technology; Brain Research Institute; University of Zurich; Swiss Federal Institute of Technology (ETH) Zurich; Winterthurerstrasse 190 CH-8057 Zurich Switzerland
| | - Laura Montani
- Department of Health Sciences and Technology; Brain Research Institute; University of Zurich; Swiss Federal Institute of Technology (ETH) Zurich; Winterthurerstrasse 190 CH-8057 Zurich Switzerland
| | - Marija M. Petrinovic
- Department of Health Sciences and Technology; Brain Research Institute; University of Zurich; Swiss Federal Institute of Technology (ETH) Zurich; Winterthurerstrasse 190 CH-8057 Zurich Switzerland
| | - Aileen Schroeter
- Department of Health Sciences and Technology; Brain Research Institute; University of Zurich; Swiss Federal Institute of Technology (ETH) Zurich; Winterthurerstrasse 190 CH-8057 Zurich Switzerland
| | - Oliver Weinmann
- Department of Health Sciences and Technology; Brain Research Institute; University of Zurich; Swiss Federal Institute of Technology (ETH) Zurich; Winterthurerstrasse 190 CH-8057 Zurich Switzerland
| | - Andrea Patrignani
- Functional Genomics Center; University of Zurich; Winterthurerstrasse 190 CH-8057 Zurich Switzerland
| | - Martin E. Schwab
- Department of Health Sciences and Technology; Brain Research Institute; University of Zurich; Swiss Federal Institute of Technology (ETH) Zurich; Winterthurerstrasse 190 CH-8057 Zurich Switzerland
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23
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Kaesbohrer A, Schroeter A, Tenhagen BA, Alt K, Guerra B, Appel B. Emerging antimicrobial resistance in commensal Escherichia coli with public health relevance. Zoonoses Public Health 2013; 59 Suppl 2:158-65. [PMID: 22958260 DOI: 10.1111/j.1863-2378.2011.01451.x] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
In 2009, 1462 Escherichia coli isolates were collected in a systematic resistance monitoring approach from primary production, slaughterhouses and at retail and evaluated on the basis of epidemiological cut-off values. Besides resistance to antimicrobial classes that have been extensively used for a long time (e.g. sulphonamides and tetracyclines), resistance to (fluoro)quinolones and third-generation cephalosporins was observed. While in the poultry production chain the majority (60%) of isolates from laying hens was susceptible to all antimicrobials tested, most isolates from broilers, chicken meat and turkey meat showed resistance to at least one (85-93%) but frequently even to several antimicrobial classes (73-84%). In the cattle and pig production chain, the share of isolates showing resistance to at least one antimicrobial was lowest (16%) in dairy cows, whereas resistance to at least one antimicrobial ranged between 43% and 73% in veal calves, veal and pork. Resistance rates to ciprofloxacin and nalidixic acid in isolates from broilers were 41.1% and 43.1%, respectively. Likewise, high resistance rates to (fluoro)quinolones were observed in isolates from chicken meat and turkey meat. In contrast, ciprofloxacin resistance was less frequent in E. coli isolates from the cattle and pig production chain with highest rate in veal calves (13.3%). Highest resistance rates to cephalosporins were observed in broilers and chicken meat, with 5.9% and 6.2% of the isolates showing resistance. In dairy cattle and veal, no isolates with cephalosporin resistance were detected, whereas 3.3% of the isolates from veal calves showed resistance to ceftazidime. Resistance to (fluoro)quinolones and cephalosporins in E. coli isolates is of special concern because they are critically important antimicrobials in human antimicrobial therapy. The emergence of this resistance warrants increased monitoring. Together with continuous monitoring of antimicrobial usage, management strategies should be regularly assessed and adapted.
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Affiliation(s)
- A Kaesbohrer
- Federal Institute for Risk Assessment, Department for Biological Safety, National Reference Laboratory for Antimicrobial Resistance, Berlin, Germany.
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24
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Windbergs M, Hansen S, Schroeter A, Schaefer U, Lehr CM, Bouwstra J. From the Structure of the Skin Barrier and Dermal Formulations to in vitro Transport Models for Skin Absorption: Skin Research in the Netherlands and in Germany. Skin Pharmacol Physiol 2013; 26:317-30. [DOI: 10.1159/000351936] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2012] [Accepted: 03/03/2013] [Indexed: 11/19/2022]
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Werner S, Schimek C, Vlaic S, Wöstemeyer J, Schuster S, Schroeter A. Model of the synthesis of trisporic acid in Mucorales showing bistability. IET Syst Biol 2012; 6:207-14. [DOI: 10.1049/iet-syb.2011.0056] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Bosshard SC, Grandjean J, Schroeter A, Baltes C, Zeilhofer HU, Rudin M. Hyperalgesia by low doses of the local anesthetic lidocaine involves cannabinoid signaling: An fMRI study in mice. Pain 2012; 153:1450-1458. [DOI: 10.1016/j.pain.2012.04.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2011] [Revised: 03/29/2012] [Accepted: 04/02/2012] [Indexed: 12/17/2022]
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Stingl K, Knüver MT, Vogt P, Buhler C, Krüger NJ, Alt K, Tenhagen BA, Hartung M, Schroeter A, Ellerbroek L, Appel B, Käsbohrer A. Quo vadis? - Monitoring Campylobacter in Germany. Eur J Microbiol Immunol (Bp) 2012; 2:88-96. [PMID: 24611125 DOI: 10.1556/eujmi.2.2012.1.12] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2012] [Accepted: 01/16/2012] [Indexed: 11/19/2022] Open
Abstract
Campylobacter is a poorly recognized foodborne pathogen, leading the statistics of bacterially caused human diarrhoea in Europe during the last years. In this review, we present qualitative and quantitative German data obtained in the framework of specific monitoring programs and from routine surveillance. These also comprise recent data on antimicrobial resistances of food isolates. Due to the considerable reduction of in vitro growth capabilities of stressed bacteria, there is a clear discrepancy between the detection limit of Campylobacter by cultivation and its infection potential. Moreover, antimicrobial resistances of Campylobacter isolates established during fattening of livestock are alarming, since they constitute an additional threat to human health. The European Food Safety Authority (EFSA) discusses the establishment of a quantitative limit for Campylobacter contamination of broiler carcasses in order to achieve an appropriate level of protection for consumers. Currently, a considerable amount of German broiler carcasses would not comply with this future criterion. We recommend Campylobacter reduction strategies to be focussed on the prevention of fecal contamination during slaughter. Decontamination is only a sparse option, since the reduction efficiency is low and its success depends on the initial contamination concentration.
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Affiliation(s)
- K Stingl
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - M-T Knüver
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - P Vogt
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - C Buhler
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - N-J Krüger
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - K Alt
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - B-A Tenhagen
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - M Hartung
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - A Schroeter
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - L Ellerbroek
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - B Appel
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
| | - A Käsbohrer
- Department of Biological Safety, Federal Institute for Risk Assessment Diedersdorfer Weg 1, 12277 Berlin Germany
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Petrinovic MM, Duncan CS, Bourikas D, Weinman O, Montani L, Schroeter A, Maerki D, Sommer L, Stoeckli ET, Schwab ME. Neuronal Nogo-A regulates neurite fasciculation, branching and extension in the developing nervous system. Development 2010; 137:2539-50. [PMID: 20573699 DOI: 10.1242/dev.048371] [Citation(s) in RCA: 80] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Wiring of the nervous system is a multi-step process involving complex interactions of the growing fibre with its tissue environment and with neighbouring fibres. Nogo-A is a membrane protein enriched in the adult central nervous system (CNS) myelin, where it restricts the capacity of axons to grow and regenerate after injury. During development, Nogo-A is also expressed by neurons but its function in this cell type is poorly known. Here, we show that neutralization of neuronal Nogo-A or Nogo-A gene ablation (KO) leads to longer neurites, increased fasciculation, and decreased branching of cultured dorsal root ganglion neurons. The same effects are seen with antibodies against the Nogo receptor complex components NgR and Lingo1, or by blocking the downstream effector Rho kinase (ROCK). In the chicken embryo, in ovo injection of anti-Nogo-A antibodies leads to aberrant innervation of the hindlimb. Genetic ablation of Nogo-A causes increased fasciculation and reduced branching of peripheral nerves in Nogo-A KO mouse embryos. Thus, Nogo-A is a developmental neurite growth regulatory factor with a role as a negative regulator of axon-axon adhesion and growth, and as a facilitator of neurite branching.
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Affiliation(s)
- Marija M Petrinovic
- Brain Research Institute, University of Zurich and Department of Biology, ETH Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland.
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Argudín MA, Fetsch A, Tenhagen BA, Hammerl JA, Hertwig S, Kowall J, Rodicio MR, Käsbohrer A, Helmuth R, Schroeter A, Mendoza MC, Bräunig J, Appel B, Guerra B. High heterogeneity within methicillin-resistant Staphylococcus aureus ST398 isolates, defined by Cfr9I macrorestriction-pulsed-field gel electrophoresis profiles and spa and SCCmec types. Appl Environ Microbiol 2010; 76:652-8. [PMID: 20023093 PMCID: PMC2813030 DOI: 10.1128/aem.01721-09] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2009] [Accepted: 12/05/2009] [Indexed: 11/20/2022] Open
Abstract
During recent years, the animal-associated methicillin-resistant Staphylococcus aureus clone ST398 has extensively been studied. The DNA of these isolates turned out to be refractory to SmaI restriction, and consequently, SmaI is unsuitable for subtyping this clone by standard pulsed-field gel electrophoresis (PFGE). Very recently, ST398 DNA was shown to be digested by Cfr9I, a neoschizomer of SmaI. In the present study, we employed Cfr9I PFGE on 100 German and 5 Dutch ST398 isolates and compared their PFGE profiles, protein A gene variable repeat regions (spa types), and types of the staphylococcal cassette chromosome mec (SCCmec). The isolates (from healthy carrier pigs, clinical samples from pigs, dust from farms, milk, and meat) were assigned to 35 profiles, which were correlated to the SCCmec type. A dendrogram with the Cfr9I patterns assigned all profiles to two clusters. Cluster A grouped nearly all isolates with SCCmec type V, and cluster B comprised all SCCmec type IVa and V* (a type V variant first identified as III) carriers plus one isolate with SCCmec type V. Both clusters also grouped methicillin-susceptible S. aureus isolates. The association of the majority of isolates with SCCmec type V in one large cluster indicated the presence of a successful subclone within the clonal complex CC398 from pigs, which has diversified. In general, the combination of Cfr9I PFGE with spa and SCCmec typing demonstrated the heterogeneity of the series analyzed and can be further used for outbreak investigations and traceability studies of the MRSA ST398 emerging clone.
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Affiliation(s)
- M. A. Argudín
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - A. Fetsch
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - B.-A. Tenhagen
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - J. A. Hammerl
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - S. Hertwig
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - J. Kowall
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - M. R. Rodicio
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - A. Käsbohrer
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - R. Helmuth
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - A. Schroeter
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - M. C. Mendoza
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - J. Bräunig
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - B. Appel
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
| | - B. Guerra
- Departmento de Biología Funcional (Área de Microbiología) and Instituto Universitario de Biotecnología, University of Oviedo, Julían Clavería 6, E-33006 Oviedo, Spain, Department of Biological Safety, Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany
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Ellerbroek L, Narapati D, Phu Tai N, Poosaran N, Pinthong R, Sirimalaisuwan A, Tshering P, Fries R, Zessin KH, Baumann M, Schroeter A. Antibiotic resistance in Salmonella isolates from imported chicken carcasses in Bhutan and from pig carcasses in Vietnam. J Food Prot 2010; 73:376-9. [PMID: 20132687 DOI: 10.4315/0362-028x-73.2.376] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The antibiotic resistance in Salmonella isolates from 400 imported chicken carcasses in Bhutan and from 178 pig carcasses in Vietnam were analyzed on a random basis against 14 antimicrobial agents. Among the poultry samples tested, 13% were positive for Salmonella. Salmonella Enteritidis dominated with a prevalence of 80.7%, and 40 of the 42 isolates harbored two or more resistance determinants. For the 178 pigs investigated, 49.4% of the swabs and 34.8% of the lymph nodes were Salmonella positive. The most prevalent serotypes in lymph nodes were Salmonella Derby (50.0%) and Salmonella Typhimurium (27.4%). From the Salmonella isolates from pigs, only 6% were sensitive to the antimicrobial agents tested. The high resistance level of Salmonella isolates from pigs and chicken carcasses to different classes of antimicrobials should be emphasized and encourage a prudent use of these agents in animal farming, especially in pig production.
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Affiliation(s)
- L Ellerbroek
- Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, D-12277 Berlin, Germany.
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Tenhagen BA, Fetsch A, Stührenberg B, Schleuter G, Guerra B, Hammerl JA, Hertwig S, Kowall J, Kämpe U, Schroeter A, Bräunig J, Käsbohrer A, Appel B. Prevalence of MRSA types in slaughter pigs in different German abattoirs. Vet Rec 2010; 165:589-93. [PMID: 19915190 DOI: 10.1136/vr.165.20.589] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
To investigate the prevalence of types of meticillin-resistant Staphylococcus aureus (MRSA) in slaughter pigs in German abattoirs, nasal swabs were collected from a total of 1026 pigs in five abattoirs after stunning in the course of two studies, and examined for MRSA. Study 1 included four abattoirs; study 2 was carried out in one large abattoir. Isolates were tested for antimicrobial susceptibility and characterised using spa-typing, multilocus sequence typing (MLST) and typing of the staphylococcal cassette chromosome, SCCmec. Overall, MRSA was isolated from 70.8 per cent of 520 samples in study 1 and from 49.0 per cent of 506 samples in study 2. The proportion of positive samples varied substantially between the abattoirs in study 1. Most isolates belonged to spa-types t011 and t034 and SCCmec types III and V. MLST of selected isolates revealed that they were all MLST ST398. Besides beta-lactams, 100 per cent of the isolates were resistant to tetracycline, 80.5 per cent were resistant to erythromycin and 80.7 per cent were resistant to clindamycin. Less than 5 per cent of the isolates were resistant to other antimicrobials.
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Affiliation(s)
- B-A Tenhagen
- Federal Institute for Risk Assessment, Berlin, Germany.
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Avsaroglu MD, Helmuth R, Junker E, Hertwig S, Schroeter A, Akcelik M, Bozoglu F, Guerra B. Plasmid-mediated quinolone resistance conferred by qnrS1 in Salmonella enterica serovar Virchow isolated from Turkish food of avian origin. J Antimicrob Chemother 2007; 60:1146-50. [PMID: 17881633 DOI: 10.1093/jac/dkm352] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVES To study the molecular characteristics of the quinolone and associated ampicillin resistance mechanisms present in Salmonella enterica serovar Virchow isolated from Turkish foods. METHODS Nine epidemiologically unrelated Salmonella Virchow strains isolated from foods (chicken and minced meat) sold in different markets in Ankara were analysed for their susceptibility to 17 antimicrobials. The strains were typed by PFGE and plasmid profiling and investigated by molecular methods (PCR/sequencing) for the presence of several resistance genes, class 1 integrons and mutations in the quinolone resistance-determining regions. Plasmids conferring quinolone resistance were analysed by restriction fragment length polymorphism (RFLP) analysis, DNA hybridization, sequencing, replicon-typing PCR and mating experiments. RESULTS All strains showed nalidixic acid resistance (MIC >or= 128 mg/L) together with a decreased susceptibility to ciprofloxacin (three strains with an MIC of 1 mg/L and six with an MIC of 0.25 mg/L), associated with mutations within the gyrA gene (Asp-87 --> Tyr-87). In three strains, qnrS1 genes were detected. Ampicillin resistance encoded by a bla(CTX-M3) gene and/or bla(TEM-1-like) gene was found in four strains. Three of these strains carried an approximately 45 kb conjugative plasmid, designated pRQ2006, harbouring qnrS1 and a Tn3-like transposon. Partial sequencing and RFLP of pRQ2006 indicated its similarity to the qnrS1 plasmid pAH03786 found in a Japanese Shigella flexneri 2b isolate. CONCLUSIONS This is the first study describing the presence of qnrS1 genes in bacterial isolates from Turkey. The pRQ2006 plasmid seems to be more related to the S. flexneri 2b qnrS1 plasmid pAH0376 than to the Salmonella qnrS1-carrying plasmids pINF5 and TPqnrS-2.
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Avsaroglu D, Junker E, Helmuth R, Schroeter A, Akcelik M, Bozoglu F, Noeckler K, Guerra B. P510 Phenotypic and genotypic characterisation of antimicrobial resistance in Turkish Salmonella infantis isolates from chicken and minced meat. Int J Antimicrob Agents 2007. [DOI: 10.1016/s0924-8579(07)70353-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Avsaroglu D, Jaber M, Akcelik M, Bozoglu F, Schroeter A, Guerra B, Helmuth R. P1241 Isolation and characterisation of Salmonella from Turkish avian food samples. Int J Antimicrob Agents 2007. [DOI: 10.1016/s0924-8579(07)71081-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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35
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Pang JC, Chiu TH, Chiou CS, Schroeter A, Guerra B, Helmuth R, Tsen HY. Pulsed-field gel electrophoresis, plasmid profiles and phage types for the human isolates of Salmonella enterica serovar Enteritidis obtained over 13 years in Taiwan. J Appl Microbiol 2005; 99:1472-83. [PMID: 16313420 DOI: 10.1111/j.1365-2672.2005.02749.x] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
AIMS Plasmid profile, phage typing, and pulsed-field gel electrophoresis (PFGE) patterns of 124 Salmonella Enteritidis strains isolated in 1998-2002 in Taiwan were analysed and the results were compared with those of the 63 strains obtained in 1991-1997, so that molecular subtypes and epidemic strains for Salmonella Enteritidis over a 13-year period (1991-2002) could be elucidated. METHODS AND RESULTS A total of 124 strains of Salmonella Enteritidis isolated from human in Taiwan between 1998 and 2002 were analysed by PFGE, plasmid analysis and phage typing. The results obtained were compared with those of the 63 strains obtained in 1991-1997, so that the clonal relationships for a total of 187 strains obtained over 13 years could be elucidated. For PFGE, restriction enzymes XbaI, SpeI and NotI were used for chromosomal DNA digestion. Results showed 28 PFGE pattern combinations for the 187 Salmonella strains. Of them, pattern X3S3N3 was the major subtype as 130 strains isolated from different locations during 1991-2002 showed this PFGE pattern. For all these 187 strains, the genetic similarity was higher than 80%. Plasmid analysis showed 17 distinct types, which consist of one to four plasmids and the predominant phage type of those strains was PT4 (71.6%) and PT6a (13.4%). The three methods identified different degrees of polymorphism in the following order: plasmid profile (18 types, D = 0.659) > PFGE (28 types, D = 0.512) > phage typing (13 types, D = 0.438). As PFGE patterns, phage type and plasmid profile were combined for subtyping, the 187 strains could be grouped into 46 subtypes and the discriminatory index was raised to 0.795. For these 46 subtypes, the predominant one was X3S3N3/P1/PT4, which contained 77 (41%) isolates. CONCLUSIONS Most of the Salmonella Enteritidis strains from sporadic cases were with pattern X3S3N3. They were the prevalent and may be the epidemic strains found in Taiwan during 1991-2002. The present study suggested that the several variants were derived from a single clonal line and the genome for strains of Salmonella Enteritidis are highly conserved over a 13-year period (1991-2002). SIGNIFICANCE AND IMPACT OF THE STUDY The results obtained here are useful for epidemiolgical study of salmonellosis caused by Salmonella Enteritidis in Taiwan. Comparing the data of the present study with those obtained for strains from other countries, the major subtypes for Salmonella Enteritidis infection in the world can be elucidated.
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Affiliation(s)
- J-C Pang
- Department of Food Science, National Chung-Hsing University, Taichung City, Taiwan
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Abstract
During 2000-2002 the National Veterinary Reference Laboratory for Salmonella (NRL-Salm) in Germany typed 11,911 isolates from animals, food, feed and the environment. All of them were tested for their susceptibility to 17 anti-microbial agents. Sixty-three per cent of all isolates were resistant and 40% were multiresistant (resistant against more than one anti-microbial). This general resistance level was strongly influenced by those specific serotypes which dominate the Salmonella epidemiology in Germany. Salmonella Typhimurium DT104 isolates from pig and cattle, and their resulting food products, were multiresistant in 98 and 94% of the cases respectively. During the period 2000-2003 an increasing quinolone resistance especially in Salmonella isolates from poultry and poultry meat (to 26%) and in S. Paratyphi B D-tartrate positive isolates (to 64%) could be observed. This increase was accompanied by a shift towards higher minimal inhibitory concentrations for ciprofloxacin.
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Affiliation(s)
- A Schroeter
- Federal Institute of Risk Assessment, National Veterinary Reference Laboratory for Salmonella, Berlin, Germany.
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Hussein R, Engelmann U, Schroeter A, Meinzer HP. Internationalization of Healthcare Applications: A Generic Approach for PACS Workstations. Methods Inf Med 2004. [DOI: 10.1055/s-0038-1633851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Summary
Objectives:
Along with the revolution of information technology and the increasing use of computers worldwide, software providers recognize the emerging need for internationalized, or global, software applications. The importance of internationalization comes from its benefits such as addressing a broader audience, making the software applications more accessible, easier to use, more flexible to support and providing users with more consistent information. In addition, some governmental agencies, e.g., in Spain, accept only fully localized software. Although the healthcare communication standards, namely, Digital Imaging and Communication in Medicine (DICOM) and Health Level Seven (HL7) support wide areas of internationalization, most of the implementers are still protective about supporting the complex languages. This paper describes a generic internationalization approach for Picture Archiving and Communication System (PACS) workstations.
Methods:
The Unicode standard is used to internationalize the application user interface. An encoding converter was developed to encode and decode the data between the rendering module (in Unicode encoding) and the DICOM data (in ISO 8859 encoding). An integration gateway was required to integrate the inter-nationalized PACS components with the different PACS installations. To introduce a pragmatic example, the described approach was applied to the CHILI PACS workstation.
Results:
The approach has enabled the application to handle the different internationalization aspects transparently, such as supporting complex languages, switching between different languages at runtime, and supporting multilingual clinical reports.
Conclusions:
In the healthcare enterprises, internationalized applications play an essential role in supporting a seamless flow of information between the heterogeneous multivendor information systems.
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Hussein R, Engelmann U, Schroeter A, Meinzer HP. Internationalization of healthcare applications: a generic approach for PACS workstations. Methods Inf Med 2004; 43:133-40. [PMID: 15136862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
OBJECTIVES Along with the revolution of information technology and the increasing use of computers world-wide, software providers recognize the emerging need for internationalized, or global, software applications. The importance of internationalization comes from its benefits such as addressing a broader audience, making the software applications more accessible, easier to use, more flexible to support and providing users with more consistent information. In addition, some governmental agencies, e.g., in Spain, accept only fully localized software. Although the healthcare communication standards, namely, Digital Imaging and Communication in Medicine (DICOM) and Health Level Seven (HL7) support wide areas of internationalization, most of the implementers are still protective about supporting the complex languages. This paper describes a generic internationalization approach for Picture Archiving and Communication System (PACS) workstations. METHODS The Unicode standard is used to internationalize the application user interface. An encoding converter was developed to encode and decode the data between the rendering module (in Unicode encoding) and the DICOM data (in ISO 8859 encoding). An integration gateway was required to integrate the internationalized PACS components with the different PACS installations. To introduce a pragmatic example, the described approach was applied to the CHILI PACS workstation. RESULTS The approach has enabled the application to handle the different internationalization aspects transparently, such as supporting complex languages, switching between different languages at runtime, and supporting multilingual clinical reports. CONCLUSIONS In the healthcare enterprises, internationalized applications play an essential role in supporting a seamless flow of information between the heterogeneous multivendor information systems.
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Affiliation(s)
- R Hussein
- German Cancer Research Center, Division of Medical and Biological Informatics, H0100, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
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Malorny B, Schroeter A, Guerra B, Helmuth R. Incidence of quinolone resistance in strains of Salmonella
isolated from poultry. cattle and pigs in Germany between 1998 and 2001. Vet Rec 2003; 153:643-8. [PMID: 14667084 DOI: 10.1136/vr.153.21.643] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
This paper reports the susceptibility to the quinolone nalidixic acid and the fluoroquinolone ciprofloxacin of 14,514 strains of Salmonella isolated in Germany from poultry, cattle and pigs between 1998 and 2001. Quinolone-resistant salmonellae were most frequently isolated from poultry, with a prevalence of 10.2 to 16.8 per cent. Poultry-associated serotypes, such as Salmonella Paratyphi B (d-tartrate positive), Salmonella Hadar and Salmonella Virchow, had the highest prevalence of quinolone resistance, ranging between 35 and 74 per cent. All the nalidixic acid-resistant strains also had a reduced susceptibility to ciprofloxacin, with minimum inhibitory concentrations (MICS) of 0.125 to 2 microg/ml. A comparison of the MICS for ciprofloxacin of the strains of these poultry-associated serotypes and Salmonella Enteritidis phage type 4 isolated in 1998/99 and 2000/01 indicated that there had been a shift towards higher MIC values of up to 2 microg/ml. The quinolone resistance-determining region (QRDR) of the gyrA gene and the homologue region of the parC gene of 31 selected strains were sequenced. Several different amino acid changes were observed in gyrA of the quinolone-resistant isolates at positions 83 and 87, but no substitutions were observed in parC.
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Affiliation(s)
- B Malorny
- Federal Institute for Risk Assessment, National Salmonella Reference Laboratory, Diedersdorfer Weg 1, D-12277 Berlin, Germany
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Malorny B, Schroeter A, Bunge C, Hoog B, Steinbeck A, Helmuth R. Evaluation of molecular typing methods for Salmonella enterica serovar Typhimurium DT104 isolated in Germany from healthy pigs. Vet Res 2001; 32:119-29. [PMID: 11361148 DOI: 10.1051/vetres:2001116] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The discriminatory power of four different DNA based typing methods was tested for the molecular subtyping of Salmonella Typhimurium phage type DT104 isolates. German DT104 strains (n = 133) originating from slaughter pigs were analysed by plasmid profiling, and 32 of them by pulsed-field gel electrophoresis (PFGE) using the restriction enzymes XbaI, SpeI or BlnI, random amplification of polymorphic DNA (RAPD) using 13 different primers and IS200 typing. A resulting subtyping scheme was obtained which is based on the most discriminatory power of the individual methods i.e. plasmid profiling and PFGE with all three enzymes. The index of discrimination obtained by the subtyping scheme was 0.909 closely approaching the maximum value of one. Although minor differences occurred in the molecular DNA pattern of single DT104 strains, a dominating subtyping pattern was observed confirming other studies which showed, that S. Typhimurium DT104 isolates are highly clonal.
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Affiliation(s)
- B Malorny
- Federal Institute for Health Protection of Consumers and Veterinary Medicine, Berlin, Germany
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Dorn C, Schroeter A, Miko A, Protz D, Helmuth R. [Increasing number of Salmonella paratyphi B isolates from slaughtered poultry sent in to the national Salmonella reference laboratory]. Berl Munch Tierarztl Wochenschr 2001; 114:179-83. [PMID: 11413710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Abstract
In the last years the number of isolations of Salmonella enterica subspecies enterica serovar paratyphi B (S. paratyphi B) sent to the national salmonella reference laboratory of Germany has increased steadily. Most of the isolates originated from fowl or poultry products. The bacteriological, serological and biochemical properties of the isolates were investigated. Special emphasis was given to the utilization of d-tartrate which subgroups the serovar. All of them belonged to the d-tartrate positive variant, which is generally considered less virulent for humans and was formerly called S. java. The performance of various tests is compared and in addition the possibility of the spread within the production line is discussed.
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Affiliation(s)
- C Dorn
- Bundesinstitut für gesundheitlichen Verbraucherschutz und Veterinärmedizin, Nationales Veterinärmedizinisches Referenzlabor für Salmonellen (NRL-Salm)
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Poser S, Zerr I, Schroeter A, Otto M, Giese A, Steinhoff BJ, Kretzschmar HA. Clinical and differential diagnosis of Creutzfeldt-Jakob disease. Arch Virol Suppl 2001:153-9. [PMID: 11214918 DOI: 10.1007/978-3-7091-6308-5_14] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
Until recently, the clinical diagnosis of CJD relied mainly on three criteria. These include patient history (rapidly progressive dementia), neurological findings (ataxia, pyramidal/extrapyramidal signs, myoclonus, akinetic mutism) and typical electroencephalographic (EEG) findings. These criteria are fulfilled in typical cases. The occurrence or increase of certain proteins in cerebrospinal fluid (CSF; 14-3-3, neuron-specific enolase) now provide important adjuncts in recognizing variant forms. Although these proteins can be detected in other neurological diseases accompanied with substantial brain damage such as encephalitis, they are also characterized by their high sensitivity and specificity with regard to other dementing processes (Alzheimer and vascular dementia). The increase in the number of positive cases during the last years in Germany reflects an improved case ascertainment rather than the appearance of the variant CJD (vCJD). Although several recent cases with a long duration of the disease were actually recognized, they did not reveal the typical florid plaques at autopsy. They were revealed as a rare variant of sporadic CJD, which is characterized by homocygosity for valine at codon 129 and PrP(Sc) type 1. This variant is positive for the 14-3-3 protein in CSF. Further subtypes described by Parchi et al. can also be characterized by a certain pattern of clinical symptomatology, EEG- and 14-3-3-findings. In addition, differential diagnosis revealed some treatable dementias among the most common diseases (Alzheimer and vascular dementia) such as herpes encephalitis, multiple sclerosis and Hashimoto encephalitis, particularly in the younger age group.
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Affiliation(s)
- S Poser
- Department of Neurology, University of Goettingen, Germany
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Engelmann U, Schroeter A, Schwab M, Eisenmann U, Vetter M, Lorenz K, Quiles J, Wolf I, Evers H, Meinzer HP. Borderless teleradiology with CHILI. J Med Internet Res 1999; 1:E8. [PMID: 11720917 PMCID: PMC1761707 DOI: 10.2196/jmir.1.2.e8] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/1999] [Accepted: 11/23/1999] [Indexed: 11/28/2022] Open
Abstract
Teleradiology is one of the most evolved areas of telemedicine, but one of the basic problems which remains unsolved concerns system compatibility. The DICOM (Digital Imaging and Communications in Medicine) standard is a prerequisite, but it is not sufficient in all aspects. Examples of other currently open issues are security and cooperative work in synchronous teleconferences. Users without a DICOM radiological workstation would benefit from the ability to join a teleradiology network without any special tools. Drawbacks of many teleradiology systems are that they are monolithic in their software design and cannot be adapted to the actual user's environment. Existing radiological systems currently cannot be extended with additional software components. Consequently, every new application usually needs a new workstation with a different look and feel, which must be connected and integrated into the existing infrastructure. This paper introduces the second generation teleradiology system CHILI. The system has been designed to match both the teleradiology requirements of the American College of Radiology (ACR), and the functionality and usability needs of the users. The experiences of software developers and teleradiology users who participated in the first years of the clinical use of CHILI's predecessor MEDICUS have been integrated into a new design. The system has been designed as a component-based architecture. The most powerful communication protocol for data exchange and teleconferencing is the CHILI protocol, which includes a strong data security concept. The system offers, in addition to its own secure protocol, several different communication Methods: DICOM, classic e-mail, Remote Copy functions (RCP), File Transfer Protocol (FTP), the internet protocols HTTP (HyperText Transfer Protocol) and HTTPS (HyperText Transfer Protocol Secure),and CD-ROMs for off-line communication. These transfer METHODS allow the user to send images to nearly anyone with a computer and a network. The drawbacks of the non-CHILI protocols are that teleconferences are not possible, and that the user must take reasonable precautions for data privacy and security. The CHILI PlugIn mechanism enables the users or third parties to extend the system capabilities by adding powerful image postprocessing functions or interfaces to other information systems. Suitable PlugIns can be either existing programs, or dedicated applications programmed with interfaces to the CHILI components. The developer may freely choose programming languages and interface toolkits. The CHILI architecture is a powerful and flexible environment for Picture Archiving and Communications Systems (PACS)and teleradiology. More than 40 systems are currently running in clinical routine in Germany. More than 300,000 images have been distributed among the communication partners in the last two years. Feedback and suggestions from the users influenced the system architecture by a great extent. The proposed and implemented system has been optimized to be as platform independent, open, and secure as possible.
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Affiliation(s)
- U Engelmann
- Abteilung Medizinische und Biologische Informatik, Deutsches Krebsforschungszentrum, Heidelberg, D-69120, Germany.
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Poser S, Mollenhauer B, Kraubeta A, Zerr I, Steinhoff BJ, Schroeter A, Finkenstaedt M, Schulz-Schaeffer WJ, Kretzschmar HA, Felgenhauer K. How to improve the clinical diagnosis of Creutzfeldt-Jakob disease. Brain 1999; 122 ( Pt 12):2345-51. [PMID: 10581227 DOI: 10.1093/brain/122.12.2345] [Citation(s) in RCA: 125] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
This paper describes a prospective follow-up of 364 patients initially notified as suspected Creutzfeldt-Jakob disease to a Surveillance Unit in Göttingen, Germany. Six patients were diagnosed as having genetic prion disease by blood analysis and were excluded from the study. After examination and review of the remaining 358, 193 were classified as probable Creutzfeldt-Jakob disease. However, autopsy revealed that five of the 193 did not have Creutzfeldt-Jakob disease (four cases, Alzheimer's disease; one case, cerebral lymphoma). Of the 54 patients classified as possible Creutzfeldt-Jakob disease, 10 had another diagnosis made at autopsy. Two of the 111 cases originally classified as having other diseases were found to have Creutzfeldt-Jakob disease on autopsy. Autopsy evidence, together with follow-up of the patients still living and those who died without autopsy, revealed a broad range of other diagnoses. In the younger age groups, the commonest were chronic inflammatory diseases including Hashimoto encephalitis, whilst rapidly progressive Alzheimer's disease was most common in the older age groups. The presence of 14-3-3 protein in the CSF discriminated better between Creutzfeldt-Jakob disease and other rapidly progressive dementias than did the EEG pattern or the MRI. The inclusion of this CSF protein in the criteria of Masters and colleagues (Ann Neurol 1979; 5: 177-88) improves the accuracy and confidence in the clinical diagnosis of Creutzfeldt-Jakob disease.
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Affiliation(s)
- S Poser
- Department of Neurology, University of Göttingen, Germany
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Malorny B, Schroeter A, Helmuth R. Incidence of quinolone resistance over the period 1986 to 1998 in veterinary Salmonella isolates from Germany. Antimicrob Agents Chemother 1999; 43:2278-82. [PMID: 10471579 PMCID: PMC89461 DOI: 10.1128/aac.43.9.2278] [Citation(s) in RCA: 98] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
A total of 24,591 nonhuman salmonella strains isolated in Germany between 1986 and 1998 were examined for their resistance to nalidixic acid by an agar diffusion method. The rate of resistance (inhibition zone, </=13 mm) ranged from 0.2% in 1986 to a peak of 14. 8% in 1990. Between 1991 and 1998 the MICs for nalidixic acid-resistant strains ranged from more than 256 microg/ml for nalidixic acid to between 0.25 and 128 microg/ml for enrofloxacin. In the early 1990s a particularly high incidence of fluoroquinolone resistance (49.5%) was seen among isolates of Salmonella enterica serotype Typhimurium (Salmonella Typhimurium) definitive phage type 204c that mainly originated from cattle. Among isolates from poultry an increase in the incidence of nalidixic acid resistance to a peak of 14.4% was observed in 1994. This peak was due to the presence of specific resistant serotypes, mainly serotypes Hadar, Saintpaul, Paratyphi B (D-tartrate positive; formerly serotype Java) and Newport. Such strains exhibited a decreased susceptibility to enrofloxacin (MIC, 1 microg/ml). Among isolates from pigs the peak incidence of resistance was reached in 1993, with 7.5% of isolates resistant to nalidixic acid and enrofloxacin. The study demonstrates an increase in the incidence of strains that are resistant to nalidixic acid and that have decreased susceptibility to enrofloxacin after the licensing of enrofloxacin. In addition, the number of other serotypes that exhibited nalidixic acid resistance or reduced enrofloxacin susceptibility increased among the total number of isolates investigated between 1992 and 1998.
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Affiliation(s)
- B Malorny
- Federal Institute for Health Protection of Consumers and Veterinary Medicine, Diedersdorfer Weg 1, D-12277 Berlin, Germany
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Dieckmann H, Dreesman J, Dieckmann H, Malorny B, Schroeter A, Pulz M. [Investigation of foodborne outbreak due to Salmonella infantis using epidemiological and microbiological methods]. Gesundheitswesen 1999; 61:241-7. [PMID: 10414018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Abstract
In foodborne outbreaks, direct microbiological diagnosis is often not possible due to lack of remaining food samples. Therefore, in this investigation of an outbreak of Salmonella infantis at a fair, we chose an epidemiological approach in addition to microbiological testing. In a case control study, fair participants with symptoms of acute gastroenteritis as well as participants showing no signs of disease were interviewed by telephone. Questions concerning what food had been eaten at the fair and the course of disease had priority. Data analysis showed a significantly elevated odds ratio of 144 (p < 0.00001) for the consumption of potato salad. Salmonella infantis was cultured in faeces of symptomatic individuals as well as from left-over potato salad in high concentration. In conclusion, our data show that the cause of a foodborne outbreak can be detected through the application of epidemiologic methods with a high degree of certainty. In order to eliminate memory bias, a structured interview should be carried out as soon as possible after the initial outbreak.
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Affiliation(s)
- H Dieckmann
- Niedersächsisches Landesgesundheitsamt, Hannover
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Martin G, Hänel I, Helmuth R, Schroeter A, Erler W, Meyer H. [Immunization with potential Salmonella enteritidis mutants--1. Production and in vitro characterization]. Berl Munch Tierarztl Wochenschr 1996; 109:325-9. [PMID: 9054331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Production and in vitro characterization of potential vaccine strains are the first steps leading to an efficient Salmonella Enteritidis oral live vaccine for homologous immunization of poultry. The paper presents the results of the production of adenine-amino acid auxotrophic mutants using N-methyl-N'-nitro-N-nitrosoguanidine mutagenesis. The mutant strains were characterized using the following properties: auxotrophy, stability of mutation, reversion rate, generation time, metabolic properties, serotype, motility, plasmid content, phage type, SDS-PAGE patterns, as well as cell culture adhesion and invasion. Ten S. Enteritidis double auxotrophic mutants were obtained which are stable auxotrophically and where the risk of reversion was minimal. All strains were found to be plasmid-free. 5 mutants were selected for further investigations concerning their attenuation and immunological value.
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Affiliation(s)
- G Martin
- Bundesinstitut für gesundheitlichen Verbraucherschutz und Veterinärmedizin, Fachbereich 4 Bakterielle Tierseuchen und Bekämpfung von Zoonosen, Jena
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Hinz KH, Legutko P, Schroeter A, Lehmacher W, Hartung M. [Prevalence of motile salmonellae in egg-laying hens at the end of the laying period]. Zentralbl Veterinarmed B 1996; 43:23-33. [PMID: 8919966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
A total of 3504 hens of the layer-type from 122 flocks (belonging to 89 farms), each with more than 10,000 animals, were culturally examined at the time of slaughter. Of these hens, 2112 (60.3%) from 74 flocks (60.7%) were obtained from 21.3% of the laying-hen farms in a selected region of Lower Saxony in Germany. The other hens came from the remaining part of Lower Saxony and seven other German states (Brandenburg, Mecklenburg Vorpommern, North Rhine Westphalia, Schleswig Holstein, Saxony, Saxony Anhalt, and Thuringia). After arrival at the slaughter house, a random sample of 29 layers was collected from each of the flocks, and liver and spleen, as well as cecal samples, were separately cultured for each bird. Motile salmonellae could be proved in 365 (10.4%) layers from 67 flocks (54.9%). In the selected region, 48 out of 74 flocks (64.9%) and 289 out of 2112 layers (13.7%) were Salmonella-positive. However, the isolation frequency of salmonellae did not differ significantly between flocks of brown and white layers. These Salmonella (S.) isolates could be serologically assigned to 6 different serovars, namely S. enteritidis (SE), S. infantis (SI), S. livingstone (SL), S. typhimurium (ST), S. indiana (SID) and S. cerro; only one isolate of serogroup D1 was incompletely serotyped. SE was detected in 5.8% of the hens from 47.5% of the tested flocks, of which 4.6% of the animals and 32.8% of the flocks came from the selected region in Lower Saxony. The SE isolates were classified into 12 different lysotypes. In 41 out of 58 SE-positive flocks (70.7%), the isolates belonged to lysotype (lt) 4, in 12 flocks (20.7%) to lt 8, in 5 flocks (8.6%) to lt 7, and in 3 flocks (5.2%) to lt 11. A total of 190 (93.1%) out of 204 isolates of the serovar SE carried plasmids. All the plasmid-positive SE-strains harboured the serovar-specific 37 MD virulence-plasmid, nine of them (4.4%) in conjunction with a second and eight strains (3.9%) with a second and a third smaller plasmid.
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Affiliation(s)
- K H Hinz
- Klinik für Geflügel, Tierärztlichen Hochschule Hannover, Deutschland
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50
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Abstract
In order to monitor the epidemiological situation of S. enteritidis in Germany, in 1990-91 1138 isolates from more than 180 locations in West Germany were phage typed. 1124 strains (98.8%) from all sources were typeable, belonging to 21 different phage types (PT). PT4 strains were isolated most frequently (70.8%). In addition, PT7, 25, 34 and 8 were of epidemiological relevance with incidences of 7.2 to 4.5%. The comparison of data shows that in Germany, like in other parts of Europe, PT4 predominates. This phage type is, however, infrequent in North America, where PT8 has the highest incidence.
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Affiliation(s)
- A Schroeter
- Federal Institute for Health Protection of Consumers and Veterinary Medicine, Berlin, Germany
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