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7 results on '"Institute of Biophysics [Graz]"'

1. Global guideline for the diagnosis and management of the endemic mycoses: an initiative of the European Confederation of Medical Mycology in cooperation with the International Society for Human and Animal Mycology

Author

Peter-Michael Rath, Methee Chayakulkeeree, Alessandro C. Pasqualotto, Christopher C. Kibbler, María José Buitrago, Thuy Le, Neil M Ampel, Flavio Queiroz-Telles, Ferry Hagen, Oliver A. Cornely, Paul E. Verweij, Ana Alastruey-Izquierdo, Ariya Chindamporn, Nelesh P. Govender, Carol A. Kauffman, Graeme Meintjes, Darius Armstrong-James, Chris Kenyon, Grégory Jouvion, Ilan S. Schwartz, Olusola Ayanlowo, Jean-Pierre Gangneux, John W Baddley, George Richard Thompson, Jasper Fuk-Woo Chan, David R. Andes, Tobias M. Hohl, Low Lee Lee, Andrej Spec, Cao Cun-wei, Robert Krause, Ebrahim Variava, Marisa H. Miceli, David C M Kong, Leili Chamani-Tabriz, Mohammad Taghi Hedayati, Bridget M. Barker, Nikolai Klimko, Leila Maria Lopes Bezerra, University of California [Davis] (UC Davis), University of California, Duke University [Durham], Chulalongkorn University [Bangkok], University of Michigan Medical School [Ann Arbor], University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Instituto de Salud Carlos III [Madrid] (ISC), University of Arizona, University of Wisconsin-Madison, Imperial College London, University of Lagos, University of Maryland School of Medicine, University of Maryland System, The Pathogen and Microbiome Institute, Northern Arizona University [Flagstaff], State University of Rio de Janeiro, The University of Hong Kong (HKU), Mahidol University [Bangkok], University Hospital of Cologne [Cologne], Guangxi University [Nanning], Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), National Institute for Communicable Diseases [Johannesburg] (NICD), University of the Witwatersrand [Johannesburg] (WITS), University Medical Center [Utrecht], Mazandaran University of Medical Sciences, Memorial Sloan Kettering Cancer Center (MSKCC), Neuropathologie expérimentale / Experimental neuropathology, Institut Pasteur [Paris]-Université de Paris (UP), Maladies génétiques d'expression pédiatrique [CHU Trousseau], CHU Trousseau [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institute of Tropical Medicine [Antwerp] (ITM), University College of London [London] (UCL), University of Ballarat [Australie] (FedUni), Institute of Biophysics [Graz], Medical University Graz, University of Cape Town, Ruhrlandklinik University Hospital, Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), Federal University of Technology - Paraná (UTFPR), Radboud University Medical Center [Nijmegen], University of Alberta, Federal University of Health Sciences of Porto Alegre = Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), University of California (UC), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Maladies génétiques d'expression pédiatrique (U933), and Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Trousseau [APHP]

Subjects
medicine.medical_specialty, Consensus, Endemic Diseases, [SDV]Life Sciences [q-bio], International Cooperation, Clinical Sciences, Clinical Decision-Making, Medizin, MEDLINE, lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], Guidelines as Topic, Global Health, Microbiology, Article, Histoplasmosis, Vaccine Related, 03 medical and health sciences, 0302 clinical medicine, All institutes and research themes of the Radboud University Medical Center, Risk Factors, Biodefense, Mycology, Epidemiology, medicine, Animals, Humans, 030212 general & internal medicine, Intensive care medicine, 0303 health sciences, Sporotrichosis, 030306 microbiology, Paracoccidioidomycosis, business.industry, Prevention, Guideline, medicine.disease, 3. Good health, Europe, Emerging Infectious Diseases, Good Health and Well Being, Infectious Diseases, Mycoses, Medical Microbiology, Public Health and Health Services, Infection, business, Blastomycosis
Abstract

International audience; The global burden of the endemic mycoses (blastomycosis, coccidioidomycosis, emergomycosis, histoplasmosis, paracoccidioidomycosis, sporotrichosis, and talaromycosis) continues to rise yearly and these infectious diseases remain a leading cause of patient morbidity and mortality worldwide. Management of the associated pathogens requires a thorough understanding of the epidemiology, risk factors, diagnostic methods and performance characteristics in different patient populations, and treatment options unique to each infection. Guidance on the management of these infections has the potential to improve prognosis. The recommendations outlined in this Review are part of the "One World, One Guideline" initiative of the European Confederation of Medical Mycology. Experts from 23 countries contributed to the development of these guidelines. The aim of this Review is to provide an up-to-date consensus and practical guidance in clinical decision making, by engaging physicians and scientists involved in various aspects of clinical management.

Published
2021

2. High hydrostatic pressure specifically affects molecular dynamics and shape of low-density lipoprotein particles

Author

Joachim Kohlbrecher, Jacques Ollivier, Maksym Golub, Judith Peters, Nicolas Martinez, Bernhard Lehofer, Ruth Prassl, Institut Laue-Langevin (ILL), ILL, Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institute of Biophysics [Graz], Medical University Graz, Paul Scherrer Institute (PSI), Institut de biologie structurale (IBS - UMR 5075 ), Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut de Recherche Interdisciplinaire de Grenoble (IRIG), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Interdisciplinaire de Physique [Saint Martin d’Hères] (LIPhy), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), ANR-12-ISV5-0002,LDLPRESS,L'impact de la pression sur la structure et la dynamique moléculaire de particules de lipoprotéine à basse densité(2012), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut de Recherche Interdisciplinaire de Grenoble (IRIG), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)

Subjects
0301 basic medicine, [PHYS.PHYS.PHYS-BIO-PH]Physics [physics]/Physics [physics]/Biological Physics [physics.bio-ph], Hydrostatic pressure, Neutron diffraction, Molecular Dynamics Simulation, Neutron scattering, 01 natural sciences, Article, 03 medical and health sciences, Molecular dynamics, chemistry.chemical_compound, Scattering, Small Angle, 0103 physical sciences, Hydrostatic Pressure, Humans, 010306 general physics, Triglycerides, Lipid Transport, Multidisciplinary, [SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], Elasticity, Lipoproteins, LDL, Neutron Diffraction, 030104 developmental biology, Membrane, Biochemistry, chemistry, Low-density lipoprotein, Biophysics, lipids (amino acids, peptides, and proteins), Protons, Lipoprotein
Abstract

Lipid composition of human low-density lipoprotein (LDL) and its physicochemical characteristics are relevant for proper functioning of lipid transport in the blood circulation. To explore dynamical and structural features of LDL particles with either a normal or a triglyceride-rich lipid composition we combined coherent and incoherent neutron scattering methods. The investigations were carried out under high hydrostatic pressure (HHP), which is a versatile tool to study the physicochemical behavior of biomolecules in solution at a molecular level. Within both neutron techniques we applied HHP to probe the shape and degree of freedom of the possible motions (within the time windows of 15 and 100 ps) and consequently the flexibility of LDL particles. We found that HHP does not change the types of motion in LDL, but influences the portion of motions participating. Contrary to our assumption that lipoprotein particles, like membranes, are highly sensitive to pressure we determined that LDL copes surprisingly well with high pressure conditions, although the lipid composition, particularly the triglyceride content of the particles, impacts the molecular dynamics and shape arrangement of LDL under pressure.

Published
2017
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3. Inter-Model Consistency and Complementarity: Learning from ex-vivo Imaging and Electrophysiological Data towards an Integrated Understanding of Cardiac Physiology

Author

Gernot Plank, Jatin Relan, Pengcheng Shi, Nicholas Ayache, Rafael Sebastian, Mihaela Pop, Hervé Delingette, Nicolas P. Smith, Heye Zhang, Oscar Camara, Pablo Lamata, Ali Pashaei, Ken C. L. Wong, Maxime Sermesant, Daniel Romero, Linwei Wang, Huafeng Liu, Graham A. Wright, Alejandro F. Frangi, Steven A. Niederer, M. De Craene, Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra [Barcelona] (UPF), Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Instituto de Salud Carlos III [Madrid] (ISC)-ministerio de ciencia e innovacion, Analysis and Simulation of Biomedical Images (ASCLEPIOS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), School of Biomedical Engineering & Imaging Sciences [London], Guy's and St Thomas' Hospital [London]-King‘s College London, Department of Computer Science [Oxford], University of Oxford, Laboratoire de chimie bactérienne (LCB), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Spectrométrie Physique (LSP), Université Joseph Fourier - Grenoble 1 (UJF)-Centre National de la Recherche Scientifique (CNRS), Biomécanique et Bioingénierie (BMBI), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), Department of Physics [Toronto], University of Toronto, Imaging Research [Sunnybrook], University of Toronto-Sunnybrook Health Sciences Centre, Laboratoire Structures, Propriétés et Modélisation des solides (SPMS), Institut de Chimie du CNRS (INC)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Institut supérieur de l'électronique et du numérique (ISEN)-Université de Valenciennes et du Hainaut-Cambrésis (UVHC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF), Beijing Institute of Technology (BIT), Institute of Biophysics [Graz], Medical University Graz, Computational Multi-Scale Physiology Lab [Valencia], Universitat de València (UV), Institut des Sciences Chimiques de Rennes (ISCR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut de biologie et chimie des protéines [Lyon] (IBCP), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Biologie moléculaire et cellulaire de la différenciation, Université Joseph Fourier - Grenoble 1 (UJF)-Institut Albert Bonniot-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Department of Chemistry [HKUST], Hong Kong University of Science and Technology (HKUST), Institució Catalana de Recerca i Estudis Avançats (ICREA), Institute of Simulation and Graphics [Magdeburg], Otto-von-Guericke-Universität Magdeburg = Otto-von-Guericke University [Magdeburg] (OVGU), Computational Biomedicine Laboratory [Rochester], Rochester Institute of Technology, Department of Medical Biophysics (MBP), King‘s College London-Guy's and St Thomas' Hospital [London], University of Oxford [Oxford], Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), and Otto-von-Guericke University [Magdeburg] (OVGU)

Subjects
Time Factors, Computer science, Swine, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Biophysics, 030204 cardiovascular system & hematology, In Vitro Techniques, computer.software_genre, Models, Biological, Biophysical Phenomena, Personalization, Membrane Potentials, Diffusion, Purkinje Fibers, 03 medical and health sciences, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Optical mapping, Maximum a posteriori estimation, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Animals, Molecular Biology, 030304 developmental biology, 0303 health sciences, Computational model, Cardiac electrophysiology, business.industry, Experimental data, Reproducibility of Results, Heart, Magnetic Resonance Imaging, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Electrophysiological Phenomena, Systems Integration, System integration, Artificial intelligence, Data mining, business, computer, Pericardium, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a perfused ex-vivo porcine heart. This data was used to develop and customize four models of cardiac electrophysiology with different level of details, including a personalized fast conduction Purkinje system, a maximum a posteriori estimation of the 3D distribution of transmembrane potential, the personalization of a simplified reaction-diffusion model, and a detailed biophysical model with generic conduction parameters. This study proposes the integration of these four models into a single modelling and simulation pipeline, after analyzing their common features and discrepancies. The proposed integrated pipeline demonstrates an increase prediction power of depolarization isochrones in different pacing conditions.

Published
2011

4. Measurement of mean subcutaneous fat thickness: eight standardised ultrasound sites compared to 216 randomly selected sites.

Author

Störchle P, Müller W, Sengeis M, Lackner S, Holasek S, and Fürhapter-Rieger A

Subjects
Adult, Body Fat Distribution standards, Body Mass Index, Calibration, Humans, Male, Reference Standards, Reproducibility of Results, Ultrasonography methods, Ultrasonography standards, Young Adult, Anthropometry methods, Body Fat Distribution methods, Subcutaneous Fat diagnostic imaging
Abstract

Ultrasound (US) provides the most accurate technique for thickness measurements of subcutaneous adipose tissue (SAT) layers. This US method was recently standardised using eight sites to capture SAT patterning and allows distinguishing between fat and embedded fibrous structures. These eight sites chosen for fat patterning studies do not represent the mean SAT thickness measured all over the body that is necessary for determining subcutaneous fat mass. This was obtained by SAT measurements at 216 sites distributed randomly all over the body. Ten participants with BMI below 28.5kgm -2 and SAT means (from eight sites) ranging from 3 mm to 10 mm were selected. The means from eight sites overestimated the means obtained from 216 sites (i.e. 2160 US measurements in the ten participants); the calibration factor of 0.65 corrects this; standard deviation (SD) was 0.05, i.e. 8%. The SD of the calibration factor transforms linearly when estimating the error range of the whole body's SAT volume (body surface area times the calibrated mean SAT thickness). The SAT masses ranged from 3.2 to 12.4 kg in this group. The standard deviations resulting from solely the calibration factor uncertainty were ±0.3 and ±1.0 kg, respectively. For these examples, the SAT percentages were 4.9(±0.4)% and 13.3(±1.0)%.

Published
2018
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5. Age is reflected in the Fractal Dimensionality of MRI Diffusion Based Tractography.

Author

Reishofer G, Studencnik F, Koschutnig K, Deutschmann H, Ahammer H, and Wood G

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Female, Healthy Volunteers, Humans, Male, Middle Aged, White Matter diagnostic imaging, White Matter physiology, Young Adult, Aging, Diffusion Tensor Imaging, Fractals, Image Processing, Computer-Assisted
Abstract

Fractal analysis is a widely used tool to analyze the geometrical complexity of biological structures. The geometry of natural objects such as plants, clouds, cellular structures, blood vessel, and many others cannot be described sufficiently with Euclidian geometric properties, but can be represented by a parameter called the fractal dimension. Here we show that a specific estimate of fractal dimension, the correlation dimension, is able to describe changes in the structural complexity of the human brain, based on data from magnetic resonance diffusion imaging. White matter nerve fiber bundles, represented by tractograms, were analyzed with regards to geometrical complexity, using fractal geometry. The well-known age-related change of white matter tissue was used to verify changes by means of fractal dimension. Structural changes in the brain were successfully be observed and quantified by fractal dimension and compared with changes in fractional anisotropy.

Published
2018
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6. Subcutaneous fat patterning in athletes: selection of appropriate sites and standardisation of a novel ultrasound measurement technique: ad hoc working group on body composition, health and performance, under the auspices of the IOC Medical Commission.

Author

Müller W, Lohman TG, Stewart AD, Maughan RJ, Meyer NL, Sardinha LB, Kirihennedige N, Reguant-Closa A, Risoul-Salas V, Sundgot-Borgen J, Ahammer H, Anderhuber F, Fürhapter-Rieger A, Kainz P, Materna W, Pilsl U, Pirstinger W, and Ackland TR

Subjects
Athletic Performance physiology, Body Composition physiology, Body Fat Distribution, Female, Health Status, Humans, Male, Muscle, Skeletal anatomy & histology, Muscle, Skeletal diagnostic imaging, Observer Variation, Subcutaneous Fat diagnostic imaging, Ultrasonography, Sports physiology, Subcutaneous Fat anatomy & histology
Abstract

Background: Precise and accurate field methods for body composition analyses in athletes are needed urgently., Aim: Standardisation of a novel ultrasound (US) technique for accurate and reliable measurement of subcutaneous adipose tissue (SAT)., Methods: Three observers captured US images of uncompressed SAT in 12 athletes and applied a semiautomatic evaluation algorithm for multiple SAT measurements., Results: Eight new sites are recommended: upper abdomen, lower abdomen, erector spinae, distal triceps, brachioradialis, lateral thigh, front thigh, medial calf. Obtainable accuracy was 0.2 mm (18 MHz probe; speed of sound: 1450 m/s). Reliability of SAT thickness sums (N=36): R(2)=0.998, SEE=0.55 mm, ICC (95% CI) 0.998 (0.994 to 0.999); observer differences from their mean: 95% of the SAT thickness sums were within ± 1 mm (sums of SAT thicknesses ranged from 10 to 50 mm). Embedded fibrous tissues were also measured., Conclusions: A minimum of eight sites is suggested to accommodate inter-individual differences in SAT patterning. All sites overlie muscle with a clearly visible fascia, which eases the acquisition of clear images and the marking of these sites takes only a few minutes. This US method reaches the fundamental accuracy and precision limits for SAT measurements given by tissue plasticity and furrowed borders, provided the measurers are trained appropriately., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)

Published
2016
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7. Body composition in sport: interobserver reliability of a novel ultrasound measure of subcutaneous fat tissue.

Author

Müller W, Horn M, Fürhapter-Rieger A, Kainz P, Kröpfl JM, Ackland TR, Lohman TG, Maughan RJ, Meyer NL, Sundgot-Borgen J, Stewart AD, and Ahammer H

Subjects
Female, Humans, Muscle, Skeletal anatomy & histology, Muscle, Skeletal diagnostic imaging, Observer Variation, Sports Medicine methods, Subcutaneous Fat anatomy & histology, Ultrasonography, Young Adult, Body Composition physiology, Gymnastics physiology, Soccer physiology, Subcutaneous Fat diagnostic imaging
Abstract

Background: Very low body mass, extreme mass changes, and extremely low per cent body fat are becoming increasingly common in many sports, but sufficiently reliable and accurate field methods for body composition assessment in athletes are missing., Methods: Nineteen female athletes were investigated (mean (SD) age: 19.5 (± 3.3) years; body mass: 59.6 (± 7.6) kg; height: 1.674 (± 0.056) m; BMI: 21.3 (± 2.3) kg/m(2)). Three observers applied diagnostic B-mode-ultrasound (US) combined with the evaluation software for subcutaneous adipose tissue measurements at eight ISAK sites (International Society for the Advancement of Kinanthrometry). Regression and reliability analyses are presented., Results: US measurements and evaluation of subcutaneous adipose tissue (SAT) thicknesses (including fibrous structures: D(included); n=378) resulted in an SE of estimate SEE=0.60 mm, R(2)=0.98 (p<0.001), limit of agreement LOA=1.18, ICC=0.968 (0.957-0.977). Similar values were found for D(excluded): SEE=0.68 mm, R(2)=0.97 (p<0.001). D(included) at individual ISAK sites: at biceps, R(2)=0.87 and intraclass-correlation coefficient ICC=0.811 were lowest and SEE=0.79 mm was highest. Values at all other sites ranged from R(2): 0.94-0.99, SEE: 0.42-0.65 mm, and ICC: 0.917-0.985. Interobserver coefficients ranged from 0.92 to 0.99, except for biceps (0.74, 0.83 and 0.87). Evaluations of 20 randomly selected US images by three observers (D(included)) resulted in: SEE=0.15 mm, R(2)=0.998(p<0.001), ICC=0.997 (0.993, 0999)., Conclusions: Subject to optimal choice of sites and certain standardisations, US can offer a highly reliable field method for measurement of uncompressed thickness of the SAT. High accuracy and high reliability of measurement, as obtained with this US approach, are essential for protection of the athlete's health and also for optimising performance.

Published
2013
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