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Mezzomo P, Weinhold A, Aurová K, Jorge LR, Kozel P, Michálek J, Nováková N, Seifert CL, Volfová T, Engström M, Salminen J, Sedio BE, Volf M. Leaf volatile and nonvolatile metabolites show different levels of specificity in response to herbivory. Ecol Evol 2023; 13:e10123. [PMID: 37255847 PMCID: PMC10225982 DOI: 10.1002/ece3.10123] [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] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 04/27/2023] [Accepted: 05/05/2023] [Indexed: 06/01/2023] Open
Abstract
Plants produce diverse chemical defenses with contrasting effects on different insect herbivores. Deploying herbivore-specific responses can help plants increase their defensive efficiency. Here, we explore how variation in induced plant responses correlates with herbivore species, order, feeding guild, and level of specialization. In a greenhouse experiment, we exposed 149 plants of Salix fragilis (Linnaeus, 1753) to 22 herbivore species naturally associated with this host. The insects belonged to four orders (Coleoptera, Lepidoptera, Hemiptera, and Hymenoptera), three feeding guilds (external leaf-chewers, leaf-tying chewers, and sap-sucking), and included both dietary specialists and generalists. Following herbivory, we quantified induced changes in volatiles and nonvolatile leaf metabolites. We performed multivariate analyses to assess the correlation between herbivore order, feeding guild, dietary specialization, chewing damage by herbivores, and induced responses. The volatile composition was best explained by chewing damage and insect order, with Coleoptera and Lepidoptera eliciting significantly different responses. Furthermore, we recorded significant differences in elicited volatiles among some species within the two orders. Variation in nonvolatile leaf metabolites was mainly explained by the presence of insects, as plants exposed to herbivores showed significantly different metabolites from controls. Herbivore order also played a role to some extent, with beetles eliciting different responses than other herbivores. The induction of volatile and nonvolatile leaf metabolites shows different levels of specificity. The specificity in volatiles could potentially serve as an important cue to specialized predators or parasitoids, increasing the efficacy of volatiles as indirect defenses. By contrast, the induction of nonvolatile leaf metabolites was largely unaffected by herbivore identity. Most nonvolatile metabolites were downregulated, possibly indicating that plants redirected their resources from leaves in response to herbivory. Our results demonstrate how diverse responses to herbivores can contribute to the diversity of plant defensive strategies.
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Affiliation(s)
- Priscila Mezzomo
- Biology Centre CASInstitute of EntomologyCeske BudejoviceCzech Republic
- Faculty of ScienceUniversity of South BohemiaCeske BudejoviceCzech Republic
| | - Alexander Weinhold
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐LeipzigLeipzigGermany
- Institute of BiodiversityUniversity of JenaJenaGermany
| | - Klára Aurová
- Biology Centre CASInstitute of EntomologyCeske BudejoviceCzech Republic
| | - Leonardo R. Jorge
- Biology Centre CASInstitute of EntomologyCeske BudejoviceCzech Republic
| | - Petr Kozel
- Biology Centre CASInstitute of EntomologyCeske BudejoviceCzech Republic
- Faculty of ScienceUniversity of South BohemiaCeske BudejoviceCzech Republic
| | - Jan Michálek
- Centre Algatech CASInstitute of MicrobiologyTřeboňCzech Republic
- Biology Centre CASInstitute of ParasitologyCeske BudejoviceCzech Republic
| | - Nela Nováková
- Faculty of ScienceUniversity of South BohemiaCeske BudejoviceCzech Republic
| | - Carlo L. Seifert
- Department of Forest Nature Conservation, Faculty of Forest Sciences and Forest EcologyGeorg‐August‐University GöttingenGöttingenGermany
| | - Tereza Volfová
- Biology Centre CASInstitute of EntomologyCeske BudejoviceCzech Republic
- Faculty of ScienceUniversity of South BohemiaCeske BudejoviceCzech Republic
| | | | | | - Brian E. Sedio
- Department of Integrative BiologyUniversity of Texas at AustinAustinTexasUSA
- Smithsonian Tropical Research InstituteBalboa, AncónRepublic of Panama
| | - Martin Volf
- Biology Centre CASInstitute of EntomologyCeske BudejoviceCzech Republic
- Faculty of ScienceUniversity of South BohemiaCeske BudejoviceCzech Republic
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Author Correction: Federated learning enables big data for rare cancer boundary detection. Nat Commun 2023; 14:436. [PMID: 36702828 PMCID: PMC9879935 DOI: 10.1038/s41467-023-36188-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Federated learning enables big data for rare cancer boundary detection. Nat Commun 2022; 13:7346. [PMID: 36470898 PMCID: PMC9722782 DOI: 10.1038/s41467-022-33407-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 09/16/2022] [Indexed: 12/12/2022] Open
Abstract
Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.
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Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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4
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Pavlatovská B, Machálková M, Brisudová P, Pruška A, Štěpka K, Michálek J, Nečasová T, Beneš P, Šmarda J, Preisler J, Kozubek M, Navrátilová J. Lactic Acidosis Interferes With Toxicity of Perifosine to Colorectal Cancer Spheroids: Multimodal Imaging Analysis. Front Oncol 2020; 10:581365. [PMID: 33344237 PMCID: PMC7746961 DOI: 10.3389/fonc.2020.581365] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [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: 07/08/2020] [Accepted: 10/20/2020] [Indexed: 11/13/2022] Open
Abstract
Colorectal cancer (CRC) is a disease with constantly increasing incidence and high mortality. The treatment efficacy could be curtailed by drug resistance resulting from poor drug penetration into tumor tissue and the tumor-specific microenvironment, such as hypoxia and acidosis. Furthermore, CRC tumors can be exposed to different pH depending on the position in the intestinal tract. CRC tumors often share upregulation of the Akt signaling pathway. In this study, we investigated the role of external pH in control of cytotoxicity of perifosine, the Akt signaling pathway inhibitor, to CRC cells using 2D and 3D tumor models. In 3D settings, we employed an innovative strategy for simultaneous detection of spatial drug distribution and biological markers of proliferation/apoptosis using a combination of mass spectrometry imaging and immunohistochemistry. In 3D conditions, low and heterogeneous penetration of perifosine into the inner parts of the spheroids was observed. The depth of penetration depended on the treatment duration but not on the external pH. However, pH alteration in the tumor microenvironment affected the distribution of proliferation- and apoptosis-specific markers in the perifosine-treated spheroid. Accurate co-registration of perifosine distribution and biological response in the same spheroid section revealed dynamic changes in apoptotic and proliferative markers occurring not only in the perifosine-exposed cells, but also in the perifosine-free regions. Cytotoxicity of perifosine to both 2D and 3D cultures decreased in an acidic environment below pH 6.7. External pH affects cytotoxicity of the other Akt inhibitor, MK-2206, in a similar way. Our innovative approach for accurate determination of drug efficiency in 3D tumor tissue revealed that cytotoxicity of Akt inhibitors to CRC cells is strongly dependent on pH of the tumor microenvironment. Therefore, the effect of pH should be considered during the design and pre-clinical/clinical testing of the Akt-targeted cancer therapy.
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Affiliation(s)
- Barbora Pavlatovská
- Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czechia
| | - Markéta Machálková
- Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czechia
| | - Petra Brisudová
- Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czechia
| | - Adam Pruška
- Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
| | - Karel Štěpka
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czechia
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czechia
| | - Tereza Nečasová
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czechia
| | - Petr Beneš
- Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czechia.,Center for Biological and Cellular Engineering, International Clinical Research Center, St. Anne's University Hospital, Brno, Czechia
| | - Jan Šmarda
- Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czechia
| | - Jan Preisler
- Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czechia
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czechia
| | - Jarmila Navrátilová
- Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czechia.,Center for Biological and Cellular Engineering, International Clinical Research Center, St. Anne's University Hospital, Brno, Czechia
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5
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Tomčala A, Michálek J, Schneedorferová I, Füssy Z, Gruber A, Vancová M, Oborník M. Fatty Acid Biosynthesis in Chromerids. Biomolecules 2020; 10:E1102. [PMID: 32722284 PMCID: PMC7464705 DOI: 10.3390/biom10081102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 07/12/2020] [Accepted: 07/15/2020] [Indexed: 12/12/2022] Open
Abstract
Fatty acids are essential components of biological membranes, important for the maintenance of cellular structures, especially in organisms with complex life cycles like protozoan parasites. Apicomplexans are obligate parasites responsible for various deadly diseases of humans and livestock. We analyzed the fatty acids produced by the closest phototrophic relatives of parasitic apicomplexans, the chromerids Chromera velia and Vitrella brassicaformis, and investigated the genes coding for enzymes involved in fatty acids biosynthesis in chromerids, in comparison to their parasitic relatives. Based on evidence from genomic and metabolomic data, we propose a model of fatty acid synthesis in chromerids: the plastid-localized FAS-II pathway is responsible for the de novo synthesis of fatty acids reaching the maximum length of 18 carbon units. Short saturated fatty acids (C14:0-C18:0) originate from the plastid are then elongated and desaturated in the cytosol and the endoplasmic reticulum. We identified giant FAS I-like multi-modular enzymes in both chromerids, which seem to be involved in polyketide synthesis and fatty acid elongation. This full-scale description of the biosynthesis of fatty acids and their derivatives provides important insights into the reductive evolutionary transition of a phototropic algal ancestor to obligate parasites.
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Affiliation(s)
- Aleš Tomčala
- Biology Centre CAS, Institute of Parasitology, Branišovská 31, 370 05 České Budějovice, Czech Republic; (A.T.); (J.M.); (I.S.); (Z.F.); (A.G.); (M.V.)
- Faculty of Fisheries and Protection of Waters, CENAKVA, Institute of Aquaculture and Protection of Waters, University of South Bohemia, Husova 458/102, 370 05 České Budějovice, Czech Republic
| | - Jan Michálek
- Biology Centre CAS, Institute of Parasitology, Branišovská 31, 370 05 České Budějovice, Czech Republic; (A.T.); (J.M.); (I.S.); (Z.F.); (A.G.); (M.V.)
- Faculty of Science, University of South Bohemia, Branišovská 31, 370 05 České Budějovice, Czech Republic
| | - Ivana Schneedorferová
- Biology Centre CAS, Institute of Parasitology, Branišovská 31, 370 05 České Budějovice, Czech Republic; (A.T.); (J.M.); (I.S.); (Z.F.); (A.G.); (M.V.)
- Faculty of Science, University of South Bohemia, Branišovská 31, 370 05 České Budějovice, Czech Republic
| | - Zoltán Füssy
- Biology Centre CAS, Institute of Parasitology, Branišovská 31, 370 05 České Budějovice, Czech Republic; (A.T.); (J.M.); (I.S.); (Z.F.); (A.G.); (M.V.)
| | - Ansgar Gruber
- Biology Centre CAS, Institute of Parasitology, Branišovská 31, 370 05 České Budějovice, Czech Republic; (A.T.); (J.M.); (I.S.); (Z.F.); (A.G.); (M.V.)
| | - Marie Vancová
- Biology Centre CAS, Institute of Parasitology, Branišovská 31, 370 05 České Budějovice, Czech Republic; (A.T.); (J.M.); (I.S.); (Z.F.); (A.G.); (M.V.)
| | - Miroslav Oborník
- Biology Centre CAS, Institute of Parasitology, Branišovská 31, 370 05 České Budějovice, Czech Republic; (A.T.); (J.M.); (I.S.); (Z.F.); (A.G.); (M.V.)
- Faculty of Science, University of South Bohemia, Branišovská 31, 370 05 České Budějovice, Czech Republic
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Michálek J, Štěpka K, Kozubek M, Navrátilová J, Pavlatovská B, Machálková M, Preisler J, Pruška A. Quantitative Assessment of Anti-Cancer Drug Efficacy From Coregistered Mass Spectrometry and Fluorescence Microscopy Images of Multicellular Tumor Spheroids. Microsc Microanal 2019; 25:1311-1322. [PMID: 31571549 DOI: 10.1017/s1431927619014983] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Spheroids-three-dimensional aggregates of cells grown from a cancer cell line-represent a model of living tissue for chemotherapy investigation. Distribution of chemotherapeutics in spheroid sections was determined using the matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). Proliferating or apoptotic cells were immunohistochemically labeled and visualized by laser scanning confocal fluorescence microscopy (LSCM). Drug efficacy was evaluated by comparing coregistered MALDI MSI and LSCM data of drug-treated spheroids with LSCM only data of untreated control spheroids. We developed a fiducial-based workflow for coregistration of low-resolution MALDI MS with high-resolution LSCM images. To allow comparison of drug and cell distribution between the drug-treated and untreated spheroids of different shapes or diameters, we introduced a common diffusion-related coordinate, the distance from the spheroid boundary. In a procedure referred to as "peeling", we correlated average drug distribution at a certain distance with the average reduction in the affected cells between the untreated and the treated spheroids. This novel approach makes it possible to differentiate between peripheral cells that died due to therapy and the innermost cells which died naturally. Two novel algorithms-for MALDI MS image denoising and for weighting of MALDI MSI and LSCM data by the presence of cell nuclei-are also presented.
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Affiliation(s)
- Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Karel Štěpka
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Jarmila Navrátilová
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
- Center for Biological and Cellular Engineering, International Clinical Research Center, St. Anne's University Hospital, Pekařská 53, 656 91 Brno, Czech Republic
| | - Barbora Pavlatovská
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Markéta Machálková
- Department of Chemistry, Faculty of Science and Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Jan Preisler
- Department of Chemistry, Faculty of Science and Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Adam Pruška
- Department of Chemistry, Faculty of Science and Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
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Machálková M, Pavlatovská B, Michálek J, Pruška A, Štěpka K, Nečasová T, Radaszkiewicz KA, Kozubek M, Šmarda J, Preisler J, Navrátilová J. Drug Penetration Analysis in 3D Cell Cultures Using Fiducial-Based Semiautomatic Coregistration of MALDI MSI and Immunofluorescence Images. Anal Chem 2019; 91:13475-13484. [DOI: 10.1021/acs.analchem.9b02462] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Markéta Machálková
- Department of Chemistry, Faculty of Science and Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Barbora Pavlatovská
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Adam Pruška
- Department of Chemistry, Faculty of Science and Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Karel Štěpka
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Tereza Nečasová
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Katarzyna Anna Radaszkiewicz
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Jan Šmarda
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Jan Preisler
- Department of Chemistry, Faculty of Science and Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Jarmila Navrátilová
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
- Center for Biological and Cellular Engineering, International Clinical Research Center, St. Anne’s University Hospital, Pekařská 53, 656 91 Brno, Czech Republic
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Michálek J, Hanzlíková P, Trinh T, Pacík D. Fast and accurate compensation of signal offset for T 2 mapping. MAGMA 2019; 32:423-436. [PMID: 30730022 DOI: 10.1007/s10334-019-00737-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 01/06/2019] [Accepted: 01/07/2019] [Indexed: 06/09/2023]
Abstract
OBJECTIVE T2 maps are more vendor independent than other MRI protocols. Multi-echo spin-echo signal decays to a non-zero offset due to imperfect refocusing pulses and Rician noise, causing T2 overestimation by the vendor's 2-parameter algorithm. The accuracy of the T2 estimate is improved, if the non-zero offset is estimated as a third parameter. Three-parameter Levenberg-Marquardt (LM) T2 estimation takes several minutes to calculate, and it is sensitive to initial values. We aimed for a 3-parameter fitting algorithm that was comparably accurate, yet substantially faster. METHODS Our approach gains speed by converting the 3-parameter minimisation problem into an empirically unimodal univariate problem, which is quickly minimised using the golden section line search (GS). RESULTS To enable comparison, we propose a novel noise-masking algorithm. For clinical data, the agreement between the GS and the LM fit is excellent, yet the GS algorithm is two orders of magnitude faster. For synthetic data, the accuracy of the GS algorithm is on par with that of the LM fit, and the GS algorithm is significantly faster. The GS algorithm requires no parametrisation or initialisation by the user. DISCUSSION The new GS T2 mapping algorithm offers a fast and much more accurate off-the-shelf replacement for the inaccurate 2-parameter fit in the vendor's software.
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Affiliation(s)
- Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic.
| | - Pavla Hanzlíková
- Department of Radiology, Faculty of Medicine and Dentistry, Palacky University, tř. Svobody 8, 77126, Olomouc, Czech Republic
| | - Tuan Trinh
- Department of Urology, Medical School, Masaryk University, Jihlavská 20, 62500, Brno, Czech Republic
| | - Dalibor Pacík
- Department of Urology, University Hospital Brno, Jihlavská 20, 62500, Brno, Czech Republic
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9
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Kovaříková J, Baranová I, Laco J, Rozkošová K, Vošmíková H, Vošmík M, Dundr P, Němejcová K, Michálek J, Palička V, Chmelařová M. Deregulation of Selected MicroRNAs in Sinonasal Squamous Cell Carcinoma: Searching for Potential Prognostic Biomarkers. Folia Biol (Praha) 2019; 65:142-151. [PMID: 31638561] [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: 06/10/2023]
Abstract
Sinonasal carcinomas are head and neck tumours arising from the nasal cavity and paranasal sinuses characterized by unfavourable outcome, difficult treatment, diagnosis and prognosis. MicroRNAs are key molecules in the regulation of development and progression of cancer and their expression profiles could be used as prognostic biomarkers, to predict the patients' survival and response to treatment. In this study, we used quantitative real‑time PCR with TaqMan® Advanced miRNA Assays to investigate the relative expression values of selected micro- RNAs in a unique set of formalin-fixed paraffin-embedded tissue samples obtained from 46 patients with sinonasal squamous cell carcinoma. Our results showed statistically significant up-regulation of three mature microRNAs: miR-9-5p (fold change: 6.80), miR-9-3p (fold change: 3.07) and let-7d (fold change: 3.93) in sinonasal carcinoma patients. Kaplan-Meier survival analysis and logrank test identified association between higher expression of miR-9-5p and longer survival of the patients (P = 0.0264). Lower expression of let-7d was detected in the patients with impaired survival, and higher expression of miR-137 was linked to shorter survival of the patients. We also identified several correlations between expression of the studied microRNAs and recorded clinicopathological data. Higher expression of miR-137 and lower expression of let-7d correlated with local recurrence (P = 0.045 and P = 0.025); lower expression of miR-9-5p and higher expression of miR-155-5p correlated with regional recurrence (P = 0.045 and P = 0.036). Higher expression of miR-9-3p correlated with occupational risk (P = 0.031), presence of vascular invasion (P = 0.013) and perineural invasion (P = 0.031). Higher expression of miR-155-5p was present in the samples originating from maxillary sinus (P = 0.011), cN1-3 classified tumours (P = 0.009) and G2-3 classified tumours (P = 0.017). In conclusion, our study supports the hypothesis of future prospect to use expression of miRNAs as prognostic biomarkers of squamous cell sinonasal carcinoma. In particular, miR-9-5p and miR-9-3p seem to be important members of the sinonasal cancer pathogenesis.
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Affiliation(s)
- J Kovaříková
- Institute of Clinical Biochemistry and Diagnostics, Charles University, Faculty of Medicine in Hradec Králové and University Hospital Hradec Králové, Czech Republic
| | - I Baranová
- Institute of Clinical Biochemistry and Diagnostics, Charles University, Faculty of Medicine in Hradec Králové and University Hospital Hradec Králové, Czech Republic
| | - J Laco
- The Fingerland Department of Pathology, Charles University, Faculty of Medicine in Hradec Králové and University Hospital Hradec Králové, Czech Republic
| | - K Rozkošová
- The Fingerland Department of Pathology, Charles University, Faculty of Medicine in Hradec Králové and University Hospital Hradec Králové, Czech Republic
| | - H Vošmíková
- The Fingerland Department of Pathology, Charles University, Faculty of Medicine in Hradec Králové and University Hospital Hradec Králové, Czech Republic
| | - M Vošmík
- Department of Oncology and Radiotherapy, Charles University, Faculty of Medicine in Hradec Králové and University Hospital Hradec Králové, Czech Republic
| | - P Dundr
- Department of Pathology, Charles University, First Faculty of Medicine and General University Hospital in Prague, Czech Republic
| | - K Němejcová
- Department of Pathology, Charles University, First Faculty of Medicine and General University Hospital in Prague, Czech Republic
| | - J Michálek
- Department of Clinical and Molecular Pathology, Palacky University Olomouc, Faculty of Medicine and Dentistry and University Hospital Olomouc, Czech Republic
| | - V Palička
- Institute of Clinical Biochemistry and Diagnostics, Charles University, Faculty of Medicine in Hradec Králové and University Hospital Hradec Králové, Czech Republic
| | - M Chmelařová
- Institute of Clinical Biochemistry and Diagnostics, Charles University, Faculty of Medicine in Hradec Králové and University Hospital Hradec Králové, Czech Republic
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Šimák J, Michálek J. Numerical and Experimental Study of a Cooling for Vanes in a Small Turbine Engine. EPJ Web of Conferences 2016. [DOI: 10.1051/epjconf/201611402106] [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: 11/14/2022] Open
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11
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Chmelařová M, Sirák I, Mžik M, Sieglová K, Vošmiková H, Dundr P, Němejcová K, Michálek J, Vošmik M, Palička V, Laco J. Importance of Tumour Suppressor Gene Methylation in Sinonasal Carcinomas. Folia Biol (Praha) 2016; 62:110-119. [PMID: 27516190] [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: 06/06/2023]
Abstract
Epigenetic changes are considered to be a frequent event during tumour development. Hypermethylation of promoter CpG islands represents an alternative mechanism for inactivation of tumour suppressor genes, DNA repair genes, cell cycle regulators and transcription factors. The aim of this study was to investigate promoter methylation of specific genes in samples of sinonasal carcinoma by comparison with normal sinonasal tissue. To search for epigenetic events we used methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) to compare the methylation status of 64 tissue samples of sinonasal carcinomas with 19 control samples. We also compared the human papilloma virus (HPV) status with DNA methylation. Using a 20% cut-off for methylation, we observed significantly higher methylation in RASSF1, CDH13, ESR1 and TP73 genes in the sinonasal cancer group compared with the control group. HPV positivity was found in 15/64 (23.4 %) of all samples in the carcinoma group and in no sample in the control group. No correlation was found between DNA methylation and HPV status. In conclusion, our study showed that there are significant differences in promoter methylation in the RASSF1, ESR 1, TP73 and CDH13 genes between sinonasal carcinoma and normal sinonasal tissue, suggesting the importance of epigenetic changes in these genes in carcinogenesis of the sinonasal area. These findings could be used as prognostic factors and may have implications for future individualised therapies based on epigenetic changes.
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Affiliation(s)
- M Chmelařová
- Institute for Clinical Biochemistry and Diagnostics, Charles University in Prague - Faculty of Medicine in Hradec Králové and University Hospital in Hradec Králové, Czech Republic
| | - I Sirák
- Department of Oncology and Radiotherapy, Charles University in Prague - Faculty of Medicine in Hradec Králové and University Hospital in Hradec Králové, Czech Republic
| | - M Mžik
- Institute for Clinical Biochemistry and Diagnostics, Charles University in Prague - Faculty of Medicine in Hradec Králové and University Hospital in Hradec Králové, Czech Republic
| | - K Sieglová
- The Fingerland Department of Pathology, Charles University in Prague - Faculty of Medicine in Hradec Králové and University Hospital in Hradec Králové, Czech Republic
| | - H Vošmiková
- The Fingerland Department of Pathology, Charles University in Prague - Faculty of Medicine in Hradec Králové and University Hospital in Hradec Králové, Czech Republic
| | - P Dundr
- Institute of Pathology, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Czech Republic
| | - K Němejcová
- Institute of Pathology, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Czech Republic
| | - J Michálek
- Department of Clinical and Molecular Pathology, Palacký University Olomouc, Faculty of Medicine and Dentistry and University Hospital Olomouc, Czech Republic
| | - M Vošmik
- Department of Oncology and Radiotherapy, Charles University in Prague - Faculty of Medicine in Hradec Králové and University Hospital in Hradec Králové, Czech Republic
| | - V Palička
- Institute for Clinical Biochemistry and Diagnostics, Charles University in Prague - Faculty of Medicine in Hradec Králové and University Hospital in Hradec Králové, Czech Republic
| | - J Laco
- The Fingerland Department of Pathology, Charles University in Prague - Faculty of Medicine in Hradec Králové and University Hospital in Hradec Králové, Czech Republic
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Michálek J. Total Variation-Based Reduction of Streak Artifacts, Ring Artifacts and Noise in 3D Reconstruction from Optical Projection Tomography. Microsc Microanal 2015; 21:1602-1615. [PMID: 26459139 DOI: 10.1017/s1431927615015226] [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] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Optical projection tomography (OPT) is a computed tomography technique at optical frequencies for samples of 0.5-15 mm in size, which fills an important "imaging gap" between confocal microscopy (for smaller samples) and large-sample methods such as fluorescence molecular tomography or micro magnetic resonance imaging. OPT operates in either fluorescence or transmission mode. Two-dimensional (2D) projections are taken over 360° with a fixed rotational increment around the vertical axis. Standard 3D reconstruction from 2D OPT uses the filtered backprojection (FBP) algorithm based on the Radon transform. FBP approximates the inverse Radon transform using a ramp filter that spreads reconstructed pixels to neighbor pixels thus producing streak and other types of artifacts, as well as noise. Artifacts increase the variation of grayscale values in the reconstructed images. We present an algorithm that improves the quality of reconstruction even for a low number of projections by simultaneously minimizing the sum of absolute brightness changes in the reconstructed volume (the total variation) and the error between measured and reconstructed data. We demonstrate the efficiency of the method on real biological data acquired on a dedicated OPT device.
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Affiliation(s)
- Jan Michálek
- Department of Biomathematics,Institute of Physiology of the Czech Academy of Sciences,Videnska 1083,14220 Prague 4,Czech Republic
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13
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Woo YH, Ansari H, Otto TD, Klinger CM, Kolisko M, Michálek J, Saxena A, Shanmugam D, Tayyrov A, Veluchamy A, Ali S, Bernal A, del Campo J, Cihlář J, Flegontov P, Gornik SG, Hajdušková E, Horák A, Janouškovec J, Katris NJ, Mast FD, Miranda-Saavedra D, Mourier T, Naeem R, Nair M, Panigrahi AK, Rawlings ND, Padron-Regalado E, Ramaprasad A, Samad N, Tomčala A, Wilkes J, Neafsey DE, Doerig C, Bowler C, Keeling PJ, Roos DS, Dacks JB, Templeton TJ, Waller RF, Lukeš J, Oborník M, Pain A. Chromerid genomes reveal the evolutionary path from photosynthetic algae to obligate intracellular parasites. eLife 2015; 4:e06974. [PMID: 26175406 PMCID: PMC4501334 DOI: 10.7554/elife.06974] [Citation(s) in RCA: 139] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2015] [Accepted: 06/16/2015] [Indexed: 12/18/2022] Open
Abstract
The eukaryotic phylum Apicomplexa encompasses thousands of obligate intracellular parasites of humans and animals with immense socio-economic and health impacts. We sequenced nuclear genomes of Chromera velia and Vitrella brassicaformis, free-living non-parasitic photosynthetic algae closely related to apicomplexans. Proteins from key metabolic pathways and from the endomembrane trafficking systems associated with a free-living lifestyle have been progressively and non-randomly lost during adaptation to parasitism. The free-living ancestor contained a broad repertoire of genes many of which were repurposed for parasitic processes, such as extracellular proteins, components of a motility apparatus, and DNA- and RNA-binding protein families. Based on transcriptome analyses across 36 environmental conditions, Chromera orthologs of apicomplexan invasion-related motility genes were co-regulated with genes encoding the flagellar apparatus, supporting the functional contribution of flagella to the evolution of invasion machinery. This study provides insights into how obligate parasites with diverse life strategies arose from a once free-living phototrophic marine alga. DOI:http://dx.doi.org/10.7554/eLife.06974.001 Single-celled parasites cause many severe diseases in humans and animals. The apicomplexans form probably the most successful group of these parasites and include the parasites that cause malaria. Apicomplexans infect a broad range of hosts, including humans, reptiles, birds, and insects, and often have complicated life cycles. For example, the malaria-causing parasites spread by moving from humans to female mosquitoes and then back to humans. Despite significant differences amongst apicomplexans, these single-celled parasites also share a number of features that are not seen in other living species. How and when these features arose remains unclear. It is known from previous work that apicomplexans are closely related to single-celled algae. But unlike apicomplexans, which depend on a host animal to survive, these algae live freely in their environment, often in close association with corals. Woo et al. have now sequenced the genomes of two photosynthetic algae that are thought to be close living relatives of the apicomplexans. These genomes were then compared to each other and to the genomes of other algae and apicomplexans. These comparisons reconfirmed that the two algae that were studied were close relatives of the apicomplexans. Further analyses suggested that thousands of genes were lost as an ancient free-living algae evolved into the apicomplexan ancestor, and further losses occurred as these early parasites evolved into modern species. The lost genes were typically those that are important for free-living organisms, but are either a hindrance to, or not needed in, a parasitic lifestyle. Some of the ancestor's genes, especially those that coded for the building blocks of flagella (structures which free-living algae use to move around), were repurposed in ways that helped the apicomplexans to invade their hosts. Understanding this repurposing process in greater detail will help to identify key molecules in these deadly parasites that could be targeted by drug treatments. It will also offer answers to one of the most fascinating questions in evolutionary biology: how parasites have evolved from free-living organisms. DOI:http://dx.doi.org/10.7554/eLife.06974.002
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Affiliation(s)
- Yong H Woo
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Hifzur Ansari
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Thomas D Otto
- Parasite Genomics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom
| | | | - Martin Kolisko
- Canadian Institute for Advanced Research, Department of Botany, University of British Columbia, Vancouver, Canada
| | - Jan Michálek
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Alka Saxena
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | | | - Annageldi Tayyrov
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Alaguraj Veluchamy
- Ecology and Evolutionary Biology Section, Institut de Biologie de l'Ecole Normale Supérieure, CNRS UMR8197 INSERM U1024, Paris, France
| | - Shahjahan Ali
- Bioscience Core Laboratory, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Axel Bernal
- Department of Biology, University of Pennsylvania, Philadelphia, United States
| | - Javier del Campo
- Canadian Institute for Advanced Research, Department of Botany, University of British Columbia, Vancouver, Canada
| | - Jaromír Cihlář
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Pavel Flegontov
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | | | - Eva Hajdušková
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Aleš Horák
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Jan Janouškovec
- Canadian Institute for Advanced Research, Department of Botany, University of British Columbia, Vancouver, Canada
| | | | - Fred D Mast
- Seattle Biomedical Research Institute, Seattle, United States
| | - Diego Miranda-Saavedra
- Centro de Biología Molecular Severo Ochoa, CSIC/Universidad Autónoma de Madrid, Madrid, Spain
| | - Tobias Mourier
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
| | - Raeece Naeem
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Mridul Nair
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Aswini K Panigrahi
- Bioscience Core Laboratory, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Neil D Rawlings
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Eriko Padron-Regalado
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Abhinay Ramaprasad
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Nadira Samad
- School of Botany, University of Melbourne, Parkville, Australia
| | - Aleš Tomčala
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Jon Wilkes
- Wellcome Trust Centre For Molecular Parasitology, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Daniel E Neafsey
- Broad Genome Sequencing and Analysis Program, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Christian Doerig
- Department of Microbiology, Monash University, Clayton, Australia
| | - Chris Bowler
- Ecology and Evolutionary Biology Section, Institut de Biologie de l'Ecole Normale Supérieure, CNRS UMR8197 INSERM U1024, Paris, France
| | - Patrick J Keeling
- Canadian Institute for Advanced Research, Department of Botany, University of British Columbia, Vancouver, Canada
| | - David S Roos
- Department of Biology, University of Pennsylvania, Philadelphia, United States
| | - Joel B Dacks
- Department of Cell Biology, University of Alberta, Edmonton, Canada
| | - Thomas J Templeton
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Ross F Waller
- School of Botany, University of Melbourne, Parkville, Australia
| | - Julius Lukeš
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Miroslav Oborník
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Arnab Pain
- Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
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14
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Peregrin JH, Janoušek R, Kautznerová D, Oliverius M, Sticová E, Přádný M, Michálek J. A comparison of portal vein embolization with poly(2-hydroxyethylmethacrylate) and a histoacryl/lipiodol mixture in patients scheduled for extended right hepatectomy. Physiol Res 2015; 64:841-8. [PMID: 26047385 DOI: 10.33549/physiolres.932992] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
To determine whether PHEMA [poly(2-hydroxyethylmethacrylate)] is suitable for portal vein embolization in patients scheduled to right hepatectomy and whether it is as effective as the currently used agent (a histoacryl/lipiodol mixture). Two groups of nine patients each scheduled for extended right hepatectomy for primary or secondary hepatic tumor, had right portal vein embolization in an effort to induce future liver remnant (FLR) hypertrophy. One group had embolization with PHEMA, the other one with the histoacryl/lipiodol mixture. In all patients, embolization was performed using the right retrograde transhepatic access. Embolization was technically successful in all 18 patients, with no complication related to the embolization agent. Eight patients of either group developed FLR hypertrophy allowing extended right hepatectomy. Likewise, one patient in each group had recanalization of a portal vein branch. Histology showed that both embolization agents reach the periphery of portal vein branches, with PHEMA penetrating somewhat deeper into the periphery. PHEMA has been shown to be an agent suitable for embolization in the portal venous system comparable with existing embolization agent (histoacryl/lipiodol mixture).
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Affiliation(s)
- J H Peregrin
- Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic.
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15
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Flegontov P, Michálek J, Janouškovec J, Lai DH, Jirků M, Hajdušková E, Tomčala A, Otto TD, Keeling PJ, Pain A, Oborník M, Lukeš J. Divergent mitochondrial respiratory chains in phototrophic relatives of apicomplexan parasites. Mol Biol Evol 2015; 32:1115-31. [PMID: 25660376 DOI: 10.1093/molbev/msv021] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.9] [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: 01/15/2023] Open
Abstract
Four respiratory complexes and ATP-synthase represent central functional units in mitochondria. In some mitochondria and derived anaerobic organelles, a few or all of these respiratory complexes have been lost during evolution. We show that the respiratory chain of Chromera velia, a phototrophic relative of parasitic apicomplexans, lacks complexes I and III, making it a uniquely reduced aerobic mitochondrion. In Chromera, putative lactate:cytochrome c oxidoreductases are predicted to transfer electrons from lactate to cytochrome c, rendering complex III unnecessary. The mitochondrial genome of Chromera has the smallest known protein-coding capacity of all mitochondria, encoding just cox1 and cox3 on heterogeneous linear molecules. In contrast, another photosynthetic relative of apicomplexans, Vitrella brassicaformis, retains the same set of genes as apicomplexans and dinoflagellates (cox1, cox3, and cob).
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Affiliation(s)
- Pavel Flegontov
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic Life Science Research Centre, Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czech Republic
| | - Jan Michálek
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic
| | - Jan Janouškovec
- Department of Botany, University of BC, Vancouver, Canada Canadian Institute for Advanced Research, Toronto, ON, Canada
| | - De-Hua Lai
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Milan Jirků
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic
| | - Eva Hajdušková
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Aleš Tomčala
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - Thomas D Otto
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Patrick J Keeling
- Department of Botany, University of BC, Vancouver, Canada Canadian Institute for Advanced Research, Toronto, ON, Canada
| | - Arnab Pain
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia
| | - Miroslav Oborník
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic Institute of Microbiology, Czech Academy of Sciences, Třeboň, Czech Republic
| | - Julius Lukeš
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic Canadian Institute for Advanced Research, Toronto, ON, Canada
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16
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Abstract
3D microscopy and image analysis provide reliable measurements of length, branching, density, tortuosity and orientation of tubular structures in biological samples. We present a survey of methods for analysis of large samples by measurement of local differences in geometrical characteristics. The methods are demonstrated on the structure of the capillary bed in a rat brain.
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Affiliation(s)
- J Janáček
- Department of Biomathematics, Institute of Physiology Academy of Sciences of the Czech Republic, Prague, Czech Republic.
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17
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Pašová P, Skorkovská K, Michálek J. [Comparison of central corneal thickness and keratometric measurements using the Scheimpflug HR imaging system, laser interferometry, automatic keratometry and ultrasound pachymetry]. Cesk Slov Oftalmol 2012; 68:116-119. [PMID: 23214460] [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: 06/01/2023]
Abstract
INTRODUCTION The aim of our study was to compare keratometry and central corneal thickness measurements obtained with three different ophthalmic devices and to decide if they can be used interchangeably in clinical practice. METHODS 43 healthy persons were included in the study (29 women and 14 men, average age 25 ± 3.5 years). Central corneal thickness (CCT) was measured with the Scheimpflug HR imaging system (Pentacam), Allegro BioGraph and with ultrasound pachymetry (RXP OcuScan). Keratometry in two main meridians of the cornea (K1, K2) was measured with Pentacam, Allegro BioGraph and automated keratometry. RESULTS The mean difference in K1-readings was 0.01 ± 0.31 D for BioGraph vs. automated keratometry, 0.06 ± 0.23 D for BioGraph vs. Pentacam and 0.05 ± 0.34 D for automated keratometry and Pentacam. The mean difference in K2-readings was 0.29 ± 0.45 D for BioGraph vs. automated keratometry, 0.11 ± 0.28 D for BioGraph vs. Pentacam and 0.19 ± 0.44 D for automated keratometry and Pentacam. The interdevice differences were in all cases statistically significant (p < 0.05). The mean difference in CCT was 4.57 ± 7.84 μm for BioGraph vs. ultrasound, 4.33 ± 7.55 μm for BioGraph vs. Pentacam and 8.90 ± 7.49 μm for ultrasound vs. Pentacam. The interdevice differences in CCT were also statistically significant (p < 0.05). CONCLUSION Our results suggest that the measurements of keratometry and CCT may differ significantly between the tested machines and therefore should not be used interchangeably in clinical practice.
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Affiliation(s)
- P Pašová
- Zilinske ocne centrum VIKOM, Zilina.
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18
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Ambrůzová B, Rédová M, Michálek J, Sachlová M, Slabý O. [New knowledge of the pathogenesis of Crohn's disease]. Vnitr Lek 2012; 58:291-298. [PMID: 22559803] [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: 05/31/2023]
Abstract
Crohns disease is a complex chronic inflammatory disease of the gastrointestinal tract with multifactorial pathogenesis. Over the recent years, there has been rather a sharp increase in the incidence of Crohn's disease and, even though this disease had been known for some time, the cause remains unknown. Studies exploring genetic basis of Crohn's disease have provided new knowledge of the pathogenesis of this disease, suggesting that this may be associated with a failure of mechanisms behind symbiosis of gut microflora and intestinal mucosal immune system. Crohn's disease seems to be caused by inadequate immune response to intestinal flora in genetically predisposed individuals. Crohn's disease has been linked to a number of genes. Many of them are related to the modulation of non-specific immune response, defects of which are considered to be key in Crohn's disease pathogenesis. The aim of this review paper is to summarize the new knowledge on the pathogenesis of Crohn's disease at the level of polymorphisms of the NOD2, ATG16L1 genes and the IL23-Th17-lymfocytes signalling pathway genes and to consider further research directions in this disease.
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Affiliation(s)
- B Ambrůzová
- Advanced Cell Immunotherapy Unit, Lekarska fakulta MU Brno
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19
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Abstract
When biological specimens are cut into physical sections for three-dimensional (3D) imaging by confocal laser scanning microscopy, the slices may get distorted or ruptured. For subsequent 3D reconstruction, images from different physical sections need to be spatially aligned by optimization of a function composed of a data fidelity term evaluating similarity between the reference and target images, and a regularization term enforcing transformation smoothness. A regularization term evaluating the total variation (TV), which enables the registration algorithm to account for discontinuities in slice deformation (ruptures), while enforcing smoothness on continuously deformed regions, was proposed previously. The function with TV regularization was optimized using a graph-cut (GC) based iterative solution. However, GC may generate visible registration artifacts, which impair the 3D reconstruction. We present an alternative, multilabel TV optimization algorithm, which in the examined samples prevents the artifacts produced by GC. The algorithm is slower than GC but can be sped up several times when implemented in a multiprocessor computing environment. For image pairs with uneven brightness distribution, we introduce a reformulation of the TV-based registration, in which intensity-based data terms are replaced by comparison of salient features in the reference and target images quantified by local image entropies.
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Affiliation(s)
- Jan Michálek
- Institute of Physiology, Academy of Sciences of the Czech Republic, v.v.i., Department of Biomathematics, Vídeňská 1083, CZ-14220 Prague 4, Czech Republic.
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20
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Michálek J, Capek M, Kubínová L. Compensation of inhomogeneous fluorescence signal distribution in 2D images acquired by confocal microscopy. Microsc Res Tech 2011; 74:831-8. [PMID: 23939671 DOI: 10.1002/jemt.20965] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [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: 09/06/2010] [Accepted: 10/04/2010] [Indexed: 11/08/2022]
Abstract
In images acquired by confocal laser scanning microscopy (CLSM), regions corresponding to the same concentration of fluorophores in the specimen should be mapped to the same grayscale levels. However, in practice, due to multiple distortion effects, CLSM images of even homogeneous specimen regions suffer from irregular brightness variations, e.g., darkening of image edges and lightening of the center. The effects are yet more pronounced in images of real biological specimens. A spatially varying grayscale map complicates image postprocessing, e.g., in alignment of overlapping regions of two images and in 3D reconstructions, since measures of similarity usually assume a spatially independent grayscale map. We present a fast correction method based on estimating a spatially variable illumination gain, and multiplying acquired CLSM images by the inverse of the estimated gain. The method does not require any special calibration of reference images since the gain estimate is extracted from the CLSM image being corrected itself. The proposed approach exploits two types of morphological filters: the median filter and the upper Lipschitz cover. The presented correction method, tested on images of both artificial (homogeneous fluorescent layer) and real biological specimens, namely sections of a rat embryo and a rat brain, proved to be very fast and yielded a significant visual improvement.
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Affiliation(s)
- Jan Michálek
- Department of Biomathematics, Institute of Physiology, Academy of Sciences of the Czech Republic, v.v.i., Vídeňská 1083, 14220 Prague 4, Czech Republic.
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21
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Gatenholm P, Michálek J, Vacík J. Synthesis and characterization of highly wettable hydrogel coatings for immobilization of marine bacteria. ACTA ACUST UNITED AC 2011. [DOI: 10.1002/masy.19961090112] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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22
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Cejka C, Pláteník J, Sirc J, Ardan T, Michálek J, Brůnová B, Čejková J. Changes of corneal optical properties after UVB irradiation investigated spectrophotometrically. Physiol Res 2009; 59:591-597. [PMID: 19929139 DOI: 10.33549/physiolres.931867] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Ozone depletion leads to an increase in UV rays of solar radiation reaching the surface of the Earth which is harmful to biological systems. Of the eye, the cornea is directly open to increased amount of UV rays of which mainly UVB rays are capable to induce reactive oxygen species damaging the cells. Previous studies showed that the irradiation of the cornea with UVB rays leads to morphological as well as metabolic disturbances of the cornea. Also, corneal hydration and corneal light absorption are increased after UVB rays. These changes were observed after five days of repeated irradiation of the cornea with UVB rays. The aim of the present paper was to examine how early the changes of corneal hydration and light absorption occur after UVB irradiation. The rabbit corneas were irradiated with UVB rays for one, two, three or four days. Corneal light absorption was examined spectrophotometrically and corneal hydration measured by pachymeter (as corneal thickness). Results show that changes of corneal hydration and light absorption appear early after UVB irradiation and increase along with the number of irradiations. In conclusion, irradiation of the rabbit cornea with UVB rays leads to harmful changes of its optical properties.
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Affiliation(s)
- C Cejka
- Laboratory of Eye Histochemistry and Pharmacology, Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Prague, Czech Republic
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23
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Hejcl A, Lesný P, Prádný M, Sedý J, Zámecník J, Jendelová P, Michálek J, Syková E. Macroporous hydrogels based on 2-hydroxyethyl methacrylate. Part 6: 3D hydrogels with positive and negative surface charges and polyelectrolyte complexes in spinal cord injury repair. J Mater Sci Mater Med 2009; 20:1571-1577. [PMID: 19252968 DOI: 10.1007/s10856-009-3714-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2008] [Accepted: 02/09/2009] [Indexed: 05/27/2023]
Abstract
Macroporous hydrogels are artificial biomaterials commonly used in tissue engineering, including central nervous system (CNS) repair. Their physical properties may be modified to improve their adhesion properties and promote tissue regeneration. We implanted four types of hydrogels based on 2-hydroxyethyl methacrylate (HEMA) with different surface charges inside a spinal cord hemisection cavity at the Th8 level in rats. The spinal cords were processed 1 and 6 months after implantation and histologically evaluated. Connective tissue deposition was most abundant in the hydrogels with positively-charged functional groups. Axonal regeneration was promoted in hydrogels carrying charged functional groups; hydrogels with positively charged functional groups showed increased axonal ingrowth into the central parts of the implant. Few astrocytes grew into the hydrogels. Our study shows that HEMA-based hydrogels carrying charged functional groups improve axonal ingrowth inside the implants compared to implants without any charge. Further, positively charged functional groups promote connective tissue infiltration and extended axonal regeneration inside a hydrogel bridge.
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Affiliation(s)
- A Hejcl
- Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Vídenská 1083, 14220 Prague 4, Czech Republic.
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24
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Ocadlíková D, Zahradová L, Kovárová L, Smejkalová J, Pour L, Vidláková P, Kyjovská D, Moravcová J, Rycová M, Novotná H, Jelínková I, Penka M, Michálek J, Hájek R. [The preparation of anticancer vaccine for patients with multiple myeloma on the base of monoclonal immunoglobulin loaded dendritic cells]. Klin Onkol 2009; 22:67-72. [PMID: 19522376] [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: 05/27/2023]
Abstract
BACKGROUND On June 2006, phase II clinical trial focused on anticancer vaccination of multiple myeloma patients, was started. On September 2007, the immune and clinical response evaluation of first four patients was finished.The anticancer vaccine contained dendritic cells loaded with monoclonal immunoglobulin produced by myeloma cells. METHODS AND PATIENTS Within the frame of phase II clinical trial were vaccinated four myeloma patients with stable disease. It was administered six vaccines for each patient, monthly. The dendritic cells were cultured from the patient's peripheral blood mononuclear cells and loaded with autologous monoclonal immunoglobulin under the good manufacturing practice conditions. After the safety and quality control, the satisfactory vaccine was administered to the patient. The functional characteristic of dendritic cells was evaluated using flow cytometry, the immune response was evaluated using ELISpot. The clinical response was monitored using monoclonal immunoglobulin concentration in patient's sera. RESULTS AND CONCLUSION The immune response detected using ELISpot was observed in 3/4 patients. The monoclonal immunoglobulin concentration was changeable for all twelve months, but never exceeded the range of 25% for minimal clinical response achievement. During the vaccination, no significant toxicities or negative side-effects were observed. The clinical trial is going on with vaccination other patients with multiple myeloma.
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Affiliation(s)
- D Ocadlíková
- Laborator experimentální hematologie a bunecné imunoterapie, Oddelení klinické hematologie, FN Brno.
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25
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Slabý O, Svoboda M, Michálek J, Vyzula R. [DNA and microRNA microarray technologies in diagnostics and prediction for patients with renal cell carcinoma]. Klin Onkol 2009; 22:202-209. [PMID: 19886357] [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: 05/28/2023]
Abstract
Renal cell carcinoma accounts for approximately 3% of adult cancers and has the highest lethality of urological malignancies. Research focusing on carcinogenesis and development of renal cell carcinoma has led to the identification of the key signalling pathways and consequently targeted cancer therapy which improves time to progression or overall survival of renal cell carcinoma patients. Today, microarray technologies are some of the most efficient methods used in gene expression studies. Through one microarray experiment we can simultaneously determine the expression of thousands of genes, thus facilitating research of examined biological models. The most frequently used of the microarray technologies are DNA microarrays enabling global analysis of the mRNA (messenger RNA) expression, while recently, microarray platforms modified to detect short non-coding RNAs (microRNAs) have been employed (microRNA microarrays). MicroRNAs significantly affect the behaviour of tumour cells by post-transcriptional regulation of the gene expression. In the research into renal cell carcinoma, microarray technologies have been applied in more than twenty studies over the past five years. These papers describe the potential of microarrays to distinguish tumour tissue from normal renal parenchyma, to classify renal cell carcinomas according to histological subtypes, to identify expression profiles predicting metastasizing in primary renal tumours, and to determine the prognosis of particular renal cell carcinoma patients. The aim of this review is to summarize the results from microarray studies of renal cell carcinoma realized to date and to present their potential usage in diagnostic and therapeutic protocols.
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Affiliation(s)
- O Slabý
- Klinika komplexní onkologické péce, Masarykův onkologický ujstav, Brno.
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Cadková I, Doudová L, Michálek J, Huvar I. [Risk factors for postsurgical uroinfection in gynecology]. Ceska Gynekol 2008; 73:241-247. [PMID: 18711964] [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: 05/26/2023]
Abstract
OBJECTIVE This study eims to evaluate risk factors for postsurgical uroinfection (UTI) in gynecology. DESIGN Clinical retrospective trial. SETTING Obstetrics and Gynecology Department, Merciful Brothers Hospital, Brno. MATERIALS AND METHODS All of 290 women who underwent hysterectomy and/or anterior vaginal repair (with or without anti-incontinence operation) in our hospital during the year 2005 were studied. The following data were noted: age, weight, anamnestic UTI, diabetes, other serious morbidity, moving disorders, estrogene deficiency, the type of surgery, the type of catheter and the duration of its indweling, intra/postoperative complications, urologic symptoms and urine analysis including bacteriology on the 6th postoperative day. There were excluded cases with antibiotic therapy (due to non-urological indications) from the study. The risk factors were assessed on the rest of 262 women, in two subgroups according to the catheter type (Foley/minicatheter), as there were remarcable differences in the indwelling time and other characteristics. "Mini-catheter" (a thin transurethral catheter) enables spontaneous voiding as well as measuring the postmiction residuum. It was used in case of anterior vaginal repair or Burch operation and extracted as soon as the voiding function had been restored, mostly on the 2nd-3rd day. The Foley was used in the others, mostly for one day. The unidimensional (Fisher and Mann-Whitney test) and multidimensional (logit model, Walds statistic) analyses were performed. The influence of the type of catheter itself was analysed within an indwelling time period (20-32 hours) in which women of both subgroups were present. RESULTS The Foley group (115 women, indwelling time 16-32 hours) had 3.5% UTI, none of studied factors was estimated as significant. In the mini-catheter group (147 women, catheterisation for 20-234 hours) was 35.4% UTI, with two risk factors: the time of catheterisation (p = 0.000029) and complications (p = 0.021515). The statistic model we have used (logit analysis) predicts UTI with sensitivity 61.5 and specificity 89.5. There was no difference in the risk of UTI between the two types of used catheters in case of equal time of their insertion. CONCLUSION Postsurgical UTI was connected significantly with the duration of catheterisation and intra/postoperative complications. In case of short time catheterisation (up to 32 hours), however, the percentage of UTI was low and no risk factor was assessed as significant.
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Affiliation(s)
- I Cadková
- Gynekologicko-porodnické oddĕlení Nemocnice Milosrdných bratrí, Brno.
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Hejcl A, Lesný P, Prádný M, Michálek J, Jendelová P, Stulík J, Syková E. Biocompatible hydrogels in spinal cord injury repair. Physiol Res 2008; 57 Suppl 3:S121-S132. [PMID: 18481908 DOI: 10.33549/physiolres.931606] [Citation(s) in RCA: 78] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Spinal cord injury results in a permanent neurological deficit due to tissue damage. Such a lesion is a barrier for "communication" between the brain and peripheral tissues, effectors as well as receptors. One of the primary goals of tissue engineering is to bridge the spinal cord injury and re-establish the damaged connections. Hydrogels are biocompatible implants used in spinal cord injury repair. They can create a permissive environment and bridge the lesion cavities by providing a scaffold for the regeneration of neurons and their axons, glia and other tissue elements. The advantage of using artificial materials is the possibility to modify their physical and chemical properties in order to develop the best implant suitable for spinal cord injury repair. As a result, several types of hydrogels have been tested in experimental studies so far. We review our work that has been done during the last 5 years with various types of hydrogels and their applications in experimental spinal cord injury repair.
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Affiliation(s)
- A Hejcl
- Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Prague, Czech Republic
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28
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Ocadlíková D, Kovárová L, Hájek R, Michálek J. [The preparation of myeloma-specific T cells activated with dendritic cells loaded with nonapeptides derived from mucin protein MUC1 and catalytic subunit of telomerase hTERT]. Klin Onkol 2008; 21:59-65. [PMID: 19102213] [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: 05/27/2023]
Abstract
BACKGROUND Multiple myeloma is an incurable hematological disease. High-dose chemotherapy including autologous stem cell transplantation is recently considered a standard therapy for myeloma. Unfortunately, a relapse of the disease is inevitable. Therefore, new approaches such as immunotherapy have been considered recently. A specific activation of cytotoxic T cells can be reached using dendritic cells loaded with tumor-specific antigens. The HLA-A2-specific nonapeptides as hTERT derived from catalytic subunit of telomerase and MUC1 derived from mucin protein can be used. DESIGN AND SUBJECTS Activation, identification, separation and expansion of myeloma-specific T cells from healthy HLA-A2 blood donors were tested in an in vitro study using hTERT and MUC1 nonapeptides as tumor-specific antigens. METHODS AND RESULTS T cells and dendritic cells were obtained from peripheral blood. T cells were repeatedly stimulated with hTERT and MUC1 nonapeptide-loaded dendritic cells. Activated myeloma-specific T cells produced interferon gamma and were evaluated by flow cytometry. The activated T cells were immunomagnetically separated and in vitro expanded to the number usable in clinical trials. CONCLUSIONS This study demonstrates feasibility of a specific activation, identification, separation and expansion of tumor-specific T cells that can be used in myeloma therapy.
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Affiliation(s)
- D Ocadlíková
- Laborator experimentální hematologie a bunecné imunoterapie, Oddelení klinické hematologie, FN Brno.
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Matejková E, Ocadlíková D, Smejkalová J, Muzíkova J, Raida L, Tousovská K, Pacasová R, Nenicková M, Tesarová E, Sterba J, Indrák K, Michálek J. [Selective depletion of alloreactive T cells and study of anti-tumor activity of specific T cell clones in patients with leukemia]. Klin Onkol 2008; 21:104-109. [PMID: 19097419] [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: 05/27/2023]
Abstract
BACKGROUND Graft-versus-host disease (GVHD) is a severe complication of allogeneic transplantation of hematopoietic stem cells. Donor T cells play a major role in GVHD leading to the host tissue damage, mainly the skin, liver, and gastrointestinal tract. A selective depletion using an anti-CD25 immunotoxin can eliminate harmful alloreactive T cells while preserving other donor T cells with antileukemic and antiinfectious reactivity. PATIENTS AND METHODS We performed 15 mixed lymphocyte reactions with clinical specimens from 12 patients with various types of leukemia (7x AML, 3x ALL, 1x CML, 1x CLL) and PBMC from 15 healthy volunteers from Transfusive station FN Brno Bohunice. RESULTS In our experiments we have demonstrated, that antileukemic (GVL) effect of donor, especially CD4+ T cells was well preserved (7.46%), while unfavourable alloreactive (GVH) reaction of donor T cells was completely removed. The graft-versus-host (GVH) reactivation of donor cells was negligible ever after repeated stimulation with irradiated patient's PBMC. CONCLUSION We have shown that anti-CD25 immunotoxin (IT), RFT5-SMPT-dgA, launched against alpha chain for human interleukin 2 (IL-2), led to long-term selective depletion of alloreactive donor T cell clones while their antileukemic activity was well preserved. Base on our results the clinical phase I/II study was designed. This study was initiated in year 2007 in three clinical centers in Czech Republic.
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Affiliation(s)
- E Matejková
- Univerzitní Centrum Bunecné Imunoterapie, Masarykova Univerzita, Brno.
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Kovárová L, Michálek J, Kýr M, Penka M, Hájek R. [Comparison of dendritic cells antigens in healthy volunteers and monoclonal gammopathy of undetermined significance and/or multiple myeloma patients]. Klin Onkol 2008; 21:20-25. [PMID: 19097411] [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: 05/27/2023]
Abstract
BACKGROUND Dendritic cells (DCs) are highly specialized antigen-presenting cells, which can be used for immunotherapy trials. Functionally normal DCs play a critical role in the activation and potentiation of antitumor antigen-specific responses. DESIGN AND SUBJECTS Maturation of DCs from 10 healthy donors, 14 monoclonal gammopathy of undetermined significance patients and 14 multiple myeloma patients was tested in an in vitro study. METHODS AND RESULTS DCs were generated from adherent mononuclear precursors of peripheral blood and cultured in presence of IL-4 and GM-CSF with human CD40Ligand stimulation. Serum-free or autologous serum conditions were used and expression of significant surface antigens, chemokines receptors and production of IL-12p70, were compared. We found no difference between groups under serum-free conditions with or without CD40L stimulation. Under autologous conditions we found negative effect on patients DCs manifested by reduction of some markers. The production of IL-12p70 was low and no difference in serum IL-6 levels between individual groups was found. CONCLUSION Under serum free conditions there was no difference between healthy volunteers, MGUS and patients, but CD40L stimulation did not lead to the full maturation ofDCs. Autologous patient serum had negative influence on DCs, with no definite dependance on the IL-6 level.
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Affiliation(s)
- L Kovárová
- Oddĕlení Klinické Hematologie - Laborator Experimentální Hematologie a Bunĕcné Imunoterapie (LEHABI), FN Brno, PMDV, Jihlavská 20, 625 00 Brno.
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Skorkovská S, Michálek J, Sedlacík M, Masková Z, Kocí J. [Correlation of the Heidelberg retinal tomograph, evaluation of the retinal nerve fiber layer and perimetry in the diagnosis of glaucoma]. Cesk Slov Oftalmol 2007; 63:403-414. [PMID: 18062164] [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: 05/25/2023]
Abstract
PURPOSE To assess the correlation of the selected structural and functional methods in the diagnosis of glaucoma. METHODS The study group (SG) of 40 patients with primary open angle glaucoma with no or early visual field changes was compared to the control group (CG) of 40 healthy persons of similar age in the first year of prospective longitudinal study. All participants underwent the examination by means of Heidelberg retinal tomograph, photography of retinal nerve fiber layer, standard white-on-white perimetry, and blue-on-yellow perimetry. Only one eye of each examined person was evaluated. Significance was assessed by means of non-parametric test (Mann-Whitney) and the correlation analysis (Spearman) was performed as well. RESULTS No significant differences in age, visual acuity, and refraction between SG and CG were found. The central corneal thickness (p< 0.05) and intraocular pressure (p< 0.01) were significantly different between both groups. The visual field mean sensitivity (MS) and mean defect (MD) of white-on-white perimetry differ significantly between SG and CG comparing to the visual field parameters of blue-on-yellow perimetry. HRT analysis found out significant parameters: cup area (CA), cup/disc ratio (C/D), rim/disc ratio (R/D), and rim volume (RV) (p< 0.05). Cup shape measure (CSM) and Mikelberg discrimination function (FSM) were significant as well (p< 0.01). The loss of retinal nerve fiber layer was significantly different (p< 0.01) between the glaucomatous and healthy eyes. Spearman's correlation analysis found out significant correlations (MS and MD) only in blue-on-yellow perimetry and CV and RV of HRT analysis by comparison of all healthy and glaucomatous eyes. Another significant correlations were found by comparison of the retinal nerve fiber layer loss to MS (p = 0.00) and MD (p = 0.03) of white-on-white perimetry. Some of HRT parameters: CA, RA, CD, RV, CSM, HVC and RNFL in the group of all 80 eyes were significantly correlated to retinal nerve fiber layer loss. In the group of glaucomatous eyes only, no significant correlations were found. CONCLUSION Combination of the structural and functional methods can positively improve diagnosis of early glaucoma and better recognize the progression of glaucomatous neuropathy of the optical nerve.
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Affiliation(s)
- S Skorkovská
- Klinika nemocí ocních a optometrie LF MU, Fakultní nemocnice U sv. Anny, Brno.
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Očadlíková D, Zahradová L, Kovářová L, Smejkalová J, Pour L, Vidláková P, Kyjovská D, Stejskalová A, Novotná H, Penka M, Michálek J, Hájek R. P135 Vaccination of myeloma patients with monoclonal immunoglobulin loaded dendritic cells: preclinical and first clinical results of a phase I/II clinical trial. Blood Rev 2007. [DOI: 10.1016/s0268-960x(07)70213-8] [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: 10/22/2022]
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Lesný P, Prádný M, Jendelová P, Michálek J, Vacík J, Syková E. Macroporous hydrogels based on 2-hydroxyethyl methacrylate. Part 4: growth of rat bone marrow stromal cells in three-dimensional hydrogels with positive and negative surface charges and in polyelectrolyte complexes. J Mater Sci Mater Med 2006; 17:829-33. [PMID: 16932865 DOI: 10.1007/s10856-006-9842-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2004] [Accepted: 10/21/2005] [Indexed: 05/11/2023]
Abstract
The growth of bone marrow stromal cells was assessed in vitro in macroporous hydrogels based on 2-hydro- xyethyl methacrylate (HEMA) copolymers with different electric charges. Copolymers of HEMA with sodium methacrylate (MA(-)) carried a negative electric charge, copolymers of HEMA with [2-(methacryloyloxy)ethyl] trimethylammonium chloride (MOETA(-)) carried a positive electric charge and terpolymers of HEMA, MA(-) and MOETA(+) carried both, positive and negative electric charges. The charges in the polyelectrolyte complexes were shielded by counter-ions. The hydrogels had similar porosities, based on a comparison of their diffusion parameters for small cations as measured by the real-time tetramethylammonium iontophoretic method of diffusion analysis. The cell growth was studied in the peripheral and central regions of the hydrogels at 2 hours and 2, 7, 14 and 28 days after cell seeding. Image analysis revealed the highest cellular density in the HEMA-MOETA(+) copolymers; most of the cells were present in the peripheral region of the hydrogels. A lower density of cells but no difference between the peripheral and central regions was observed in the HEMA-MA(-) copolymers and in polyelectrolyte complexes. This study showed that positively charged functional groups promote the adhesion of cells.
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Affiliation(s)
- P Lesný
- Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Prague, Czech Republic
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Prádný M, Lesný P, Smetana K, Vacík J, Slouf M, Michálek J, Syková E. Macroporous hydrogels based on 2-hydroxyethyl methacrylate. Part II. Copolymers with positive and negative charges, polyelectrolyte complexes. J Mater Sci Mater Med 2005; 16:767-73. [PMID: 15965748 DOI: 10.1007/s10856-005-2615-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2003] [Accepted: 12/17/2004] [Indexed: 05/03/2023]
Abstract
Crosslinked macroporous hydrogels based on 2-hydroxyethyl methacrylate (HEMA)-[2-(methacryloyloxy)ethyl]trimethylammonium chloride (MOETACl) copolymer, HEMA-MOETACl-methacrylic acid (MA) terpolymer, and on a polyelectrolyte complex of HEMA-MA copolymer with poly(MOETACl) were prepared. All the hydrogels were prepared in the presence of fractionated sodium chloride particles. The hydrogels were characterized by the number of pores and the total volume of all pores in unit volume, the average volume and the average diameter of single pore. Morphology of the hydrogels was investigated by confocal and scanning electron microscopy. The hydrogels based on polyelectrolyte complexes were also characterized by chemical composition. Homogeneous (non-porous) hydrogels with the same composition as macroporous hydrogels were prepared and characterized by their biocompatibility.
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Affiliation(s)
- M Prádný
- Institute of Macromolecular Chemistry, Academy of Sciences of the Czech Republic, 162 06, Prague 6, Czech Republic.
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Michálek J, Prádný M, Artyukhov A, Slouf M, Smetana K. Macroporous hydrogels based on 2-hydroxyethyl methacrylate. Part III. Hydrogels as carriers for immobilization of proteins. J Mater Sci Mater Med 2005; 16:783-6. [PMID: 15965750 DOI: 10.1007/s10856-005-2617-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2003] [Accepted: 12/17/2004] [Indexed: 05/03/2023]
Abstract
Four series of macroporous hydrogels based on crosslinked copolymers of 2-hydroxyethyl methacrylate (HEMA)-sodium methacrylate (MANa), copolymer HEMA-[2-(methacryloyloxy)ethyl]trimethylammonium chloride (MOETACl), terpolymer HEMA-MANa-MOETACl and on a polyelectrolyte complex were used as carriers for immobilization of proteins, chicken egg white albumin and avidin. The adsorption capacity of the hydrogels for the two proteins, kinetics and pH dependence of albumin adsorption and desorption were studied. The morphology of the hydrogels with and without immobilized albumin was studied by low-vacuum scanning electron microscopy.
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Affiliation(s)
- J Michálek
- Institute of Macromolecular Chemistry, Academy of Sciences of the Czech Republic, 162 06, Prague 6, Czech Republic.
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Skorkovská K, Skorkovská S, Michálek J, Kocí J. [Influrence of age, gender, refraction, keratometry and disc area on the topographic parameters of the optic nerve head]. Cesk Slov Oftalmol 2005; 61:245-52. [PMID: 16164092] [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: 05/04/2023]
Abstract
Optic nerve head (ONH) examination using the Heidelberg Retina Tomograph II was carried out in a study group of 39 healthy persons aged 42-79 years. Refraction and keratometry were measured by means of the autorefractometer. The following topographic parameters of the ONH were tested: disc area, rim area and cup area, cup/disc ratio, rim/disc ratio, rim volume, cup volume, mean and maximum cup depth, height variation contour, cup shape measure, mean RNFL thickness and RNFL cross sectional area. Influence of gender on the topographic parameters of the ONH was not found. The age significantly influenced values of the disc area, rim area, rim volume and RNFL cross sectional area. Refraction significantly influenced the parameters disc area and rim area, keratometry significantly correlated with the disc area and cup shape measure. Disc area significantly influenced most parameters of the ONH (cup area, rim area, C/D ratio, R/D ratio, cup volume, rim volume, mean and maximum cup depth, cup shape measure, RNFL cross sectional area). Our study showed that refraction, keratometry, age and disc area significantly influence many topographic parameters of the optic nerve head in the Heidelberg Retina Tomograph ONH analysis.
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Affiliation(s)
- K Skorkovská
- Klinika nemocí ocních a optometrie LF MU, Fakultní nemocnice u sv. Anny, Brno.
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Skorkovská S, Michálek J, Masková Z, Synek S. [Effect of viscoelastic substances on postoperative intraocular pressure in phacoemulsification]. Cesk Slov Oftalmol 2005; 61:13-9. [PMID: 15782854] [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: 05/02/2023]
Abstract
The Influence of the Type of Viscoelastic Substances on the Level of Intraocular Pressure after Phacoemulsification The aim of study was to asses the influence of the type of viscoelastic substances on the level of intraocular pressure (IOP) after cataract surgery and intraocular lens (IOL) implantation. In the study group of 100 patients Viscoat was used at 32 operated eyes, Provisc at 14 eyes and Duovisc in 54 eyes during phacoemulsification and IOL implantation. IOP was measured before surgery, one day after surgery and one week after surgery. Mean IOP level 1. day postoperatively was 24.94 mmHg in the Viscoat group of eyes, 24.65 mmHg in the Provisc group and 21.09 mmHg in the Duovisc group. The type of viscoelastic substance used during the surgery significantly influenced the level of IOP in the first postoperative day. The level of IOP was significantly lower in the Duovisc group comparing to Viscoat and Provisc. The level of IOP did not differ significantly between the Viscoat and Provisc group. One week after surgery the level of IOP was not significantly different between all types of viscoelastic device. Duovisc was the most profitable viscoleastic substance in the point of view of the course of phacoemulsification, IOL implantation and postoperative level of IOP.
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Affiliation(s)
- S Skorkovská
- Klinika nemocí ocních a optometrie LF MU, Fakultní nemocnice u sv. Anny, Brno
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Skorkovská K, Skorkovská S, Michálek J, Kocí J, Synek S. [Structural analysis of the optic nerve head in healthy eyes and in eyes with glaucoma]. Cesk Slov Oftalmol 2004; 60:400-7. [PMID: 15745408] [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: 05/02/2023]
Abstract
PURPOSE Assess the possibilities of structural analysis of the optic nerve head by Heidelberg Retina Tomograph (HRT) and its use in detection of glaucomatous changes of the optic nerve in particular. Indicate the topographical parameters that are most influenced by glaucoma and are therefore vital in early diagnosis of glaucomatous changes of the optic nerve. PATIENTS AND METHODS Laser scanning tomography (HRT II) was used to examine 68 healthy eyes (control group) and 42 eyes with open angle glaucoma (study group). All the examined subjects were older than 35 years of age. The analysis concerned the following topographical parameters of the optic nerve head: disc area, cup area and rim area, cup volume, rim volume, cup/disc area ratio, mean cup depth, maximum cup depth, mean retinal nerve fiber layer thickness (RNFL), RNFL cross sectional area, height variation contour and cup shape measure and discriminant functions used for classification of the optic nerve head finding according to F. S. Mikelberg and R. Burk. Statistical analysis was employed to ascertain the significant difference in these topographical parameters for the healthy eyes and the eyes with glaucoma. This method was used for both the whole optic disc and the 6 sectors of the optic nerve head. Another aim of the analysis was also to find out the correlation between the topographical parameters and age. RESULTS Significant difference in the topographical parameters for the whole optic disc was spotted in the following parameters: rim volume, mean RNFL thickness, RNFL cross sectional area and discriminant function FSM. Significant differences were also found in between individual sectors of the optic nerve head, except for the upper temporal and upper nasal sector. The parameter, which varied most frequently between the groups, was rim volume. Significant correlations between age and topographical parameters were found for the following parameters: rim area, cup shape measure and mean RNFL thickness. CONCLUSION Results of our study showed, that HRT is able to distinguish between normal and the pathological findings of optic nerve head according to topographical parameters significantly different between the two examined groups. These parameters are important in the diagnosis of glaucoma and also in the follow-up of patients with open angle glaucoma.
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Affiliation(s)
- K Skorkovská
- Klinika nemocí ocních a optometrie LF MU, Fakultní nemocnice u sv. Anny, Brno
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Büchler T, Kovárová L, Musilová R, Bourková L, Ocadlíková D, Buliková A, Hanák L, Michálek J, Hájek R. Generation of dendritic cells using cell culture bags--description of a method and review of literature. ACTA ACUST UNITED AC 2004; 9:199-205. [PMID: 15204101 DOI: 10.1080/10245330410001701486] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Anticancer immunotherapy using dendritic cell-based vaccines is a strategy aimed at the induction and maintenance of immune responses against cancer cells. Clinical applications of dendritic cells (DCs) require stringent adherence to Good Manufacturing Practice (GMP) methods and rigorous standardization of DC-based vaccine preparation. Recently, closed systems for DC culture have been developed with a goal to minimize the risk of contamination. Here, we compare the yield, immunophenotype, and functional properties of DCs generated in Lifecell X-Fold culture bags and in plastic wells, both from adherence-selected monocytes, and review the current literature on closed systems for DC generation. We found that both the overall yield and the yield of CD83+ cells in cell culture bags was lower than in the standard culture method. No statistically significant differences were observed in the expression of DC immunophenotypic markers. The capability of DCs cultured in bags and in wells to induce the proliferation of allogeneic mononuclear cells were equivalent. The performance of DCs in mixed lymphocyte reaction correlated significantly (p = 0.005) with the CD83 expression but not with the CD80, CD86, HLA-DR, CD1a, and CD1c expression. We conclude that the immunophenotype and stimulatory properties of DCs cultured in closed cell culture bags are similar to those generated by conventional method using cell culture wells.
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Affiliation(s)
- T Büchler
- Department of Clinical Hematology, Brno, Czech Republic.
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Michálek J, Büchler T, Hájek R. T lymphocyte therapy of cancer. Physiol Res 2004; 53:463-9. [PMID: 15479123] [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: 04/30/2023] Open
Abstract
The rationale for the use of T lymphocytes to fight cancer is the immunogenicity of tumor cells. T cells are capable to recognize and finally to kill tumor cells. Adoptive cell transfer therapies provide the opportunity to overcome tolerogenic mechanisms by enabling the selection and activation of highly reactive T cell subpopulations and by manipulation of the host environment into which the T cells are introduced. The aim of this article is to review the possibilities, limitations and recent clinical experience with this novel anticancer treatment, namely with adoptive immunotherapy using antigen-specific T cells.
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Affiliation(s)
- J Michálek
- Department of Pediatrics, Children's Hospital of J.G. Mendel, Medical Faculty, Masaryk University, Cernopolní 9, Brno 66263, Czech Republic.
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Michálek J, Büchler T, Hájek R. T lymphocyte therapy of cancer. Physiol Res 2004. [DOI: 10.33549/physiolres.930498] [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: 02/25/2023] Open
Abstract
The rationale for the use of T lymphocytes to fight cancer is the immunogenicity of tumor cells. T cells are capable to recognize and finally to kill tumor cells. Adoptive cell transfer therapies provide the opportunity to overcome tolerogenic mechanisms by enabling the selection and activation of highly reactive T cell subpopulations and by manipulation of the host environment into which the T cells are introduced. The aim of this article is to review the possibilities, limitations and recent clinical experience with this novel anticancer treatment, namely with adoptive immunotherapy using antigen-specific T cells.
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Skorkovská S, Michálek J, Ruberová M, Synek S. [Comparison of ultrasound and optic biometry with respect to ocular refraction after cataract surgery]. Cesk Slov Oftalmol 2004; 60:24-9. [PMID: 15011303] [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: 04/29/2023]
Abstract
In the prospective study of 56 patients with cataract (67 eyes) the authors compared axial length biometry) regarding to postoperative refraction of the eyes. Dioptric power of the intraocular lens (IOL) was determined by SRK II. formula. The difference between predicted and actual postoperative refraction in the spherical equivalent were compared 3 months postoperatively. Axial length measured by ultrasound differed significantly from the axial length measured by optical biometry (p = 0.016). Dioptric power of IOL calculated according to the axial length measured by ultrasound was significantly different from the dioptric power of IOL calculated according to the axial length measured by optical biometry (p = 0.003). The difference between predicted and actual postoperative refraction was not statistically significant (p = 0.384) even if we considered both type of measurement. In conclusion, we found partial coherence interferometry was an accurate and reproducible method for measurement of axial length of the eye before cataract surgery. In the cases of advanced dense cataracts backup of ultrasonic biometry is still necessary.
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Affiliation(s)
- S Skorkovská
- Klinika nemocí ocních a optometrie LF MU, FN u sv. Anny, Brno.
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Michálek J, Collins RH, Vitetta ES. Clinical-scale selective depletion of alloreactive T cells using an anti-CD25 immunotoxin. Neoplasma 2003; 50:296-9. [PMID: 12937844] [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: 03/04/2023]
Abstract
Allogeneic hematopoietic stem cell transplantation is the treatment of choice for many hematological malignancies. Its efficacy is limited by graft-versus-host disease (GVHD), the leading cause of post-transplant morbidity and mortality. GVHD is mediated by a subpopulation of T cells in the stem cell graft. Ex vivo T cell depletion of all T cells of the graft can prevent development of GVHD but can lead to a delay in immune reconstitution and an increase of potentially lethal opportunistic infections and leukemic relapses. Hypothetically, an approach that enables a selective depletion of the alloreactive donor T cells that cause GVHD while preserving third party (anti-leukemic and anti-microbial) reactivity would be optimal for recipients of HSCT. Our preliminary data demonstrated that an anti-CD25 immunotoxin, which reacts with a cell surface activation antigen, can selectively deplete alloreactive donor T cells activated by non-leukemic recipient white blood cells while preserving the beneficial third-party reactivity in vitro. In this report we describe a method for clinical-scale ex vivo selective depletion of alloreactive donor T cells using the anti-CD25 immunotoxin, RFT5-SMPT-dgRTA. Two logs of alloreactive T cells could be selectively depleted while preserving third party reactivity. This method was reproducible in 10 pre-clinical experiments with 8 HLA-mismatched healthy volunteer pairs and 2 HLA-matched sibling donor/patient pairs.
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Affiliation(s)
- J Michálek
- Cancer Immunobiology Center, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390 USA.
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Dendis M, Horváth R, Michálek J, Růzicka F, Grijalva M, Bartos M, Benedík J. PCR-RFLP detection and species identification of fungal pathogens in patients with febrile neutropenia. Clin Microbiol Infect 2003; 9:1191-202. [PMID: 14686984 DOI: 10.1111/j.1469-0691.2003.00719.x] [Citation(s) in RCA: 40] [Impact Index Per Article: 1.9] [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: 12/01/2022]
Abstract
OBJECTIVE To assess the usefulness of polymerase chain reaction (PCR) assays in the diagnosis of fungal infections in immunocompromised patients. METHODS A rapid and sensitive PCR-based assay for the detection and identification of fungal pathogens was designed and applicability of this method was investigated in a group of children with cancer and febrile neutropenia (FN). RESULTS The ITS2 sequences and adjacent regions of 40 fungal pathogens were analyzed and primers for detection of all analyzed fungal species were designed. Amplification product length polymorphism (APLP) and restriction fragment length polymorphism (RFLP) generated genus- or species-specific patterns. The sensitivity of the method was approximately three cells of Candida albicans per 1 mL of blood. The results were available within 8 h after sample collection. The method was tested on 53 blood samples and one lung biopsy sample from 24 children with cancer and febrile neutropenia (FN). The PCR assay detected fungal DNA in 25 clinical samples from ten patients. Blood cultures were positive in only five samples, while another two blood-culture negative patients had positive cultures from throat swabs. The remaining 14 patients were both culture- and PCR-negative. Culture-isolated strains matched completely those obtained by PCR-APLP-RFLP identification. The identity of fungal species was confirmed by direct sequencing of amplified products. CONCLUSION Our results suggest that PCR-APLP-RFLP assays can be useful in the diagnosis of fungal infections in immunocompromised patients.
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MESH Headings
- Adolescent
- Child
- Child, Preschool
- DNA, Fungal/chemistry
- DNA, Fungal/genetics
- DNA, Ribosomal Spacer/chemistry
- DNA, Ribosomal Spacer/genetics
- Female
- Fever/microbiology
- Fungi/genetics
- Fungi/isolation & purification
- Humans
- Immunocompromised Host
- Infant
- Male
- Mycoses/microbiology
- Neutropenia/microbiology
- Polymerase Chain Reaction/methods
- Polymorphism, Restriction Fragment Length
- RNA, Ribosomal/chemistry
- RNA, Ribosomal/genetics
- RNA, Ribosomal, 5.8S/chemistry
- RNA, Ribosomal, 5.8S/genetics
- Sensitivity and Specificity
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Solomon SR, Tran T, Carter CS, Donnelly S, Hensel N, Schindler J, Bahceci E, Ghetie V, Michálek J, Mavroudis D, Read EJ, Vitetta ES, Barrett AJ. Optimized clinical-scale culture conditions for ex vivo selective depletion of host-reactive donor lymphocytes: a strategy for GvHD prophylaxis in allogeneic PBSC transplantation. Cytotherapy 2003; 4:395-406. [PMID: 12473206 DOI: 10.1080/146532402320775982] [Citation(s) in RCA: 54] [Impact Index Per Article: 2.6] [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: 10/27/2022]
Abstract
BACKGROUND Ex vivo selective depletion (SD) is a strategy to prevent GvHD, in which host-reactive donor lymphocytes are selectively eliminated from a PBSC allograft while conserving useful donor immune function. Prior to testing this strategy in patients, our goal was to develop a clinical-scale SD process, which involves co-culture of donor lymphocytes and irradiated recipient cells, followed by the addition of an immunotoxin (IT) directed against the alpha-chain of the IL-2 receptor (CD25), expressed on activated donor T cells. METHODS Stimulator cells were generated from immunomagnetically selected and expanded recipient T lymphocytes. Donor PBMCs from G-CSF-mobilized peripheral blood were co-cultured for 72 h with irradiated stimulator cells. Alloreactive T cells were targeted for elimination by the addition of the anti-CD25 IT, RFT5-SMPT-dgA, and the IT enhancer, NH(4)Cl. RESULTS Stimulator-cell selection/expansion yielded > 2 x 10(10) highly enriched CD3(+) cells (98.9 +/- 2.2%). After SD, cell recovery was 68.5 +/- 23.3% and viability was 84.6 +/- 6.4%. This permitted a potential T-cell dose >/= 1 x 10(8) CD3(+) cells kg(-1) to transplant recipients. Although SD donor lymphocytes retained little proliferative capacity against the original stimulator cells (2.6 +/- 0.6%), responses were conserved against third party cells (107.6 +/- 18.6%), the bacterial superantigen staphylococcus enterotoxin B (108.2 +/- 4.2%), and CMV Ag (72.1 +/- 3.8%). DISCUSSION We have demonstrated that ex vivo SD is feasible in clinical-scale culture conditions. The ability of this strategy to prevent GvHD is the subject of an ongoing clinical trial, in which the SD lymphocyte product is transplanted in conjunction with a T cell-depleted PBSC allograft.
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Affiliation(s)
- S R Solomon
- Stem Cell Allotransplantation Section, Hematology Branch, NHLBI, National Institutes of Health, Bethesda, MD 20892-1652, USA
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Abstract
Hydrogel implants for urinary incontinence treatment based on HEMA supplemented with 10% methacrylic acid have been developed. The swelling properties of implants were tested in vitro and in vivo after implantation to laboratory mice. Biocompatibility has been determined by incubation of implants in tissue culture, by histological examination of adjacent tissues after subcutaneous application of implants to laboratory mouse in a long-term experiment, and by flow cytometry examination of blood cells. The swelling of hydrogel implants was completed in 6-24 h. There was no effect on in vitro growth of cells incubated with implants. In mice, implants were well tolerated without any sign of inflammatory reaction. The material allows an elastic compression of urethra compensating a damaged sphincter after trans-urethral sub-mucosal implantation of hydrogel cylinders.
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Affiliation(s)
- L Sefc
- Institute of Pathophysiology, First Faculty of Medicine, Charles University, Prague, Czech Republic.
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Fialová M, Sevcíková S, Smarda J, Michálek J. Determination of optimal conditions for detection of acute myeloid leukemia t(8;21) and t(15;17) translocations using RT-PCR. Neoplasma 2002; 49:33-7. [PMID: 12044057] [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: 02/25/2023]
Abstract
Prognosis of patients with acute myeloid leukemia (AML) is not satisfactory. Long time remission can be achieved only in 25-40% children with AML. The aim of the study is to improve diagnosis of AML in cases characterized by specific chromosomal translocations t(8;21) and t(15;17). These translocations can be efficiently detected using reverse transcriptase-polymerase chain reaction (RT-PCR). To determine optimal conditions for detection of the t(8;21) and t(15;17) translocations in human cells, we performed a detail study of experimental conditions for RT-PCR on human cell lines NB-4 and KASUMI-1. For detection of t(8;21) using Pfx polymerase, the optimal PCR conditions included magnesium ion concentration in the range of 0.6 to 1 mM, 0.4 microM primer concentration, 5 degrees C annealing temperature and 1 microl of template cDNA. For detection of t(15;17) using the Pfx polymerase, the optimal conditions included 1 mM magnesium ion concentration, 0.6 microM primer concentration, 63 degrees C-66 degrees C annealing temperature and 2 microl of template cDNA. The results proved to be valid for clinical diagnostics of these chromosomal aberrations in blood and/or bone marrow samples of AML patients.
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Affiliation(s)
- M Fialová
- Masaryk University, Faculty of Science, Brno, Czech Republic
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Abstract
The implantation of non-resorbable biocompatible polymer hydrogels into defects in the central nervous system can reduce glial scar formation, bridge the lesion and lead to tissue regeneration within the hydrogel. We implanted hydrogels based on crosslinked poly hydroxyethyl-methacrylate (pHEMA) and poly N-(2-hydroxypropyl)-methacrylamide (pHPMA) into the rat cortex and evaluated the cellular invasion into the hydrogels by means of immunohistochemical methods and tetramethylammonium diffusion measurements. Astrocytes and NF160-positive axons grew similarly into both types of hydrogels. We found no cell types other than astrocytes in the pHEMA hydrogels. In the pHPMA hydrogels, we found a massive ingrowth of connective tissue elements. These changes were accompanied by corresponding changes in the extracellular space volume fraction and tortuosity of the hydrogels.
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Affiliation(s)
- P Lesný
- Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Vídenská 1083, 142 20, Prague, Czech Republic
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Jóna E, Ondrušová D, Pajtášová M, P. Šimon, Michálek J. A study of curative interactions in the presence of cobalt(II) stearate. J Appl Polym Sci 2001. [DOI: 10.1002/app.1744] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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