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Reinke A, Tizabi MD, Baumgartner M, Eisenmann M, Heckmann-Nötzel D, Kavur AE, Rädsch T, Sudre CH, Acion L, Antonelli M, Arbel T, Bakas S, Benis A, Buettner F, Cardoso MJ, Cheplygina V, Chen J, Christodoulou E, Cimini BA, Farahani K, Ferrer L, Galdran A, van Ginneken B, Glocker B, Godau P, Hashimoto DA, Hoffman MM, Huisman M, Isensee F, Jannin P, Kahn CE, Kainmueller D, Kainz B, Karargyris A, Kleesiek J, Kofler F, Kooi T, Kopp-Schneider A, Kozubek M, Kreshuk A, Kurc T, Landman BA, Litjens G, Madani A, Maier-Hein K, Martel AL, Meijering E, Menze B, Moons KGM, Müller H, Nichyporuk B, Nickel F, Petersen J, Rafelski SM, Rajpoot N, Reyes M, Riegler MA, Rieke N, Saez-Rodriguez J, Sánchez CI, Shetty S, Summers RM, Taha AA, Tiulpin A, Tsaftaris SA, Van Calster B, Varoquaux G, Yaniv ZR, Jäger PF, Maier-Hein L. Understanding metric-related pitfalls in image analysis validation. Nat Methods 2024; 21:182-194. [PMID: 38347140 DOI: 10.1038/s41592-023-02150-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 12/12/2023] [Indexed: 02/15/2024]
Abstract
Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multistage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides a reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Although focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation.
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Affiliation(s)
- Annika Reinke
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany.
- German Cancer Research Center (DKFZ) Heidelberg, HI Helmholtz Imaging, Heidelberg, Germany.
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany.
| | - Minu D Tizabi
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and University Medical Center Heidelberg, Heidelberg, Germany.
| | - Michael Baumgartner
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
| | - Matthias Eisenmann
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Doreen Heckmann-Nötzel
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and University Medical Center Heidelberg, Heidelberg, Germany
| | - A Emre Kavur
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, HI Applied Computer Vision Lab, Heidelberg, Germany
| | - Tim Rädsch
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, HI Helmholtz Imaging, Heidelberg, Germany
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL and Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Laura Acion
- Instituto de Cálculo, CONICET - Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Michela Antonelli
- School of Biomedical Engineering and Imaging Science, King's College London, London, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - Tal Arbel
- Centre for Intelligent Machines and MILA (Quebec Artificial Intelligence Institute), McGill University, Montréal, Quebec, Canada
| | - Spyridon Bakas
- Division of Computational Pathology, Dept of Pathology & Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
| | - Arriel Benis
- Department of Digital Medical Technologies, Holon Institute of Technology, Holon, Israel
- European Federation for Medical Informatics, Le Mont-sur-Lausanne, Switzerland
| | - Florian Buettner
- German Cancer Consortium (DKTK), partner site Frankfurt/Mainz, a partnership between DKFZ and UCT Frankfurt-Marburg, Frankfurt am Main, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Heidelberg, Germany
- Goethe University Frankfurt, Department of Medicine, Frankfurt am Main, Germany
- Goethe University Frankfurt, Department of Informatics, Frankfurt am Main, Germany
- Frankfurt Cancer Insititute, Frankfurt am Main, Germany
| | - M Jorge Cardoso
- School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Veronika Cheplygina
- Department of Computer Science, IT University of Copenhagen, Copenhagen, Denmark
| | - Jianxu Chen
- Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany
| | - Evangelia Christodoulou
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Beth A Cimini
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Keyvan Farahani
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, MD, USA
| | - Luciana Ferrer
- Instituto de Investigación en Ciencias de la Computación (ICC), CONICET-UBA, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Adrian Galdran
- Universitat Pompeu Fabra, Barcelona, Spain
- University of Adelaide, Adelaide, South Australia, Australia
| | - Bram van Ginneken
- Fraunhofer MEVIS, Bremen, Germany
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ben Glocker
- Department of Computing, Imperial College London, South Kensington Campus, London, UK
| | - Patrick Godau
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and University Medical Center Heidelberg, Heidelberg, Germany
| | - Daniel A Hashimoto
- Department of Surgery, Perelman School of Medicine, Philadelphia, PA, USA
- General Robotics Automation Sensing and Perception Laboratory, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael M Hoffman
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
- Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada
| | - Merel Huisman
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Fabian Isensee
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, HI Applied Computer Vision Lab, Heidelberg, Germany
| | - Pierre Jannin
- Laboratoire Traitement du Signal et de l'Image - UMR_S 1099, Université de Rennes 1, Rennes, France
- INSERM, Paris, France
| | - Charles E Kahn
- Department of Radiology and Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Dagmar Kainmueller
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Biomedical Image Analysis and HI Helmholtz Imaging, Berlin, Germany
- University of Potsdam, Digital Engineering Faculty, Potsdam, Germany
| | - Bernhard Kainz
- Department of Computing, Faculty of Engineering, Imperial College London, London, UK
- Department AIBE, Friedrich-Alexander-Universität (FAU), Erlangen-Nürnberg, Germany
| | | | - Jens Kleesiek
- Translational Image-guided Oncology (TIO), Institute for AI in Medicine (IKIM), University Medicine Essen, Essen, Germany
| | | | | | - Annette Kopp-Schneider
- German Cancer Research Center (DKFZ) Heidelberg, Division of Biostatistics, Heidelberg, Germany
| | - Michal Kozubek
- Centre for Biomedical Image Analysis and Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Anna Kreshuk
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Health Science Center, Stony Brook, NY, USA
| | | | - Geert Litjens
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Amin Madani
- Department of Surgery, University Health Network, Philadelphia, PA, USA
| | - Klaus Maier-Hein
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Anne L Martel
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Erik Meijering
- School of Computer Science and Engineering, University of New South Wales, UNSW Sydney, Kensington, New South Wales, Australia
| | - Bjoern Menze
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Karel G M Moons
- Julius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Henning Müller
- Information Systems Institute, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland
- Medical Faculty, University of Geneva, Geneva, Switzerland
| | - Brennan Nichyporuk
- MILA (Quebec Artificial Intelligence Institute), Montréal, Quebec, Canada
| | - Felix Nickel
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Petersen
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
| | | | - Nasir Rajpoot
- Tissue Image Analytics Laboratory, Department of Computer Science, University of Warwick, Coventry, UK
| | - Mauricio Reyes
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
- Department of Radiation Oncology, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Michael A Riegler
- Simula Metropolitan Center for Digital Engineering, Oslo, Norway
- UiT The Arctic University of Norway, Tromsø, Norway
| | | | - Julio Saez-Rodriguez
- Institute for Computational Biomedicine, Heidelberg University, Heidelberg, Germany
- Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Clara I Sánchez
- Informatics Institute, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | | | - Ronald M Summers
- National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Abdel A Taha
- Institute of Information Systems Engineering, TU Wien, Vienna, Austria
| | - Aleksei Tiulpin
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
- Neurocenter Oulu, Oulu University Hospital, Oulu, Finland
| | | | - Ben Van Calster
- Department of Development and Regeneration and EPI-centre, KU Leuven, Leuven, Belgium
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Gaël Varoquaux
- Parietal project team, INRIA Saclay-Île de France, Palaiseau, France
| | - Ziv R Yaniv
- National Institute of Allergy and Infectious Diseases, Bethesda, MD, USA
| | - Paul F Jäger
- German Cancer Research Center (DKFZ) Heidelberg, HI Helmholtz Imaging, Heidelberg, Germany.
- German Cancer Research Center (DKFZ) Heidelberg, Interactive Machine Learning Group, Heidelberg, Germany.
| | - Lena Maier-Hein
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany.
- German Cancer Research Center (DKFZ) Heidelberg, HI Helmholtz Imaging, Heidelberg, Germany.
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and University Medical Center Heidelberg, Heidelberg, Germany.
- Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany.
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Maier-Hein L, Reinke A, Godau P, Tizabi MD, Buettner F, Christodoulou E, Glocker B, Isensee F, Kleesiek J, Kozubek M, Reyes M, Riegler MA, Wiesenfarth M, Kavur AE, Sudre CH, Baumgartner M, Eisenmann M, Heckmann-Nötzel D, Rädsch T, Acion L, Antonelli M, Arbel T, Bakas S, Benis A, Blaschko MB, Cardoso MJ, Cheplygina V, Cimini BA, Collins GS, Farahani K, Ferrer L, Galdran A, van Ginneken B, Haase R, Hashimoto DA, Hoffman MM, Huisman M, Jannin P, Kahn CE, Kainmueller D, Kainz B, Karargyris A, Karthikesalingam A, Kofler F, Kopp-Schneider A, Kreshuk A, Kurc T, Landman BA, Litjens G, Madani A, Maier-Hein K, Martel AL, Mattson P, Meijering E, Menze B, Moons KGM, Müller H, Nichyporuk B, Nickel F, Petersen J, Rajpoot N, Rieke N, Saez-Rodriguez J, Sánchez CI, Shetty S, van Smeden M, Summers RM, Taha AA, Tiulpin A, Tsaftaris SA, Van Calster B, Varoquaux G, Jäger PF. Metrics reloaded: recommendations for image analysis validation. Nat Methods 2024; 21:195-212. [PMID: 38347141 DOI: 10.1038/s41592-023-02151-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 12/12/2023] [Indexed: 02/15/2024]
Abstract
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint-a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases.
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Affiliation(s)
- Lena Maier-Hein
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany.
- German Cancer Research Center (DKFZ) Heidelberg, HI Helmholtz Imaging, Heidelberg, Germany.
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany.
- Medical Faculty, Heidelberg University, Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and University Medical Center Heidelberg, Heidelberg, Germany.
| | - Annika Reinke
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany.
- German Cancer Research Center (DKFZ) Heidelberg, HI Helmholtz Imaging, Heidelberg, Germany.
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany.
| | - Patrick Godau
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and University Medical Center Heidelberg, Heidelberg, Germany
| | - Minu D Tizabi
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and University Medical Center Heidelberg, Heidelberg, Germany
| | - Florian Buettner
- German Cancer Consortium (DKTK), partner site Frankfurt/Mainz, a partnership between DKFZ and UCT Frankfurt-Marburg, Frankfurt am Main, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Heidelberg, Germany
- Department of Medicine, Goethe University Frankfurt, Frankfurt am Main, Germany
- Department of Informatics, Goethe University Frankfurt, Frankfurt am Main, Germany
- Frankfurt Cancer Insititute, Frankfurt am Main, Germany
| | - Evangelia Christodoulou
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Ben Glocker
- Department of Computing, Imperial College London, South Kensington Campus, London, UK
| | - Fabian Isensee
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, HI Applied Computer Vision Lab, Heidelberg, Germany
| | - Jens Kleesiek
- Institute for AI in Medicine, University Medicine Essen, Essen, Germany
| | - Michal Kozubek
- Centre for Biomedical Image Analysis and Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Mauricio Reyes
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
- Department of Radiation Oncology, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Michael A Riegler
- Simula Metropolitan Center for Digital Engineering, Oslo, Norway
- Department of Computer Science, UiT The Arctic University of Norway, Tromsø, Norway
| | - Manuel Wiesenfarth
- German Cancer Research Center (DKFZ) Heidelberg, Division of Biostatistics, Heidelberg, Germany
| | - A Emre Kavur
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, HI Applied Computer Vision Lab, Heidelberg, Germany
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL and Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Michael Baumgartner
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
| | - Matthias Eisenmann
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Doreen Heckmann-Nötzel
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and University Medical Center Heidelberg, Heidelberg, Germany
| | - Tim Rädsch
- German Cancer Research Center (DKFZ) Heidelberg, Division of Intelligent Medical Systems, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, HI Helmholtz Imaging, Heidelberg, Germany
| | - Laura Acion
- Instituto de Cálculo, CONICET - Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Michela Antonelli
- School of Biomedical Engineering and Imaging Science, King's College London, London, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - Tal Arbel
- Centre for Intelligent Machines and MILA (Québec Artificial Intelligence Institute), McGill University, Montréal, Quebec, Canada
| | - Spyridon Bakas
- Division of Computational Pathology, Department of Pathology & Laboratory Medicine, Indiana University School of Medicine, IU Health Information and Translational Sciences Building, Indianapolis, IN, USA
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
| | - Arriel Benis
- Department of Digital Medical Technologies, Holon Institute of Technology, Holon, Israel
- European Federation for Medical Informatics, Le Mont-sur-Lausanne, Switzerland
| | - Matthew B Blaschko
- Center for Processing Speech and Images, Department of Electrical Engineering, KU Leuven, Leuven, Belgium
| | - M Jorge Cardoso
- School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Veronika Cheplygina
- Department of Computer Science, IT University of Copenhagen, Copenhagen, Denmark
| | - Beth A Cimini
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Gary S Collins
- Centre for Statistics in Medicine, University of Oxford, Nuffield Orthopaedic Centre, Oxford, UK
| | - Keyvan Farahani
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, MD, USA
| | - Luciana Ferrer
- Instituto de Investigación en Ciencias de la Computación (ICC), CONICET-UBA, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Adrian Galdran
- BCN Medtech, Universitat Pompeu Fabra, Barcelona, Spain
- Australian Institute for Machine Learning AIML, University of Adelaide, Adelaide, South Australia, Australia
| | - Bram van Ginneken
- Fraunhofer MEVIS, Bremen, Germany
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Robert Haase
- Technische Universität (TU) Dresden, DFG Cluster of Excellence 'Physics of Life', Dresden, Germany
- Center for Systems Biology, Dresden, Germany
- Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Leipzig University, Leipzig, Germany
| | - Daniel A Hashimoto
- Department of Surgery, Perelman School of Medicine, Philadelphia, PA, USA
- General Robotics Automation Sensing and Perception Laboratory, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael M Hoffman
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Merel Huisman
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Pierre Jannin
- Laboratoire Traitement du Signal et de l'Image - UMR_S 1099, Université de Rennes 1, Rennes, France
- INSERM, Paris, France
| | - Charles E Kahn
- Department of Radiology and Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Dagmar Kainmueller
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Biomedical Image Analysis and HI Helmholtz Imaging, Berlin, Germany
- Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
| | - Bernhard Kainz
- Department of Computing, Faculty of Engineering, Imperial College London, London, UK
- Department AIBE, Friedrich-Alexander-Universität (FAU), Erlangen-Nürnberg, Germany
| | | | | | | | - Annette Kopp-Schneider
- German Cancer Research Center (DKFZ) Heidelberg, Division of Biostatistics, Heidelberg, Germany
| | - Anna Kreshuk
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Health Science Center, Stony Brook, NY, USA
| | | | - Geert Litjens
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Amin Madani
- Department of Surgery, University Health Network, Philadelphia, PA, USA
| | - Klaus Maier-Hein
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Anne L Martel
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Peter Mattson
- Google, 1600 Amphitheatre Pkwy, Mountain View, CA, USA
| | - Erik Meijering
- School of Computer Science and Engineering, University of New South Wales, UNSW Sydney, Kensington, New South Wales, Australia
| | - Bjoern Menze
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Karel G M Moons
- Julius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Henning Müller
- Information Systems Institute, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland
- Medical Faculty, University of Geneva, Geneva, Switzerland
| | - Brennan Nichyporuk
- MILA (Québec Artificial Intelligence Institute), Montréal, Quebec, Canada
| | - Felix Nickel
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Petersen
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Heidelberg, Germany
| | - Nasir Rajpoot
- Tissue Image Analytics Laboratory, Department of Computer Science, University of Warwick, Coventry, UK
| | | | - Julio Saez-Rodriguez
- Institute for Computational Biomedicine, Heidelberg University, Heidelberg, Germany
- Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Clara I Sánchez
- Informatics Institute, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | | | - Maarten van Smeden
- Julius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Ronald M Summers
- National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Abdel A Taha
- Institute of Information Systems Engineering, TU Wien, Vienna, Austria
| | - Aleksei Tiulpin
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
- Neurocenter Oulu, Oulu University Hospital, Oulu, Finland
| | | | - Ben Van Calster
- Department of Development and Regeneration and EPI-centre, KU Leuven, Leuven, Belgium
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Gaël Varoquaux
- Parietal project team, INRIA Saclay-Île de France, Palaiseau, France
| | - Paul F Jäger
- German Cancer Research Center (DKFZ) Heidelberg, HI Helmholtz Imaging, Heidelberg, Germany.
- German Cancer Research Center (DKFZ) Heidelberg, Interactive Machine Learning Group, Heidelberg, Germany.
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Abdel Hamed EF, Taha AA, Abdel Ghany SM, Saleh AA, Fawzy EM. Acetazolamide loaded-silver nanoparticles: A potential treatment for murine trichinellosis. J Helminthol 2023; 97:e86. [PMID: 37970645 DOI: 10.1017/s0022149x23000731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2023]
Abstract
Trichinellosis is a global food-borne disease caused by viviparous parasitic nematodes of the genus Trichinella. Due to the lack of effective, safe therapy and the documented adverse effects of traditional therapy, this study aimed to evaluate the therapeutic effect of acetazolamide-loaded silver nanoparticles (AgNPs) on murine trichinellosis. Fifty male Swiss albino mice were divided into five groups of ten mice each: Group I, normal control group; Group II, infected with T. spiralis and not treated; Group III, infected and given AgNPs; Group IV, infected and treated with acetazolamide; and Group V, infected and treated with acetazolamide-loaded AgNPs. Mice were infected orally with 250 larvae. The efficacy was assessed by counting T. spiralis adults and larvae, measuring serum total antioxidant capacity, and observing the histopathological and ultrastructural alterations. Acetazolamide-loaded AgNPs treatment exhibited the highest percentage of reduction (84.72% and 80.74%) for the intestinal adults and the muscular larvae of T. spiralis-infected animals, respectively. Furthermore, during the intestinal and muscular phases, the serum of the same group had the best free-radical scavenging capacity (antioxidant capacity), which reduced tissue damage induced by oxidative stress. Histopathologically, the normal intestinal and muscular architecture was restored in the group treated with acetazolamide-loaded AgNPs, in addition to the reduced inflammatory infiltrate that alleviated inflammation compared to infected animals. Our results confirmed the marked destruction of the ultrastructural features of T. spiralis adults and larvae. Acetazolamide-loaded AgNPs are a promising therapy against T. spiralis infection.
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Affiliation(s)
- E F Abdel Hamed
- Department of Medical Parasitology, Faculty of Medicine, Zagazig University, Sharkia, Egypt
| | - A A Taha
- Department of Medical Parasitology, Faculty of Medicine, Zagazig University, Sharkia, Egypt
| | - S M Abdel Ghany
- Department of Medical Parasitology, Faculty of Medicine, Zagazig University, Sharkia, Egypt
| | - A A Saleh
- Department of Medical Parasitology, Faculty of Medicine, Zagazig University, Sharkia, Egypt
| | - E M Fawzy
- Department of Medical Parasitology, Faculty of Medicine, Zagazig University, Sharkia, Egypt
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Salih RA, Mohamed NS, Taha AA. Genetic Sequence of Coronavirus Strains Isolated from Iraqi Patients and their Relationship with some Liver Enzymes and Interleukins. Arch Razi Inst 2022; 77:809-819. [PMID: 36284985 PMCID: PMC9548273 DOI: 10.22092/ari.2022.357089.1967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 01/16/2022] [Indexed: 05/24/2023]
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is a positive-sense single-stranded RNA virus from the genus Betacoronavirus causes COVID-19 (coronavirus disease 2019). According to daily reports issued by the Iraqi Ministry of Health, the SARS-COV-2 was firstly detected in Al-Najaf city in February 2020 and identified in the Central Public Health Laboratory (CPHL) in Baghdad, Iraq. The outcomes of this study were based on 100 nasopharyngeal swaps and venous blood samples from hospitalized patients in Al-Kindy and CPHL. Patients were assigned to five groups (Asymptomatic, Mild, Moderate, Severe, and Deceased) based on disease severity as indicated by World Health Organization (WHO). The positive samples were identified by real-time quantitative polymerase chain reaction (RT-PCR) and subjected to some liver enzyme assays and interleukins measurements, and the correlation with the genetic sequence was determined by Illumina Miseq technology. Liver enzymes levels of Aspartate aminotransferase (AST), Alanine aminotransferase (ALT), and lactate dehydrogenase (LDH) showed statistically significant differences, especially between the deceased groups. Interleukins (IL-10, IL-18, and TNF- α) significantly differed among groups. This study revealed that three isolates belonging to the original strain isolated from Wuhan (A19) and characterized by their virulence caused severe symptoms and led to admission to isolation hospitals and intensive care units, and the last two isolates of (UK alpha V1) appeared in Iraq in early 2021. These strains which were less virulent than the Wuhan strain spread faster and appear in moderate and asymptomatic patients.
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Affiliation(s)
- R A Salih
- Central Public Health Laboratory, Ministry of Health, Baghdad, Iraq
| | - N S Mohamed
- Pharmacy College, Al- Nahrain University, Baghdad, Iraq
| | - A A Taha
- Department of Applied Science, University of Technology, Baghdad, Iraq
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5
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Al-Rawi M, Al-Mudallal NHAL, Taha AA. Determination of Ferrous Oxide Nanoparticles Minimum Inhibitory Concentration against Local Virulent Bacterial Isolates. Arch Razi Inst 2021; 76:795-808. [PMID: 35096315 PMCID: PMC8790978 DOI: 10.22092/ari.2021.355997.1758] [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] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 09/21/2021] [Indexed: 12/25/2022]
Abstract
The improvement of multi-resistance properties of the bacterial pathogen has recently been discussed as an emerging issue. In this regard, iron oxide nanoparticles have attracted the researchers' attention due to their wide application in the realm of medicine. Iron oxide nanoparticles have a high specific surface area that enables them to interact with the bacterial surface structure and has considerable antibacterial activity. The current study aimed to synthesize a novel antimicrobial agent from iron oxide nanoparticles and determine its minimum inhibitory concentration (MIC) on different gram-positive and negative variant bacterial strains isolated and characterized from the infected urinary tract of Iraqi elderly patients. This study was conducted from September 2020 to December 2020 on 75 urine samples collected from the infected urinary tract of elderly patients in the ages range of 60-75 years admitted to Al-Yarmouk Medical Hospital, Baghdad, Iraq. Isolation of bacterial isolates was carried out using differential and selective media. Afterward, they were characterized and confirmed using different biochemical tests and VITEK 2 system, respectively. Magnetic nanoparticles were fabricated by co-precipitation of ferric ions (Fe3+) and ferrous ions (Fe2+) in presence of ammonium hydroxide solution (25%). The characterization of synthesized nanoparticles was performed subsequently using UV-VIS spectroscopy analysis, Scanning Electron Microscope (SEM), Fourier transform infrared spectroscopy analysis, X-ray Diffraction analysis (XRD), and Energy-dispersive X-ray spectrum (EDX). The MIC of synthesized sonicated Fe3O4NP against different bacterial strains was determined using the broth culture dilution method through making serial dilutions of 50, 100, 200, 400, 500, 600, 800, 900 µg/ml from a 5mg/ml nanoparticle stock solution. Afterward, the lowest concentration of nanoparticles required to arrest the growth of bacteria was determined through the colony-forming unit of each treated bacteria on brain heart infusion agar. In total, 17bacterial isolates were identified from the infected urinary tract, five bacterial isolates (E. coli, Pseudomanas aeruginosa, Staphylococcus aureus, Enterococcus faecalis, and Micrococcus luteus). In addition, two Proteus mirabilis strains were identified separately and were tested against synthesized Fe3O4NP to determine the MIC. The novel synthesized antibacterial agent showed excellent bioactivity, compared with controls (consisting of bacterial suspension without ferrous oxide nanoparticles), and the synthesized antibacterial agent was considered significantly active against all the bacterial strains at a p-value less than 0.05. The Fe3O4NP were active against gram-negative more than gram-positive bacteria. The MIC of synthesized and characterized Fe3O4NP wasapplied on seven gram-positive and negative bacterial isolates using bacteria-Fe3O4NP complex. Significant effects were observed on all strains, compared with controls, and this complex could significantly inhibit gram-negative more than gram-positive bacteria.
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Affiliation(s)
- M Al-Rawi
- Department of Medical Microbiology, College of Medicine, Al-Iraqia University, Baghdad, Iraq
| | - N H A L Al-Mudallal
- Department of Medical Microbiology, College of Medicine, Al-Iraqia University, Baghdad, Iraq
| | - A A Taha
- Department of Applied Science, Division of Biotechnology, University of Technology, Baghdad, Iraq
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Hilbert A, Madai VI, Akay EM, Aydin OU, Behland J, Sobesky J, Galinovic I, Khalil AA, Taha AA, Wuerfel J, Dusek P, Niendorf T, Fiebach JB, Frey D, Livne M. BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation in Patients With Cerebrovascular Disease. Front Artif Intell 2020; 3:552258. [PMID: 33733207 PMCID: PMC7861225 DOI: 10.3389/frai.2020.552258] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [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: 04/15/2020] [Accepted: 08/25/2020] [Indexed: 12/02/2022] Open
Abstract
Introduction: Arterial brain vessel assessment is crucial for the diagnostic process in patients with cerebrovascular disease. Non-invasive neuroimaging techniques, such as time-of-flight (TOF) magnetic resonance angiography (MRA) imaging are applied in the clinical routine to depict arteries. They are, however, only visually assessed. Fully automated vessel segmentation integrated into the clinical routine could facilitate the time-critical diagnosis of vessel abnormalities and might facilitate the identification of valuable biomarkers for cerebrovascular events. In the present work, we developed and validated a new deep learning model for vessel segmentation, coined BRAVE-NET, on a large aggregated dataset of patients with cerebrovascular diseases. Methods: BRAVE-NET is a multiscale 3-D convolutional neural network (CNN) model developed on a dataset of 264 patients from three different studies enrolling patients with cerebrovascular diseases. A context path, dually capturing high- and low-resolution volumes, and deep supervision were implemented. The BRAVE-NET model was compared to a baseline Unet model and variants with only context paths and deep supervision, respectively. The models were developed and validated using high-quality manual labels as ground truth. Next to precision and recall, the performance was assessed quantitatively by Dice coefficient (DSC); average Hausdorff distance (AVD); 95-percentile Hausdorff distance (95HD); and via visual qualitative rating. Results: The BRAVE-NET performance surpassed the other models for arterial brain vessel segmentation with a DSC = 0.931, AVD = 0.165, and 95HD = 29.153. The BRAVE-NET model was also the most resistant toward false labelings as revealed by the visual analysis. The performance improvement is primarily attributed to the integration of the multiscaling context path into the 3-D Unet and to a lesser extent to the deep supervision architectural component. Discussion: We present a new state-of-the-art of arterial brain vessel segmentation tailored to cerebrovascular pathology. We provide an extensive experimental validation of the model using a large aggregated dataset encompassing a large variability of cerebrovascular disease and an external set of healthy volunteers. The framework provides the technological foundation for improving the clinical workflow and can serve as a biomarker extraction tool in cerebrovascular diseases.
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Affiliation(s)
- Adam Hilbert
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Vince I. Madai
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
- Faculty of Computing, Engineering and the Built Environment, School of Computing and Digital Technology, Birmingham City University, Birmingham, United Kingdom
| | - Ela M. Akay
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Orhun U. Aydin
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Jonas Behland
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Jan Sobesky
- Centre for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
- Johanna-Etienne-Hospital, Neuss, Germany
| | - Ivana Galinovic
- Centre for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Ahmed A. Khalil
- Centre for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Berlin School of Mind and Brain, Mind, Brain, Body Institute, Humboldt-Universität Berlin, Berlin, Germany
- Biomedical Innovation Academy, Berlin Institute of Health, Berlin, Germany
| | - Abdel A. Taha
- Research Studio Data Science, Research Studios Austria, Salzburg, Austria
| | - Jens Wuerfel
- Department Biomedical Engineering, Medical Image Analysis Center AG, University of Basel, Basel, Switzerland
| | - Petr Dusek
- Department of Neurology, 1st Faculty of Medicine, Centre of Clinical Neuroscience, General University Hospital in Prague, Charles University, Prague, Czechia
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Jochen B. Fiebach
- Centre for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Dietmar Frey
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Michelle Livne
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
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Taha AA, Moustafa AHE, Abdel-Rahman HH, Abd El-Hameed MMA. Comparative biosorption study of Hg (II) using raw and chemically activated almond shell. ADSORPT SCI TECHNOL 2018; 36:521-548. [DOI: 10.1177/0263617417705473] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/02/2023] Open
Abstract
This work presents a comparison between the biosorption of Hg (II) by raw almond shell and activated almond shell. Almond shell based activated carbon has been obtained by physicochemical activation. Batch biosorption results confirmed that, activating condition has a strong influence on the final biosorption process. The biosorbent was characterized using scanning electron microscopy and Fourier transform infrared spectroscopy. To optimize the biosorption conditions pH, adsorbent dose, initial concentration, contact time, stirring speed, and temperature on Hg (II) removal were studied. The optimum conditions for maximum Hg (II) was achieved at 20 and 10 min for raw almond shell and activated almond shell, respectively. The equilibrium data were described well by Langmuir, Freundlich, Dubinin–Radushkevich isotherm models and appling a test of model fitness. Best fit of Langmuir and Freundlich models were found for experimental data, which reveal the homogenous surface of raw almond shell and the heterogeneity of activated almond shell surface. The kinetic data had been divided into either pseudo first order or second order on the basis of the best fit obtained from calculations, confirmed by a test of kinetic validity. An industrial application was examined to improve high biosorption capacity of raw and activated almond shells toward Hg (II).
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Affiliation(s)
- AA Taha
- Chemistry Department, Faculty of Science, Alexandria University, Alexandria, Egypt
| | - AHE Moustafa
- Chemistry Department, Faculty of Science, Alexandria University, Alexandria, Egypt
| | - HH Abdel-Rahman
- Chemistry Department, Faculty of Science, Alexandria University, Alexandria, Egypt
| | - MMA Abd El-Hameed
- Chemistry Department, Faculty of Science, Alexandria University, Alexandria, Egypt
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8
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Abstract
The cementation of cadmium ions (Cd(2+)) from aqueous solution onto zinc was studied in two batch reactors, a batch stirred reactor lined with a cylindrical zinc sheet and another that used a rotating zinc cylinder. The rate of cadmium removal was studied as a function of speed of rotation, initial cadmium concentration, and the addition of certain surfactants and their mixtures. Rotational speed and initial cadmium concentration affect the rate of cadmium cementation. It was found that sodium dodecyl sulfate (SDS) improves the rate of cadmium cementation, while Triton X-100 and cetyltrimethylammonium bromide (CTAB) inhibit it. Thermodynamic parameters were calculated and discussed. Visual observations showed that cadmium deposits on the zinc sheet are in the form of a powder, while cadmium deposits on the zinc cylinder, in the presence of SDS, give porous grains which increases the roughness of the surface, leading to an increase in the cementation rate. The lowest deposit porosity was observed in the presence of CTAB, which corresponds to the highest decrease obtained in the rate of cadmium cementation. The cementation process was successfully applied to recover Cd(2+) spiked into an industrial wastewater sample.
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Affiliation(s)
- A A Taha
- Department of Chemistry, Faculty of Science, University of Alexandria, Alexandria, Egypt.
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9
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Taha AA. Effect of surfactants on the rate of solid-liquid mass transfer with gas generation at the interface. J Colloid Interface Sci 2004; 275:235-42. [PMID: 15158404 DOI: 10.1016/j.jcis.2004.01.031] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2003] [Accepted: 01/13/2004] [Indexed: 10/26/2022]
Abstract
The effect of Triton X-100 (nonionic surfactant) and cetyltrimethylammonium bromide (CTAB), cationic surfactant, on the mass transfer coefficient of the cathodic reduction of ferricyanide ions and anodic oxidation of ferrocyanide ions at hydrogen- and oxygen-evolving electrodes, respectively, was studied. It was found that the limiting current decreases by amounts ranging from 26.67 to 54.67% for Triton X-100 and from 20 to 46.0% for CTAB in the case of cathodic reduction of ferricyanide ions under natural convection at H2-evolving electrodes and from 23.81 to 51.43% for Triton X-100 and from 18.10 to 40.95% for CTAB in the case of anodic oxidation of ferrocyanide ions under natural convection at O2-evolving electrodes, depending on the concentration of surfactant. Also the effects of Triton X-100 and CTAB on the gas hold-up and cell voltage were studied. The presence of surfactant in electrolytes was found to decrease the mass transfer coefficient by an amount ranging from 5.37 to 95.9%, depending on the operating conditions. Gas hold-up, cell voltage, and power consumption were found to increase in the presence of surfactant.
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Affiliation(s)
- A A Taha
- Department of Chemistry, Faculty of Science, University of Alexandria, Egypt.
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Ortner MAE, Taha AA, Schreiber S, Wirth J, Weber-Eibl J, Ernst H, Lochs H. Endoscopic injection of mitomycin adsorbed on carbon particles for advanced esophageal cancer: a pilot study. Endoscopy 2004; 36:421-5. [PMID: 15100951 DOI: 10.1055/s-2004-814327] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
BACKGROUND AND STUDY AIMS Patients with advanced, unresectable esophageal carcinoma have an extremely poor prognosis, with dysphagia being the major problem. The aim of this prospective pilot study was to evaluate the efficacy of local injections of mitomycin adsorbed onto activated carbon particles (MMC-CH) in advanced unresectable esophageal squamous-cell carcinoma. The primary outcome parameter was survival time; secondary parameters were dysphagia and quality of life. PATIENTS AND METHODS Ten consecutive patients with stage IV esophageal carcinoma (age: median 58, range 32 - 78), median tumor length 11 cm (range 5 - 15) received four weekly injections of 15 mg (10 ml) MMC-CH into the endoscopically visualized tumor, via a 5-mm sclerotherapy needle. The tumor stage, symptom score, and quality of life (measured using the Karnofsky index) were assessed before and after therapy and every 2 months thereafter. RESULTS The median survival time after MMC-CH therapy was 16 weeks (95 % CI, 11.7 to 20.4). Dysphagia was reduced ( P < 0.001) in parallel with the reduction in the tumor mass ( r = 0.82, P = 0.01). The Karnofsky index ( P < 0.01) also improved after MMC-CH treatment. MMC-CH was well tolerated, and no side effects were observed. CONCLUSIONS Endoluminal MMC-CH therapy appears to be an effective, inexpensive, and well-tolerated treatment for unresectable advanced squamous-cell esophageal carcinoma.
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Affiliation(s)
- M-A E Ortner
- Department of Gastroenterology/Hepatology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.
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Abdel-Magied EM, Taha AA, al-Qarawi AA, Elfaki MG. The parotid, mandibular and lateral retropharyngeal lymph nodes of the camel (Camelus dromedarius). Anat Histol Embryol 2001; 30:199-203. [PMID: 11534324 DOI: 10.1046/j.1439-0264.2001.00308.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
The parotid, mandibular and lateral retropharyngeal lymph nodes of the dromedary camel were examined using both light and electron microscopy. All three lymph nodes were lobulated. They did not show the characteristic medulla, cortex and paracortex of typical lymph nodes. Instead, they contained lymphatic nodules, dense anodular lymphoid tissue and diffuse lymphoid tissue dispersed throughout the lymph node. Networks of sinuses were present in the diffuse lymphoid tissue. The diffuse lymphoid tissue in the periphery of all lymph nodes examined was characterized by numerous erythrocytes within and around its network of sinuses. The nodal sinuses were contiguous with the septal vessels, which are considered the possible source of erythrocytes seen in this study. The lymph nodes that were seen in this study resembled the haemolymph nodes of other mammals with regard to their content of erythrocytes but were unique in being located in sites that were typical of ordinary lymph nodes. Morphometric analysis has shown that the percentage volume densities of the stroma and the various parenchymal components were similar in the three lymph nodes.
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Affiliation(s)
- E M Abdel-Magied
- Department of Veterinary Medicine, King Saud University, PO Box 1482, Buraidah, Kingdom of Saudi Arabia
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12
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Abstract
The Et2O extract from Psathyrella scobinacea culture fluids contained three new acetylenic alcohols: deca-5,7,9-triynol, (-)hepta-4,6-diyne-2,3-diol, and (-)hept-cis 4-en-6-yne-2,3-diol; two known dichloroanisoles: 3,5-dichloro-4-methoxybenzaldehyde and 3,5-dichloro-4-methoxybenzyl alcohol; and three known acetylenic acids: octa-2,4,6-triynoic acid, dec-trans-2-ene-4,6,8-triynoic acid and its cis-isomer.
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Affiliation(s)
- A A Taha
- Department of Chemistry, College of Science, University of Bahrain, Isa Town.
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13
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Abstract
The thyroid gland of sexually immature dromedary camels was studied using both light and electron microscopy. The thyroid gland contained follicles of different sizes in both summer and winter. However, most of the follicles were large in summer and small in winter. The large follicles were lined by very low cuboidal or semi-squamous follicular cells whereas the small ones were lined by high cuboidal or low columnar follicular cells. Electron microscopy showed that the very low cuboidal follicular cells were poor in organelles and were considered hypoactive. High cuboidal follicular cells on the other hand, were rich in organelles that included mitochondria, cisternae of rough endoplasmic reticulum, secretory vesicles, colloid droplets, heterosomes and autophagic vacuoles; they were considered to be very active. The possible role played by these organelles is synthesis of thyroglobulin and liberation of tri- and tetraiodothyronine is discussed. A few degenerate follicular cells were infrequently encountered in the camel thyroid. Parafollicular (C) cells were not seen in this study either with light or electron microscopy.
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Affiliation(s)
- E M Abdel-Magied
- Department of Veterinary Medicine, King Saud University, PO Box 1482, Buraidah, Kingdom of Saudi Arabia
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Abstract
The pharmacokinetics of amoxicillin were studied in five Desert sheep and five Nubian goats after intravenous (i.v.) or intramuscular (i.m.) administration of a single dose of 10 mg/kg body weight. Following i.v. injection, the plasma concentration-versus-time data were best described by a two-compartment open model. The kinetic variables were similar in both species except for the volume of the central compartment (Vc), which was larger in sheep (p<0.05). Following i.m. injection, except for the longer half-life time of absorption in goats (p<0.05), there were no significant differences in other pharmacokinetic parameters between sheep and goats. The route of amoxicillin administration had no significant effect on the terminal elimination half-life in either species. The bioavailability of the drug (F) after i.m. administration was high (> 0.90) in both species. These results indicate that the pharmacokinetics of amoxicillin did not differ between sheep and goats; furthermore, because of the high availability and short half-life of absorption, the i.m. route gives similar results to the i.v. route. Therefore, identical intramuscular and intravenous dose regimens should be applicable to both species.
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Affiliation(s)
- H A Elsheikh
- Department of Veterinary Basic Sciences, Faculty of Veterinary Medicine, Jordan University of Science and Technology, Irbid.
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Taha AA, Elsheikh HA, Khalafalla AE, Osman IA, Abdullah AS. Disposition kinetics of tylosin administered intravenously and intramuscularly in desert sheep and Nubian goats. Vet J 1999; 158:210-5. [PMID: 10558841 DOI: 10.1053/tvjl.1999.0374] [Citation(s) in RCA: 20] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The pharmacokinetic behaviour of tylosin was compared in five Desert sheep and five Nubian goats. The animals were given a single dose of 20% tylosin (15 mg/kg), either intravenously (i.v.) or intramuscularly (i.m.). Following i.v. administration, the volumes of distribution and the elimination half-life times were similar in both species, whereas in goats a greater volume of the central compartment and faster clearance were observed. For the i.m. route, similar pharmacokinetics were observed in both species. The bioavailability (f) of the drug in goats (0.84 +/- 0.11) was not significantly higher than that in sheep (0.73 +/- 0.08). The present study has shown that, despite the significant differences in some of the drug pharmacokinetic parameters between sheep and goats for the i.v. route, identical intravenous and intramuscular dosage regimens of tylosin may be recommended for the two species.
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Affiliation(s)
- A A Taha
- Department of Medicine, Faculty of Veterinary Science, University of Khartoum, Khartoum North, Sudan
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Abstract
OBJECTIVE To review our 10-year experience of reconstruction of the supra-aortic trunks. DESIGN Retrospective study. SETTING Teaching hospital, The Netherlands. SUBJECTS 47 patients who required reconstruction of the supra-aortic trunks for stenotic or occlusive disease between April 1987 and May 1997. INTERVENTIONS Right-sided bifurcation graft through a sternotomy (n = 25), left-sided thoracotomy (n = 1), and extra-anatomic bypass (n = 21). MAIN OUTCOME MEASURES Morbidity, mortality, and long term patency. RESULTS 3 patients died (6%); 7 (15%) developed major complications (leak from the brachiocephalic stump, n = 2, and acute occlusion of the bypass graft, n = 5) all of which were successfully treated by immediate reoperation; and 9 (19%) developed minor complications, all of which resolved within 3 months. The median follow up was 36 months (range 1-108), and the 3-year patency rate was 80%. No patient died during the follow up period, but a further 3 were lost to follow up. The remaining 41 were all assessed by duplex scanning or angiography, and 3 required further operation for recurrent symptoms; 33 remained completely free of symptoms. CONCLUSION Symptomatic stenotic or occlusive lesions of the supra-aortic trunks can be treated with acceptable morbidity and mortality, giving long term benefit to patients.
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Affiliation(s)
- A A Taha
- Department of Vascular Surgery, University Hospital Vrije Universiteit, Amsterdam, The Netherlands
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Abstract
The pattern of distribution of the coronary arteries of the camel was studied by combining dissection and vinyl acetate casts. The results showed that in the camel the right coronary artery supplies the interventricular subsinuosal artery, characteristic of a right coronary pattern. The septal branch that supplied the interventricular septum originated from the paraconal interventricular artery. A muscular bridge was observed crossing each of the paraconal and subsinuosal interventricular arteries in the middle third of the longitudinal grooves.
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Affiliation(s)
- A A Taha
- Department of Veterinary Medicine, Faculty of Agriculture and Veterinary Medicine, King Saud University, Kingdom of Saudi Arabia
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Abstract
The carotid body of the goat was found to be a small oval or rounded parenchymatous organ. It was characterized by its profound vascularity. Delicate septa divided the parenchyma into small feebly defined lobules. Electron microscopy revealed that the parenchyma comprised type I cells, type II cells, nerve endings, axons and fenestrated dilated capillaries. Type I cells were characterized with electron dense-cored vesicles. They showed variations in size and concentration of the dense-cored vesicles and number of mitochondria. The possibility that these variations are reflections of different stages of activity is discussed. Type II cells were less numerous than type I cells, relatively small and devoid of dense-cored vesicles. They usually surrounded small groups of type I cells and associated nerve endings and axons. Presumptive afferent nerve endings characterized with many clear vesicles, occasional large granular vesicles and varying numbers of slender mitochondria, lay apposed to type I cells. Nerve endings of this kind showed afferent and efferent synaptic junctions with type I cells. Presumptive sympathetic efferent endings were occasionally seen within the lobules but never lay apposed to type I cells or afferent nerve ending.
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Affiliation(s)
- E M Abdel-Magied
- Department of Veterinary Medicine, King Saud University, Buraidah, Kingdom of Saudi Arabia
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Abstract
The poll glands of the camel are tubuloalveolar glands. They consist of lobules separated by interlobular connective tissue. Adrenergic axons and blood vessels including fenestrated capillaries are present in the intralobular connective tissue in close proximity to the secretory cells. The prominent features of the secretory cell cytoplasm are many mitochondria, smooth endoplasmic reticulum, and many vesicles in various secretory stages. It is concluded that the secretory cells have apocrine as well as merocrine modes of secretion. The glands may have the ability to uptake hormones and concentrate them. Additional work is needed before considering these glands as steroid-secreting glands.
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Affiliation(s)
- A A Taha
- Department of Veterinary Medicine, Faculty of Agriculture and Veterinary Medicine, Buraydah, Kingdom of Saudi Arabia
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Homeida AM, Khalil MG, Taha AA. Plasma concentrations of progesterone, oestrogens, testosterone and LH-like activity during the oestrous cycle of the camel (Camelus dromedarius). J Reprod Fertil 1988; 83:593-8. [PMID: 3411553 DOI: 10.1530/jrf.0.0830593] [Citation(s) in RCA: 28] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Peripheral plasma concentrations of progesterone, total oestrogens and testosterone (measured by RIAs) and LH (monitored by the mouse Leydig cell bio-assay) were measured in 8 female camels for a complete oestrous cycle (23.1 +/- 1.2 days). The absence of an LH surge and a low concentration of progesterone (less than 1 ng/ml) during oestrus (5 days) and throughout the cycle indicated a failure of spontaneous ovulation and absence of a subsequent luteal phase in this species. High concentrations of testosterone and oestrogens indicated that the oestrous cycle in the camel is mostly follicular and that the increasing values of the two hormones during follicular development (5 days) is probably the stimulus to behavioural oestrus.
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Affiliation(s)
- A M Homeida
- Department of Veterinary Medicine, University of Khartoum, Sudan
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Taha AA, Abdalla MA. Ultrastructural morphometric observations on the extramural aortico-pulmonary bodies of the domestic fowl. J Anat 1988; 157:169-73. [PMID: 3198477 PMCID: PMC1261951] [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: 01/04/2023] Open
Abstract
The extramural aortico-pulmonary bodies of the domestic fowl were analysed in electron micrographs by point-counting morphometry. The Type I cell constituted about 34% of the total volume of the parenchyma, whereas the supporting cells (Type II cells, pericytes and Schwann cells) constituted about 26%. The blood capillaries occupied the lowest volume density of about 5%. The mitochondria and the dense-cored vesicles occupied about the same volume (8%) of the Type I cell cytoplasm. The results obtained in the present study are compared with other similar studies on the aortic and carotid bodies of mammals.
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Affiliation(s)
- A A Taha
- Department of Anatomy, Faculty of Veterinary Science, Khartoum North, Sudan
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Taha AA. Ultrastructure of the sebaceous glands of the camel (Camelus dromedarius). J Anat 1988; 156:157-68. [PMID: 3417542 PMCID: PMC1261919] [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: 01/05/2023] Open
Abstract
The sebaceous gland of the camel has been studied by light and electron microscopy. The gland is lobed but the lobes are not subdivided into lobules. The ultrastructure of the sebaceous gland of the camel is generally similar to that of other animals. It consists of cells at different stages of development and maturation. The cells which are programmed to produce lipid secretion are probably those which lose contact with the basal lamina. Various forms of smooth endoplasmic reticulum are seen in the sebaceous cells. These forms include grid lattice, membranous whorls, and parallel cisterns; all of them are associated with lipid droplets which suggest that the smooth endoplasmic reticulum may be involved in lipid synthesis. The connective tissue around the sebaceous gland contains myelinated and unmyelinated axons. Some of these axons possibly penetrate the basal lamina to innervate the cells at the periphery. Encapsulated endings, which closely resemble Ruffini endings, are occasionally observed in the vicinity of the gland.
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Affiliation(s)
- A A Taha
- Department of Anatomy, Faculty of Veterinary Science, Khartoum North, Sudan
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Taha AA. Effects of denervation on baroreceptor and chemoreceptor endings in the aorta and pulmonary trunk of the domestic fowl (Gallus gallus domesticus). J Anat 1987; 150:49-60. [PMID: 3654341 PMCID: PMC1261664] [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: 01/06/2023] Open
Abstract
Denervation experiments were carried out on twelve adult domestic fowls in order to investigate the location of the cell bodies of baroreceptor and chemoreceptor endings of the aorta and pulmonary trunk. Soon after both distal vagal ganglionectomy and midcervical vagotomy, baroreceptor and chemoreceptor endings showed distinct signs of abnormalities. These abnormal signs included many irregular and deformed clear vesicles, large membranous whorls and vacuolated mitochondria. The endings which were severely affected became greatly swollen and almost empty except for a flocculent substance and disordered filamentous material. It is suggested that the cell bodies of the majority of baroreceptor and chemoreceptor endings are not in the distal vagal ganglion and may be in the proximal vagal ganglion and/or proximal or distal glossopharyngeal ganglia. The chief cells of the aortico-pulmonary bodies were also affected after denervation when their axonal endings degenerated. The degenerative changes took the form of many expanded membrane-bound empty spaces and increased size and number of the dense-cored vesicles. It is concluded that the axonal endings exert a trophic effect upon the granular cells.
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Affiliation(s)
- A A Taha
- Department of Anatomy, Faculty of Veterinary Science, University of Khartoum, Sudan
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Taha AA, King AS. Aortico-pulmonary bodies in the domestic fowl: ultrastructure, innervation and secretion. J Anat 1986; 149:41-53. [PMID: 3693109 PMCID: PMC1261632] [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: 01/07/2023] Open
Abstract
In adult and immature domestic fowl, aggregations of large pale-staining cells were found in the wall of the aorta, and of the pulmonary trunk and arteries, in modified regions typified by interruption or loss of elastic laminae and smooth muscle cells. Encapsulated extramural aggregations of similar cells were identified either on the actual surface or well outside the arterial wall of the aorta, and pulmonary trunk and arteries. The electron microscope revealed that the pale cells in these intramural and extramural structures were granular cells characterised by dense-cored vesicles typically about 60-140 nm in diameter. Supporting cells partly invested the granular cells. These intramural and extramural structures are interpreted as aortico-pulmonary bodies. The extramural and to a lesser extent the intramural cells were associated with many axonal endings and fenestrated blood capillaries. The axonal endings formed presumptive afferent, efferent and reciprocal synapses with the granular cells. Both intra- and extramural granular cells displayed evidence of exocytosis and were also shown by autoradiography to handle amines. It is concluded that the ultrastructural features of these aortico-pulmonary bodies resemble those of the carotid body. It is therefore suggested that the aortico-pulmonary bodies of the domestic fowl have a chemoreceptor function similar to that of the carotid body. It is also suggested that they may have a general secretory function.
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Affiliation(s)
- A A Taha
- Department of Anatomy, Faculty of Veterinary Science, University of Khartoum, Sudan
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Taha AA, Abdel-Magied EM, King AS. Ultrastructure of aortic and pulmonary baroreceptors in the domestic fowl. J Anat 1983; 137 (Pt 1):197-207. [PMID: 6630033 PMCID: PMC1171803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Baroreceptor regions are definitely present in the arterial wall of the aorta and pulmonary arteries of the domestic fowl. In such regions, the arterial wall is modified by the interruption and absence of the elastic laminae and smooth muscle cells. The baroreceptor endings are similar ultrastructurally to the baroreceptors of the mammalian aorta and carotid sinus; therefore they are slowly adapting. Some of the amine- or peptide-containing endings, which are present in the modified regions, share the same Schwann cell with the baroreceptor endings; they probably modulate the stimulus threshold of the baroreceptor endings. Likewise, some of the cholinergic endings share the same Schwann cell with the baroreceptor endings, and may form the efferent branch of a reflex arc and thereby modify the tension of the arterial musculature which is then registered by the baroreceptor endings. There is a possibility that aminergic anc cholinergic endings interact with each other since they sometimes share the same Schwann cell. The encapsulated endings which are reported in this investigation are similar to those of the avian carotid arteries, and they, too, should be slowly adapting to pressure changes in the arterial wall.
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Abstract
Tritiated leucine was injected into the distal vagal ganglion of 11 domestic fowl, which survived for 12-24 h under general anaesthesia. The cells of this ganglion are known to be exclusively afferent. EM autoradiography showed that in all 11 birds the vast majority of the silver grains fell upon the nervous tissues of the carotid body. In 5 of these birds a quantitative analysis was made, using point-counting morphometry. The incidence of silver grain per unit area was found to be 26 times greater in axonal endings than in the non-nervous components, and 15 times greater in axons in transit than in non-nervous components. The difference in incidence per unit area between these nervous and non-nervous components was highly significant (P less than 0.001). Of all the observed axonal endings 77% were labelled, but there is evidence that this is a substantial underestimate of the total population of afferent endings; in one bird 88% of the endings were labelled. Of the axons in transit, 18% were labelled. This low value is believed to be related to transfer of the label to the axonal endings by the fast component of axonal transport. Afferent and reciprocal synapses occurred in labelled axonal endings, which were therefore considered to have an afferent function. 'Efferent' type synapses also occurred in labelled endings, and therefore belonged to axons which in fact were afferent in function. It is concluded that the innervation of the carotid body of the domestic fowl is almost entirely afferent, the nerve cell bodies being in the distal vagal ganglion. Only very few efferent axonal endings are present. Ultrastructural features, including synaptic morphology, appear to constitute unreliable criteria for distinguishing between afferent and efferent axonal endings in the carotid body.
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Brewer D, Feicht A, Taylor A, Keeping JW, Taha AA, Thaller V. Ovine ill-thrift in Nova Scotia. 9. Production of experimental quantities of isocyanide metabolites of Trichoderma hamatum. Can J Microbiol 1982; 28:1252-60. [PMID: 6758924 DOI: 10.1139/m82-186] [Citation(s) in RCA: 20] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Laboratory cultures of Trichoderma hamatum produce metabolites that are characterized by an isocyanide functionality. Three such metabolites predominate. One is the known compound trichoviridin (I). The other two, described here for the first time, are 3-(3-isocyano-6-oxabicyclo[3,1,0]hex-2-en-5-yl)acrylic acid (II) and a very unstable compound 3-(3-isocyanocyclopent-2-enylidene-)propionic acid (III). Production of these three metabolites by a random sample of wild isolates of the fungus has been examined. At least one of these isocyanides was isolated from all cultures in which the culture broth inhibited the growth of Micrococcus luteus. The relative amounts of the three isocyanides produced by individual isolates were not the same and cultures were found in which I, II, or III was the main product. The isocyanide III was produced by all wild isolates which had antibiotic activity in their culture broth, and it was present in the concentration range 2-40 mg X L-1.
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Abdel-Magied EM, Taha AA, King AS. An ultrastructural investigation of a baroreceptor zone in the common carotid artery of the domestic fowl. J Anat 1982; 135:463-75. [PMID: 7153167 PMCID: PMC1169397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
The wall of the common carotid artery of the domestic fowl possesses a baroreceptor zone around the origin of the artery to the carotid body. The zone comprises about 20 small foci which have undergone a fibrous modification. Within these foci there are bare endings, which closely resemble ultrastructurally the baroreceptors of the mammalian carotid sinus in their mitochondrial content, relationship to collagen and elastic fibres, and abnormal organelles. These should be slowly adapting baroreceptors, similar functionally to the baroreceptors of the mammalian carotid sinus. Also present in the baroreceptor zone are a few encapsulated endings, resembling in structure the simplest encapsulated mechanoreceptors of mammals. These, too, should be slowly adapting but may be capable of slightly more subtle responses to pressure changes in the arterial wall. Some presumptive efferent axonal endings are associated with smooth muscle cells, and may modify the tension of the arterial musculature. In general, the afferent innervation of the avian carotid baroreceptor zone appears to be less profuse than that of the mammalian carotid sinus.
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