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Model systems for investigating disease processes in neurocysticercosis

Published online by Cambridge University Press:  15 November 2018

Anja de Lange
Affiliation:
Division of Cell Biology, Department of Human Biology, Neuroscience Institute and Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory, Cape Town, Western Cape 7935, South Africa
Siddhartha Mahanty
Affiliation:
Department of Medicine, The Peter Doherty Institute for Infection and Immunity and the Victorian Infectious Diseases Service, University of Melbourne/The Royal Melbourne Hospital, 792 Elizabeth Street, Melbourne, VIC 3000, Australia
Joseph V. Raimondo*
Affiliation:
Division of Cell Biology, Department of Human Biology, Neuroscience Institute and Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory, Cape Town, Western Cape 7935, South Africa
*
Author for correspondence: Joseph V. Raimondo, E-mail: joseph.raimondo@uct.ac.za

Abstract

Neurocysticercosis (NCC) occurs following brain infection by larvae of the cestode Taenia solium. It is the leading cause of preventable epilepsy worldwide and therefore constitutes a critical health challenge with significant global relevance. Despite this, much is still unknown about many key pathogenic aspects of the disease, including how cerebral infection with T. solium results in the development of seizures. Over the past century, valuable mechanistic insights have been generated using both clinical studies and animal models. In this review, we critically assess model systems for investigating disease processes in NCC. We explore the respective strengths and weaknesses of each model and summarize how they have contributed to current knowledge of the disease. We call for the continued development of animal models of NCC, with a focus on novel strategies for understanding this debilitating but often neglected disorder.

Type
Review Article
Copyright
Copyright © Cambridge University Press 2018 

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