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Slow and Persistent Virus Infections of Neurones — A Compromise for Neuronal Survival

  • U. G. Liebert
Chapter
Part of the Current Topics in Microbiology and Immunology book series (CT MICROBIOLOGY, volume 253)

Abstract

Infections of the central nervous system (CNS) with intracellular pathogens are different in many respects from infections in other parts of the body due to both the anatomical and functional properties of the brain and the biological basis of immune surveillance in the CNS. Damage to brain cells might have severe consequences for the entire body and, in many instances, would conceivably interfere with vital functions. The CNS is particularly vulnerable to pathological stimuli since it consists of highly differentiated cell populations with complex functionally integrated cell-to-cell connections and specialised cytoplasmic membranes. Furthermore, CNS tissue is unique in its high metabolic rate and relative lack of capacity to regenerate. While persistent infection by a non-cytopathogenic virus in cells of an organ with a low-energy requirement and a high rate of regeneration may be tolerated, in CNS tissue such infections may interfere with normal function, especially when neurones are affected (Johnson 1982). From this point of view, the paucity of lymphatic drainage and the lack of constitutive expression of immuneregulatory molecules, e.g. MHC class II and even class I, make sense. Fortunately, the participation of the CNS in a viral infection is relatively uncommon, but it may develop as a complication of many systemic viral infections. The special situation in CNS with its quasi-syncytium favours persistent infection without immediate destruction of the infected target cells. In the long run, however, functional deficits, progressive disease and eventually death of the individual ensue.

Keywords

Rabies Virus Measle Virus Central Nervous System Infection Mouse Hepatitis Virus Subacute Sclerosing Panencephalitis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • U. G. Liebert
    • 1
  1. 1.Institute of VirologyUniversity of LeipzigLeipzigGermany

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