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Sigma Proteins: Evolution of the Concept of Sigma Receptors

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Attention for Chapter 8: Sigma-1 Receptor and Neuronal Excitability
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Chapter title
Sigma-1 Receptor and Neuronal Excitability
Chapter number 8
Book title
Sigma Proteins: Evolution of the Concept of Sigma Receptors
Published in
Handbook of experimental pharmacology, January 2017
DOI 10.1007/164_2017_8
Pubmed ID
Book ISBNs
978-3-31-965851-3, 978-3-31-965853-7
Authors

Saïd Kourrich, Kourrich, Saïd

Abstract

The sigma-1 receptor (Sig-1R), via interaction with various proteins, including voltage-gated and ligand-gated ion channels (VGICs and LGICs), is involved in a plethora of neuronal functions. This capability to regulate a variety of ion channel targets endows the Sig-1R with a powerful capability to fine tune neuronal excitability, and thereby the transmission of information within brain circuits. This versatility may also explain why the Sig-1R is associated to numerous diseases at both peripheral and central levels. To date, how the Sig-1R chooses its targets and how the combinations of target modulations alter overall neuronal excitability is one of the challenges in the field of Sig-1R-dependent regulation of neuronal activity. Here, we will describe and discuss the latest findings on Sig-1R-dependent modulation of VGICs and LGICs, and provide hypotheses that may explain the diverse excitability outcomes that have been reported so far.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 38%
Student > Bachelor 3 19%
Student > Master 1 6%
Lecturer > Senior Lecturer 1 6%
Other 1 6%
Other 2 13%
Unknown 2 13%
Readers by discipline Count As %
Neuroscience 8 50%
Biochemistry, Genetics and Molecular Biology 3 19%
Medicine and Dentistry 2 13%
Agricultural and Biological Sciences 1 6%
Engineering 1 6%
Other 0 0%
Unknown 1 6%