Moult, P. R. (2009) Neuronal glutamate and GABAA receptor function in health and disease. Biochemical Society Transactions, 37(6), pp. 1317-1322. (doi: 10.1042/BST0371317) (PMID:19909268)
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Abstract
Glutamate and GABA (γ-aminobutyric acid) are the predominant excitatory and inhibitory neurotransmitters in the mammalian CNS (central nervous system) respectively, and as such have undergone intense investigation. Given their predominance, it is no wonder that the reciprocal receptors for these neurotransmitters have attracted so much attention as potential targets for the promotion of health and the treatment of disease. Indeed, dysfunction of these receptors underlies a number of well-characterized neuropathological conditions such as anxiety, epilepsy and neurodegenerative diseases. Although intrinsically linked, the glutamatergic and GABAergic systems have, by and large, been investigated independently, with researchers falling into the ‘excitatory’ or ‘inhibitory’ camps. Around 70 delegates gathered at the University of St Andrews for this Biochemical Society Focused Meeting aimed at bringing excitation and inhibition together. With sessions on behaviour, receptor structure and function, receptor trafficking, activity-dependent changes in gene expression and excitation/inhibition in disease, the meeting was the ideal occasion for delegates from both backgrounds to interact. This issue of Biochemical Society Transactions contains papers written by those who gave oral presentations at the meeting. In this brief introductory review, I put into context and give a brief overview of these contributions.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Moult, Dr Peter |
Authors: | Moult, P. R. |
College/School: | College of Medical Veterinary and Life Sciences > School of Life Sciences College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience |
Journal Name: | Biochemical Society Transactions |
Publisher: | Portland Press |
ISSN: | 0300-5127 |
ISSN (Online): | 1470-8752 |
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