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Current Directions in Biomedical Engineering

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering

Editor-in-Chief: Dössel, Olaf

Wissenschaftlicher Beirat: Augat, Peter / Buzug, Thorsten M. / Haueisen, Jens / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Kraft, Marc / Lenarz, Thomas / Leonhardt, Steffen / Malberg, Hagen / Penzel, Thomas / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Urban, Gerald A.

CiteScore 2018: 0.47

Source Normalized Impact per Paper (SNIP) 2018: 0.377

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Analysis of the in-vivo GABAB receptor relocalization and oligomerization in chronic pain conditions using spatial intensity distribution analysis

Jonas Bienzeisler / Marc Landry / Alberto Llorente / Gereon Hüttmann
Online erschienen: 07.09.2017 | DOI: https://doi.org/10.1515/cdbme-2017-0141


The response to the synaptic release of γ-Aminobutyric acid (GABA) in the central nervous system is mediated by the GABAB receptor, inter alia dependent on the formation of receptor oligomers. Spatial intensity distribution analysis (SpIDA) is an image analysis method measuring the oligomerization and density of proteins. It was used to quantify the oligomerization of GABAB receptors in the rodent spinal cord under conditions of chronic pain and inflammation. SpIDA reports a lowered density of tetrameric GABAB receptor entities in GABAergic neurons of the dorsal horn under these conditions compared to sham samples. The soma of neurons in the ventral horn is shown to be populated by single entities of the GABAB receptor. The findings underline the role of receptor oligomerization, as well as the membrane environment in regulating receptor function.

Keywords: Spatial Intensity Distribution Analysis; GABAB receptor; oligomerization; chronic pain


Online erschienen: 07.09.2017

Quellenangabe: Current Directions in Biomedical Engineering, Band 3, Heft 2, Seiten 669–673, ISSN (Online) 2364-5504, DOI: https://doi.org/10.1515/cdbme-2017-0141.

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©2017 Jonas Bienzeisler et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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