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Numerical optimization of gene electrotransfer into muscle tissue

BACKGROUND: Electroporation-based gene therapy and DNA vaccination are promising medical applications that depend on transfer of pDNA into target tissues with use of electric pulses. Gene electrotransfer efficiency depends on electrode configuration and electric pulse parameters, which determine the...

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Autores principales: Zupanic, Anze, Corovic, Selma, Miklavcic, Damijan, Pavlin, Mojca
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2990758/
https://www.ncbi.nlm.nih.gov/pubmed/21050435
http://dx.doi.org/10.1186/1475-925X-9-66
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author Zupanic, Anze
Corovic, Selma
Miklavcic, Damijan
Pavlin, Mojca
author_facet Zupanic, Anze
Corovic, Selma
Miklavcic, Damijan
Pavlin, Mojca
author_sort Zupanic, Anze
collection PubMed
description BACKGROUND: Electroporation-based gene therapy and DNA vaccination are promising medical applications that depend on transfer of pDNA into target tissues with use of electric pulses. Gene electrotransfer efficiency depends on electrode configuration and electric pulse parameters, which determine the electric field distribution. Numerical modeling represents a fast and convenient method for optimization of gene electrotransfer parameters. We used numerical modeling, parameterization and numerical optimization to determine the optimum parameters for gene electrotransfer in muscle tissue. METHODS: We built a 3D geometry of muscle tissue with two or six needle electrodes (two rows of three needle electrodes) inserted. We performed a parametric study and optimization based on a genetic algorithm to analyze the effects of distances between the electrodes, depth of insertion, orientation of electrodes with respect to muscle fibers and applied voltage on the electric field distribution. The quality of solutions were evaluated in terms of volumes of reversibly (desired) and irreversibly (undesired) electroporated muscle tissue and total electric current through the tissue. RESULTS: Large volumes of reversibly electroporated muscle with relatively little damage can be achieved by using large distances between electrodes and large electrode insertion depths. Orienting the electrodes perpendicular to muscle fibers is significantly better than the parallel orientation for six needle electrodes, while for two electrodes the effect of orientation is not so pronounced. For each set of geometrical parameters, the window of optimal voltages is quite narrow, with lower voltages resulting in low volumes of reversibly electroporated tissue and higher voltages in high volumes of irreversibly electroporated tissue. Furthermore, we determined which applied voltages are needed to achieve the optimal field distribution for different distances between electrodes. CONCLUSION: The presented numerical study of gene electrotransfer is the first that demonstrates optimization of parameters for gene electrotransfer on tissue level. Our method of modeling and optimization is generic and can be applied to different electrode configurations, pulsing protocols and different tissues. Such numerical models, together with knowledge of tissue properties can provide useful guidelines for researchers and physicians in selecting optimal parameters for in vivo gene electrotransfer, thus reducing the number of animals used in studies of gene therapy and DNA vaccination.
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spelling pubmed-29907582010-12-13 Numerical optimization of gene electrotransfer into muscle tissue Zupanic, Anze Corovic, Selma Miklavcic, Damijan Pavlin, Mojca Biomed Eng Online Research BACKGROUND: Electroporation-based gene therapy and DNA vaccination are promising medical applications that depend on transfer of pDNA into target tissues with use of electric pulses. Gene electrotransfer efficiency depends on electrode configuration and electric pulse parameters, which determine the electric field distribution. Numerical modeling represents a fast and convenient method for optimization of gene electrotransfer parameters. We used numerical modeling, parameterization and numerical optimization to determine the optimum parameters for gene electrotransfer in muscle tissue. METHODS: We built a 3D geometry of muscle tissue with two or six needle electrodes (two rows of three needle electrodes) inserted. We performed a parametric study and optimization based on a genetic algorithm to analyze the effects of distances between the electrodes, depth of insertion, orientation of electrodes with respect to muscle fibers and applied voltage on the electric field distribution. The quality of solutions were evaluated in terms of volumes of reversibly (desired) and irreversibly (undesired) electroporated muscle tissue and total electric current through the tissue. RESULTS: Large volumes of reversibly electroporated muscle with relatively little damage can be achieved by using large distances between electrodes and large electrode insertion depths. Orienting the electrodes perpendicular to muscle fibers is significantly better than the parallel orientation for six needle electrodes, while for two electrodes the effect of orientation is not so pronounced. For each set of geometrical parameters, the window of optimal voltages is quite narrow, with lower voltages resulting in low volumes of reversibly electroporated tissue and higher voltages in high volumes of irreversibly electroporated tissue. Furthermore, we determined which applied voltages are needed to achieve the optimal field distribution for different distances between electrodes. CONCLUSION: The presented numerical study of gene electrotransfer is the first that demonstrates optimization of parameters for gene electrotransfer on tissue level. Our method of modeling and optimization is generic and can be applied to different electrode configurations, pulsing protocols and different tissues. Such numerical models, together with knowledge of tissue properties can provide useful guidelines for researchers and physicians in selecting optimal parameters for in vivo gene electrotransfer, thus reducing the number of animals used in studies of gene therapy and DNA vaccination. BioMed Central 2010-11-04 /pmc/articles/PMC2990758/ /pubmed/21050435 http://dx.doi.org/10.1186/1475-925X-9-66 Text en Copyright ©2010 Anze et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Zupanic, Anze
Corovic, Selma
Miklavcic, Damijan
Pavlin, Mojca
Numerical optimization of gene electrotransfer into muscle tissue
title Numerical optimization of gene electrotransfer into muscle tissue
title_full Numerical optimization of gene electrotransfer into muscle tissue
title_fullStr Numerical optimization of gene electrotransfer into muscle tissue
title_full_unstemmed Numerical optimization of gene electrotransfer into muscle tissue
title_short Numerical optimization of gene electrotransfer into muscle tissue
title_sort numerical optimization of gene electrotransfer into muscle tissue
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2990758/
https://www.ncbi.nlm.nih.gov/pubmed/21050435
http://dx.doi.org/10.1186/1475-925X-9-66
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