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导联场理论为设计用于生物细胞检测和观察的微电极阵列阻抗测量提供了一个强大的工具。

Lead field theory provides a powerful tool for designing microelectrode array impedance measurements for biological cell detection and observation.

作者信息

Böttrich Marcel, Tanskanen Jarno M A, Hyttinen Jari A K

机构信息

Biosignal Processing Group, Department of Computer Science and Automation, Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Gustav-Kirchhoff-Straße 2, 98693, Ilmenau, Germany.

Computational Biophysics and Imaging Group, BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Lääkärinkatu 1, 33520, Tampere, Finland.

出版信息

Biomed Eng Online. 2017 Jun 26;16(1):85. doi: 10.1186/s12938-017-0372-5.

DOI:10.1186/s12938-017-0372-5
PMID:28651645
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5485748/
Abstract

BACKGROUND

Our aim is to introduce a method to enhance the design process of microelectrode array (MEA) based electric bioimpedance measurement systems for improved detection and viability assessment of living cells and tissues. We propose the application of electromagnetic lead field theory and reciprocity for MEA design and measurement result interpretation. Further, we simulated impedance spectroscopy (IS) with two- and four-electrode setups and a biological cell to illustrate the tool in the assessment of the capabilities of given MEA electrode constellations for detecting cells on or in the vicinity of the microelectrodes.

RESULTS

The results show the power of the lead field theory in electromagnetic simulations of cell-microelectrode systems depicting the fundamental differences of two- and four-electrode IS measurement configurations to detect cells. Accordingly, the use in MEA system design is demonstrated by assessing the differences between the two- and four-electrode IS configurations. Further, our results show how cells affect the lead fields in these MEA system, and how we can utilize the differences of the two- and four-electrode setups in cell detection. The COMSOL simulator model is provided freely in public domain as open source.

CONCLUSIONS

Lead field theory can be successfully applied in MEA design for the IS based assessment of biological cells providing the necessary visualization and insight for MEA design. The proposed method is expected to enhance the design and usability of automated cell and tissue manipulation systems required for bioreactors, which are intended for the automated production of cell and tissue grafts for medical purposes. MEA systems are also intended for toxicology to assess the effects of chemicals on living cells. Our results demonstrate that lead field concept is expected to enhance also the development of such methods and devices.

摘要

背景

我们的目标是引入一种方法,以改进基于微电极阵列(MEA)的生物电阻抗测量系统的设计过程,从而更好地检测活细胞和组织并评估其活力。我们建议将电磁导联场理论和互易性应用于MEA设计和测量结果解释。此外,我们用双电极和四电极设置以及一个生物细胞对阻抗谱(IS)进行了模拟,以说明该工具在评估给定MEA电极配置检测微电极上或其附近细胞能力方面的作用。

结果

结果显示了导联场理论在细胞 - 微电极系统电磁模拟中的作用,描绘了双电极和四电极IS测量配置在检测细胞方面的根本差异。相应地,通过评估双电极和四电极IS配置之间的差异,证明了其在MEA系统设计中的应用。此外,我们的结果展示了细胞如何影响这些MEA系统中的导联场,以及我们如何利用双电极和四电极设置在细胞检测中的差异。COMSOL模拟器模型作为开源软件在公共领域免费提供。

结论

导联场理论可以成功应用于基于IS的生物细胞评估的MEA设计中,为MEA设计提供必要的可视化和深入理解。所提出的方法有望改进生物反应器所需的自动化细胞和组织操作系 统的设计和可用性,这些系统旨在用于医疗目的的细胞和组织移植物的自动化生产。MEA系统也用于毒理学,以评估化学物质对活细胞的影响。我们的结果表明,导联场概念有望促进此类方法和设备的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/0a8216843e95/12938_2017_372_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/2f9cb128f892/12938_2017_372_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/a8dcf7c93e83/12938_2017_372_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/721aaa4a66d0/12938_2017_372_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/94cf67648bdd/12938_2017_372_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/5066cf8ffc05/12938_2017_372_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/e738881c60fa/12938_2017_372_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/0a8216843e95/12938_2017_372_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/2f9cb128f892/12938_2017_372_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/a8dcf7c93e83/12938_2017_372_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/721aaa4a66d0/12938_2017_372_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/94cf67648bdd/12938_2017_372_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/5066cf8ffc05/12938_2017_372_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/e738881c60fa/12938_2017_372_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c75/5485748/0a8216843e95/12938_2017_372_Fig7_HTML.jpg

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