Data-Analytics Modeling of Electrical Impedance Measurements for Cell Culture Monitoring
Data-Analytics Modeling of Electrical Impedance Measurements for Cell Culture Monitoring
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DOI：
10.3390/s19214639
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发表时间：
2019-11-01
期刊：
影响因子：
3.9
通讯作者：
Yufera, Alberto
中科院分区：
文献类型：
--
作者：
Garcia, Elvira;Perez, Pablo;Yufera, Alberto
实验室自动化和芯片实验室设备应用中的高通量数据分析挑战不断增加。在细胞培养监测中，特别是细胞-基质阻抗传感技术（ECIS）已被广泛用于各种应用。 ECIS 的主要缺点之一是需要实现复杂的电气模型来解码由电极、介质和细胞组成的整个系统的电气性能。在这项工作中，我们提出了一种基于多项式回归、数据分析模型的数据分析和特定生物参数（细胞培养物的填充因子）预测的新方法。该方法成功应用于特定的 ECIS 回路和两种不同的细胞培养物：N2A（小鼠神经母细胞瘤细胞系）和成肌细胞。数据分析建模方法可用于解码不同细胞系的电阻抗测量值，前提是细胞培养物生长的代表性数据量可用，从而解决了传统上在电模型实施中发现的困难。这对于组织工程方案、芯片实验室和可穿戴设备应用中细胞培养的控制算法的设计特别重要。
High-throughput data analysis challenges in laboratory automation and lab-on-a-chip devices' applications are continuously increasing. In cell culture monitoring, specifically, the electrical cell-substrate impedance sensing technique (ECIS), has been extensively used for a wide variety of applications. One of the main drawbacks of ECIS is the need for implementing complex electrical models to decode the electrical performance of the full system composed by the electrodes, medium, and cells. In this work we present a new approach for the analysis of data and the prediction of a specific biological parameter, the fill-factor of a cell culture, based on a polynomial regression, data-analytic model. The method was successfully applied to a specific ECIS circuit and two different cell cultures, N2A (a mouse neuroblastoma cell line) and myoblasts. The data-analytic modeling approach can be used in the decoding of electrical impedance measurements of different cell lines, provided a representative volume of data from the cell culture growth is available, sorting out the difficulties traditionally found in the implementation of electrical models. This can be of particular importance for the design of control algorithms for cell cultures in tissue engineering protocols, and labs-on-a-chip and wearable devices applications.