Comparison of polynomial fitting versus single time point analysis of ECIS data for barrier assessment.
Comparison of polynomial fitting versus single time point analysis of ECIS data for barrier assessment.
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DOI：
10.14814/phy2.14983
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发表时间：
2021-10
影响因子：
2.5
通讯作者：
Damarla M
中科院分区：
文献类型：
--
作者：
Suresh K;Servinsky L;Johnston L;Punjabi NM;Dudek SM;Damarla M
电细胞基质阻抗传感（ECIS）是一种用于测量各种细胞类型（包括肺内皮细胞）屏障完整性的体外方法。这些实验经常用于肺损伤的体外评估。来自ECIS实验的数据由跨内皮单层的阻力的重复测量组成。因此，这些数据反映了电阻随时间发生的动态变化。目前评估ECIS数据的方法依赖于屏障功能的单点评估，例如跨内皮电阻的最大下降（TERMax）。然而，这种方法忽略了在TERMax数据点之前和之后发生的电阻变化。在这里，我们利用多项式曲线拟合实验生成的ECIS数据，从而允许通过检查组之间的平均多项式系数比较ECIS实验。我们发现，多项式曲线准确地拟合各种ECIS数据，和TERMax和系数分析之间的一致性不同类型的刺激，这表明TERMax的差异可能并不总是与一个显着的差异，在整体形状的ECIS配置文件。最后，我们确定了影响分析中获得的系数值的因素，包括在添加刺激之前用于基线测量的时间长度。多项式系数分析是另一种工具，可用于更全面地询问ECIS数据，以更好地了解导致体外屏障功能障碍变化的生物学基础。电细胞基质阻抗传感（ECIS）是用于评估细胞渗透性的常用方法。在这里，我们使用多项式拟合，以改善拟合和量化的电阻测量ECIS实验产生的。
Electrical cell‐substrate impedance sensing (ECIS) is an in vitro methodology for measuring the barrier integrity of a variety of cell types, including pulmonary endothelial cells. These experiments are frequently used for in vitro assessment of lung injury. The data derived from ECIS experiments consists of repeated measures of resistance across an endothelial monolayer. As such, these data reflect the dynamic changes in electrical resistance that occur over time. Currently methodologies for assessing ECIS data rely on single point assessments of barrier function, such as the maximal drop in trans‐endothelial electrical resistance (TERMax). However, this approach ignores the myriad of changes in resistance that occur before and after the TERMax data point. Herein, we utilize polynomial curve fitting on experimentally generated ECIS data, thus allowing for comparing ECIS experiments by examining the mean polynomial coefficients between groups. We show that polynomial curves accurately fit a variety of ECIS data, and that concordance between TERMax and coefficient analysis varies by type of stimulus, suggesting that TERMax differences may not always correlate with a significant difference in the overall shape of the ECIS profile. Lastly, we identify factors that impact coefficient values obtained in our analyses, including the length of time devoted to baseline measurements before addition of stimuli. Polynomial coefficient analysis is another tool that can be used for more comprehensive interrogation of ECIS data to better understand the biological underpinnings that lead to changes in barrier dysfunction in vitro. Electrical cell‐substrate impedance sensing (ECIS) is a common method for assessing cell permeability. Herein, we use polynomial fitting to improve fitting and quantification of resistance measurements generated by ECIS experiments.
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10.1165/rcmb.2003-0432oc
发表时间：
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影响因子：
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