Dynamic Modelling and Prediction of Cytotoxicity on Microelectronic cell Sensor Array

Abstract

A real‐time cell electronic sensing (RT‐CES) system has been used for label‐free dynamic measurements of cell responses to toxicant. Cells are grown onto the surfaces of the microelectronic sensors. Changes in cell number expressed as cell index (CI) have been recorded on‐line as time series. The CI data are used for dynamic modelling or parameter estimation for cell cytotoxicity process. We consider two dynamic modelling approaches, namely data‐based system identification and first principle modelling. It is shown that data‐based system identification can provide a quick solution for the cytotoxicity dynamic models and is effective for short‐term predictions. It, however, can be poor for long‐term predictions, particularly if there is no output correction, i.e., when the model is used for simulation. In view of this, the first principle modelling approach by considering fundamental physical principles such as toxicant transport is explored. For long‐term prediction or simulation, the prediction performance for some of cytotoxicity process is dramatically improved using the models obtained from the latter approach. This happens only if the underlying mechanism is truly understood. Through several cytotoxicity modelling and validation studies, it is shown that the black box modelling and first principle modelling both should be considered in challenging modelling problems such as the cytotoxicity. Pros and cons of the two modelling approaches are discussed.

Early determination of toxicant concentration in water supply using MHE

“…The RT-CES system (ACEA Biosciences, CA, U.S.A.) is used for this study and has been described in (Xing et al, 2005;Huang and Xing, 2006). Briefly, as shown in Fig.…”

“…In Huang and Xing (2006), two types of models were developed and validated 62; 0.91; 1.97; 2.89; 4.25; 5.78 in the unit of μM. Increasing dose leads to decreasing (CI).…”

“…The uptake mechanism describes the transport process of the toxicant into a cell as illustrated in Fig. 4 (Huang and Xing, 2006). This mechanism relates the extracellular concentration c e (representing the concentration of a toxicant in the environment) and the intracellular concentration c i (concentration inside the cell) and it is described by El-Kareh and Secomb (2005) as follows : The first step in cytotoxicity (the uptake mechanism) is supposed to be rather consistent; however the second step (cell killing) differs with respect to the toxicant and can be described through cell population dynamics aṡ N = f (C, N ) where N is the cell population and C can be the intracellular or the extracellular concentration of the toxicant or a combination of them.…”

“…To achieve this purpose, mathematical modeling and real-time measurements are necessary. Two mathematical models have been developed and validated by Huang and Xing (2006) to predict cell toxicity response to mercury (II) chloride and sodium dichromate [chromium (VI)] toxicity. The measurements of toxicity…”

A critical comparison of cell-based sensor systems for the detection of Cr(VI) in aquatic environment

“…In this context, Electrical cell impedance spectroscopy [22] has been demonstrated to be feasible to monitor various aquatic toxicants including heavy metals and industrial pollutants [23]. Cr(VI) detection using cell-based impedance sensors was already performed before, using the Real-Time Cell Electronic Sensor [24]. Generally, heavy metals are the most insidious pollutants because of their non-biodegradable nature and ability to persist for long periods [25].…”