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Predictive Cell Culture Time Evolution Based on Electric Models. | LitMetric

Predictive Cell Culture Time Evolution Based on Electric Models.

Biosensors (Basel)

Instituto de Microelectrónica de Sevilla (IMSE-CSIC), Av. Americo Vespuccio 24, 41092 Sevilla, Spain.

Published: June 2023

AI Article Synopsis

Article Abstract

Obtaining cell concentration measurements from a culture assay by using bioimpedance is a very useful method that can be used to translate impedances to cell concentration values. The purpose of this study was to find a method to obtain the cell concentration values of a given cell culture assay in real time by using an oscillator as the measurement circuit. From a basic cell-electrode model, enhanced models of a cell culture immersed in a saline solution (culture medium) were derived. These models were used as part of a fitting routine to estimate the cell concentration in a cell culture in real time by using the oscillation frequency and amplitude delivered by the measurement circuits proposed by previous authors. Using real experimental data (the frequency and amplitude of oscillations) that were obtained by connecting the cell culture to an oscillator as the load, the fitting routine was simulated, and real-time data of the cell concentration were obtained. These results were compared to concentration data that were obtained by using traditional optical methods for counting. In addition, the error that we obtained was divided and analyzed in two parts: the first part of the experiment (when the few cells were adapting to the culture medium) and the second part of the experiment (when the cells exponentially grew until they completely covered the well). Low error values were obtained during the growth phase of the cell culture (the relevant phase); therefore, the results obtained were considered promising and show that the fitting routine is valid and that the cell concentration can be measured in real time by using an oscillator.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10296600PMC
http://dx.doi.org/10.3390/bios13060668DOI Listing

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