Remote Cell Growth Sensing Using Self-Sustained Bio-Oscillations

Pérez, Pablo; Huertas, Gloria; Olmo, Alberto; Maldonado-Jacobi, Andrés; Serrano, Juan Alfonso; Martín, María; Daza, Paula; Yufera, A.

doi:10.3390/s18082550

Cited by 4 publications

(9 citation statements)

References 23 publications

(35 reference statements)

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“…The use of electrical impedance spectroscopy has been studied for cell culture monitoring in different works for a wide variety of applications, such as the study of cell proliferation [1,[27][28][29], cell toxicity [30], or cellular differentiation [31]. In [28], an oscillation-based circuit was proposed for the measurement of electrical impedance in cell cultures.…”

Section: Range Of Porementioning

confidence: 99%

Characterization and Monitoring of Titanium Bone Implants with Impedance Spectroscopy

Olmo

Hernández

Chicardi

et al. 2020

Sensors

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Porous titanium is a metallic biomaterial with good properties for the clinical repair of cortical bone tissue, although the presence of pores can compromise its mechanical behavior and clinical use. It is therefore necessary to characterize the implant pore size and distribution in a suitable way. In this work, we explore the new use of electrical impedance spectroscopy for the characterization and monitoring of titanium bone implants. Electrical impedance spectroscopy has been used as a non-invasive route to characterize the volumetric porosity percentage (30%, 40%, 50% and 60%) and the range of pore size (100–200 and 355–500 mm) of porous titanium samples obtained with the space-holder technique. Impedance spectroscopy is proved to be an appropriate technique to characterize the level of porosity of the titanium samples and pore size, in an affordable and non-invasive way. The technique could also be used in smart implants to detect changes in the service life of the material, such as the appearance of fractures, the adhesion of osteoblasts and bacteria, or the formation of bone tissue.

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Section: Range Of Porementioning

confidence: 99%

Characterization and Monitoring of Titanium Bone Implants with Impedance Spectroscopy

Olmo

Hernández

Chicardi

et al. 2020

Sensors

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“…As the computational tasks of specific smart sensors are usually less taxing than those of industrial field computers, the requirements for computational capacity are also less demanding. With the fast development of cheaper and smaller hardware platforms, functional OSs, power-supplies, and micromanufacturing techniques, the application of smart sensors in various fields is increasing (Lee et al, 2015;Zhao et al, 2016;Perez et al, 2018;Zhang et al, 2018).…”

Section: Integration Of Signal Processing Actuation Computation Anmentioning

confidence: 99%

“…To date, smart sensors have found wide-ranging applications in healthcare, smart driving, smart cities, industrial plants, and IoT networks, as well as in bioreactor control (Lee et al, 2015;Hernandez-Rojas et al, 2018;Perez et al, 2018;Zhang et al, 2018). In one study, Lee et al (2015) introduced a RFIDbased wireless smart-sensor system, composed of a Pt_rGO RFID sensor tag and an RFID-reader antenna-connected network analyzer, to detect hydrogen gas.…”

Section: Integration Of Signal Processing Actuation Computation Anmentioning

confidence: 99%

“…This sensor has wide application prospects in environmental gas detection, including bioprocess monitoring and control (Lee et al, 2015). In a more recent study, Perez et al (2018) introduced a smart sensor designed to monitor cell growth in a micro-well. The investigated cell culture served as a "biological oscillator" for extracting signals of cell growth and cell number.…”

Section: Integration Of Signal Processing Actuation Computation Anmentioning

confidence: 99%

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Development of Novel Bioreactor Control Systems Based on Smart Sensors and Actuators

Wang

Chen

et al. 2020

Front. Bioeng. Biotechnol.

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Bioreactors of various forms have been widely used in environmental protection, healthcare, industrial biotechnology, and space exploration. Robust demand in the field stimulated the development of novel designs of bioreactor geometries and process control strategies and the evolution of the physical structure of the control system. After the introduction of digital computers to bioreactor process control, a hierarchical structure control system (HSCS) for bioreactors has become the dominant physical structure, having high efficiency and robustness. However, inherent drawbacks of the HSCS for bioreactors have produced a need for a more consolidated solution of the control system. With the fast progress in sensors, machinery, and information technology, the development of a flat organizational control system (FOCS) for bioreactors based on parallel distributed smart sensors and actuators may provide a more concise solution for process control in bioreactors. Here, we review the evolution of the physical structure of bioreactor control systems and discuss the properties of the novel FOCS for bioreactors and related smart sensors and actuators and their application circumstances, with the hope of further improving the efficiency, robustness, and economics of bioprocess control.

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“…In [12], a specific implementation of the ECIS technique was presented based on an oscillation-based-technique (OBT) circuit, wherein oscillation parameters (frequency and amplitude) directly correlate with the cell growth status [13,14]. Specifically, the oscillation parameters were related with the fill-factor parameter of the cell culture, defined as the ratio of the area covered by the cell culture in the electrodes, from 0 (no cells) to 1 (cells fully covering the electrode area), that being an important biological parameter for the characterization of cell growth.…”

Section: Introductionmentioning

confidence: 99%

Data-Analytics Modeling of Electrical Impedance Measurements for Cell Culture Monitoring

Garcia

Pérez

Olmo

et al. 2019

Sensors

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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.

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Remote Cell Growth Sensing Using Self-Sustained Bio-Oscillations

Cited by 4 publications

References 23 publications

Characterization and Monitoring of Titanium Bone Implants with Impedance Spectroscopy

Characterization and Monitoring of Titanium Bone Implants with Impedance Spectroscopy

Development of Novel Bioreactor Control Systems Based on Smart Sensors and Actuators

Data-Analytics Modeling of Electrical Impedance Measurements for Cell Culture Monitoring

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