scholarly journals Highly sensitivity detection of label-free H1N1 influenza A virus on electrical impedance spectroscopy using microsystems technologies

2018 ◽  
Vol 73 ◽  
pp. 167-168
Author(s):  
R. Kumar ◽  
M.K. Nayak ◽  
G. Sahoo ◽  
K. Pandey ◽  
R. Topno ◽  
...  
Biosensors ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 401
Author(s):  
Ina Turcan ◽  
Iuliana Caras ◽  
Thomas Gabriel Schreiner ◽  
Catalin Tucureanu ◽  
Aurora Salageanu ◽  
...  

Here, we reported a study on the detection and electrical characterization of both cancer cell line and primary tumor cells. Dielectrophoresis (DEP) and electrical impedance spectroscopy (EIS) were jointly employed to enable the rapid and label-free differentiation of various cancer cells from normal ones. The primary tumor cells that were collected from two colorectal cancer patients and cancer cell lines (SW-403, Jurkat, and THP-1), and healthy peripheral blood mononuclear cells (PBMCs) were trapped first at the level of interdigitated microelectrodes with the help of dielectrophoresis. Correlation of the cells dielectric characteristics that was obtained via electrical impedance spectroscopy (EIS) allowed evident differentiation of the various types of cell. The differentiations were assigned to a “dielectric phenotype” based on their crossover frequencies. Finally, Randles equivalent circuit model was employed for highlighting the differences with regard to a series group of charge transport resistance and constant phase element for cancerous and normal cells.


2021 ◽  
Vol 232 (2) ◽  
Author(s):  
Rakibul Islam Chowdhury ◽  
Rinku Basak ◽  
Khan Arif Wahid ◽  
Katy Nugent ◽  
Helen Baulch

2020 ◽  
Vol 28 ◽  
pp. 1679-1685
Author(s):  
Angeliki-Eirini Dimou ◽  
Ioanna Sakellariou ◽  
George M. Maistros ◽  
Nikolaos D. Alexopoulos

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 1001
Author(s):  
Sooin Huh ◽  
Hye-Jin Kim ◽  
Seungah Lee ◽  
Jinwoo Cho ◽  
Aera Jang ◽  
...  

This study presents a system for assessing the freshness of meat with electrical impedance spectroscopy (EIS) in the frequency range of 125 Hz to 128 kHz combined with an image classifier for non-destructive and low-cost applications. The freshness standard is established by measuring the aerobic plate count (APC), 2-thiobarbituric acid reactive substances (TBARS), and composition analysis (crude fat, crude protein, and moisture) values of the microbiological detection to represent the correlation between EIS and meat freshness. The EIS and images of meat are combined to predict the freshness with the Adaboost classification and gradient boosting regression algorithms. As a result, when the elapsed time of beef storage for 48 h is classified into three classes, the time prediction accuracy is up to 85% compared to prediction accuracy of 56.7% when only images are used without EIS information. Significantly, the relative standard deviation (RSD) of APC and TBARS value predictions with EIS and images datum achieves 0.890 and 0.678, respectively.


Allergy ◽  
2021 ◽  
Author(s):  
Arturo O. Rinaldi ◽  
Angelica Korsfeldt ◽  
Siobhan Ward ◽  
Daniel Burla ◽  
Anita Dreher ◽  
...  

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