Abstract
AbstractThe paper presents the principles and the results of the implementation of dielectrophoresis for separation and identification of rare cells such as circulation tumor cells (CTCs) from diluted blood specimens in media and further label-free identification of the origins of separated cells using radio-frequency (RF) imaging. The separation and the identification units use same fabrication methods which enable system integration on the same platform. The designs use the advantage of higher surface volume ratio which represents the particular feature for micro- and nanotechnologies. Diluted blood in solution of sucrose–dextrose 1–10 is used for cell separation that yields more than 95.3% efficiency. For enhanced sensitivity in identification, RF imaging is performed in 3.5–1 solution of glycerol and trypsin. Resonance cavity performance method is used to determine the constant permittivity of the cell lines. The results illustrated by the signature of specific cells subjected to RF imaging suggest a reliable label-free single cell detection method for identification of the type of CTC.
Highlights
Over the last few decades, medical research has gained signifi‐ cant evolvement that has gently led toward a paradigm shift approach in medicine: moving the observation from patient and organ toward a more in-depth observation—single cells within the organ
Both real and imaginary parts of the complex permittivity (CP) are shown for imaging frequencies between 2 GHz and 4.5 GHz
From the measurement of the CP of a few cancer cells lines, the frequency range 2–4.5 GHz shows very small dispersion and this frequency range is selected for cell identification by RF imaging. doi:10.1038/micronano.2015.31
Summary
Over the last few decades, medical research has gained signifi‐ cant evolvement that has gently led toward a paradigm shift approach in medicine: moving the observation from patient and organ toward a more in-depth observation—single cells within the organ. This advancement has been enabled to some extent by engineering sciences, among which a major momentum was driven by the microsystems technologies. Some of the investigations on microsystems have been directed toward the applications on medical sciences which enabled promising progress of few research topics in medicine[1]. As a good example to the above statement, single living cell analysis has the potential to help in early detection of medical conditions involving modifications in the cell functions such as cancer genesis and progression[3]
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