Monitoring sepsis using electrical cell profiling
Name
nihms880883.pdf
Description
Accepted version
Size
1.96 MB
Format
Adobe PDF
Checksum (MD5)
feaa91f4046305e7e8da097251eadabe
Author(s)
Prieto Tejedor, Javier
Su, Hao-wei
Hou, Han Wei
Vera, Miguel Pinilla
Levy, Bruce D.
Baron, Rebecca M.
Han, Jongyoon
Voldman, Joel
han, jongyoon
Date Issued
September 22, 2016
Publisher
Royal Society of Chemistry (RSC)
Citation
Cifuentes, Diego, and Pablo A. Parrilo. “Chordal Networks of Polynomial Ideals.” SIAM Journal on Applied Algebra and Geometry 1, no. 1 (January 2017): 73–110.
Version
Author's final manuscript
Abstract
Sepsis is a potentially lethal condition that might benefit from early monitoring of circulating activated leukocytes for faster stratification of severity of illness and improved administration of targeted treatment. Characterization of the intrinsic electrical properties of leukocytes is lable-free and can provide a quick way to quantify the number of activated cells as sepsis progresses. Isodielectric separation (IDS) uses dielectrophoresis (DEP) to characterize the electrical signatures of cells. Here we use IDS to show that activated and non-activated leukocytes have different electrical properties. We then present a double-sided version of the IDS platform to increase throughput to
characterize thousands of cells. This new platform is less prone to cell fouling and allows faster characterization. Using peripheral blood samples from a cecal-ligation and puncture (CLP) model of polymicrobial sepsis in mice, we estimate the number of activated leukocytes by looking into differences in the electrical properties of cells. We show for the first time using animal models that electrical cell profiling correlates with flow cytometry (FC) results and that IDS is therefore a good candidate to provide rapid monitoring of sepsis by quantifying the number of circulating
activated leukocytes.
MIT Department
Massachusetts Institute of Technology. Research Laboratory of Electronics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1039/c6lc00940a
