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Statistic estimation of cell compressibility based on acoustophoretic separation data

Garofalo, Fabio LU ; Lenshof, Andreas LU ; Urbansky, Anke LU ; Olm, Franziska LU ; Bonestroo, Alexander C. ; Ekblad, Lars LU ; Scheding, Stefan LU and Laurell, Thomas LU (2020) In Microfluidics and Nanofluidics 24(8).
Abstract

We present a new experimental method that measures the compressibility of phenotype-specific cell populations. This is done by performing statistical analysis of the cell counts from the outlets of an acoustophoresis chip as a function of the increasing actuator voltage (i.e. acoustic energy density) during acoustophoretic separation. The theoretical separation performance curve, henceforth, Side-Stream Recovery (SSR), vs the piezo-actuator voltage (V) is derived by moment analysis of a one-dimensional model of acoustophoresis separation, accounting for distributions of the cell or microparticle properties and the system parameters (hydrodynamics, radiation force, drag enhancement, and acoustic streaming). The acoustophoretic device is... (More)

We present a new experimental method that measures the compressibility of phenotype-specific cell populations. This is done by performing statistical analysis of the cell counts from the outlets of an acoustophoresis chip as a function of the increasing actuator voltage (i.e. acoustic energy density) during acoustophoretic separation. The theoretical separation performance curve, henceforth, Side-Stream Recovery (SSR), vs the piezo-actuator voltage (V) is derived by moment analysis of a one-dimensional model of acoustophoresis separation, accounting for distributions of the cell or microparticle properties and the system parameters (hydrodynamics, radiation force, drag enhancement, and acoustic streaming). The acoustophoretic device is calibrated with polymer microbeads of known properties by fitting the experimental SSR with the theoretical SSR , in which the acoustic energy density is considered proportional to the squared voltage, i.e. Eac=αV2. The fitting parameter α for the calibration procedure is the device effectivity, reflecting the efficiency in performing acoustophoretic microparticle displacement. Once calibrated, the compressibility of unknown cells is estimated by fitting experimental SSR cell data points with the theoretical SSR curve. In this procedure, the microparticle compressibility is the fitting parameter. The method is applied to estimate the compressibility of a variety of cell populations showing its utility in terms of rapid analysis and need for minute sample amounts.

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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Acoustofluidics, Acoustophoresis, Dispersion, Measurements, Microparticle compressibility, Statistics
in
Microfluidics and Nanofluidics
volume
24
issue
8
article number
64
publisher
Springer
external identifiers
  • scopus:85088896748
ISSN
1613-4982
DOI
10.1007/s10404-020-02360-4
language
English
LU publication?
yes
id
21e032a1-3018-4519-8a62-063873592aea
date added to LUP
2020-08-11 13:48:31
date last changed
2020-08-19 08:50:44
@article{21e032a1-3018-4519-8a62-063873592aea,
  abstract     = {<p>We present a new experimental method that measures the compressibility of phenotype-specific cell populations. This is done by performing statistical analysis of the cell counts from the outlets of an acoustophoresis chip as a function of the increasing actuator voltage (i.e. acoustic energy density) during acoustophoretic separation. The theoretical separation performance curve, henceforth, Side-Stream Recovery (SSR), vs the piezo-actuator voltage (V) is derived by moment analysis of a one-dimensional model of acoustophoresis separation, accounting for distributions of the cell or microparticle properties and the system parameters (hydrodynamics, radiation force, drag enhancement, and acoustic streaming). The acoustophoretic device is calibrated with polymer microbeads of known properties by fitting the experimental SSR with the theoretical SSR , in which the acoustic energy density is considered proportional to the squared voltage, i.e. Eac=αV2. The fitting parameter α for the calibration procedure is the device effectivity, reflecting the efficiency in performing acoustophoretic microparticle displacement. Once calibrated, the compressibility of unknown cells is estimated by fitting experimental SSR cell data points with the theoretical SSR curve. In this procedure, the microparticle compressibility is the fitting parameter. The method is applied to estimate the compressibility of a variety of cell populations showing its utility in terms of rapid analysis and need for minute sample amounts.</p>},
  author       = {Garofalo, Fabio and Lenshof, Andreas and Urbansky, Anke and Olm, Franziska and Bonestroo, Alexander C. and Ekblad, Lars and Scheding, Stefan and Laurell, Thomas},
  issn         = {1613-4982},
  language     = {eng},
  month        = {08},
  number       = {8},
  publisher    = {Springer},
  series       = {Microfluidics and Nanofluidics},
  title        = {Statistic estimation of cell compressibility based on acoustophoretic separation data},
  url          = {http://dx.doi.org/10.1007/s10404-020-02360-4},
  doi          = {10.1007/s10404-020-02360-4},
  volume       = {24},
  year         = {2020},
}