ArticleMicrosystems & nanoengineering2023
Microparticles with tunable, cell-like properties for quantitative acoustic mechanophenotyping.
Article in Microsystems & nanoengineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Selection of Force Sensors forTissue engineering. Part A · 2025Article
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3 authors.
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Abstract
Mechanical properties of biological cells have been shown to correlate with their biomolecular state and function, and therefore methods to measure these properties at scale are of interest. Emerging microfluidic technologies can measure the mechanical properties of cells at rates over 20,000 cells/s, which is more than four orders of magnitude faster than conventional instrumentation. However, precise and repeatable means to calibrate and test these new tools remain lacking, since cells themselves are by nature variable. Commonly, microfluidic tools use rigid polymer microspheres for calibration because they are widely available in cell-similar sizes, but conventional microspheres do not fully capture the physiological range of other mechanical properties that are equally important to device function (e.g., elastic modulus and density). Here, we present for the first time development of monodisperse polyacrylamide microparticles with both tunable elasticity and tunable density. Using these size, elasticity, and density tunable particles, we characterized a custom acoustic microfluidic device that makes single-cell measurements of mechanical properties. We then applied the approach to measure the distribution of the acoustic properties within samples of human leukocytes and showed that the system successfully discriminates lymphocytes from other leukocytes. This initial demonstration shows how the tunable microparticles with properties within the physiologically relevant range can be used in conjunction with microfluidic devices for efficient high-throughput measurements of mechanical properties at single-cell resolution.
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