Hauptseite > Publikationsdatenbank > Sharp-edged geometric obstacles in microfluidics promote deformability-based sorting of cells > print |
001 | 860771 | ||
005 | 20240610120015.0 | ||
024 | 7 | _ | |2 arXiv |a arXiv:1901.03863 |
024 | 7 | _ | |2 doi |a 10.1103/PhysRevFluids.4.024201 |
024 | 7 | _ | |2 Handle |a 2128/21936 |
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037 | _ | _ | |a FZJ-2019-01434 |
082 | _ | _ | |a 530 |
100 | 1 | _ | |0 P:(DE-Juel1)172729 |a Chien, Wei |b 0 |
245 | _ | _ | |a Sharp-edged geometric obstacles in microfluidics promote deformability-based sorting of cells |
260 | _ | _ | |a College Park, MD |b APS |c 2019 |
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336 | 7 | _ | |2 BibTeX |a ARTICLE |
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520 | _ | _ | |a Sorting cells based on their intrinsic properties is a highly desirable objective, since changes in cell deformability are often associated with various stress conditions and diseases. Deterministic lateral displacement (DLD) devices offer high precision for rigid spherical particles, while their success in sorting deformable particles remains limited due to the complexity of cell traversal in DLDs. We employ mesoscopic hydrodynamics simulations and demonstrate prominent advantages of sharp-edged DLD obstacles for probing deformability properties of red blood cells (RBCs). By consecutive sharpening of the pillar shape from circular to diamond to triangular geometry, a pronounced cell bending around an edge is achieved, serving as a deformability sensor. Bending around the edge is the primary mechanism, which governs the traversal of RBCs through such DLD device. This strategy requires an appropriate degree of cell bending by fluid stresses, which can be controlled by the flow rate, and exhibits good sensitivity to moderate changes in cell deformability. We expect that similar mechanisms should be applicable for the development of novel DLD devices that target intrinsic properties of many other cells. |
536 | _ | _ | |0 G:(DE-HGF)POF3-552 |a 552 - Engineering Cell Function (POF3-552) |c POF3-552 |f POF III |x 0 |
536 | _ | _ | |0 G:(DE-Juel1)jics21_20181101 |a Blood flow in microvascular networks (jics21_20181101) |c jics21_20181101 |f Blood flow in microvascular networks |x 1 |
588 | _ | _ | |a Dataset connected to arXivarXiv |
700 | 1 | _ | |0 P:(DE-Juel1)161194 |a Henry, Ewan |b 1 |
700 | 1 | _ | |0 P:(DE-Juel1)140336 |a Fedosov, Dmitry |b 2 |e Corresponding author |
700 | 1 | _ | |0 P:(DE-Juel1)130665 |a Gompper, Gerhard |b 3 |e Corresponding author |
773 | _ | _ | |0 PERI:(DE-600)2868596-9 |a 10.1103/PhysRevFluids.4.024201 |g Vol. 4, no. 2, p. 024201 |n 2 |p 024201-1 |t Physical review fluids |v 4 |x 2469-990X |y 2019 |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/860771/files/PhysRevFluids.4.024201.pdf |y OpenAccess |
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