Dataset Information

Stigmatic Microscopy Enables Low-Cost, 3D, Microscale Particle Imaging Velocimetry in Rehydrating Aqueous Two-Phase Systems.

ABSTRACT: This paper describes the construction of a novel stigmatic microscope and image analysis algorithm to simultaneously analyze convective mixing both inside and outside of rehydrating μL-scale aqueous two-phase system (ATPS) droplets. Stigmatic microscopy is inexpensive and advantageous because it modifies the point-spread function of fluorescent particles to enable measurement of their 3D positions from single 2D images, without needing to take slices. In one application of the technique, the convection patterns captured clarify how different ATPS formulations succeed or fail to exclude cells for patterning. Particle flow traces reveal speed and directionality of circulation, indicating temporary eddies at the outer edge of the rehydrating droplet. In another application, the speed of circulation during rehydration was analyzed for different ATPS formulations and the results used to develop a new fast ELISA procedure. While this paper focuses on ATPS rehydration, the microscope and algorithm should be applicable to a broad range of microfluidic flows where microscale 3D convection is important.

SUBMITTER: Yamanishi C

PROVIDER: S-EPMC6538919 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language-quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data.ResultsQuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data.ConclusionsThe presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview.

Dataset Information

Stigmatic Microscopy Enables Low-Cost, 3D, Microscale Particle Imaging Velocimetry in Rehydrating Aqueous Two-Phase Systems.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets