In-droplet cell separation based on bipolar dielectrophoretic response to facilitate cellular droplet assays

Lab on a Chip ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 3832-3841 ◽  
Author(s):  
Song-I Han ◽  
Can Huang ◽  
Arum Han
Keyword(s):  
Cell Separation ◽  
Cell Types ◽  
Free Cell ◽  
Label Free ◽  
Separation Technology ◽  
Cellular Assays ◽  
System P ◽  
Distinct Cell

Novel in-droplet label-free cell separation technology is presented in this paper by utilizing different dielectrophoretic responses of two distinct cell types, enabling broader ranges of cellular assays to be implemented in the droplet-based microfluidics system.

A ‘smart’ aptamer-functionalized continuous label-free cell catch-transport-release system

2021 ◽  
Author(s):  
Bozhen Zhang ◽  
Canran Wang ◽  
Yingjie Du ◽  
Rebecca Paxton ◽  
Ximin He
Keyword(s):  
Biomedical Research ◽  
Cell Sorting ◽  
Free Cell ◽  
Label Free ◽  
Clinical Therapeutics ◽  
Release System ◽  
System P

Label-free cell sorting devices are of great significance for biomedical research and clinical therapeutics. However, current platforms for label-free cell sorting cannot achieve continuity and selectivity simultaneously, resulting in complex...

3D-printed smartphone-based device for label-free cell separation

2017 ◽  
Vol 1 (3) ◽  
pp. 155-164 ◽  
Author(s):  
Reza Amin ◽  
Stephanie Knowlton ◽  
Joshua Dupont ◽  
Johann S Bergholz ◽  
Ashwini Joshi ◽  
...  
Keyword(s):  
Cell Separation ◽  
Free Cell ◽  
Label Free ◽  
3D Printed

scholarly journals Role of the σD-Dependent Autolysins in Bacillus subtilis Population Heterogeneity

2008 ◽  
Vol 191 (18) ◽  
pp. 5775-5784 ◽  
Author(s):  
Rui Chen ◽  
Sarah B. Guttenplan ◽  
Kris M. Blair ◽  
Daniel B. Kearns
Keyword(s):  
Bacillus Subtilis ◽  
Cell Separation ◽  
Cell Types ◽  
Population Heterogeneity ◽  
Gene Encoding ◽  
Swarming Motility ◽  
Morphological Heterogeneity ◽  
Distinct Cell ◽  
Flagellum Biosynthesis ◽  
Necessary And Sufficient

ABSTRACT Exponentially growing populations of Bacillus subtilis contain two morphologically and functionally distinct cell types: motile individuals and nonmotile multicellular chains. Motility differentiation arises because RNA polymerase and the alternative sigma factor σD activate expression of flagellin in a subpopulation of cells. Here we demonstrate that the peptidoglycan-remodeling autolysins under σD control, LytC, LytD, and LytF, are expressed in the same subpopulation of cells that complete flagellar synthesis. Morphological heterogeneity is explained by the expression of LytF that is necessary and sufficient for cell separation. Moreover, LytC is required for motility but not at the level of cell separation or flagellum biosynthesis. Rather, LytC appears to be important for flagellar function, and motility was restored to a LytC mutant by mutation of either lonA, encoding the LonA protease, or a gene encoding a previously unannotated swarming motility inhibitor, SmiA. We conclude that heterogeneous activation of σD-dependent gene expression is sufficient to explain both the morphological heterogeneity and functional heterogeneity present in vegetative B. subtilis populations.

scholarly journals Multiparametric biophysical profiling of red blood cells in malaria infection

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Shreya S. Deshmukh ◽  
Bikash Shakya ◽  
Anna Chen ◽  
Naside Gozde Durmus ◽  
Bryan Greenhouse ◽  
...  
Keyword(s):  
Magnetic Susceptibility ◽  
Cell Separation ◽  
Magnetic Levitation ◽  
Morphological Characteristics ◽  
Cell Types ◽  
Live Cells ◽  
Label Free ◽  
Infected Cells ◽  
Unique Cell ◽  
First Time

AbstractBiophysical separation promises label-free, less-invasive methods to manipulate the diverse properties of live cells, such as density, magnetic susceptibility, and morphological characteristics. However, some cellular changes are so minute that they are undetectable by current methods. We developed a multiparametric cell-separation approach to profile cells with simultaneously changing density and magnetic susceptibility. We demonstrated this approach with the natural biophysical phenomenon of Plasmodium falciparum infection, which modifies its host erythrocyte by simultaneously decreasing density and increasing magnetic susceptibility. Current approaches have used these properties separately to isolate later-stage infected cells, but not in combination. We present biophysical separation of infected erythrocytes by balancing gravitational and magnetic forces to differentiate infected cell stages, including early stages for the first time, using magnetic levitation. We quantified height distributions of erythrocyte populations—27 ring-stage synchronized samples and 35 uninfected controls—and quantified their unique biophysical signatures. This platform can thus enable multidimensional biophysical measurements on unique cell types.

scholarly journals Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuka Akagi ◽  
Nobuhito Mori ◽  
Teruhisa Kawamura ◽  
Yuzo Takayama ◽  
Yasuyuki S. Kida
Keyword(s):  
Drug Evaluation ◽  
Low Cost ◽  
Scattered Light ◽  
Cell Types ◽  
Mouse Cell ◽  
Free Cell ◽  
Label Free ◽  
Cell Classification ◽  
Entire Cell ◽  
Spectroscopy System

AbstractRaman scattering represents the distribution and abundance of intracellular molecules, including proteins and lipids, facilitating distinction between cellular states non-invasively and without staining. However, the scattered light obtained from cells is faint and cells have complex structures, making it difficult to obtain a Raman spectrum covering the entire cell in a short time using conventional methods. This also prevents efficient label-free cell classification. In the present study, we developed the Paint Raman Express Spectroscopy System, which uses two fast-rotating galvano mirrors to obtain spectra from a wide area of a cell. By using this system and applying machine learning, we were able to acquire broad spectra of a variety of human and mouse cell types, including pluripotent stem cells and confirmed that each cell type can be classified with high accuracy. Moreover, we classified different activation states of human T cells, despite their similar morphology. This system could be used for rapid and low-cost drug evaluation and quality management for drug screening in cell-based assays.

scholarly journals Robust Optical Flow Algorithm for General, Label-free Cell Segmentation

2020 ◽  
Author(s):  
Michael C. Robitaille ◽  
Jeff M. Byers ◽  
Joseph A. Christodoulides ◽  
Marc P. Raphael
Keyword(s):  
Optical Flow ◽  
Cell Biology ◽  
Cell Movement ◽  
Time Lapse ◽  
Cell Types ◽  
Free Cell ◽  
Cell Segmentation ◽  
Label Free ◽  
Segmentation Approach

ABSTRACTCell segmentation is crucial to the field of cell biology, as the accurate extraction of cell morphology, migration, and ultimately behavior from time-lapse live cell imagery are of paramount importance to elucidate and understand basic cellular processes. Here, we introduce a novel segmentation approach centered around optical flow and show that it achieves robust segmentation by validating it on multiple cell types, phenotypes, optical modalities, and in-vitro environments without the need of labels. By leveraging cell movement in time-lapse imagery as a means to distinguish cells from their background and augmenting the output with machine vision operations, our algorithm reduces the number of adjustable parameters needed for optimization to two. The code is packaged within a MATLAB executable file, offering an accessible means for general cell segmentation typically unavailable in most cell biology laboratories.

scholarly journals Label-free cell separation and sorting in microfluidic systems

2010 ◽  
Vol 397 (8) ◽  
pp. 3249-3267 ◽  
Author(s):  
Daniel R. Gossett ◽  
Westbrook M. Weaver ◽  
Albert J. Mach ◽  
Soojung Claire Hur ◽  
Henry Tat Kwong Tse ◽  
...  
Keyword(s):  
Cell Separation ◽  
Free Cell ◽  
Label Free ◽  
Microfluidic Systems

Optical mobility of blood cells for label-free cell separation applications

2013 ◽  
Vol 102 (14) ◽  
pp. 141911 ◽  
Author(s):  
Kyung Heon Lee ◽  
Kang Soo Lee ◽  
Jin Ho Jung ◽  
Cheong Bong Chang ◽  
Hyung Jin Sung
Keyword(s):  
Blood Cells ◽  
Cell Separation ◽  
Free Cell ◽  
Label Free
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