1,275 research outputs found

    Development of an Integrated Chip for Automatic Tracking and Positioning Manipulation for Single Cell Lysis

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    This study adopted a microelectromechanical fabrication process to design a chip integrated with electroosmotic flow and dielectrophoresis force for single cell lysis. Human histiocytic lymphoma U937 cells were driven rapidly by electroosmotic flow and precisely moved to a specific area for cell lysis. By varying the frequency of AC power, 15 V AC at 1 MHz of frequency configuration achieved 100% cell lysing at the specific area. The integrated chip could successfully manipulate single cells to a specific position and lysis. The overall successful rate of cell tracking, positioning, and cell lysis is 80%. The average speed of cell driving was 17.74 μm/s. This technique will be developed for DNA extraction in biomolecular detection. It can simplify pre-treatment procedures for biotechnological analysis of samples

    Micro/Nanofluidic Devices for Single Cell Analysis

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    Microdevices and Microsystems for Cell Manipulation

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    Microfabricated devices and systems capable of micromanipulation are well-suited for the manipulation of cells. These technologies are capable of a variety of functions, including cell trapping, cell sorting, cell culturing, and cell surgery, often at single-cell or sub-cellular resolution. These functionalities are achieved through a variety of mechanisms, including mechanical, electrical, magnetic, optical, and thermal forces. The operations that these microdevices and microsystems enable are relevant to many areas of biomedical research, including tissue engineering, cellular therapeutics, drug discovery, and diagnostics. This Special Issue will highlight recent advances in the field of cellular manipulation. Technologies capable of parallel single-cell manipulation are of special interest

    Microfluidics and Nanofluidics Handbook

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    The Microfluidics and Nanofluidics Handbook: Two-Volume Set comprehensively captures the cross-disciplinary breadth of the fields of micro- and nanofluidics, which encompass the biological sciences, chemistry, physics and engineering applications. To fill the knowledge gap between engineering and the basic sciences, the editors pulled together key individuals, well known in their respective areas, to author chapters that help graduate students, scientists, and practicing engineers understand the overall area of microfluidics and nanofluidics. Topics covered include Finite Volume Method for Numerical Simulation Lattice Boltzmann Method and Its Applications in Microfluidics Microparticle and Nanoparticle Manipulation Methane Solubility Enhancement in Water Confined to Nanoscale Pores Volume Two: Fabrication, Implementation, and Applications focuses on topics related to experimental and numerical methods. It also covers fabrication and applications in a variety of areas, from aerospace to biological systems. Reflecting the inherent nature of microfluidics and nanofluidics, the book includes as much interdisciplinary knowledge as possible. It provides the fundamental science background for newcomers and advanced techniques and concepts for experienced researchers and professionals

    Deep learning with microfluidics for on-chip droplet generation, control, and analysis

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    Droplet microfluidics has gained widespread attention in recent years due to its advantages of high throughput, high integration, high sensitivity and low power consumption in droplet-based micro-reaction. Meanwhile, with the rapid development of computer technology over the past decade, deep learning architectures have been able to process vast amounts of data from various research fields. Nowadays, interdisciplinarity plays an increasingly important role in modern research, and deep learning has contributed greatly to the advancement of many professions. Consequently, intelligent microfluidics has emerged as the times require, and possesses broad prospects in the development of automated and intelligent devices for integrating the merits of microfluidic technology and artificial intelligence. In this article, we provide a general review of the evolution of intelligent microfluidics and some applications related to deep learning, mainly in droplet generation, control, and analysis. We also present the challenges and emerging opportunities in this field

    Roadmap for optofluidics

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    Optofluidics, nominally the research area where optics and fluidics merge, is a relatively new research field and it is only in the last decade that there has been a large increase in the number of optofluidic. applications, as well as in the number of research groups, devoted to the topic. Nowadays optofluidics applications include, without being limited to, lab-on-a-chip devices, fluid-based and controlled lenses, optical sensors for fluids and for suspended particles, biosensors, imaging tools, etc. The long list of potential optofluidics applications, which have been recently demonstrated, suggests that optofluidic technologies will become more and more common in everyday life in the future, causing a significant impact on many aspects of our society. A characteristic of this research field, deriving from both its interdisciplinary origin and applications, is that in order to develop suitable solutions a. combination of a deep knowledge in different fields, ranging from materials science to photonics, from microfluidics to molecular biology and biophysics,. is often required. As a direct consequence, also being able to understand the long-term evolution of optofluidics research is not. easy. In this article, we report several expert contributions on different topics. so as to provide guidance for young scientists. At the same time, we hope that this document will also prove useful for funding institutions and stakeholders. to better understand the perspectives and opportunities offered by this research field

    Automated Microraft Array Platform for Immune Cell Assays and Cell Sorting

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    Immunology research and cell therapies have provided great advancements in recent years and have highlighted the need to understand the effects of single cell heterogeneity within immune cell populations. Single cell platforms currently used in immune cell analysis often include tedious manual work, are not able to measure immune cell function in a time-dependent manner, or are not selective. The following work describes the development of an automated microraft array platform for analyzing the function of individual immune cells, including helper T cells and chimeric antigen receptor T cells (CAR-T cells), and for the sorting of cells of interest. In this dissertation, an automated microraft array platform was developed and adapted to address the challenges seen in immune cell research. In Chapter 2, an automated microraft array platform was developed to assay thousands of single cells in parallel and sort individual cells of interest. The platform was used to assay single CD4+ T cells, isolate cells displaying proliferation in response to allogeneic cell stimulation, and sequence their T cell receptor genes. In Chapter 3, a next-generation magnetic microbead-based microraft array was developed as an alternative to nanoparticle-based microraft arrays. The microbead-based arrays were shown to substantially reduce fabrication time compared to nanoparticle-based microraft arrays and improve performance in imaging of fluorescently labeled cells. Chapter 4 focused on the development and application of the automated microraft array platform to assay CD19 CAR-T cells for cell-mediated cytotoxicity and isolate T cells of interest for gene expression analysis. CAR-T cells were shown to participate in serial-killing of target cells and T cells demonstrating high cytotoxicity were isolated for future gene expression analysis using single-cell multiplex qPCR. The findings presented in this dissertation demonstrate the capabilities of an automated microraft array platform and its uses in immunology research. The studies described in each chapter provided valuable insight into the behavior and phenotype of immune cells at the single cell level.Doctor of Philosoph

    Tools for single cell proteomics

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    Despite recent advances that offer control of single cells, in terms of manipulation and sorting and the ability to measure gene expression, the need to measure protein copy number remains unmet. Measuring protein copy number in single cells and related quantities such as levels of phosphorylation and protein-protein interaction is the basis of single cell proteomics. A technology platform to undertake the analysis of protein copy number from single cells has been developed. The approach described is ‘all-optical’ whereby single cells are manipulated into separate analysis chambers using an optical trap; single cells are lysed by mechanical shearing caused by laser-induced microcavitation; and the protein released from a single cell is measured by total internal reflection microscopy as it is bound to micro-printed antibody spots within the device. The platform was tested using GFP transfected cells and the relative precision of the measurement method was determined to be 88%. Single cell measurements were also made on a breast cancer cell line to measure the relative levels of unlabelled human tumour suppressor protein p53 using a chip incorporating an antibody sandwich assay format. This demonstrates the ability count protein copy number from single cells in a manner which could be applied in principle to any set of proteins and for any cell type without the need for genetic engineering. Metabolism can undergo alteration in diseases such as cancer and heart failure and also as cells differentiate during development. In order to assess how it may inform a proteomic measurement, multidimensional two-photon fluorescence metabolic imaging is conducted on a cultured cancer cell line, primary adult rat cardiomyocytes and human embryonic stem cells. By measuring the parameters of fluorescence such as intensity and lifetime of the autofluorescent metabolic co-factors NADH and FAD, it was found to be possible to contrast cells under various conditions and metabolic stimuli. In particular, human embryonic stem cells were able to be contrasted at 3 stages of development as they underwent differentiation into embryonic stem cell derived cardiomyocytes. Metabolic imaging provides a non-destructive method to monitor cellular metabolic activity with high resolution. This is complimentary to the single cell proteomic platform and the convergence of both techniques holds promise in future investigations into how metabolism influences cell function and the proteome in development and disease
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