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Microchip Diagnostics

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Cover of 'Microchip Diagnostics'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Microfluidics-Enabled Diagnostic Systems: Markets, Challenges, and Examples.
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    Chapter 2 Capillary-Driven Microfluidic Chips for Miniaturized Immunoassays: Efficient Fabrication and Sealing of Chips Using a "Chip-Olate" Process.
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    Chapter 3 Capillary-Driven Microfluidic Chips for Miniaturized Immunoassays: Patterning Capture Antibodies Using Microcontact Printing and Dry-Film Resists.
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    Chapter 4 Fabrication and Evaluation of Microfluidic Immunoassay Devices with Antibody-Immobilized Microbeads Retained in Porous Hydrogel Micropillars.
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    Chapter 5 Using Electrophoretic Immunoassay to Monitor Hormone Secretion.
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    Chapter 6 On-Chip Magnetic Particle-Based Immunoassays Using Multilaminar Flow for Clinical Diagnostics.
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    Chapter 7 Digital Microfluidics Assisted Sealing of Individual Magnetic Particles in Femtoliter-Sized Reaction Wells for Single-Molecule Detection.
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    Chapter 8 Microfluidic DNA Stretching Device for Single-Molecule Diagnostics.
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    Chapter 9 Droplet Microfluidic and Magnetic Particles Platform for Cancer Typing.
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    Chapter 10 SlipChip Device for Digital Nucleic Acid Amplification.
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    Chapter 11 Multiplex Detection of KRAS Mutations Using Passive Droplet Fusion.
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    Chapter 12 Droplet-Based Microfluidics Digital PCR for the Detection of KRAS Mutations.
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    Chapter 13 Negative Enrichment of Circulating Tumor Cells in Blood Using a Microfluidic Chip.
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    Chapter 14 Microfluidic-Based Bacteria Isolation from Whole Blood for Diagnostics of Blood Stream Infection.
  16. Altmetric Badge
    Chapter 15 Microfluidic Platform for Parallel Single Cell Analysis for Diagnostic Applications.
  17. Altmetric Badge
    Chapter 16 FISH-in-CHIPS: A Microfluidic Platform for Molecular Typing of Cancer Cells.
Attention for Chapter 15: Microfluidic Platform for Parallel Single Cell Analysis for Diagnostic Applications.
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Chapter title
Microfluidic Platform for Parallel Single Cell Analysis for Diagnostic Applications.
Chapter number 15
Book title
Microchip Diagnostics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6734-6_15
Pubmed ID
Book ISBNs
978-1-4939-6732-2, 978-1-4939-6734-6
Authors

Séverine Le Gac PhD, Séverine Le Gac

Editors

Valérie Taly, Jean-Louis Viovy, Stéphanie Descroix

Abstract

Cell populations are heterogeneous: they can comprise different cell types or even cells at different stages of the cell cycle and/or of biological processes. Furthermore, molecular processes taking place in cells are stochastic in nature. Therefore, cellular analysis must be brought down to the single cell level to get useful insight into biological processes, and to access essential molecular information that would be lost when using a cell population analysis approach. Furthermore, to fully characterize a cell population, ideally, information both at the single cell level and on the whole cell population is required, which calls for analyzing each individual cell in a population in a parallel manner. This single cell level analysis approach is particularly important for diagnostic applications to unravel molecular perturbations at the onset of a disease, to identify biomarkers, and for personalized medicine, not only because of the heterogeneity of the cell sample, but also due to the availability of a reduced amount of cells, or even unique cells. This chapter presents a versatile platform meant for the parallel analysis of individual cells, with a particular focus on diagnostic applications and the analysis of cancer cells. We first describe one essential step of this parallel single cell analysis protocol, which is the trapping of individual cells in dedicated structures. Following this, we report different steps of a whole analytical process, including on-chip cell staining and imaging, cell membrane permeabilization and/or lysis using either chemical or physical means, and retrieval of the cell molecular content in dedicated channels for further analysis. This series of experiments illustrates the versatility of the herein-presented platform and its suitability for various analysis schemes and different analytical purposes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 22%
Student > Ph. D. Student 1 11%
Unspecified 1 11%
Researcher 1 11%
Student > Master 1 11%
Other 0 0%
Unknown 3 33%
Readers by discipline Count As %
Chemical Engineering 1 11%
Unspecified 1 11%
Agricultural and Biological Sciences 1 11%
Earth and Planetary Sciences 1 11%
Engineering 1 11%
Other 0 0%
Unknown 4 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 January 2017.
All research outputs
#18,510,888
of 22,931,367 outputs
Outputs from Methods in molecular biology
#7,929
of 13,127 outputs
Outputs of similar age
#310,860
of 420,713 outputs
Outputs of similar age from Methods in molecular biology
#692
of 1,074 outputs
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