Literature DB >> 21704837

Rise of the micromachines: microfluidics and the future of cytometry.

Donald Wlodkowic1, Zbigniew Darzynkiewicz.   

Abstract

The past decade has brought many innovations to the field of flow and image-based cytometry. These advancements can be seen in the current miniaturization trends and simplification of analytical components found in the conventional flow cytometers. On the other hand, the maturation of multispectral imaging cytometry in flow imaging and the slide-based laser scanning cytometers offers great hopes for improved data quality and throughput while proving new vistas for the multiparameter, real-time analysis of cells and tissues. Importantly, however, cytometry remains a viable and very dynamic field of modern engineering. Technological milestones and innovations made over the last couple of years are bringing the next generation of cytometers out of centralized core facilities while making it much more affordable and user friendly. In this context, the development of microfluidic, lab-on-a-chip (LOC) technologies is one of the most innovative and cost-effective approaches toward the advancement of cytometry. LOC devices promise new functionalities that can overcome current limitations while at the same time promise greatly reduced costs, increased sensitivity, and ultra high throughputs. We can expect that the current pace in the development of novel microfabricated cytometric systems will open up groundbreaking vistas for the field of cytometry, lead to the renaissance of cytometric techniques and most importantly greatly support the wider availability of these enabling bioanalytical technologies.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21704837      PMCID: PMC3241275          DOI: 10.1016/B978-0-12-374912-3.00005-5

Source DB:  PubMed          Journal:  Methods Cell Biol        ISSN: 0091-679X            Impact factor:   1.441


  93 in total

1.  Microfluidic sorting of mammalian cells by optical force switching.

Authors:  Mark M Wang; Eugene Tu; Daniel E Raymond; Joon Mo Yang; Haichuan Zhang; Norbert Hagen; Bob Dees; Elinore M Mercer; Anita H Forster; Ilona Kariv; Philippe J Marchand; William F Butler
Journal:  Nat Biotechnol       Date:  2004-12-19       Impact factor: 54.908

2.  Microfluidics in medical applications.

Authors:  U Michelsen
Journal:  Med Device Technol       Date:  2007 May-Jun

3.  Negative DEP traps for single cell immobilisation.

Authors:  Rupert S Thomas; Hywel Morgan; Nicolas G Green
Journal:  Lab Chip       Date:  2009-03-06       Impact factor: 6.799

Review 4.  Microfluidics for miniaturized laboratories on a chip.

Authors:  Thomas A Franke; Achim Wixforth
Journal:  Chemphyschem       Date:  2008-10-24       Impact factor: 3.102

Review 5.  Managing evaporation for more robust microscale assays. Part 1. Volume loss in high throughput assays.

Authors:  Erwin Berthier; Jay Warrick; Hongmeiy Yu; David J Beebe
Journal:  Lab Chip       Date:  2008-04-08       Impact factor: 6.799

Review 6.  The application of microfluidics in biology.

Authors:  David Holmes; Shady Gawad
Journal:  Methods Mol Biol       Date:  2010

Review 7.  Screening the cellular microenvironment: a role for microfluidics.

Authors:  Jay W Warrick; William L Murphy; David J Beebe
Journal:  IEEE Rev Biomed Eng       Date:  2008-11-05

8.  Surface characterization of laser-ablated polymers used for microfluidics.

Authors:  D L Pugmire; E A Waddell; R Haasch; M J Tarlov; L E Locascio
Journal:  Anal Chem       Date:  2002-02-15       Impact factor: 6.986

9.  A microfluidic device for characterizing the invasion of cancer cells in 3-D matrix.

Authors:  Tingjiao Liu; Chunyu Li; Hongjing Li; Shaojiang Zeng; Jianhua Qin; Bingcheng Lin
Journal:  Electrophoresis       Date:  2009-12       Impact factor: 3.535

Review 10.  Living-cell microarrays.

Authors:  Martin L Yarmush; Kevin R King
Journal:  Annu Rev Biomed Eng       Date:  2009       Impact factor: 9.590

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  8 in total

1.  Microfluidic flow cytometry: The role of microfabrication methodologies, performance and functional specification.

Authors:  Anil B Shrirao; Zachary Fritz; Eric M Novik; Gabriel M Yarmush; Rene S Schloss; Jeffrey D Zahn; Martin L Yarmush
Journal:  Technology (Singap World Sci)       Date:  2018-03-16

Review 2.  Opportunities and challenges for use of tumor spheroids as models to test drug delivery and efficacy.

Authors:  Geeta Mehta; Amy Y Hsiao; Marylou Ingram; Gary D Luker; Shuichi Takayama
Journal:  J Control Release       Date:  2012-05-18       Impact factor: 9.776

Review 3.  From single cells to deep phenotypes in cancer.

Authors:  Sean C Bendall; Garry P Nolan
Journal:  Nat Biotechnol       Date:  2012-07-10       Impact factor: 54.908

Review 4.  Chromosomes in the flow to simplify genome analysis.

Authors:  Jaroslav Doležel; Jan Vrána; Jan Safář; Jan Bartoš; Marie Kubaláková; Hana Simková
Journal:  Funct Integr Genomics       Date:  2012-08-16       Impact factor: 3.410

Review 5.  Microfluidic chip-based technologies: emerging platforms for cancer diagnosis.

Authors:  Li Ying; Qi Wang
Journal:  BMC Biotechnol       Date:  2013-09-27       Impact factor: 2.563

6.  A contact-imaging based microfluidic cytometer with machine-learning for single-frame super-resolution processing.

Authors:  Xiwei Huang; Jinhong Guo; Xiaolong Wang; Mei Yan; Yuejun Kang; Hao Yu
Journal:  PLoS One       Date:  2014-08-11       Impact factor: 3.240

Review 7.  Tumour Heterogeneity: The Key Advantages of Single-Cell Analysis.

Authors:  Marta Tellez-Gabriel; Benjamin Ory; Francois Lamoureux; Marie-Francoise Heymann; Dominique Heymann
Journal:  Int J Mol Sci       Date:  2016-12-20       Impact factor: 5.923

Review 8.  Understanding breast cancer heterogeneity through non-genetic heterogeneity.

Authors:  Neda Barzgar Barough; Fakhrosadat Sajjadian; Nazila Jalilzadeh; Hajar Shafaei; Kobra Velaei
Journal:  Breast Cancer       Date:  2021-03-15       Impact factor: 4.239

  8 in total

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