Literature DB >> 24049682

Label-free high-throughput cell screening in flow.

Ata Mahjoubfar1, Claire Chen, Kayvan R Niazi, Shahrooz Rabizadeh, Bahram Jalali.   

Abstract

Flow cytometry is a powerful tool for cell counting and biomarker detection in biotechnology and medicine especially with regards to blood analysis. Standard flow cytometers perform cell type classification both by estimating size and granularity of cells using forward- and side-scattered light signals and through the collection of emission spectra of fluorescently-labeled cells. However, cell surface labeling as a means of marking cells is often undesirable as many reagents negatively impact cellular viability or provide activating/inhibitory signals, which can alter the behavior of the desired cellular subtypes for downstream applications or analysis. To eliminate the need for labeling, we introduce a label-free imaging-based flow cytometer that measures size and cell protein concentration simultaneously either as a stand-alone instrument or as an add-on to conventional flow cytometers. Cell protein concentration adds a parameter to cell classification, which improves the specificity and sensitivity of flow cytometers without the requirement of cell labeling. This system uses coherent dispersive Fourier transform to perform phase imaging at flow speeds as high as a few meters per second.

Keywords:  (100.5070) Phase retrieval; (170.0180) Microscopy; (170.1530) Cell analysis; (170.3890) Medical optics instrumentation; (170.7160) Ultrafast technology

Year:  2013        PMID: 24049682      PMCID: PMC3771832          DOI: 10.1364/BOE.4.001618

Source DB:  PubMed          Journal:  Biomed Opt Express        ISSN: 2156-7085            Impact factor:   3.732


  26 in total

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Journal:  Methods       Date:  1998-11       Impact factor: 3.608

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Authors:  Sai Siva Gorthi; Ethan Schonbrun
Journal:  Opt Lett       Date:  2012-02-15       Impact factor: 3.776

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Authors:  Gabriel Popescu; Takahiro Ikeda; Keisuke Goda; Catherine A Best-Popescu; Michael Laposata; Suliana Manley; Ramachandra R Dasari; Kamran Badizadegan; Michael S Feld
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4.  Measurement of the integral refractive index and dynamic cell morphometry of living cells with digital holographic microscopy.

Authors:  Benjamin Rappaz; Pierre Marquet; Etienne Cuche; Yves Emery; Christian Depeursinge; Pierre Magistretti
Journal:  Opt Express       Date:  2005-11-14       Impact factor: 3.894

5.  Measuring single-cell density.

Authors:  William H Grover; Andrea K Bryan; Monica Diez-Silva; Subra Suresh; John M Higgins; Scott R Manalis
Journal:  Proc Natl Acad Sci U S A       Date:  2011-06-20       Impact factor: 11.205

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Journal:  Analyst       Date:  2012-10-11       Impact factor: 4.616

8.  Hormone-induced cell death. Purification ad properties of thymocytes undergoing apoptosis after glucocorticoid treatment.

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Journal:  Am J Pathol       Date:  1982-10       Impact factor: 4.307

9.  Concentration and separation of erythrocytes infected with Plasmodium falciparum by gradient centrifugation.

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Journal:  Bull World Health Organ       Date:  1979       Impact factor: 9.408

10.  Quantification of cellular volume and sub-cellular density fluctuations: comparison of normal peripheral blood cells and circulating tumor cells identified in a breast cancer patient.

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Journal:  Front Oncol       Date:  2012-08-09       Impact factor: 6.244

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  20 in total

1.  In vivo cell characteristic extraction and identification by photoacoustic flow cytography.

Authors:  Guo He; Dong Xu; Huan Qin; Sihua Yang; Da Xing
Journal:  Biomed Opt Express       Date:  2015-09-03       Impact factor: 3.732

2.  28 MHz swept source at 1.0 μm for ultrafast quantitative phase imaging.

Authors:  Xiaoming Wei; Andy K S Lau; Yiqing Xu; Kevin K Tsia; Kenneth K Y Wong
Journal:  Biomed Opt Express       Date:  2015-09-08       Impact factor: 3.732

3.  Optical chromatographic sample separation of hydrodynamically focused mixtures.

Authors:  A Terray; C G Hebert; S J Hart
Journal:  Biomicrofluidics       Date:  2014-11-11       Impact factor: 2.800

4.  Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM).

Authors:  Anson H L Tang; Queenie T K Lai; Bob M F Chung; Kelvin C M Lee; Aaron T Y Mok; G K Yip; Anderson H C Shum; Kenneth K Y Wong; Kevin K Tsia
Journal:  J Vis Exp       Date:  2017-06-28       Impact factor: 1.355

5.  Large population cell characterization using quantitative phase cytometer.

Authors:  Di Jin; Yongjin Sung; Niyom Lue; Yang-Hyo Kim; Peter T C So; Zahid Yaqoob
Journal:  Cytometry A       Date:  2017-04-26       Impact factor: 4.355

6.  Invited Article: Digital refocusing in quantitative phase imaging for flowing red blood cells.

Authors:  Han Sang Park; Silvia Ceballos; Will J Eldridge; Adam Wax
Journal:  APL Photonics       Date:  2018-10-02

7.  Label-free imaging flow cytometer for analyzing large cell populations by line-field quantitative phase microscopy with digital refocusing.

Authors:  Hidenao Yamada; Amane Hirotsu; Daisuke Yamashita; Osamu Yasuhiko; Toyohiko Yamauchi; Tsukasa Kayou; Hiroaki Suzuki; Shigetoshi Okazaki; Hirotoshi Kikuchi; Hiroya Takeuchi; Yukio Ueda
Journal:  Biomed Opt Express       Date:  2020-03-26       Impact factor: 3.732

Review 8.  Review: imaging technologies for flow cytometry.

Authors:  Yuanyuan Han; Yi Gu; Alex Ce Zhang; Yu-Hwa Lo
Journal:  Lab Chip       Date:  2016-11-29       Impact factor: 6.799

9.  Optical data compression in time stretch imaging.

Authors:  Claire Lifan Chen; Ata Mahjoubfar; Bahram Jalali
Journal:  PLoS One       Date:  2015-04-23       Impact factor: 3.240

Review 10.  The palette of techniques for cell cycle analysis.

Authors:  Anna E Eastman; Shangqin Guo
Journal:  FEBS Lett       Date:  2020-05-22       Impact factor: 3.864

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