Literature DB >> 25231594

Coincidence detection of heterogeneous cell populations from whole blood with coplanar electrodes in a microfluidic impedance cytometer.

U Hassan1, R Bashir.   

Abstract

Particle counting finds many industrial applications especially in medical healthcare. In particular, cell counting from whole blood is used pervasively for disease diagnostics. Microfluidic impedance cytometry is fast, requires a small volume of blood, can be used at point of care and can perform absolute enumeration of different cell types in the sample. Coincidence detection is very essential for accurate counting results and becomes more significant while counting specific target cells, e.g. CD4(+) or CD8(+) T cell count in HIV/AIDS patient blood samples. In heterogeneous samples, e.g. blood, cell differentiation for all coincidence occurrences is essential in addition to the coincidence detection for accurate cell enumeration. In this paper, we have characterized the coincidence detection with cell differentiation using a microfluidic impedance biochip. The pure population of leukocytes is obtained after all erythrocytes are lysed on-chip from whole blood. Leukocytes were counted electrically as they pass over coplanar microfabricated electrodes bonded to the 15 μm × 15 μm cross section counting channel while generating a bipolar pulse for each cell passage. We have developed a mathematical model to simulate the electrical cell pulse and its coincidences. We show that coincidence detection can be characterized into three main types based on the range of time delay at which the coincidence occurs. We have also characterized cell differentiation for all the three coincidence types and show that multiple coincidences of different types can also occur. We used healthy and HIV-infected patient blood samples and used our coincidence detection technique to count CD4(+) and CD8(+) T cells and show the improvement in accuracy of cell counts compared to that without coincidence detection. We have also shown the improvement in the erythrocyte counting with coincidence detection in diluted whole blood samples.

Entities:  

Mesh:

Year:  2014        PMID: 25231594     DOI: 10.1039/c4lc00879k

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  12 in total

1.  Hydrodynamic self-focusing in a parallel microfluidic device through cross-filtration.

Authors:  S Torino; M Iodice; I Rendina; G Coppola; E Schonbrun
Journal:  Biomicrofluidics       Date:  2015-11-20       Impact factor: 2.800

2.  A microfluidic biochip for complete blood cell counts at the point-of-care.

Authors:  U Hassan; B Reddy; G Damhorst; O Sonoiki; T Ghonge; C Yang; R Bashir
Journal:  Technology (Singap World Sci)       Date:  2015-12-11

Review 3.  Recent advances in the use of microfluidic technologies for single cell analysis.

Authors:  Travis W Murphy; Qiang Zhang; Lynette B Naler; Sai Ma; Chang Lu
Journal:  Analyst       Date:  2017-12-18       Impact factor: 4.616

4.  Microfluidic differential immunocapture biochip for specific leukocyte counting.

Authors:  Umer Hassan; Nicholas N Watkins; Bobby Reddy; Gregory Damhorst; Rashid Bashir
Journal:  Nat Protoc       Date:  2016-03-10       Impact factor: 13.491

5.  BARKER-CODED NODE-PORE RESISTIVE PULSE SENSING WITH BUILT-IN COINCIDENCE CORRECTION.

Authors:  Michael Kellman; Francois Rivest; Alina Pechacek; Lydia Sohn; Michael Lustig
Journal:  Proc IEEE Int Conf Acoust Speech Signal Process       Date:  2017-06-19

6.  Time-domain signal averaging to improve microparticles detection and enumeration accuracy in a microfluidic impedance cytometer.

Authors:  Brandon K Ashley; Umer Hassan
Journal:  Biotechnol Bioeng       Date:  2021-08-16       Impact factor: 4.530

7.  Single-cell microfluidic impedance cytometry: from raw signals to cell phenotypes using data analytics.

Authors:  Carlos Honrado; Paolo Bisegna; Nathan S Swami; Federica Caselli
Journal:  Lab Chip       Date:  2021-01-05       Impact factor: 6.799

8.  A wide-band bio-chip for real-time optical detection of bioelectromagnetic interactions with cells.

Authors:  Caterina Merla; Micaela Liberti; Paolo Marracino; Adeline Muscat; Antoine Azan; Francesca Apollonio; Lluis M Mir
Journal:  Sci Rep       Date:  2018-03-22       Impact factor: 4.379

Review 9.  Smart Cell Culture Systems: Integration of Sensors and Actuators into Microphysiological Systems.

Authors:  Mario M Modena; Ketki Chawla; Patrick M Misun; Andreas Hierlemann
Journal:  ACS Chem Biol       Date:  2018-02-15       Impact factor: 5.100

10.  A point-of-care microfluidic biochip for quantification of CD64 expression from whole blood for sepsis stratification.

Authors:  U Hassan; T Ghonge; B Reddy; M Patel; M Rappleye; I Taneja; A Tanna; R Healey; N Manusry; Z Price; T Jensen; J Berger; A Hasnain; E Flaugher; S Liu; B Davis; J Kumar; K White; R Bashir
Journal:  Nat Commun       Date:  2017-07-03       Impact factor: 14.919

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.