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Flow Cytometry

Flow Cytometry

The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
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Related Experiment Video

Updated: Oct 8, 2025

Semi-automatic PD-L1 Characterization and Enumeration of Circulating Tumor Cells from Non-small Cell Lung Cancer Patients by Immunofluorescence

Semi-automatic PD-L1 Characterization and Enumeration of Circulating Tumor Cells from Non-small Cell Lung Cancer Patients by Immunofluorescence

Published on: August 14, 2019

Natural killer cell detection, quantification, and subpopulation identification on paper microfluidic cell

Ryan Zenhausern¹, Alexander S Day¹, Babak Safavinia¹

¹Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, 85721, United States.

Biosensors & Bioelectronics

|January 2, 2022

Summary

A novel smartphone device quantifies natural killer (NK) cells and inflammatory markers. This innovation enables rapid clinical assessment of immune cell function and cancer immunotherapy effectiveness.

Keywords:

CD56 IL-2 NK cell therapy Random forest machine learning Smartphone fluorescence microscope

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Last Updated: Oct 8, 2025

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Field-Deployable Lens-Free Imaging Platform for Rapid Label-Free Analysis of Natural Killer Cell Activation

Field-Deployable Lens-Free Imaging Platform for Rapid Label-Free Analysis of Natural Killer Cell Activation

Published on: August 8, 2025

Area of Science:

Immunology
Biotechnology
Medical Diagnostics

Background:

Natural killer (NK) cells are crucial immune cells for combating viral infections and cancer, playing a key role in immunotherapies.
NK cell subpopulations, CD56^dim and CD56^bright, have distinct functions in cytokine production and direct cell killing.
Current methods for NK cell analysis, such as flow cytometry, require specialized equipment and fluorescent dyes, limiting rapid clinical application.

Purpose of the Study:

To develop a rapid, accessible method for quantifying NK cells and their subpopulations.
To identify inflammatory markers, specifically Interleukin-2 (IL-2), using a portable device.
To enable point-of-care assessment of immune status and cancer immunotherapy efficacy.

Main Methods:

A smartphone-based platform integrated with a two-component paper microfluidic chip was employed.
One component measured cytokine (IL-2) and total NK cell concentrations via flow velocity analysis of buffy coat blood.
The second component spatially separated CD56^dim and CD56^bright NK cells using anti-CD56 nanoparticle binding, analyzed by a smartphone microscope and machine learning.

Main Results:

The system achieved limits of detection of 98 IU/mL for IL-2 and 68 cells/mL for total NK cells.
The machine learning model, utilizing a random forest algorithm, demonstrated 89% accuracy in differentiating NK cell subpopulations.
The device successfully quantified cytokine and NK cell concentrations in undiluted blood samples.

Conclusions:

A smartphone-based microfluidic device offers a promising solution for rapid NK cell quantification and subpopulation analysis.
This technology can potentially overcome the limitations of traditional methods, facilitating quicker clinical decisions.
The developed system aids in assessing immune function and monitoring cancer immunotherapies with high accuracy and accessibility.