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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: Jun 8, 2025

Microfluidic Buffer Exchange for Interference-free Micro/Nanoparticle Cell Engineering

Microfluidic Buffer Exchange for Interference-free Micro/Nanoparticle Cell Engineering

Published on: July 10, 2016

Deep Learning-Assisted Label-Free Parallel Cell Sorting with Digital Microfluidics.

Zongliang Guo¹, Fenggang Li¹, Hang Li²

¹Beijing Advanced Innovation Center for Intelligent Robots and Systems, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, 100081, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)

|November 5, 2024

Summary

This summary is machine-generated.

A new label-free cell sorting method uses deep learning and microfluidics to differentiate cells by morphology. This technique achieves high precision and purity, enabling advanced diagnostics and research.

Keywords:

artificial intelligence cell sorting digital microfluidics droplet label‐free single cell research

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Separating Beads and Cells in Multi-channel Microfluidic Devices Using Dielectrophoresis and Laminar Flow

Separating Beads and Cells in Multi-channel Microfluidic Devices Using Dielectrophoresis and Laminar Flow

Published on: February 4, 2011

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Last Updated: Jun 8, 2025

Microfluidic Buffer Exchange for Interference-free Micro/Nanoparticle Cell Engineering

Microfluidic Buffer Exchange for Interference-free Micro/Nanoparticle Cell Engineering

Published on: July 10, 2016

Label-free Isolation and Enrichment of Cells Through Contactless Dielectrophoresis

Label-free Isolation and Enrichment of Cells Through Contactless Dielectrophoresis

Published on: September 3, 2013

Separating Beads and Cells in Multi-channel Microfluidic Devices Using Dielectrophoresis and Laminar Flow

Separating Beads and Cells in Multi-channel Microfluidic Devices Using Dielectrophoresis and Laminar Flow

Published on: February 4, 2011

Area of Science:

Biotechnology
Microfluidics
Artificial Intelligence

Background:

Cell sorting is crucial for research and clinical applications.
Existing methods often require cell labeling, which can affect cell viability.
A label-free approach is needed for efficient and non-invasive cell separation.

Purpose of the Study:

To develop and validate a novel label-free cell sorting method.
To integrate deep learning with microfluidic manipulation for morphological cell differentiation.
To assess the performance and applicability of the developed cell sorting technique.

Main Methods:

Utilized an Active-Matrix Digital Microfluidics (AM-DMF) platform.
Employed the YOLOv8 object detection model for precise droplet classification.
Implemented Safe Interval Path Planning for collision-free multi-target droplet manipulation.

Main Results:

Achieved 98.5% sorting precision, 96.49% purity, and 80% recovery over three cycles using HeLa cells and polystyrene beads.
Demonstrated successful sorting of HeLa cells from red blood cells.
Showcased differentiation of cancer cells from white blood cells and white blood cell subtypes.

Conclusions:

The integrated deep learning and AM-DMF system offers a highly precise and efficient label-free cell sorting solution.
The method minimizes sample loss, allowing for direct on-chip lysis and downstream bioanalysis.
This innovative technique has significant potential for advancing diagnostics, therapeutics, and cell biology research.