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Related Concept Videos

Flow Cytometry01:23

Flow Cytometry

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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: Aug 13, 2025

Fully Automated Centrifugal Microfluidic Device for Ultrasensitive Protein Detection from Whole Blood
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Label-free microfluidic cell sorting and detection for rapid blood analysis.

Nan Lu1,2, Hui Min Tay1, Chayakorn Petchakup1

  • 1School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Blk N3, Level 2, Room 86 (N3-02c-86), 639798, Singapore. hwhou@ntu.edu.sg.

Lab on a Chip
|January 19, 2023
PubMed
Summary
This summary is machine-generated.

Label-free microfluidics offer advanced blood analysis by separating cells based on intrinsic properties, improving disease detection without antibodies. This technology enhances health profiling and identifies novel biomarkers for diagnostics.

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Area of Science:

  • Biomedical Engineering
  • Analytical Chemistry
  • Clinical Diagnostics

Background:

  • Blood analysis faces challenges due to complex cellular composition (>99.9% RBCs).
  • Current methods can be limited in detecting subtle cellular dysfunctions.
  • Point-of-care diagnostics require innovative, efficient analytical techniques.

Purpose of the Study:

  • To review advances in label-free microfluidic technologies for blood cell separation and analysis.
  • To explore the use of intrinsic cellular properties as novel biomarkers.
  • To highlight the integration of microfluidics with machine learning for enhanced diagnostics.

Main Methods:

  • Microfluidic devices for label-free separation of blood components (CTCs, leukocytes, platelets, EVs).
  • Single-cell analysis of morphology, spectrochemical, dielectric, and biophysical properties.
  • Integration of machine learning algorithms with microfluidic platforms.

Main Results:

  • Demonstrated efficacy of label-free microfluidics in fractionating diverse blood components.
  • Identification of intrinsic cellular phenotypes as complementary diagnostic biomarkers.
  • Improved sensitivity and specificity in clinical studies through microfluidics-ML integration.

Conclusions:

  • Label-free microfluidics represent a promising approach for comprehensive blood analysis and disease detection.
  • The technology enables identification of non-traditional circulating biomarkers.
  • Future outlook includes high-throughput, multi-dimensional analysis for advanced clinical diagnostics.