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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: Oct 21, 2025

A Semi-automated Approach to Preparing Antibody Cocktails for Immunophenotypic Analysis of Human Peripheral Blood
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Panel Optimization for High-Dimensional Immunophenotyping Assays Using Full-Spectrum Flow Cytometry.

Laura Ferrer-Font1,2, Sam J Small1, Brittany Lewer1

  • 1Malaghan Institute of Medical Research, Wellington, New Zealand.

Current Protocols
|September 7, 2021
PubMed
Summary
This summary is machine-generated.

This study provides step-by-step protocols for optimizing high-dimensional full-spectrum flow cytometry panels. It bridges the gap between theoretical design and practical application for immunophenotyping, aiding in troubleshooting and data quality assessment.

Keywords:
assay optimization and troubleshootingfull-spectrum flow cytometryhigh-dimensional flow cytometry panel

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Area of Science:

  • Immunology
  • Biotechnology
  • Analytical Chemistry

Background:

  • Advancements in fluorescence flow cytometry enable complex, high-parameter panels for single-cell analysis.
  • Full-spectrum flow cytometry utilizes unique spectral fingerprints for larger panels, overcoming limitations of conventional methods.
  • A knowledge gap exists in optimizing high-dimensional full-spectrum flow cytometry panels for robust downstream analysis.

Purpose of the Study:

  • To provide comprehensive, step-by-step protocols for optimizing high-dimensional full-spectrum flow cytometry panels.
  • To guide users from theoretical panel design to practical implementation for immunophenotyping.
  • To offer troubleshooting strategies for common issues encountered in panel optimization.

Main Methods:

  • Development of protocols for spectral reference control preparation and evaluation.
  • Detailed procedures for antibody titration and instrument setting adjustments.
  • Methods for unmixing evaluation, marker resolution assessment, and autofluorescence management.
  • Guidance on assessing data quality using expert gating and dimensionality reduction algorithms.

Main Results:

  • Demonstration of a practical approach to optimizing a 24-color full-spectrum flow cytometry panel for T-cell identification.
  • Validation of protocols for ensuring high-quality data suitable for high-dimensional analysis.
  • Establishment of a framework for troubleshooting and refining complex flow cytometry panels.

Conclusions:

  • The provided protocols effectively bridge the gap between full-spectrum flow cytometry panel design and optimization.
  • These methods enable robust immunophenotyping and high-dimensional data analysis.
  • The protocols serve as a valuable resource for researchers using advanced flow cytometry techniques.