ArticleACS sensors2023
Development of a Microfluidic Flow Cytometer with a Uniform Optical Field (Uni-μFCM) Enabling Quantitative Analysis of Single-Cell Proteins and Its Applications in Leukemia Gating, Tumor Classification, and Hierarchy of Cancer Stem Cells.
Article in ACS sensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Microfluidics for Blood Disorders and Hematological Disease Monitoring and Modeling.International journal of molecular sciences · 2026Review
- Single-Cell Protein Assays in Context: From 2D to 3D and In Situ Analysis.Annual review of analytical chemistry (Palo Alto, Calif.) · 2026Review
- Enhancing cell characterization with microfluidics and AI: a comprehensive review of mechanical, electrical, and hybrid techniques.Biotechnology reports (Amsterdam, Netherlands) · 2025Review
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fast and quantitative estimation of single-cell proteins with various distribution patterns remains a technical challenge. Here, a microfluidic flow cytometer with a uniform optical field (Uni-μFCM) was developed, which enabled the translation of multicolor fluorescence signals of bound antibodies into targeted protein numbers with arbitrary distributions of biological cells. As the core of Uni-μFCM, a uniform optical field for optical excitation and fluorescence detection was realized by adopting a microfabricated metal window to shape the optical beam for excitation, which was modeled and validated by both numerical simulation and experimental characterization. After the validation of Uni-μFCM in single-cell protein quantification by measuring single-cell expressions of three transcriptional factors from four cell lines of variable sizes and origins, Uni-μFCM was applied to (1) quantify membrane and cytoplasmic markers of myeloid and lymphocytic leukocytes to classify cell lines and normal and patient blood samples; (2) measure single-cell expressions of key cytokines affiliated with gene stabilities, differentiating paired oral and colon tumor cell lines with varied malignancies, and (3) quantify single-cell stemming markers of liver tumor cell lines, cell subtypes, and liver patient samples to determine a variety of lineage hierarchy. By quantitatively assessing complex cellular phenotypes, Uni-μFCM substantially expanded the phenotypic space accessible to single-cell applications in leukemia gating, tumor classification, and hierarchy determination of cancer stem cells.
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