What question did this study set out to answer?

To develop a low-cost, pump-free microfluidic cytometer powered by artificial intelligence for rapid CD4+ T cell quantification in whole blood with minimal sample processing.

February 28, 2025Microsystems & NanoengineeringOpen Access

Artificial intelligence-enabled microfluidic cytometer using gravity-driven slug flow for rapid CD4+ T cell quantification in whole blood

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Authors

DDDesh Deepak Dixit TGTyler P. Graf KMKevin J. McHugh

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Overview

Validation study demonstrates rapid CD4+ T cell counting in healthy donor blood, indicating utility for low-resource point-of-care diagnostics.

Key Points

To develop a low-cost, pump-free microfluidic cytometer powered by artificial intelligence for rapid CD4+ T cell quantification in whole blood with minimal sample processing.
Whole blood was labeled with anti-CD4 antibody-coated microbeads and loaded into a microfluidic chip operated via gravity-driven slug flow without external pumps.
A microscope camera recorded the sample flow, and a convolutional neural network was trained to automatically identify and quantify bead-labeled CD4+ T cells from video frames.
The system was validated using fingerprick blood samples collected from healthy donors and benchmarked against conventional flow cytometry.
The microfluidic cytometer quantified CD4+ T cells within <10% deviation relative to standard flow cytometry measurements.
The automated platform completed analysis at least 4× faster than standard flow cytometry while requiring simpler instrumentation and lower operational costs.

Cite This Study

Dixit et al. (2025) studied this question.

synapsesocial.com/papers/6a7eb2a0084666b5350d27ff https://doi.org/10.1038/s41378-025-00881-y

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February 28, 2025Microsystems & NanoengineeringOpen Access

Artificial intelligence-enabled microfluidic cytometer using gravity-driven slug flow for rapid CD4+ T cell quantification in whole blood

View Full Paper

Ask AI

Bookmark

Authors

DDDesh Deepak Dixit TGTyler P. Graf KMKevin J. McHugh

Discussion

Member takes

Overview

Validation study demonstrates rapid CD4+ T cell counting in healthy donor blood, indicating utility for low-resource point-of-care diagnostics.

Key Points

To develop a low-cost, pump-free microfluidic cytometer powered by artificial intelligence for rapid CD4+ T cell quantification in whole blood with minimal sample processing.
Whole blood was labeled with anti-CD4 antibody-coated microbeads and loaded into a microfluidic chip operated via gravity-driven slug flow without external pumps.
A microscope camera recorded the sample flow, and a convolutional neural network was trained to automatically identify and quantify bead-labeled CD4+ T cells from video frames.
The system was validated using fingerprick blood samples collected from healthy donors and benchmarked against conventional flow cytometry.
The microfluidic cytometer quantified CD4+ T cells within <10% deviation relative to standard flow cytometry measurements.
The automated platform completed analysis at least 4× faster than standard flow cytometry while requiring simpler instrumentation and lower operational costs.

Cite This Study

Dixit et al. (2025) studied this question.

synapsesocial.com/papers/6a7eb2a0084666b5350d27ff https://doi.org/10.1038/s41378-025-00881-y

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