ArticleMicromachines2026
Real-Time Biophysical Phenotyping and Sorting of Transiting Cells Along a Constriction Microchannel.
Article in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
We present a microfluidic platform for real-time, label-free cytometry and sorting of single cells based on intrinsic biophysical properties. The system integrates impedance-based electrokinetic sensing with a constriction microchannel architecture to induce controlled deformation during cell transit. Electrical signals captured via lock-in amplification are processed through a parallel software pipeline incorporating deep learning algorithms for event detection and feature extraction. A biomechanical model enables conversion of raw signal features into cell size and whole-cell elasticity, validated against imaging measurements. Experimental results demonstrate accurate phenotyping and sorting of live and dead MCF-7 cells, achieving sorting accuracy of 84%. This approach offers a cost-effective and scalable solution for biophysical analysis, with potential applications in liquid biopsy, disease diagnostics, and personalized medicine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.