Mechanistic insights into cellular deformation enable enhanced extensional-flow cytometry for label-free...

Area of Science:

• Biophysics
• Cell Biology
• Biotechnology

Background:

• Cellular biomechanics offer label-free indicators for cell population stratification in disease.
• Current deformability cytometry lacks specificity, interpretability, and real-time sorting capabilities, hindering translational use.

Purpose of the Study:

• To develop an advanced extensional-flow cytometry platform for tumor cell profiling and sorting.
• To enhance the mechanistic understanding and interpretation of cellular deformation dynamics.
• To enable real-time, label-free sorting with high purity and cell viability.

Main Methods:

• Utilized fluid-structure interaction simulations for mechanistic reinterpretation of cellular deformation.
• Developed a lightweight detection algorithm with auto-localization filters and attention modules for enhanced image analysis.
• Implemented a fully integrated pipeline for droplet encapsulation, electrostatic charging, and voltage-controlled deflection for sorting.

Main Results:

• Achieved a mean average precision of 96.8% in cell detection and morphological sensitivity.
• Demonstrated a sorting purity of 90.2% ± 4.4% with cell viability above 95%.
• Established a robust and scalable platform bridging mechanistic insight with real-time sorting.

Conclusions:

• The developed extensional-flow cytometry platform provides an interpretable solution for mechanophenotyping.
• This technology advances functional cytometric decision-making and label-free cell sorting.
• The platform offers a significant improvement over existing deformability-based systems for translational applications.