Simulation-Based Microfluidic Deformation Mapping for Region-Dependent Apparent Young’s Modulus Estimation of Single Cells

High-throughput microfluidic deformation assays enable label-free single-cell mechanophenotyping by quantifying how cells deform under controlled hydrodynamic loading. These approaches commonly extract deformation-related observables, such as projected area, axis ratio, and deformation index, and use them as indicators for cellular mechanical properties. However, deformation is not solely determined by stiffness; it is a coupled outcome of cell size, local hydrodynamic stress, and intrinsic mechanical response. Therefore, we present a simulation-based microfluidic framework for estimating region-dependent apparent Young’s modulus (E, a quantitative indicator characterizing cellular mechanical stiffness) from diameter–deformation measurements at the single-cell level. A three-region microfluidic channel is designed to impose distinct hydrodynamic loading conditions, while numerical simulations establish quantitative maps linking cell diameter, deformation, and E. Based on these results, region-specific nonlinear surface models are constructed to invert experimental diameter–deformation measurements into E values. Finally, application to primary T cells and K562 cells demonstrates clear region-dependent differences in E, highlighting the influence of local loading conditions on inferred mechanical properties. Overall, this work provides a simplified but practical route for transforming deformation-based phenotypes into quantitative, loading-aware mechanical parameters for single-cell analysis.

Authors

Institutions

Publication Details

Journal
Biosensors
Published
2026-08-25
DOI
https://doi.org/10.3390/bios16090461
Primary Topic
Cellular Mechanics and Interactions
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simulation-Based Microfluidic Deformation Mapping for Region-Dependent Apparent Young’s Modulus Estimation of Single Cells

Jianwei Zhong, Jiawei Lyu, Lin Lin, Han Li et al.
Biosensors
Cellular Mechanics and Interactions
article

Simulation-Based Microfluidic Deformation Mapping for Region-Dependent Apparent Young’s Modulus Estimation of Single Cells

Jianwei Zhong, Jiawei Lyu, Lin Lin, Han Li, Minhui Liang, Dawei Ming, Yilong Zhou
article en

Abstract

High-throughput microfluidic deformation assays enable label-free single-cell mechanophenotyping by quantifying how cells deform under controlled hydrodynamic loading. These approaches commonly extract deformation-related observables, such as projected area, axis ratio, and deformation index, and use them as indicators for cellular mechanical properties. However, deformation is not solely determined by stiffness; it is a coupled outcome of cell size, local hydrodynamic stress, and intrinsic mechanical response. Therefore, we present a simulation-based microfluidic framework for estimating region-dependent apparent Young’s modulus (E, a quantitative indicator characterizing cellular mechanical stiffness) from diameter–deformation measurements at the single-cell level. A three-region microfluidic channel is designed to impose distinct hydrodynamic loading conditions, while numerical simulations establish quantitative maps linking cell diameter, deformation, and E. Based on these results, region-specific nonlinear surface models are constructed to invert experimental diameter–deformation measurements into E values. Finally, application to primary T cells and K562 cells demonstrates clear region-dependent differences in E, highlighting the influence of local loading conditions on inferred mechanical properties. Overall, this work provides a simplified but practical route for transforming deformation-based phenotypes into quantitative, loading-aware mechanical parameters for single-cell analysis.

BiosensorsVol. 16(9)
Guangxi University (CN), The People's Hospital of Guangxi Zhuang Autonomous Region (CN), South China University of Technology (CN)
Natural Science Foundation of Guangxi Zhuang Autonomous Region, National Natural Science Foundation of China
Openalex Percentile: Top 13%
Cellular Mechanics and Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.