A vacuum-driven microfluidic platform for single-cell elastic modulus measurement

The cellular elastic modulus serves as a crucial biophysical indicator for evaluating the cellular state in physiological and pathological contexts. However, traditional measurement techniques, such as atomic force microscopy, are often limited by low throughput, high cost, and complexity. Here, we present a vacuum-driven microfluidic platform for quantification of cellular elasticity. The platform operates without external actuation and integrates a YOLOv12-based deep learning framework for automated cell deformation analysis. We demonstrate a self-driven strategy based on degassed poly(dimethylsiloxane) and achieve precise identification of multi-stage cell deformation using the YOLOv12 model, which achieves a mean average precision (mAP50-95) of 93.3%. The vacuum-driven microfluidic platform processes 8–10 cells per test within 10 min. Using the vacuum-driven microfluidic platform, we measured the elastic modulus of A549 and HepG2 cells, obtaining values of 270 ± 110 Pa and 110 ± 56 Pa, respectively. By eliminating external power requirements and minimizing hardware complexity, the vacuum-driven microfluidic platform provides a cost-effective, accessible, and reliable solution for single-cell mechanophenotyping, with broad potential for applications in biomedical research, including disease progression studies and drug response assessment.