Automated Shear Adhesion Force Measurement of Batch-Adherent Cell Based on Balance Pressure in Micropipette

Cellular shear adhesion, which is the adhesion between cells and the substrates, plays an important role in cell activities. This article aimed to develop a robotic system with automated cell aspiration and in situ micropipette cleaning for shear adhesion force measurement. We proposed a shear adhesion force measurement method based on the balance pressure model and designed a cell placement device with a double-Petri dish to improve the accuracy and efficiency of the measurement. Then we achieved the whole measurement automation by cell selection based on image texture analysis, contact detection based on motion history image (MHI) analysis, and cell aspiration state detection based on sub-pixel image registration. Three types of adherent cells (pancreatic cancer cell, osteoblast, and osteoclast) were used to validate the automated measurement system. The system demonstrated an overall success rate of 75.6% with an average measurement time of 5 min. The experimental results show that pancreatic cancer cells possessed higher shear adhesion force than osteoblasts and osteoclasts. There was a significant difference in adhesion between osteoblasts and osteoclasts. Conclusion: The experimental results demonstrate that the system was an efficient, reproducible approach for shear adhesion force measurement automatically. The robotic system eliminated the stringent skill requirements of operators and improved the consistency and efficiency of the shear adhesion measurement, which can be applied to life science.