Robotic Intracellular Pressure Measurement Based on Improved Balance Pressure Model
Jinyu Qiu, Minghui Li, Ruimin Li, Yue Du, Yaowei Liu, Mingzhu Sun, Xin Zhao, Qili Zhao
- 发表年份
- 2024
- 引用次数
- 4
- 访问权限
- 开放获取
摘要
Intracellular pressure regulates cell physiological activities and impacts cell micromanipulation results. The measurement of intracellular pressure may reveal the mechanism of these cell physiological activities and improve the micromanipulation accuracy for cells. Current intracellular pressure measurement methods usually rely on specialized and expensive devices or have significant cytotoxicities on cells. In this paper, a simple robotic intracellular measurement method based on an improved balance pressure model is developed on the traditional cell manipulation system setup. First, an improved balance pressure model is proposed to calculate the intracellular pressure. Then, a traditional glass micropipette is utilized as a probe to penetrate the cell membrane to measure intracellular pressure. After cell membrane penetration, the key parameters of the improved balance pressure model including the cell deformation and the moving distance of the gas-liquid interface (GLI) inside the micropipette are measured in time to calculate the intracellular pressure. The experimental results on porcine oocytes demonstrate that the proposed method has an 80% success rate at an average measurement speed of 12 seconds/cell. Further, no intracellular pressure leaking was tested during the measurement process, guaranteeing measurement accuracy. Further, an 87.5% survival rate of operated oocytes was obtained after the measurement, proving limited damage to cell viability. Our method is highly expected to be applied in biological applications requiring in situ measurement of intracellular pressure.
关键词
相关论文
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
Oussama Khatib
1986
A Mathematical Introduction to Robotic Manipulation
Richard M. Murray, Zexiang Li, Shankar Sastry
2017
Robot dynamics and control
Mark W. Spong
1989
A tutorial on visual servo control
Seth Hutchinson, Gregory D. Hager, Peter Corke
1996