Single-cell transportation is one of the most common cell operations. Transporting cells with micropipettes is convenient for a wide range of biomedical applications. For high-efficiency cell transportation, the cells must be aspirated into the orifice of a micropipette. However, this is very difficult to achieve, as there is relative movement between the cell and the culture medium when the fluid drives the cell in the culture medium. It is crucial to use cell dynamics rather than fluid dynamics as the control objects to improve control performance and stop the cell immediately when it approaches the micropipette. In this study, the cell dynamics were modeled using a second-order model by integrating the dynamic model between the fluid and the cell into a first-order fluid dynamic model. A backstepping controller-based extended state observer was proposed to control the cell movement inside the micropipette. Experiments demonstrated that the proposed controller could aspirate cells into the orifice of the micropipette with high accuracy and no overshoot. Furthermore, the proposed controller was applied to automated somatic cell nuclear transfer, and it significantly boosted operational efficiency. Note to Practitioners —The need to apply advanced automation methods to transfer cells in life sciences has increased at a steady pace. The key feature of such systems is the ability to select and transfer cells at a predetermined position in space and time for biological applications. We propose a cell positioning control method based on vision-guided robotics that can directly aspirate cells to specified positions near the orifice of a micropipette. In somatic cell nuclear transfer, the proposed method of transferring somatic cells into oocytes occurs at a faster pace than manual operation. This provides essential functionality for single-cell transfer and is an appropriate technology for practitioners with this functional requirement.

Measuring the mechanical force applied to a cell during penetration has long been studied. However, existing sensor methods can disturb or even prevent a planned cell surgery because of their physical units. We propose a contactless mechanical force estimation method based on an improved point-load model and cell contour detection. We extended the point-load model to large cell deformations and obtained a relationship between the mechanical force and the morphology of the deformed cell. We designed two cell contour detection methods for visually detecting the deformation of different cell morphologies to obtain the geometric parameters required by the model. Finally, we carried out penetration experiments on porcine oocytes and zebrafish embryos. The contour detection methods showed a consistency of up to 99.29% compared with manual marking, and the force estimation accuracy was 1.05 μN. We compared the estimation results of our method with measurements taken in real experiments and confirmed that our method accurately estimated the mechanical force applied to the cell without contact. Thus, it may be applied to estimating the applied force during cell surgery in real time.

Contraction and relaxation are important functions of cardiomyocytes, and measuring their characteristics provides an evaluation index to explore the effects of drugs on cardiomyocytes. In addition, cardiomyocytes have an innate advantage in acting as a biopower by virtue of their ability to contract and relax, which also requires the detection of cardiomyocyte actions. However, existing measurement methods, such as mechanosensor measurements and calcium concentration measurements, have high requirements for experimental equipment and operation and are challenging to perform simultaneously with other cellular manipulations. Here, we propose a simple visual detection method for cardiomyocyte contraction and relaxation. We first recorded the contraction and relaxation of cardiomyocytes under a bright-field microscope, then used the optical flow method to track the sampling points on the cardiomyocytes in the video, and obtained the frequency of cardiomyocyte contraction and relaxation by analyzing the optical flow matrices. This method does not require the use of additional equipment or additional processing of cardiomyocytes, which significantly reduces the operational difficulty of detection and provides a method to achieve real-time detection of cardiomyocyte contraction and relaxation.

Cell transportation is a key step in many biological applications. Currently, most cell transportation research relies on microscopic vision feedback, which limits its application at places when a microscopic view is unavailable. For the first time, this paper proposed a robotic microscopic view-free cell transportation method based on pressure variation model inside a self-made bilayer micropipette. The bilayer micropipette, made by inserting a thin micropipette into a thicker one, picks the target cell with the outsider micropipette and holds it with the inner micropipette in cell transportation. To achieve this, the appropriate fluidic forces to pick and place the cell were determined based on force analysis. Then, the appropriate inner diameter of the inner thin micropipette was determined based on the micropipette aspiration model. Further, the pressure variation inside the bilayer micropipette during holding and releasing process were modeled to conduct a robotic microscopic vision-fee cell transportation. Experimental results demonstrated that our system was capable of transporting zebrafish embryos at an average speed of 25 s/cell with a success rate of 90%, with a transportation efficiency comparable to the related methods with microscopic view feedback. Besides, ignorable mechanical harm to the development competence of the zebrafish embryos was confirmed through culturing experiments. Note to Practitioners —Cell transportation is an important step in many biomedical researches. Currently, cell transportation usually relies on microscopy for picking up, and releasing cells, limiting its application in special environments without microscopic view feedback. In this paper, a robotic microscopic vision-free cell transportation method is proposed for the first time. In this method, cells are transported within a self-made bilayer micropipette. Pressure variations inside the micropipette are utilized to determine cell picking up and release. This robotic transport method demonstrated a high success rate and low harm to cells in experiments. Our research may contribute to the future development of vision-free and fully automated robotic cell culture techniques. Our research may spike inspiration for future research on microscopic vision-free cell transportation in fully automated cell culture system.

We developed a somatic cell nuclear transfer-electrofusion system for pairing and fusing oocytes and somatic cells with a thousand-fold volume difference. The system showed a 90.56% pairing efficiency, potentially boosting batch cloning efficiency.