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Qiu J, Zhao Q, Li R, Liu Y, Ma B, Zhao X. Robotic Fast Patch Clamp in Brain Slices Based on Stepwise Micropipette Navigation and Gigaseal Formation Control. SENSORS (BASEL, SWITZERLAND) 2025; 25:1128. [PMID: 40006358 PMCID: PMC11859202 DOI: 10.3390/s25041128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2025] [Revised: 02/09/2025] [Accepted: 02/11/2025] [Indexed: 02/27/2025]
Abstract
The patch clamp technique has become the gold standard for neuron electrophysiology research in brain science. Brain slices have been widely utilized as the targets of the patch clamp technique due to their higher optical transparency compared to a live brain and their intercellular connectivity in comparison to cultured single neurons. However, the narrow working space, small scope, and depth of the field of view make the positioning of the operation's micropipette to the target neuron a time-consuming task reliant on a high level of experience, significantly slowing down operation of the patch clamp technique in brain slices. Further, the current poor controllability in gigaseal formation, which is the key to electrophysiology signal recording, significantly lowers the patch clamp success rate. In this paper, a stepwise navigation of the micropipette is conducted to accelerate the positioning process of the micropipette tip to the target neuron in the brain slice. Then, a fuzzy proportional-integral-derivative controller is designed to control the gigaseal formation process along a designed resistance curve. The experimental results demonstrate an almost doubled patch clamp technique speed, with a 25% improvement in the success rate compared to the conventional manual method. The above advantages may promote the application of our method in brain science research based on brain slice platforms.
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Affiliation(s)
- Jinyu Qiu
- Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China; (J.Q.); (Q.Z.); (R.L.); (Y.L.); (B.M.)
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
| | - Qili Zhao
- Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China; (J.Q.); (Q.Z.); (R.L.); (Y.L.); (B.M.)
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
| | - Ruimin Li
- Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China; (J.Q.); (Q.Z.); (R.L.); (Y.L.); (B.M.)
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
| | - Yuzhu Liu
- Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China; (J.Q.); (Q.Z.); (R.L.); (Y.L.); (B.M.)
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
| | - Biting Ma
- Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China; (J.Q.); (Q.Z.); (R.L.); (Y.L.); (B.M.)
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
| | - Xin Zhao
- Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China; (J.Q.); (Q.Z.); (R.L.); (Y.L.); (B.M.)
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
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Zhang Y, Zhao H, Chen Z, Liu Z, Huang H, Qu Y, Liu Y, Sun M, Sun D, Zhao X. Optical tweezer-assisted cell pairing and fusion for somatic cell nuclear transfer within an open microchannel. LAB ON A CHIP 2024; 24:5215-5224. [PMID: 39503358 DOI: 10.1039/d4lc00561a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2024]
Abstract
Somatic cell nuclear transfer (SCNT), referred to as somatic cell cloning, is a pivotal biotechnological technique utilized across various applications. Although robotic SCNT is currently available, the subsequent oocyte electrical activation/reconstructed embryo electrofusion is still manually completed by skilled operators, presenting challenges in efficient manipulation due to the uncontrollable positioning of the reconstructed embryo. This study introduces a robotic SCNT-electrofusion system to enable high-precision batch SCNT cloning. The proposed system integrates optical tweezers and microfluidic technologies. An optical tweezer is employed to facilitate somatic cells in precisely reaching the fusion site, and a specific polydimethylsiloxane (PDMS) chip is designed to assist in positioning and pairing oocytes and somatic cells. Enhancement in the electric field distribution between two parallel electrodes by PDMS pillars significantly reduces the required external voltage for electrofusion/electrical activation. We employed porcine oocytes and porcine fetal fibroblasts for SCNT experiments. The experimental results show that 90.56% of oocytes successfully paired with somatic cells to form reconstructed embryos, 76.43% of the reconstructed embryos successfully fused, and 70.55% of these embryos underwent cleavage. It demonstrates that the present system achieves the robotic implementation of oocyte electrical activation/reconstructed embryo electrofusion. By leveraging the advantages of batch operations using microfluidics, it proposes an innovative robotic cloning procedure that scales embryo cloning.
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Affiliation(s)
- Yidi Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Tianjin Key Laboratory of Intelligent Robotic (tjKLIR), Institute of Robotics and Automatic Information System (IRAIS), Nankai University, Tianjin 300350, China.
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, SAR, China.
| | - Han Zhao
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, SAR, China.
| | - Zhenlin Chen
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, SAR, China.
| | - Zhen Liu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, SAR, China.
| | - Hanjin Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, SAR, China.
| | - Yun Qu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, SAR, China.
| | - Yaowei Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Tianjin Key Laboratory of Intelligent Robotic (tjKLIR), Institute of Robotics and Automatic Information System (IRAIS), Nankai University, Tianjin 300350, China.
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
| | - Mingzhu Sun
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Tianjin Key Laboratory of Intelligent Robotic (tjKLIR), Institute of Robotics and Automatic Information System (IRAIS), Nankai University, Tianjin 300350, China.
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
| | - Dong Sun
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, SAR, China.
| | - Xin Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Tianjin Key Laboratory of Intelligent Robotic (tjKLIR), Institute of Robotics and Automatic Information System (IRAIS), Nankai University, Tianjin 300350, China.
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China
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Hu W, Ma Y, Zhan Z, Hussain D, Hu C. Robotic Intracellular Electrochemical Sensing for Adherent Cells. CYBORG AND BIONIC SYSTEMS 2022; 2022:9763420. [PMID: 36285318 PMCID: PMC9494721 DOI: 10.34133/2022/9763420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 07/25/2022] [Indexed: 11/22/2022] Open
Abstract
Nanopipette-based observation of intracellular biochemical processes is an important approach to revealing the intrinsic characteristics and heterogeneity of cells for better investigation of disease progression or early disease diagnosis. However, the manual operation needs a skilled operator and faces problems such as low throughput and poor reproducibility. This paper proposes an automated nanopipette-based microoperation system for cell detection, three-dimensional nonovershoot positioning of the nanopipette tip in proximity to the cell of interest, cell approaching and proximity detection between nanopipette tip and cell surface, and cell penetration and detection of the intracellular reactive oxygen species (ROS). A robust focus algorithm based on the number of cell contours was proposed for adherent cells, which have sharp peaks while retaining unimodality. The automated detection of adherent cells was evaluated on human umbilical cord vein endothelial cells (HUVEC) and NIH/3T3 cells, which provided an average of 95.65% true-positive rate (TPR) and 7.59% false-positive rate (FPR) for in-plane cell detection. The three-dimensional nonovershoot tip positioning of the nanopipette was achieved by template matching and evaluated under the interference of cells. Ion current feedback was employed for the proximity detection between the nanopipette tip and cell surface. Finally, cell penetration and electrochemical detection of ROS were demonstrated on human breast cancer cells and zebrafish embryo cells. This work provides a systematic approach for automated intracellular sensing for adherent cells, laying a solid foundation for high-throughput detection, diagnosis, and classification of different forms of biochemical reactions within single cells.
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Affiliation(s)
- Weikang Hu
- Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Yanmei Ma
- Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Zhen Zhan
- Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Danish Hussain
- Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
- Department of Mechatronics Engineering, National University of Sciences and Technology, Islamabad, Pakistan
| | - Chengzhi Hu
- Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China
- Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, China
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Zhuang S, Dai C, Shan G, Ru C, Zhang Z, Sun Y. Robotic Rotational Positioning of End-Effectors for Micromanipulation. IEEE T ROBOT 2022. [DOI: 10.1109/tro.2022.3142671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Sha X, Sun H, Zhao Y, Li W, Li WJ. A Review on Microscopic Visual Servoing for Micromanipulation Systems: Applications in Micromanufacturing, Biological Injection, and Nanosensor Assembly. MICROMACHINES 2019; 10:E843. [PMID: 31810244 PMCID: PMC6953108 DOI: 10.3390/mi10120843] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 11/23/2019] [Accepted: 11/28/2019] [Indexed: 01/25/2023]
Abstract
Micromanipulation is an interdisciplinary technology that integrates advanced knowledge of microscale/nanoscale science, mechanical engineering, electronic engineering, and control engineering. Over the past two decades, it has been widely applied in the fields of MEMS (microelectromechanical systems), bioengineering, and microdevice integration and manufacturing. Microvision servoing is the basic tool for enabling the automatic and precise micromanipulation of microscale/nanoscale entities. However, there are still many problems surrounding microvision servoing in theory and the application of this technology's micromanipulation processes. This paper summarizes the research, development status, and practical applications of critical components of microvision servoing for micromanipulation, including geometric calibration, autofocus techniques, depth information, and visual servoing control. Suggestions for guiding future innovation and development in this field are also provided in this review.
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Affiliation(s)
- Xiaopeng Sha
- School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China; (X.S.); (H.S.); (W.L.)
| | - Hui Sun
- School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China; (X.S.); (H.S.); (W.L.)
| | - Yuliang Zhao
- School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China; (X.S.); (H.S.); (W.L.)
| | - Wenchao Li
- School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China; (X.S.); (H.S.); (W.L.)
| | - Wen J. Li
- Department of Mechanical Engineering, City University of Hong Kong, Kowloon, Hong Kong 999077, China
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Sadak F, Saadat M, Hajiyavand AM. Vision-Based Sensor for Three-Dimensional Vibrational Motion Detection in Biological Cell Injection. SENSORS 2019; 19:s19235074. [PMID: 31757099 PMCID: PMC6929175 DOI: 10.3390/s19235074] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 11/15/2019] [Accepted: 11/18/2019] [Indexed: 11/16/2022]
Abstract
Intracytoplasmic sperm injection (ICSI) is an infertility treatment where a single sperm is immobilised and injected into the egg using a glass injection pipette. Minimising vibration in three orthogonal axes is essential to have precise injector motion and full control during the egg injection procedure. Vibration displacement sensing using physical sensors in ICSI operation is challenging since the sensor interfacing is not practically feasible. This study proposes a non-invasive technique to measure the three-dimensional vibrational motion of the injection pipette by a single microscope camera during egg injection. The contrast-limited adaptive histogram equalization (CHALE) method and blob analyses technique were employed to measure the vibration displacement in axial and lateral axes, while the actual dimension of the focal axis was directly measured using the Brenner gradient algorithm as a focus measurement algorithm. The proposed algorithm operates between the magnifications range of 4× to 40× with a resolution of half a pixel. Experiments using the proposed vision-based algorithm were conducted to measure and verify the vibration displacement in axial and lateral axes at various magnifications. The results were compared against manual procedures and the differences in measurements were up to 2% among all magnifications. Additionally, the effect of injection speed on lateral vibration displacement was measured experimentally and was used to determine the values for egg deformation, force fluctuation, and penetration force. It was shown that increases in injection speed significantly increases the lateral vibration displacement of the injection pipette by as much as 54%. It has been demonstrated successfully that visual sensing has played a key role in identifying the limitation of the egg injection speed created by lateral vibration displacement of the injection pipette tip.
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Zhang Z, Dai C, Huang J, Wang X, Liu J, Ru C, Pu H, Xie S, Zhang J, Moskovtsev S, Librach C, Jarvi K, Sun Y. Robotic Immobilization of Motile Sperm for Clinical Intracytoplasmic Sperm Injection. IEEE Trans Biomed Eng 2018; 66:444-452. [PMID: 29993453 DOI: 10.1109/tbme.2018.2848972] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE In clinical intracytoplasmic sperm injection (ICSI), a motile sperm must be immobilized before insertion into an oocyte. This paper aims to develop a robotic system for automated tracking, orientation control, and immobilization of motile sperms for clinical ICSI applications. METHODS We adapt the probabilistic data association filter by adding sperm head orientation into state variables for robustly tracking the sperm head and estimating sperm tail positions under interfering conditions. The robotic system also utilizes a motorized rotational microscopy stage and a new visual servo control strategy that predicts and compensates for sperm movements to actively adjust sperm orientation for immobilizing a sperm swimming in any direction. RESULTS The system robustly tracked sperm head with a tracking success rate of 96.0% and estimated sperm tail position with an accuracy of 1.08 μm under clinical conditions where the occlusion of the target sperm and interference from other sperms occur. Experimental results from robotic immobilization of 400 sperms confirmed that the system achieved a consistent immobilization success rate of 94.5%, independent of sperm velocity or swimming direction. CONCLUSION Our adapted tracking algorithm effectively distinguishes the target sperm from interfering sperms. Predicting and compensating for sperm movements significantly reduce the positioning error during sperm orientation control. These features make the robotic system suitable for automated sperm immobilization. SIGNIFICANCE The robotic system eliminates stringent skill requirements in manual sperm immobilization. It is capable of manipulating sperms swimming in an arbitrary direction with a high success rate.
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Asmad Vergara M, Jacquot M, Laurent GJ, Sandoz P. Digital Holography as Computer Vision Position Sensor with an Extended Range of Working Distances. SENSORS 2018; 18:s18072005. [PMID: 29932146 PMCID: PMC6068586 DOI: 10.3390/s18072005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 06/13/2018] [Accepted: 06/16/2018] [Indexed: 11/16/2022]
Abstract
Standard computer vision methods are usually based on powerful contact-less measurement approaches but applications, especially at the micro-scale, are restricted by finite depth-of-field and fixed working distance of imaging devices. Digital holography is a lensless, indirect imaging method recording the optical wave diffracted by the object onto the image sensor. The object is reconstructed numerically by propagating the recorded wavefront backward. The object distance becomes a computation parameter that can be chosen arbitrarily and adjusted to match the object position. No refractive lens is used and usual depth-of-field and working distance limitations are replaced by less restrictive ones tied to the laser-source coherence-length and to the size and resolution of the camera sensor. This paper applies digital holography to artificial visual in-plane position sensing with an extra-large range-to-resolution ratio. The object is made of a pseudoperiodic pattern allowing a subpixel resolution as well as a supra field-of-observation displacement range. We demonstrate an in-plane resolution of 50 nm and 0.002deg. in X, Y and θ respectively, over a working distance range of more than 15 cm. The allowed workspace extends over 12×10×150mm3. Digital holography extends the field of application of computer vision by allowing an extra-large range of working distances inaccessible to refractive imaging systems.
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Affiliation(s)
- Miguel Asmad Vergara
- FEMTO-ST Institute, Université Bourgogne Franche-Comté, CNRS, 25000 Besançon, France.
- Sección Física, Departamento de Ciencias, Pontificia Universidad Católica del Perú, Apartado 1761, Lima, Peru.
| | - Maxime Jacquot
- FEMTO-ST Institute, Université Bourgogne Franche-Comté, CNRS, 25000 Besançon, France.
| | - Guillaume J Laurent
- FEMTO-ST Institute, Université Bourgogne Franche-Comté, CNRS, 25000 Besançon, France.
| | - Patrick Sandoz
- FEMTO-ST Institute, Université Bourgogne Franche-Comté, CNRS, 25000 Besançon, France.
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Yu J, Xu T, Lu Z, Vong CI, Zhang L. On-Demand Disassembly of Paramagnetic Nanoparticle Chains for Microrobotic Cargo Delivery. IEEE T ROBOT 2017. [DOI: 10.1109/tro.2017.2693999] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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10
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Zhuang S, Lin W, Zhong J, Zhang G, Li L, Qiu J, Gao H. Visual Servoed Three-Dimensional Rotation Control in Zebrafish Larva Heart Microinjection System. IEEE Trans Biomed Eng 2017; 65:64-73. [PMID: 28422649 DOI: 10.1109/tbme.2017.2688375] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Zebrafish larva heart microinjection is a widely used technique in cardiac disease study. Compared with intensively researched rotation control of spherical or nearly spherical targets with clear structures, such as cells and embryos, 3-D rotation control of zebrafish larva demands new techniques due to its nontransparent structures and irregular outlines. METHODS In this paper, we present a vision-servo system to automate the rotation process of zebrafish larva body. A switched control strategy is adopted to rotate zebrafish larva about the optical axis by using two micropipettes. Precisely rolling about larva body is performed, which involves a custom-designed rotational micromanipulator. A vision detection and online tracking algorithm is also developed to meet the requirement of visual servoing. With designed rotation control strategy, zebrafish larva heart can be adjusted to a desired orientation, which is often towards the injection pipette tip. RESULTS Experimental results show that the designed system is capable of achieving high success rate of 94% about -axis rotation and 100% about -axis with 50 trails. The system also performs an average speed of 44 s/larva with a satisfied rotation accuracy of 0.5 in the horizontal plane and 2.5 about its roll axis. CONCLUSION The proposed strategy is effective in flexibly manipulating larvae in 3-D. SIGNIFICANCE The developed 3-D rotation control scheme is able to be applied to injection of various organs in zebrafish larva body for different experimental requirements.
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Liu J, Zhang Z, Wang X, Liu H, Zhao Q, Zhou C, Tan M, Pu H, Xie S, Sun Y. Automated Robotic Measurement of 3-D Cell Morphologies. IEEE Robot Autom Lett 2017. [DOI: 10.1109/lra.2016.2645145] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Wang H, Huang Q, Shi Q, Yue T, Chen S, Nakajima M, Takeuchi M, Fukuda T. Automated Assembly of Vascular-Like Microtube With Repetitive Single-Step Contact Manipulation. IEEE Trans Biomed Eng 2016; 62:2620-8. [PMID: 26513766 DOI: 10.1109/tbme.2015.2437952] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Fabricated vessel-mimetic microtubes are essential for delivering sufficient nutrient to engineered composite tissues. In this paper, vascular-like microtubes are engineered by automated assembly of donut-shaped micromodules that embed fibroblast cells. A microrobotic system is set up with dual manipulators of 30-nm positioning resolution under an optical microscope. The system assembles the micromodules by repeated single-step pick-up motions. This process is specifically designed to avoid human interference and ensure high reproducibility for automation. We optimized the single-step motion by calibrating the key parameters (the micromodule dimensions) in a force analysis. The optimal motion achieved a 98% pick-up success rate. The automated repetitive single-step assembly is achieved by an algorithm that acquires the 3-D location and tracks the micromanipulator without being affected by low contrast. The accuracy of the acquired 3-D location was experimentally determined as approximately 1 pixel (2 μm under 4× magnification), and the tracking under different observation conditions is proved effective. Finally, we automatically assembled microtubes at 6 micromodules/min, sufficiently fast for fabricating macroscopic vessel-mimetic substitutes in biological applications.
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Fridman MD, Liu J, Sun Y, Hamilton RM. Microinjection Technique for Assessment of Gap Junction Function. Methods Mol Biol 2016; 1437:145-154. [PMID: 27207292 DOI: 10.1007/978-1-4939-3664-9_10] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Gap junctions are essential for the proper function of many native mammalian tissues including neurons, cardiomyocytes, embryonic tissues, and muscle. Assessing these channels is therefore fundamental to understanding disease pathophysiology, developing therapies for a multitude of acquired and genetic conditions, and providing novel approaches to drug delivery and cellular communication. Microinjection is a robust, albeit difficult, technique, which provides considerable information that is superior to many of the simpler techniques due to its ability to isolate cells, quantify kinetics, and allow cross-comparison of multiple cell lines. Despite its user-dependent nature, the strengths of the technique are considerable and with the advent of new, automation technologies may improve further. This text describes the basic technique of microinjection and briefly discusses modern automation advances that can improve the success rates of this technique.
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Affiliation(s)
- Michael D Fridman
- Department of Physiology and Experimental Medicine, Hospital for Sick Children, Toronto, ON, Canada
| | - Jun Liu
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Yu Sun
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Robert M Hamilton
- Department of Physiology and Experimental Medicine, Hospital for Sick Children, Toronto, ON, Canada.
- Department of Pediatrics - Division of Cardiology, Hospital for Sick Children, Toronto, ON, Canada.
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Tan N, Clevy C, Laurent GJ, Sandoz P, Chaillet N. Accuracy Quantification and Improvement of Serial Micropositioning Robots for In-Plane Motions. IEEE T ROBOT 2015. [DOI: 10.1109/tro.2015.2498301] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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15
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Liu J, Siragam V, Gong Z, Chen J, Fridman MD, Leung C, Lu Z, Ru C, Xie S, Luo J, Hamilton RM, Sun Y. Robotic adherent cell injection for characterizing cell-cell communication. IEEE Trans Biomed Eng 2014; 62:119-25. [PMID: 25073160 DOI: 10.1109/tbme.2014.2342036] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Compared to robotic injection of suspended cells (e.g., embryos and oocytes), fewer attempts were made to automate the injection of adherent cells (e.g., cancer cells and cardiomyocytes) due to their smaller size, highly irregular morphology, small thickness (a few micrometers thick), and large variations in thickness across cells. This paper presents a robotic system for automated microinjection of adherent cells. The system is embedded with several new capabilities: automatically locating micropipette tips; robustly detecting the contact of micropipette tip with cell culturing surface and directly with cell membrane; and precisely compensating for accumulative positioning errors. These new capabilities make it practical to perform adherent cell microinjection truly via computer mouse clicking in front of a computer monitor, on hundreds and thousands of cells per experiment (versus a few to tens of cells as state of the art). System operation speed, success rate, and cell viability rate were quantitatively evaluated based on robotic microinjection of over 4000 cells. This paper also reports the use of the new robotic system to perform cell-cell communication studies using large sample sizes. The gap junction function in a cardiac muscle cell line (HL-1 cells), for the first time, was quantified with the system.
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Liu J, Siragam V, Chen J, Fridman MD, Hamilton RM, Sun Y. High-throughput measurement of gap junctional intercellular communication. Am J Physiol Heart Circ Physiol 2014; 306:H1708-13. [PMID: 24778169 DOI: 10.1152/ajpheart.00110.2014] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Gap junctional intercellular communication (GJIC) is a critical part of cellular activities and is necessary for electrical propagation among contacting cells. Disorders of gap junctions are a major cause for cardiac arrhythmias. Dye transfer through microinjection is a conventional technique for measuring GJIC. To overcome the limitations of manual microinjection and perform high-throughput GJIC measurement, here we present a new robotic microinjection system that is capable of injecting a large number of cells at a high speed. The highly automated system enables large-scale cell injection (thousands of cells vs. a few cells) without major operator training. GJIC of three cell lines of differing gap junction density, i.e., HeLa, HEK293, and HL-1, was evaluated. The effect of a GJIC inhibitor (18-α-glycyrrhetinic acid) was also quantified in the three cell lines. System operation speed, success rate, and cell viability rate were quantitatively evaluated based on robotic microinjection of over 4,000 cells. Injection speed was 22.7 cells per min, with 95% success for cell injection and >90% survival. Dye transfer cell counts and dye transfer distance correlated with the expected connexin expression of each cell type, and inhibition of dye transfer correlated with the concentration of GJIC inhibitor. Additionally, real-time monitoring of dye transfer enables the calculation of coefficients of molecular diffusion through gap junctions. This robotic microinjection dye transfer technique permits rapid assessment of gap junction function in confluent cell cultures.
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Affiliation(s)
- Jun Liu
- Advanced Micro and Nanosystems Laboratory, University of Toronto, Toronto, Ontario, Canada; and
| | - Vinayakumar Siragam
- Division of Cardiology, the Hospital of Sick Children, Toronto, Ontario, Canada
| | - Jun Chen
- Advanced Micro and Nanosystems Laboratory, University of Toronto, Toronto, Ontario, Canada; and
| | - Michael D Fridman
- Division of Cardiology, the Hospital of Sick Children, Toronto, Ontario, Canada
| | - Robert M Hamilton
- Division of Cardiology, the Hospital of Sick Children, Toronto, Ontario, Canada
| | - Yu Sun
- Advanced Micro and Nanosystems Laboratory, University of Toronto, Toronto, Ontario, Canada; and
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