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Huang Y, Zhang Y, Wu W, Wang Y, Qiu W, Zhang Z, Yu Y. Fast acoustic droplet ejection based on annular array transducer. ULTRASONICS 2024; 145:107448. [PMID: 39243532 DOI: 10.1016/j.ultras.2024.107448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 08/04/2024] [Accepted: 08/27/2024] [Indexed: 09/09/2024]
Abstract
Acoustic droplet ejection (ADE) has become the preferred method for liquid transfer in a variety of applications including synthetic biology, genotyping and drug discovery. Comparing with traditional pipetting techniques, the accuracy and data reproducibility of ADE based liquid transfer are improved, waste and cost are reduced, and cross-contamination is eliminated. The key component in the ADE system is the ultrasound transducer, which is responsible for generating focused ultrasound beam for droplet ejection. However, current ADE systems commonly utilize a single-element focused transducer with a fixed focal length that require mechanical movement to focus on the liquid surface, resulting in reduced liquid transfer efficiency. In this study, we first present a high-frequency annular array transducer for the ADE technology, which enables rapid and dynamic axial focusing to the liquid surface without mechanically moving the transducer, thereby accelerating liquid transfer. Experimental results show that the proposed 10 MHz, 5-element annular array transducer has good dynamic axial focusing ability, and can achieve accurate and stable droplet ejection of nanoliter volume at the designed focal length of 26-32 mm. Our results highlight the potential of the annular array transducer in advancing ADE system for rapid liquid transfer. This technology is expected to be useful in a variety of applications where precise and high-throughput liquid transfer is crucial.
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Affiliation(s)
- Youta Huang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 508055 China; The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen 518055, China; National-Reginoal Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China; Shenzhen Key Laboratory of Ultrasound Imaging and Therapy, Shenzhen 518055, China
| | - Yang Zhang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 508055 China; The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen 518055, China; School of Electrical Engineering, University of South China, Hengyang, China; Shenzhen Key Laboratory of Ultrasound Imaging and Therapy, Shenzhen 518055, China
| | - Weichang Wu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 508055 China; The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen Key Laboratory of Ultrasound Imaging and Therapy, Shenzhen 518055, China
| | - Yan Wang
- School of Electrical Engineering, University of South China, Hengyang, China
| | - Weibao Qiu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 508055 China; The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen Key Laboratory of Ultrasound Imaging and Therapy, Shenzhen 518055, China.
| | - Zhiqiang Zhang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 508055 China; The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen 518055, China; Shenzhen Key Laboratory of Ultrasound Imaging and Therapy, Shenzhen 518055, China.
| | - Yanyan Yu
- National-Reginoal Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China.
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Rimmer MA, Twarog NR, Li Y, Shelat AA, Rankovic Z, Yang L. A high-throughput quality control method for assessing the serial dilution performance of dose-response plates with acoustic ejection mass spectrometry. SLAS Technol 2024; 29:100115. [PMID: 37925158 DOI: 10.1016/j.slast.2023.10.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 09/26/2023] [Accepted: 10/31/2023] [Indexed: 11/06/2023]
Abstract
This study aimed to develop a streamlined method for evaluating the dilution ratio of drug dose-response plates created by automated liquid handlers in the early stages of drug discovery. The quantitative techniques commonly used for this purpose have restrictions due to their limited linear dynamic range and inaccuracies in assessing serial dilution performance. To address this challenge, we describe a method based on acoustic ejection mass spectrometry (AEMS). The method involves using standard compounds and an internal standard to evaluate each dilution point in quality control (QC) plates. The samples are transferred to a chromatography-free tandem mass spectrometry system through an acoustic source, enabling the analysis of one sample per three seconds from a microtiter plate. This approach provides precise, accurate, label-free, and rapid data acquisition to support high-throughput screening efforts.
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Affiliation(s)
- Mary Ashley Rimmer
- Analytical Technologies Center, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Nathaniel R Twarog
- Lead Discovery Informatics, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Yong Li
- Analytical Technologies Center, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Anang A Shelat
- Lead Discovery Informatics, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Zoran Rankovic
- Analytical Technologies Center, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN, United States.
| | - Lei Yang
- Analytical Technologies Center, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN, United States.
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Park CY, Yeon J, Song HJ, Kim YS, Nahm KB, Kim JD. Automated pipette failure monitoring using image processing for point-of-care testing devices. Biomed Eng Online 2018; 17:144. [PMID: 30396357 PMCID: PMC6219047 DOI: 10.1186/s12938-018-0578-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Background The accuracy and precision of liquid handling can be altered by several causes including wearing or failure of parts, and human error. The last cause is crucial since point-of-care testing (POCT) devices can be used by non-experienced users or patients themselves. Therefore it is important to improve the method of informing the users of POCT device malfunctions due to damage of parts or human error. Methods In this paper, image-based failure monitoring of the automated pipetting was introduced for POCT devices. An inexpensive, high-performance camera for smartphones was employed in our previous work to resolve various malfunctions such as incorrect insertion of the tip, false positioning of the tip and pump, and improper operation of the pump. The image acquired from the camera was analyzed to detect the malfunctions. In this paper, the reagent volume in the tip was estimated from the image processing to verify the pump operation. First, the color component corresponding to the reagent intrinsic color was extracted to identify the reagent area in the tip before applying the binary image processing. The extracted reagent area was projected horizontally and the support length of the projection image was calculated. As the support length was related to the reagent volume, it was referred to the volume length. The relationship between the measured volume length and the previously measured solution mass was investigated. If we can predict the mass of the solution by the volume length, we will be able to detect the pump malfunction. Results The cube of the volume length obtained by the proposed image processing method showed a very linear relationship with the reagent mass in the tip injected by the pumping operation (R2 = 0.996), indicating that the volume length could be utilized to estimate the reagent volume to monitor the accuracy and precision of the pumping operation. Conclusions An inexpensive smartphone camera was enough to detect various malfunctions of a POCT device with pumping operation. The proposed image processing could monitor the level of inaccuracy of pumping volume in limited range. The simple image processing such as a fixed threshold and projections was employed for the cost optimization and system robustness. However it delivered the promising results because the imaging condition was highly controllable in the devices.
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Affiliation(s)
- Chan-Young Park
- Department of Convergence Software, Hallym University, Chuncheon, South Korea.,Bio-IT Research Center, Hallym University, Chuncheon, South Korea
| | - Jun Yeon
- Department of Convergence Software, Hallym University, Chuncheon, South Korea.,Bio-IT Research Center, Hallym University, Chuncheon, South Korea
| | - Hye-Jeong Song
- Department of Convergence Software, Hallym University, Chuncheon, South Korea.,Bio-IT Research Center, Hallym University, Chuncheon, South Korea
| | - Yu-Seop Kim
- Department of Convergence Software, Hallym University, Chuncheon, South Korea.,Bio-IT Research Center, Hallym University, Chuncheon, South Korea
| | - Ki-Bong Nahm
- Department of Electron Physics, Hallym University, Chuncheon, South Korea
| | - Jong-Dae Kim
- Department of Convergence Software, Hallym University, Chuncheon, South Korea. .,Bio-IT Research Center, Hallym University, Chuncheon, South Korea.
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