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Rames M, Kenison JP, Heineck D, Civitci F, Szczepaniak M, Zheng T, Shangguan J, Zhang Y, Tao K, Esener S, Nan X. Multiplexed and Millimeter-Scale Fluorescence Nanoscopy of Cells and Tissue Sections via Prism-Illumination and Microfluidics-Enhanced DNA-PAINT. CHEMICAL & BIOMEDICAL IMAGING 2023; 1:817-830. [PMID: 38155726 PMCID: PMC10751790 DOI: 10.1021/cbmi.3c00060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/24/2023] [Accepted: 08/18/2023] [Indexed: 12/30/2023]
Abstract
Fluorescence nanoscopy has become increasingly powerful for biomedical research, but it has historically afforded a small field-of-view (FOV) of around 50 μm × 50 μm at once and more recently up to ∼200 μm × 200 μm. Efforts to further increase the FOV in fluorescence nanoscopy have thus far relied on the use of fabricated waveguide substrates, adding cost and sample constraints to the applications. Here we report PRism-Illumination and Microfluidics-Enhanced DNA-PAINT (PRIME-PAINT) for multiplexed fluorescence nanoscopy across millimeter-scale FOVs. Built upon the well-established prism-type total internal reflection microscopy, PRIME-PAINT achieves robust single-molecule localization with up to ∼520 μm × 520 μm single FOVs and 25-40 nm lateral resolutions. Through stitching, nanoscopic imaging over mm2 sample areas can be completed in as little as 40 min per target. An on-stage microfluidics chamber facilitates probe exchange for multiplexing and enhances image quality, particularly for formalin-fixed paraffin-embedded (FFPE) tissue sections. We demonstrate the utility of PRIME-PAINT by analyzing ∼106 caveolae structures in ∼1,000 cells and imaging entire pancreatic cancer lesions from patient tissue biopsies. By imaging from nanometers to millimeters with multiplexity and broad sample compatibility, PRIME-PAINT will be useful for building multiscale, Google-Earth-like views of biological systems.
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Affiliation(s)
- Matthew
J. Rames
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - John P. Kenison
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
| | - Daniel Heineck
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Fehmi Civitci
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
| | - Malwina Szczepaniak
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Ting Zheng
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
| | - Julia Shangguan
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Yujia Zhang
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Kai Tao
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Sadik Esener
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
| | - Xiaolin Nan
- Cancer
Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, 2720 South Moody Avenue, Portland, Oregon 97201, United States
- Program
in Quantitative and Systems Biology, Department of Biomedical Engineering, Oregon Health & Science University, 2730 South Moody Avenue, Portland, Oregon 97201, United States
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2
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Wei Y, Zhao M, He T, Chen N, Rao L, Chen L, Zhang Y, Yang Y, Yuan Q. Quantitatively Lighting up the Spatial Organization of CD47/SIRPα Immune Checkpoints on the Cellular Membrane with Single-Molecule Localization Microscopy. ACS NANO 2023; 17:21626-21638. [PMID: 37878521 DOI: 10.1021/acsnano.3c06709] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/27/2023]
Abstract
Immunotherapy including immune checkpoint inhibition has reinvigorated the current cancer treatment field. The development of efficient cancer immunotherapies depends on a thorough understanding of the status of immune checkpoints and how they interact. However, the distribution and spatial organization changes of immune checkpoints during their interactions at the single-molecule level remain difficult to directly visualize due to the lack of in situ imaging techniques with appropriate spatial and stoichiometric resolution. Herein, we report the direct visualization and quantification of the spatial distribution and organization of CD47 on the bladder tumor cell membrane and SIRPα on the macrophage membrane by using a single-molecule localization imaging technique called quantitative direct stochastic optical reconstruction microscopy (QdSTORM). Results showed that a portion of CD47 and SIRPα was present on cell membranes as heterogeneous clusters of varying sizes and densities prior to activation. Quantitative analyses of the reconstructed super-resolution images and theoretical simulation revealed that CD47 and SIRPα were reorganized into larger clusters upon binding to each other. Furthermore, we found that blocking the immune checkpoint interaction with small-molecule inhibitors or antibodies significantly impacted the spatial clustering behavior of CD47 on bladder tumor cells, demonstrating the promise of our QdSTORM strategy in elucidating the molecular mechanisms underlying immunotherapy. This work offers a promising strategy to advance our understanding of immune checkpoint state and interactions while also contributing to the fields including signal regulation and cancer therapy.
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Affiliation(s)
- Yurong Wei
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers of Ministry of Education, Institute of Molecular Medicine, Renmin Hospital of Wuhan University, School of Microelectronics, Wuhan University, Wuhan 430072, P. R. China
| | - Min Zhao
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers of Ministry of Education, Institute of Molecular Medicine, Renmin Hospital of Wuhan University, School of Microelectronics, Wuhan University, Wuhan 430072, P. R. China
| | - Tianpei He
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers of Ministry of Education, Institute of Molecular Medicine, Renmin Hospital of Wuhan University, School of Microelectronics, Wuhan University, Wuhan 430072, P. R. China
| | - Na Chen
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers of Ministry of Education, Institute of Molecular Medicine, Renmin Hospital of Wuhan University, School of Microelectronics, Wuhan University, Wuhan 430072, P. R. China
| | - Li Rao
- Hubei International Scientific and Technological Cooperation Base of Pesticide and Green Synthesis, Key Laboratory of Pesticide & Chemical Biology of Ministry of Education, College of Chemistry, Central China Normal University, Wuhan 430079, P. R. China
| | - Long Chen
- Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau 999078, P. R. China
| | - Yun Zhang
- CAS Key Laboratory of Design and Assembly of Functional Nanostructures, and Fujian Provincial Key Laboratory of Nanomaterials, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350025, P. R. China
| | - Yanbing Yang
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers of Ministry of Education, Institute of Molecular Medicine, Renmin Hospital of Wuhan University, School of Microelectronics, Wuhan University, Wuhan 430072, P. R. China
| | - Quan Yuan
- College of Chemistry and Molecular Sciences, Key Laboratory of Biomedical Polymers of Ministry of Education, Institute of Molecular Medicine, Renmin Hospital of Wuhan University, School of Microelectronics, Wuhan University, Wuhan 430072, P. R. China
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3
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Zhou Z, Wu J, Wang Z, Huang ZL. Deep learning using a residual deconvolutional network enables real-time high-density single-molecule localization microscopy. BIOMEDICAL OPTICS EXPRESS 2023; 14:1833-1847. [PMID: 37078057 PMCID: PMC10110325 DOI: 10.1364/boe.484540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 03/03/2023] [Accepted: 03/17/2023] [Indexed: 05/03/2023]
Abstract
High-density localization based on deep learning is a very effective method to accelerate single molecule localization microscopy (SMLM). Compared with traditional high-density localization methods, deep learning-based methods enable a faster data processing speed and a higher localization accuracy. However, the reported high-density localization methods based on deep learning are still not fast enough to enable real time data processing for large batches of raw images, which is probably due to the heavy computational burden and computation complexity in the U-shape architecture used in these models. Here we propose a high-density localization method called FID-STORM, which is based on an improved residual deconvolutional network for the real-time processing of raw images. In FID-STORM, we use a residual network to extract the features directly from low-resolution raw images rather than the U-shape network from interpolated images. We also use a model fusion from TensorRT to further accelerate the inference of the model. In addition, we process the sum of the localization images directly on GPU to obtain an additional speed gain. Using simulated and experimental data, we verified that the FID-STORM method achieves a processing speed of 7.31 ms/frame at 256 × 256 pixels @ Nvidia RTX 2080 Ti graphic card, which is shorter than the typical exposure time of 10∼30 ms, thus enabling real-time data processing in high-density SMLM. Moreover, compared with a popular interpolated image-based method called Deep-STORM, FID-STORM enables a speed gain of ∼26 times, without loss of reconstruction accuracy. We also provided an ImageJ plugin for our new method.
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Affiliation(s)
- Zhiwei Zhou
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
| | - Junnan Wu
- Key laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
| | - Zhengxia Wang
- School of Computer Science and Technology, Hainan University, Haikou 570228, China
| | - Zhen-Li Huang
- Key laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
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Li M, Song Q, Xiao Y, Wu J, Kuang W, Zhang Y, Huang ZL. LuckyProfiler: an ImageJ plug-in capable of quantifying FWHM resolution easily and effectively for super-resolution images. BIOMEDICAL OPTICS EXPRESS 2022; 13:4310-4325. [PMID: 36032567 PMCID: PMC9408243 DOI: 10.1364/boe.462197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/09/2022] [Accepted: 07/12/2022] [Indexed: 06/15/2023]
Abstract
Quantifying the resolution of a super-resolution image is vital for biologists trying to apply super-resolution microscopy in various research fields. Among the reported image resolution estimation methods, the one that calculates the full width at half maximum (FWHM) of line profile, called FWHM resolution, continues the traditional resolution criteria and has been popularly used by many researchers. However, quantifying the FWHM resolution of a super-resolution image is a time-consuming, labor-intensive, and error-prone process because this method typically involves a manual and careful selection of one or several of the smallest structures. In this paper, we investigate the influencing factors in FWHM resolution quantification systematically and present an ImageJ plug-in called LuckyProfiler for biologists so that they can have an easy and effective way of quantifying the FWHM resolution of super-resolution images.
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Affiliation(s)
- Mengting Li
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
| | - Qihang Song
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
| | - Yinghao Xiao
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
| | - Junnan Wu
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
| | - Weibing Kuang
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yingjun Zhang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
| | - Zhen-Li Huang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
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5
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Li M, Shang M, Li L, Wang Y, Song Q, Zhou Z, Kuang W, Zhang Y, Huang ZL. Real-time image resolution measurement for single molecule localization microscopy. OPTICS EXPRESS 2022; 30:28079-28090. [PMID: 36236964 DOI: 10.1364/oe.463996] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 07/05/2022] [Indexed: 06/16/2023]
Abstract
Recent advancements in single molecule localization microscopy (SMLM) have demonstrated outstanding potential applications in high-throughput and high-content screening imaging. One major limitation to such applications is to find a way to optimize imaging throughput without scarifying image quality, especially the homogeneity in image resolution, during the imaging of hundreds of field-of-views (FOVs) in heterogeneous samples. Here we introduce a real-time image resolution measurement method for SMLM to solve this problem. This method is under the heuristic framework of overall image resolution that counts on localization precision and localization density. Rather than estimating the mean localization density after completing the entire SMLM process, this method uses the spatial Poisson process to model the random activation of molecules and thus determines the localization density in real-time. We demonstrate that the method is valid in real-time resolution measurement and is effective in guaranteeing homogeneous image resolution across multiple representative FOVs with optimized imaging throughput.
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Gui D, Chen Y, Kuang W, Shang M, Zhang Y, Huang ZL. PCIe-based FPGA-GPU heterogeneous computation for real-time multi-emitter fitting in super-resolution localization microscopy. BIOMEDICAL OPTICS EXPRESS 2022; 13:3401-3415. [PMID: 35781968 PMCID: PMC9208611 DOI: 10.1364/boe.459198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 06/15/2023]
Abstract
Real-time multi-emitter fitting is a key technology for advancing super-resolution localization microscopy (SRLM), especially when it is necessary to achieve dynamic imaging quality control and/or optimization of experimental conditions. However, with the increase of activation densities, the requirements in the computing resources would increase rapidly due to the complexity of the fitting algorithms, making it difficult to realize real-time multi-emitter fitting for emitter density more than 0.6 mol/µm2 in large field of view (FOV), even after acceleration with the popular Graphics Processing Unit (GPU) computation. Here we adopt the task parallelism strategy in computer science to construct a Peripheral Component Interconnect Express (PCIe) based all-in-one heterogeneous computing platform (AIO-HCP), where the data between two major parallel computing hardware, Field Programmable Gate Array (FPGA) and GPU, are interacted directly and executed simultaneously. Using simulated and experimental data, we verify that AIO-HCP could achieve a data throughput of up to ∼ 1.561 GB/s between FPGA and GPU. With this new platform, we develop a multi-emitter fitting method, called AIO-STORM, under big data stream parallel scheduling. We show that AIO-STORM is capable of providing real-time image processing on raw images with 100 µm × 100 µm FOV, 10 ms exposure time and 5.5 mol/µm2 structure density, without scarifying image quality. This study overcomes the data throughput limitation of heterogeneous devices, demonstrates the power of the PCIe-based heterogeneous computation platform, and offers opportunities for multi-scale stitching of super-resolution images.
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Affiliation(s)
- Dan Gui
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
- School of Electronic Engineering, Wuhan Vocational College of Software and Engineering, Wuhan 430205, China
| | - Yunjiu Chen
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
| | - Weibing Kuang
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
| | - Mingtao Shang
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yingjun Zhang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
| | - Zhen-Li Huang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China
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Shang M, Huang ZL, Wang Y. Influence of drift correction precision on super-resolution localization microscopy. APPLIED OPTICS 2022; 61:3516-3522. [PMID: 36256388 DOI: 10.1364/ao.451561] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 03/24/2022] [Indexed: 06/16/2023]
Abstract
Super-resolution localization microscopy (SRLM) breaks the diffraction limit successfully and improves the resolution of optical imaging systems by nearly an order of magnitude. However, SRLM typically takes several minutes or longer to collect a sufficient number of image frames that are required for reconstructing a final super-resolution image. During this long image acquisition period, system drift should be tightly controlled to ensure the imaging quality; thus, several drift correction methods have been developed. However, it is still unclear whether the performance of these methods is able to ensure sufficient image quality in SRLM. Without a clear answer to this question, it is hard to choose a suitable drift correction method for a specific SRLM experiment. In this paper, we use both theoretical analysis and simulation to investigate the relationship among drift correction precision, localization precision, and position estimation precision. We propose a concept of relative localization precision for evaluating the effect of drift correction on imaging resolution, which would help to select an appropriate drift correction method for a specific experiment.
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Abstract
Blood cell analysis is essential for the diagnosis and identification of hematological malignancies. The use of digital microscopy systems has been extended in clinical laboratories. Super-resolution microscopy (SRM) has attracted wide attention in the medical field due to its nanoscale spatial resolution and high sensitivity. It is considered to be a potential method of blood cell analysis that may have more advantages than traditional approaches such as conventional optical microscopy and hematology analyzers in certain examination projects. In this review, we firstly summarize several common blood cell analysis technologies in the clinic, and analyze the advantages and disadvantages of these technologies. Then, we focus on the basic principles and characteristics of three representative SRM techniques, as well as the latest advances in these techniques for blood cell analysis. Finally, we discuss the developmental trend and possible research directions of SRM, and provide some discussions on further development of technologies for blood cell analysis.
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Dhiman S, Andrian T, Gonzalez BS, Tholen MME, Wang Y, Albertazzi L. Can super-resolution microscopy become a standard characterization technique for materials chemistry? Chem Sci 2022; 13:2152-2166. [PMID: 35310478 PMCID: PMC8864713 DOI: 10.1039/d1sc05506b] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/01/2021] [Indexed: 12/20/2022] Open
Abstract
The characterization of newly synthesized materials is a cornerstone of all chemistry and nanotechnology laboratories. For this purpose, a wide array of analytical techniques have been standardized and are used routinely by laboratories across the globe. With these methods we can understand the structure, dynamics and function of novel molecular architectures and their relations with the desired performance, guiding the development of the next generation of materials. Moreover, one of the challenges in materials chemistry is the lack of reproducibility due to improper publishing of the sample preparation protocol. In this context, the recent adoption of the reporting standard MIRIBEL (Minimum Information Reporting in Bio-Nano Experimental Literature) for material characterization and details of experimental protocols aims to provide complete, reproducible and reliable sample preparation for the scientific community. Thus, MIRIBEL should be immediately adopted in publications by scientific journals to overcome this challenge. Besides current standard spectroscopy and microscopy techniques, there is a constant development of novel technologies that aim to help chemists unveil the structure of complex materials. Among them super-resolution microscopy (SRM), an optical technique that bypasses the diffraction limit of light, has facilitated the study of synthetic materials with multicolor ability and minimal invasiveness at nanometric resolution. Although still in its infancy, the potential of SRM to unveil the structure, dynamics and function of complex synthetic architectures has been highlighted in pioneering reports during the last few years. Currently, SRM is a sophisticated technique with many challenges in sample preparation, data analysis, environmental control and automation, and moreover the instrumentation is still expensive. Therefore, SRM is currently limited to expert users and is not implemented in characterization routines. This perspective discusses the potential of SRM to transition from a niche technique to a standard routine method for material characterization. We propose a roadmap for the necessary developments required for this purpose based on a collaborative effort from scientists and engineers across disciplines.
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Affiliation(s)
- Shikha Dhiman
- Laboratory of Macromolecular and Organic Chemistry, Eindhoven University of Technology P. O. Box 513 5600 MB Eindhoven The Netherlands
- Institute for Complex Molecular Systems, Eindhoven University of Technology P. O. Box 513 5600 MB Eindhoven The Netherlands
| | - Teodora Andrian
- Institute of Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology Barcelona Spain
| | - Beatriz Santiago Gonzalez
- Department of Biomedical Engineering, Institute of Complex Molecular Systems, Eindhoven University of Technology Eindhoven The Netherlands
| | - Marrit M E Tholen
- Department of Biomedical Engineering, Institute of Complex Molecular Systems, Eindhoven University of Technology Eindhoven The Netherlands
| | - Yuyang Wang
- Institute for Complex Molecular Systems, Eindhoven University of Technology P. O. Box 513 5600 MB Eindhoven The Netherlands
- Department of Applied Physics, Eindhoven University of Technology Postbus 513 5600 MB Eindhoven The Netherlands
| | - Lorenzo Albertazzi
- Institute of Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology Barcelona Spain
- Department of Biomedical Engineering, Institute of Complex Molecular Systems, Eindhoven University of Technology Eindhoven The Netherlands
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Martens KJA, Turkowyd B, Endesfelder U. Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy. FRONTIERS IN BIOINFORMATICS 2022; 1:817254. [PMID: 36303761 PMCID: PMC9580916 DOI: 10.3389/fbinf.2021.817254] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 12/28/2021] [Indexed: 09/28/2023] Open
Abstract
Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (∼5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a "black box" for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.
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Affiliation(s)
- Koen J. A. Martens
- Department of Physics, Carnegie Mellon University, Pittsburgh, PA, United States
- Institute for Microbiology and Biotechnology, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Bartosz Turkowyd
- Department of Physics, Carnegie Mellon University, Pittsburgh, PA, United States
- Institute for Microbiology and Biotechnology, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
- Department of Systems and Synthetic Microbiology, Max Planck Institute for Terrestrial Microbiology, LOEWE Center for Synthetic Microbiology (SYNMIKRO), Marburg, Germany
| | - Ulrike Endesfelder
- Department of Physics, Carnegie Mellon University, Pittsburgh, PA, United States
- Institute for Microbiology and Biotechnology, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
- Department of Systems and Synthetic Microbiology, Max Planck Institute for Terrestrial Microbiology, LOEWE Center for Synthetic Microbiology (SYNMIKRO), Marburg, Germany
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11
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Kuang W, Xin B, Huang ZL, Shi B. A labeling strategy with effective preservation of fluorophores for expansion single-molecule localization microscopy (Ex-SMLM). Analyst 2021; 147:139-146. [PMID: 34859796 DOI: 10.1039/d1an01680f] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Expansion microscopy (ExM) significantly improves the resolution of conventional diffraction-limited optical microscopy by using physically expanding biological samples. Combining ExM with single-molecule localization microscopy (SMLM) could further enhance the resolving power of SMLM, which is typically in the order of 20-30 nm. However, to make this combination successful, we need to solve three key issues related to sample preparation, including mainly hydrogel shrinking in an ionic photoswitching buffer, fluorescence photobleaching due to a free-radical reaction and reduced labelling efficiency from protease digestion. Re-embedding polyacrylamide gel or using an improved photoswitching buffer with a low ionic strength is able to minimize or even solve the hydrogel shrinking problem, while the development of post-expansion labelling approaches avoids fluorescence bleaching. However, the preservation of protein epitopes (which determines the labelling efficiency) remains to be challenging. In this paper, we propose to tackle this challenge by introducing the highly selective and stable biotin-streptavidin interaction into the post-expansion labelling strategy. After upgrading the popular immunolabelling linkage scheme from Epitope-Primary antibody-Secondary antibody-Fluorophores to Epitope-Primary antibody-Secondary antibody-Biotin-Streptavidin-Fluorophores, we were able to label protein epitopes with biotin, which was stable during the expansion process, and thus avoid the troublesome problem in preserving protein epitopes or antibodies. We demonstrate that combining Ex-SMLM with the new post-expansion linkage scheme enables new possibilities in resolving the detailed arrangement of Nup133 proteins in the nuclear pore complex, which helps researchers to observe a clearer structure. This study provides new opportunities for studying the ultrastructural details of subcellular organelles or even biomacromolecules, using the conventional SMLM system.
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Affiliation(s)
- Weibing Kuang
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, China
| | - Bo Xin
- Wuhan Institute for Food and Cosmetic Control, Wuhan 430040, China
| | - Zhen-Li Huang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China.
| | - Bing Shi
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China.
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12
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State-of-the-Art Approaches for Image Deconvolution Problems, including Modern Deep Learning Architectures. MICROMACHINES 2021; 12:mi12121558. [PMID: 34945408 PMCID: PMC8707587 DOI: 10.3390/mi12121558] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/29/2021] [Accepted: 12/09/2021] [Indexed: 01/06/2023]
Abstract
In modern digital microscopy, deconvolution methods are widely used to eliminate a number of image defects and increase resolution. In this review, we have divided these methods into classical, deep learning-based, and optimization-based methods. The review describes the major architectures of neural networks, such as convolutional and generative adversarial networks, autoencoders, various forms of recurrent networks, and the attention mechanism used for the deconvolution problem. Special attention is paid to deep learning as the most powerful and flexible modern approach. The review describes the major architectures of neural networks used for the deconvolution problem. We describe the difficulties in their application, such as the discrepancy between the standard loss functions and the visual content and the heterogeneity of the images. Next, we examine how to deal with this by introducing new loss functions, multiscale learning, and prior knowledge of visual content. In conclusion, a review of promising directions and further development of deconvolution methods in microscopy is given.
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Gui D, Chen Y, Kuang W, Shang M, Wang Z, Huang ZL. Accelerating multi-emitter localization in super-resolution localization microscopy with FPGA-GPU cooperative computation. OPTICS EXPRESS 2021; 29:35247-35260. [PMID: 34808963 DOI: 10.1364/oe.439976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 10/03/2021] [Indexed: 06/13/2023]
Abstract
The real-time multi-emitter localization method is essential for advancing high-throughput super-resolution localization microscopy (HT-SRLM). In the past decade, the graphics processing unit (GPU) computation has been dominantly used to accelerate the execution speed of the multi-emitter localization method. However, if HT-SRLM is combined with a scientific complementary metal-oxide-semiconductor (sCMOS) camera working at full frame rate, real-time image processing is still difficult to achieve using this acceleration approach, thus resulting in a massive data storage challenge and even system crash. Here we take advantage of the cooperative acceleration power of field programming gate array (FPGA) computation and GPU computation, and propose a method called HCP-STORM to enable real-time multi-emitter localization. Using simulated images, we verified that HCP-STORM is capable of providing real-time image processing for raw images from a representative Hamamatsu Flash 4 V3 sCMOS camera working at full frame rate (that is, 2048×2048 pixels @ 10 ms exposure time). Using experimental images, we prove that HCP-STORM is 25 times faster than QC-STORM and 295 times faster than ThunderSTORM, with a small but acceptable degradation in image quality. This study shows the potential of FPGA-GPU cooperative computation in accelerating multi-emitter localization, and pushes a significant step toward the maturity of HT-SRLM technology.
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Shang M, Zhou Z, Kuang W, Wang Y, Xin B, Huang ZL. High-precision 3D drift correction with differential phase contrast images. OPTICS EXPRESS 2021; 29:34641-34655. [PMID: 34809249 DOI: 10.1364/oe.438160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 10/01/2021] [Indexed: 06/13/2023]
Abstract
Single molecule localization microscopy (SMLM) usually requires long image acquisition time at the order of minutes and thus suffers from sample drift, which deteriorates image quality. A drift estimation method with high precision is typically used in SMLM, which can be further combined with a drift compensation device to enable active microscope stabilization. Among all the reported methods, the drift estimation method based on bright-field image correlation requires no extra sample preparation or complicated modification to the imaging setup. However, the performance of this method is limited by the contrast of bright-field images, especially for the structures without sufficient features. In this paper, we proposed to use differential phase contrast (DPC) microscopy to enhance the image contrast and presented a 3D drift correction method with higher precision and robustness. This DPC-based drift correction method is suitable even for biological samples without clear morphological features. We demonstrated that this method can achieve a correction precision of < 6 nm in both the lateral direction and axial direction. Using SMLM imaging of microtubules, we verified that this method provides a comparable drift estimation performance as redundant cross-correlation.
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Estimating the dynamic range of quantitative single-molecule localization microscopy. Biophys J 2021; 120:3901-3910. [PMID: 34437847 DOI: 10.1016/j.bpj.2021.08.024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 08/09/2021] [Accepted: 08/19/2021] [Indexed: 01/01/2023] Open
Abstract
In recent years, there have been significant advances in quantifying molecule copy number and protein stoichiometry with single-molecule localization microscopy (SMLM). However, as the density of fluorophores per diffraction-limited spot increases, distinguishing between detection events from different fluorophores becomes progressively more difficult, affecting the accuracy of such measurements. Although essential to the design of quantitative experiments, the dynamic range of SMLM counting techniques has not yet been studied in detail. Here, we provide a working definition of the dynamic range for quantitative SMLM in terms of the relative number of missed localizations or blinks and explore the photophysical and experimental parameters that affect it. We begin with a simple two-state model of blinking fluorophores, then extend the model to incorporate photobleaching and temporal binning by the detection camera. From these models, we first show that our estimates of the dynamic range agree with realistic simulations of the photoswitching. We find that the dynamic range scales inversely with the duty cycle when counting both blinks and localizations. Finally, we validate our theoretical approach on direct stochastic optical reconstruction microscopy (dSTORM) data sets of photoswitching Alexa Fluor 647 dyes. Our results should help guide researchers in designing and implementing SMLM-based molecular counting experiments.
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Hauser F, Jacak J. Real-time 3D single-molecule localization microscopy analysis using lookup tables. BIOMEDICAL OPTICS EXPRESS 2021; 12:4955-4968. [PMID: 34513235 PMCID: PMC8407837 DOI: 10.1364/boe.424016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 06/14/2021] [Accepted: 06/20/2021] [Indexed: 05/11/2023]
Abstract
Herein, we present a new algorithm for real-time analysis of 3D single molecule localization microscopy images with a small impact on fitting accuracy using lookup-tables with discrete xyz-positions. The algorithm realizes real-time visualization during acquisition. We demonstrate its performance on simulated and measured data. Additionally, combining real-time fitting with a feedback loop controlling the activation laser pulse keeps the number of emitters per image frame constant.
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Affiliation(s)
- Fabian Hauser
- University of Applied Sciences, Upper Austria School of Medical Engineering and Applied Social Sciences, Garnisonstraße 21, 4020 Linz, Austria
- Austrian Cluster for Tissue Regeneration, Vienna 1200, Austria
| | - Jaroslaw Jacak
- University of Applied Sciences, Upper Austria School of Medical Engineering and Applied Social Sciences, Garnisonstraße 21, 4020 Linz, Austria
- Austrian Cluster for Tissue Regeneration, Vienna 1200, Austria
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Xu J, Liu Y. Probing Chromatin Compaction and Its Epigenetic States in situ With Single-Molecule Localization-Based Super-Resolution Microscopy. Front Cell Dev Biol 2021; 9:653077. [PMID: 34178982 PMCID: PMC8222792 DOI: 10.3389/fcell.2021.653077] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 05/18/2021] [Indexed: 11/13/2022] Open
Abstract
Chromatin organization play a vital role in gene regulation and genome maintenance in normal biological processes and in response to environmental insults. Disruption of chromatin organization imposes a significant effect on many cellular processes and is often associated with a range of pathological processes such as aging and cancer. Extensive attention has been attracted to understand the structural and functional studies of chromatin architecture. Biochemical assays coupled with the state-of-the-art genomic technologies have been traditionally used to probe chromatin architecture. Recent advances in single molecule localization microscopy (SMLM) open up new opportunities to directly visualize higher-order chromatin architecture, its compaction status and its functional states at nanometer resolution in the intact cells or tissue. In this review, we will first discuss the recent technical advantages and challenges of using SMLM to image chromatin architecture. Next, we will focus on the recent applications of SMLM for structural and functional studies to probe chromatin architecture in key cellular processes. Finally, we will provide our perspectives on the recent development and potential applications of super-resolution imaging of chromatin architecture in improving our understanding in diseases.
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Affiliation(s)
- Jianquan Xu
- Biomedical Optical Imaging Laboratory, Department of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Yang Liu
- Biomedical Optical Imaging Laboratory, Department of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- University of Pittsburgh Hillman Cancer Center, Pittsburgh, PA, United States
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Kubalová I, Němečková A, Weisshart K, Hřibová E, Schubert V. Comparing Super-Resolution Microscopy Techniques to Analyze Chromosomes. Int J Mol Sci 2021; 22:ijms22041903. [PMID: 33672992 PMCID: PMC7917581 DOI: 10.3390/ijms22041903] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/04/2021] [Accepted: 02/10/2021] [Indexed: 12/21/2022] Open
Abstract
The importance of fluorescence light microscopy for understanding cellular and sub-cellular structures and functions is undeniable. However, the resolution is limited by light diffraction (~200–250 nm laterally, ~500–700 nm axially). Meanwhile, super-resolution microscopy, such as structured illumination microscopy (SIM), is being applied more and more to overcome this restriction. Instead, super-resolution by stimulated emission depletion (STED) microscopy achieving a resolution of ~50 nm laterally and ~130 nm axially has not yet frequently been applied in plant cell research due to the required specific sample preparation and stable dye staining. Single-molecule localization microscopy (SMLM) including photoactivated localization microscopy (PALM) has not yet been widely used, although this nanoscopic technique allows even the detection of single molecules. In this study, we compared protein imaging within metaphase chromosomes of barley via conventional wide-field and confocal microscopy, and the sub-diffraction methods SIM, STED, and SMLM. The chromosomes were labeled by DAPI (4′,6-diamidino-2-phenylindol), a DNA-specific dye, and with antibodies against topoisomerase IIα (Topo II), a protein important for correct chromatin condensation. Compared to the diffraction-limited methods, the combination of the three different super-resolution imaging techniques delivered tremendous additional insights into the plant chromosome architecture through the achieved increased resolution.
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Affiliation(s)
- Ivona Kubalová
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, D-06466 Seeland, Germany;
| | - Alžběta Němečková
- Centre of the Region Hana for Biotechnological and Agricultural Research, Institute of Experimental Botany of the Czech Academy of Sciences, 77900 Olomouc, Czech Republic; (A.N.); (E.H.)
| | | | - Eva Hřibová
- Centre of the Region Hana for Biotechnological and Agricultural Research, Institute of Experimental Botany of the Czech Academy of Sciences, 77900 Olomouc, Czech Republic; (A.N.); (E.H.)
| | - Veit Schubert
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, D-06466 Seeland, Germany;
- Correspondence: ; Tel.: +49-394-825-212
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Möckl L, Moerner WE. Super-resolution Microscopy with Single Molecules in Biology and Beyond-Essentials, Current Trends, and Future Challenges. J Am Chem Soc 2020; 142:17828-17844. [PMID: 33034452 PMCID: PMC7582613 DOI: 10.1021/jacs.0c08178] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Indexed: 12/31/2022]
Abstract
Single-molecule super-resolution microscopy has developed from a specialized technique into one of the most versatile and powerful imaging methods of the nanoscale over the past two decades. In this perspective, we provide a brief overview of the historical development of the field, the fundamental concepts, the methodology required to obtain maximum quantitative information, and the current state of the art. Then, we will discuss emerging perspectives and areas where innovation and further improvement are needed. Despite the tremendous progress, the full potential of single-molecule super-resolution microscopy is yet to be realized, which will be enabled by the research ahead of us.
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Affiliation(s)
- Leonhard Möckl
- Department of Chemistry, Stanford University, Stanford, California 94305, United States
| | - W. E. Moerner
- Department of Chemistry, Stanford University, Stanford, California 94305, United States
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Sun Y. Potential quality improvement of stochastic optical localization nanoscopy images obtained by frame by frame localization algorithms. Sci Rep 2020; 10:11844. [PMID: 32678167 PMCID: PMC7367355 DOI: 10.1038/s41598-020-68564-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 06/26/2020] [Indexed: 12/28/2022] Open
Abstract
A data movie of stochastic optical localization nanoscopy contains spatial and temporal correlations, both providing information of emitter locations. The majority of localization algorithms in the literature estimate emitter locations by frame-by-frame localization (FFL), which exploit only the spatial correlation and leave the temporal correlation into the FFL nanoscopy images. The temporal correlation contained in the FFL images, if exploited, can improve the localization accuracy and the image quality. In this paper, we analyze the properties of the FFL images in terms of root mean square minimum distance (RMSMD) and root mean square error (RMSE). It is shown that RMSMD and RMSE can be potentially reduced by a maximum fold equal to the square root of the average number of activations per emitter. Analyzed and revealed are also several statistical properties of RMSMD and RMSE and their relationship with respect to a large number of data frames, bias and variance of localization errors, small localization errors, sample drift, and the worst FFL image. Numerical examples are taken and the results confirm the prediction of analysis. The ideas about how to develop an algorithm to exploit the temporal correlation of FFL images are also briefly discussed. The results suggest development of two kinds of localization algorithms: the algorithms that can exploit the temporal correlation of FFL images and the unbiased localization algorithms.
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Affiliation(s)
- Yi Sun
- Electrical Engineering Department, Nanoscopy Laboratory, The City College of City University of New York, New York, NY, 10031, USA.
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