The structure analysis of amorphous materials still leaves much room for improvement. Owing to the lack of translational or rotational symmetry of amorphous materials, it is important to develop a different approach from that used for crystals for the structure analysis of amorphous materials. Here, the angstrom-beam electron diffraction method was used to obtain the local structure information of amorphous materials at a sub-nanometre scale. In addition, we discussed the relationship between the global and local diffraction intensities of amorphous structures, and verified the effectiveness of the proposed method through basic diffraction simulations. Finally, some applications of the proposed method to structural and functional amorphous materials are summarized.
{"title":"Local structure analysis of amorphous materials by angstrom-beam electron diffraction","authors":"Akihiko Hirata","doi":"10.1093/jmicro/dfaa075","DOIUrl":"10.1093/jmicro/dfaa075","url":null,"abstract":"The structure analysis of amorphous materials still leaves much room for improvement. Owing to the lack of translational or rotational symmetry of amorphous materials, it is important to develop a different approach from that used for crystals for the structure analysis of amorphous materials. Here, the angstrom-beam electron diffraction method was used to obtain the local structure information of amorphous materials at a sub-nanometre scale. In addition, we discussed the relationship between the global and local diffraction intensities of amorphous structures, and verified the effectiveness of the proposed method through basic diffraction simulations. Finally, some applications of the proposed method to structural and functional amorphous materials are summarized.","PeriodicalId":18515,"journal":{"name":"Microscopy","volume":"70 1","pages":"171-177"},"PeriodicalIF":1.8,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/jmicro/dfaa075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38723444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Phase-shifting electron holography (PS-EH) is an interference transmission electron microscopy technique that accurately visualizes potential distributions in functional materials, such as semiconductors. In this paper, we briefly introduce the features of the PS-EH that overcome some of the issues facing the conventional EH based on Fourier transformation. Then, we present a high-precision PS-EH technique with multiple electron biprisms and a sample preparation technique using a cryo-focused-ion-beam, which are important techniques for the accurate phase measurement of semiconductors. We present several applications of PS-EH to demonstrate the potential in organic and inorganic semiconductors and then discuss the differences by comparing them with previous reports on the conventional EH. We show that in situ biasing PS-EH was able to observe not only electric potential distribution but also electric field and charge density at a GaAs p–n junction and clarify how local band structures, depletion layer widths and space charges changed depending on the biasing conditions. Moreover, the PS-EH clearly visualized the local potential distributions of two-dimensional electron gas layers formed at AlGaN/GaN interfaces with different Al compositions. We also report the results of our PS-EH application for organic electroluminescence multilayers and point out the significant potential changes in the layers. The proposed PS-EH enables more precise phase measurement compared to the conventional EH, and our findings introduced in this paper will contribute to the future research and development of high-performance semiconductor materials and devices.
{"title":"Phase-shifting electron holography for accurate measurement of potential distributions in organic and inorganic semiconductors","authors":"Kazuo Yamamoto;Satoshi Anada;Takeshi Sato;Noriyuki Yoshimoto;Tsukasa Hirayama","doi":"10.1093/jmicro/dfaa061","DOIUrl":"10.1093/jmicro/dfaa061","url":null,"abstract":"Phase-shifting electron holography (PS-EH) is an interference transmission electron microscopy technique that accurately visualizes potential distributions in functional materials, such as semiconductors. In this paper, we briefly introduce the features of the PS-EH that overcome some of the issues facing the conventional EH based on Fourier transformation. Then, we present a high-precision PS-EH technique with multiple electron biprisms and a sample preparation technique using a cryo-focused-ion-beam, which are important techniques for the accurate phase measurement of semiconductors. We present several applications of PS-EH to demonstrate the potential in organic and inorganic semiconductors and then discuss the differences by comparing them with previous reports on the conventional EH. We show that in situ biasing PS-EH was able to observe not only electric potential distribution but also electric field and charge density at a GaAs p–n junction and clarify how local band structures, depletion layer widths and space charges changed depending on the biasing conditions. Moreover, the PS-EH clearly visualized the local potential distributions of two-dimensional electron gas layers formed at AlGaN/GaN interfaces with different Al compositions. We also report the results of our PS-EH application for organic electroluminescence multilayers and point out the significant potential changes in the layers. The proposed PS-EH enables more precise phase measurement compared to the conventional EH, and our findings introduced in this paper will contribute to the future research and development of high-performance semiconductor materials and devices.","PeriodicalId":18515,"journal":{"name":"Microscopy","volume":"70 1","pages":"24-38"},"PeriodicalIF":1.8,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/jmicro/dfaa061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38482800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Differential-phase-contrast scanning transmission electron microscopy (DPC STEM) is a technique to directly visualize local electromagnetic field distribution inside materials and devices at very high spatial resolution. Owing to the recent progress in the development of high-speed segmented and pixelated detectors, DPC STEM now constitutes one of the major imaging modes in modern aberration-corrected STEM. While qualitative imaging of electromagnetic fields by DPC STEM is readily possible, quantitative imaging by DPC STEM is still under development because of the several fundamental issues inherent in the technique. In this report, we review the current status and future prospects of DPC STEM for quantitative electromagnetic field imaging from atomic scale to mesoscopic scale.
{"title":"Toward quantitative electromagnetic field imaging by differential-phase-contrast scanning transmission electron microscopy","authors":"Takehito Seki;Yuichi Ikuhara;Naoya Shibata","doi":"10.1093/jmicro/dfaa065","DOIUrl":"10.1093/jmicro/dfaa065","url":null,"abstract":"Differential-phase-contrast scanning transmission electron microscopy (DPC STEM) is a technique to directly visualize local electromagnetic field distribution inside materials and devices at very high spatial resolution. Owing to the recent progress in the development of high-speed segmented and pixelated detectors, DPC STEM now constitutes one of the major imaging modes in modern aberration-corrected STEM. While qualitative imaging of electromagnetic fields by DPC STEM is readily possible, quantitative imaging by DPC STEM is still under development because of the several fundamental issues inherent in the technique. In this report, we review the current status and future prospects of DPC STEM for quantitative electromagnetic field imaging from atomic scale to mesoscopic scale.","PeriodicalId":18515,"journal":{"name":"Microscopy","volume":"70 1","pages":"148-160"},"PeriodicalIF":1.8,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/jmicro/dfaa065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38576141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accurate assessment of three-dimensional (3D) characteristics, such as the shape and size distribution, of discrete elements (e.g. particles, granules, grains, voids, crystals, cells and fibers) is required in various fields. But generally, in practice, two-dimensional (2D) instead of 3D assessment is conducted due to limitations in time, cost or measurement technology (as in microscopic observation of discrete elements). In this study, experimental validation was conducted for a 2D–3D conversion method, developed in 2018, which estimates multiple 3D parameters based on 2D counterparts, using an x-ray computed tomography analysis of silica sand. Six 3D parameters (volume, surface area, long-axis length, sphericity and long/middle and long/short axis ratios) were successfully estimated based on five measured 2D parameters (sectional area, perimeter, long-axis length, circularity and long/short axis ratio). An experimental validation was conducted for a 2D–3D conversion method, which estimates multiple 3D parameters based on 2D counterparts, using X-ray computed tomography analysis of silica sand. Six 3D parameters (volume, surface area, long-axis length, sphericity, long/middle and long/short axis ratio) were successfully estimated based on measured 2D parameters.
{"title":"Experimental validation of a 2D–3D conversion method for estimation of multiple 3D characteristics of discrete elements","authors":"Takao Ueda","doi":"10.1093/jmicro/dfz112","DOIUrl":"10.1093/jmicro/dfz112","url":null,"abstract":"Accurate assessment of three-dimensional (3D) characteristics, such as the shape and size distribution, of discrete elements (e.g. particles, granules, grains, voids, crystals, cells and fibers) is required in various fields. But generally, in practice, two-dimensional (2D) instead of 3D assessment is conducted due to limitations in time, cost or measurement technology (as in microscopic observation of discrete elements). In this study, experimental validation was conducted for a 2D–3D conversion method, developed in 2018, which estimates multiple 3D parameters based on 2D counterparts, using an x-ray computed tomography analysis of silica sand. Six 3D parameters (volume, surface area, long-axis length, sphericity and long/middle and long/short axis ratios) were successfully estimated based on five measured 2D parameters (sectional area, perimeter, long-axis length, circularity and long/short axis ratio). An experimental validation was conducted for a 2D–3D conversion method, which estimates multiple 3D parameters based on 2D counterparts, using X-ray computed tomography analysis of silica sand. Six 3D parameters (volume, surface area, long-axis length, sphericity, long/middle and long/short axis ratio) were successfully estimated based on measured 2D parameters.","PeriodicalId":18515,"journal":{"name":"Microscopy","volume":"69 1","pages":"37-43"},"PeriodicalIF":1.8,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/jmicro/dfz112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37669470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cementocytes in cementum form a lacuna-canalicular network. However, the 3D ultrastructure and range of the cementocyte network are unclear. Here, the 3D ultrastructure of the cementocyte network at the interface between cementum and periodontal ligament (PDL) was investigated on the mesoscale using FIB/SEM tomography. The results revealed a cellular network of cementocytes and PDL cells. A previous histomorphological study revealed the osteocyte-osteoblast-PDL cellular network. We extended this knowledge and revealed the cementum-PDL-bone cellular network, which may orchestrate the remodeling and modification of periodontal tissue, using a suitable method for imaging of complex tissue. The 3D ultrastructure of the cementocyte architecture around the interface between cementum and periodontal ligament (PDL) was investigated using FIB/SEM tomography. As a result, we showed a cellular interconnection between cementocytes and PDL cells and revealed the cementum-PDL-bone cellular network, extending our previous morphological discovery of the osteocyte-osteoblast-PDL cellular network.
{"title":"Cellular network across cementum and periodontal ligament elucidated by FIB/SEM tomography","authors":"Shingo Hirashima;Keisuke Ohta;Tomonoshin Kanazawa;Akinobu Togo;Risa Tsuneyoshi;Jingo Kusukawa;Kei-ichiro Nakamura","doi":"10.1093/jmicro/dfz117","DOIUrl":"10.1093/jmicro/dfz117","url":null,"abstract":"Cementocytes in cementum form a lacuna-canalicular network. However, the 3D ultrastructure and range of the cementocyte network are unclear. Here, the 3D ultrastructure of the cementocyte network at the interface between cementum and periodontal ligament (PDL) was investigated on the mesoscale using FIB/SEM tomography. The results revealed a cellular network of cementocytes and PDL cells. A previous histomorphological study revealed the osteocyte-osteoblast-PDL cellular network. We extended this knowledge and revealed the cementum-PDL-bone cellular network, which may orchestrate the remodeling and modification of periodontal tissue, using a suitable method for imaging of complex tissue. The 3D ultrastructure of the cementocyte architecture around the interface between cementum and periodontal ligament (PDL) was investigated using FIB/SEM tomography. As a result, we showed a cellular interconnection between cementocytes and PDL cells and revealed the cementum-PDL-bone cellular network, extending our previous morphological discovery of the osteocyte-osteoblast-PDL cellular network.","PeriodicalId":18515,"journal":{"name":"Microscopy","volume":"69 1","pages":"53-58"},"PeriodicalIF":1.8,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/jmicro/dfz117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37635747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The shape and orientation of second-phase precipitates in a Eu 2+ -doped equimolar KCl:KBr solid solution are reported in this paper as they were unveiled by epifluorescence microscopy. To make this, microscopy images of different optical cross sections of some precipitate fields and, also, of some representative precipitates in these fields, were recorded by using the Eu 2+ ion itself as a fluorochrome. From these images, the corresponding precipitate fields and individual precipitates were electronically reconstructed into the host lattice space. Previously, the KCl:KBr:Eu 2+ system was characterized by absorption and fluorescence optical spectrophotometry, to tailor properly the fluorescence mirror unit, as well as by powder and single-plate X-ray diffraction, to correlate the host lattice orientation with those of the observed precipitates. These are shaped as plates, with broad faces parallel to host lattice {100}, {110} or {120}planes (the {100}, {110} and {120} precipitates, respectively), and as rods, aligned with a host lattice ˂100> direction (the ˂100> precipitates). The {100}, {110}, {120}-precipitate broad faces are in the shapes of 72.6° rhomboids, rectangles and 59.5° rhomboids, with a side lying along host lattice <310>, <110> and <421> directions, respectively, and with another side lying along a <100> direction. A typical precipitate field and the spatial reconstructions of typical {100}, {110}, {120} and ˂100> precipitates, as well as their corresponding electronic 3D-geometrical models, are described in detail. It is discussed that four different europium precipitation states are responsible for the precipitation and that the precipitate lattices are spatially coherent with the host lattice. The shapes and spatial orientations, in relation to the matrix lattice, of europium second-phase precipitates in an equi-molar KCl:KBr solid solution host are studied for the fi rst time ever. This was performed by epifl uorescence optical microscopy by using the doping divalent europium ion as a fl uorochrome.
{"title":"Morphology and orientated growth of second-phase precipitates in a Eu2+-doped equimolar KCl:KBr solid solution: an epifluorescence microscopy study by using the doping ion as a fluorochrome","authors":"Adolfo Ernesto Cordero-Borboa;Rodrigo Unda-Angeles","doi":"10.1093/jmicro/dfz110","DOIUrl":"10.1093/jmicro/dfz110","url":null,"abstract":"The shape and orientation of second-phase precipitates in a Eu\u0000<sup>2+</sup>\u0000-doped equimolar KCl:KBr solid solution are reported in this paper as they were unveiled by epifluorescence microscopy. To make this, microscopy images of different optical cross sections of some precipitate fields and, also, of some representative precipitates in these fields, were recorded by using the Eu\u0000<sup>2+</sup>\u0000 ion itself as a fluorochrome. From these images, the corresponding precipitate fields and individual precipitates were electronically reconstructed into the host lattice space. Previously, the KCl:KBr:Eu\u0000<sup>2+</sup>\u0000 system was characterized by absorption and fluorescence optical spectrophotometry, to tailor properly the fluorescence mirror unit, as well as by powder and single-plate X-ray diffraction, to correlate the host lattice orientation with those of the observed precipitates. These are shaped as plates, with broad faces parallel to host lattice {100}, {110} or {120}planes (the {100}, {110} and {120} precipitates, respectively), and as rods, aligned with a host lattice ˂100> direction (the ˂100> precipitates). The {100}, {110}, {120}-precipitate broad faces are in the shapes of 72.6° rhomboids, rectangles and 59.5° rhomboids, with a side lying along host lattice <310>, <110> and <421> directions, respectively, and with another side lying along a <100> direction. A typical precipitate field and the spatial reconstructions of typical {100}, {110}, {120} and ˂100> precipitates, as well as their corresponding electronic 3D-geometrical models, are described in detail. It is discussed that four different europium precipitation states are responsible for the precipitation and that the precipitate lattices are spatially coherent with the host lattice. The shapes and spatial orientations, in relation to the matrix lattice, of europium second-phase precipitates in an equi-molar KCl:KBr solid solution host are studied for the fi rst time ever. This was performed by epifl uorescence optical microscopy by using the doping divalent europium ion as a fl uorochrome.","PeriodicalId":18515,"journal":{"name":"Microscopy","volume":"69 1","pages":"17-25"},"PeriodicalIF":1.8,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/jmicro/dfz110","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37576356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Materials characterization is indispensable for materials development. In particular, spectroscopy provides atomic configuration, chemical bonding and vibrational information, which are crucial for understanding the mechanism underlying the functions of a material. Despite its importance, the interpretation of spectra using human-driven methods, such as manual comparison of experimental spectra with reference/simulated spectra, is becoming difficult owing to the rapid increase in experimental spectral data. To overcome the limitations of such methods, we develop new data-driven approaches based on machine learning. Specifically, we use hierarchical clustering, a decision tree and a feedforward neural network to investigate the electron energy loss near edge structures (ELNES) spectrum, which is identical to the X-ray absorption near edge structure (XANES) spectrum. Hierarchical clustering and the decision tree are used to interpret and predict ELNES/XANES, while the feedforward neural network is used to obtain hidden information about the material structure and properties from the spectra. Further, we construct a prediction model that is robust against noise by data augmentation. Finally, we apply our method to noisy spectra and predict six properties accurately. In summary, the proposed approaches can pave the way for fast and accurate spectrum interpretation/prediction as well as local measurement of material functions.
{"title":"Machine learning approaches for ELNES/XANES","authors":"Teruyasu Mizoguchi;Shin Kiyohara","doi":"10.1093/jmicro/dfz109","DOIUrl":"10.1093/jmicro/dfz109","url":null,"abstract":"Materials characterization is indispensable for materials development. In particular, spectroscopy provides atomic configuration, chemical bonding and vibrational information, which are crucial for understanding the mechanism underlying the functions of a material. Despite its importance, the interpretation of spectra using human-driven methods, such as manual comparison of experimental spectra with reference/simulated spectra, is becoming difficult owing to the rapid increase in experimental spectral data. To overcome the limitations of such methods, we develop new data-driven approaches based on machine learning. Specifically, we use hierarchical clustering, a decision tree and a feedforward neural network to investigate the electron energy loss near edge structures (ELNES) spectrum, which is identical to the X-ray absorption near edge structure (XANES) spectrum. Hierarchical clustering and the decision tree are used to interpret and predict ELNES/XANES, while the feedforward neural network is used to obtain hidden information about the material structure and properties from the spectra. Further, we construct a prediction model that is robust against noise by data augmentation. Finally, we apply our method to noisy spectra and predict six properties accurately. In summary, the proposed approaches can pave the way for fast and accurate spectrum interpretation/prediction as well as local measurement of material functions.","PeriodicalId":18515,"journal":{"name":"Microscopy","volume":"69 1","pages":"92-109"},"PeriodicalIF":1.8,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/jmicro/dfz109","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37589132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Various protein-labeling methods based on the specific interactions between genetically encoded tags and synthetic probes have been proposed to complement fluorescent protein-based labeling. In particular, labeling methods based on enzyme reactions have been intensively developed by taking advantage of the highly specific interactions between enzymes and their substrates. In this approach, the peptides or proteins are genetically attached to the target proteins as a tag, and the various labels are then incorporated into the tags by enzyme reactions with the substrates carrying those labels. On the other hand, we have been developing an enzyme-based protein-labeling system distinct from the existing ones. In our system, the substrate protein is attached to the target proteins as a tag, and the labels are incorporated into the tag by post-translational modification with an enzyme carrying those labels followed by tight complexation between the enzyme and the substrate protein. In this review, I summarize the enzyme-based protein-labeling systems with a focus on several typical methods and then describe our labeling system based on tight complexation between the enzyme and the substrate protein.
{"title":"Enzyme-based protein-tagging systems for site-specific labeling of proteins in living cells","authors":"Shinji Sueda","doi":"10.1093/jmicro/dfaa011","DOIUrl":"10.1093/jmicro/dfaa011","url":null,"abstract":"Various protein-labeling methods based on the specific interactions between genetically encoded tags and synthetic probes have been proposed to complement fluorescent protein-based labeling. In particular, labeling methods based on enzyme reactions have been intensively developed by taking advantage of the highly specific interactions between enzymes and their substrates. In this approach, the peptides or proteins are genetically attached to the target proteins as a tag, and the various labels are then incorporated into the tags by enzyme reactions with the substrates carrying those labels. On the other hand, we have been developing an enzyme-based protein-labeling system distinct from the existing ones. In our system, the substrate protein is attached to the target proteins as a tag, and the labels are incorporated into the tag by post-translational modification with an enzyme carrying those labels followed by tight complexation between the enzyme and the substrate protein. In this review, I summarize the enzyme-based protein-labeling systems with a focus on several typical methods and then describe our labeling system based on tight complexation between the enzyme and the substrate protein.","PeriodicalId":18515,"journal":{"name":"Microscopy","volume":"69 1","pages":"156-166"},"PeriodicalIF":1.8,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/jmicro/dfaa011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37733667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Single-molecule imaging analysis has been applied to study the dynamics and kinetics of molecular behaviors and interactions in living cells. In spite of its high potential as a technique to investigate the molecular mechanisms of cellular phenomena, single-molecule imaging analysis has not been extended to a large scale of molecules in cells due to the low measurement throughput as well as required expertise. To overcome these problems, we have automated the imaging processes by using computer operations, robotics and artificial intelligence (AI). AI is an ideal substitute for expertise to obtain high-quality images for quantitative analysis. Our automated in-cell single-molecule imaging system, AiSIS, could analyze 1600 cells in 1 day, which corresponds to ∼ 100-fold higher efficiency than manual analysis. The large-scale analysis revealed cell-to-cell heterogeneity in the molecular behavior, which had not been recognized in previous studies. An analysis of the receptor behavior and downstream signaling was accomplished within a significantly reduced time frame and revealed the detailed activation scheme of signal transduction, advancing cell biology research. Furthermore, by combining the high-throughput analysis with our previous finding that a receptor changes its behavioral dynamics depending on the presence of a ligand/agonist or inhibitor/antagonist, we show that AiSIS is applicable to comprehensive pharmacological analysis such as drug screening. This AI-aided automation has wide applications for single-molecule analysis.
{"title":"Large-scale single-molecule imaging aided by artificial intelligence","authors":"Michio Hiroshima;Masato Yasui;Masahiro Ueda","doi":"10.1093/jmicro/dfz116","DOIUrl":"10.1093/jmicro/dfz116","url":null,"abstract":"Single-molecule imaging analysis has been applied to study the dynamics and kinetics of molecular behaviors and interactions in living cells. In spite of its high potential as a technique to investigate the molecular mechanisms of cellular phenomena, single-molecule imaging analysis has not been extended to a large scale of molecules in cells due to the low measurement throughput as well as required expertise. To overcome these problems, we have automated the imaging processes by using computer operations, robotics and artificial intelligence (AI). AI is an ideal substitute for expertise to obtain high-quality images for quantitative analysis. Our automated in-cell single-molecule imaging system, AiSIS, could analyze 1600 cells in 1 day, which corresponds to ∼ 100-fold higher efficiency than manual analysis. The large-scale analysis revealed cell-to-cell heterogeneity in the molecular behavior, which had not been recognized in previous studies. An analysis of the receptor behavior and downstream signaling was accomplished within a significantly reduced time frame and revealed the detailed activation scheme of signal transduction, advancing cell biology research. Furthermore, by combining the high-throughput analysis with our previous finding that a receptor changes its behavioral dynamics depending on the presence of a ligand/agonist or inhibitor/antagonist, we show that AiSIS is applicable to comprehensive pharmacological analysis such as drug screening. This AI-aided automation has wide applications for single-molecule analysis.","PeriodicalId":18515,"journal":{"name":"Microscopy","volume":"69 1","pages":"69-78"},"PeriodicalIF":1.8,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/jmicro/dfz116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37669469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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