{"title":"Role of lipids in the organization of tight junction.","authors":"Junichi Ikenouchi, Kenta Shigetomi","doi":"10.1093/jmicro/dfae039","DOIUrl":"10.1093/jmicro/dfae039","url":null,"abstract":"<p><p>Cell membrane structures are supramolecular complexes that require the ordered assembly of membrane proteins and lipids. The morphology of various cell adhesion structures in multicellular organisms, such as those between epithelial cells, neural synapses and immune synapses, was initially described through electron microscopic analyses. Subsequent studies aimed to catalog their constituent proteins, which encompass transmembrane cell adhesion molecules, cytoskeletal proteins and scaffolding proteins that bind the two components. However, the diversity of plasma membrane lipids and their significance in the organization of cell adhesion structures were underappreciated until recently. It is now understood that phase separation of lipids and liquid-liquid phase separation of proteins are important driving forces for such self-assembly. In this review, we summarized recent findings on the role of lipids as scaffolds for supramolecular complexes using tight junctions in epithelial cells as an example.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":"457-462"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142057513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Visualization of Bacillus subtilis spore structure and germination using quick-freeze deep-etch electron microscopy.","authors":"Kiran Jalil, Yuhei O Tahara, Makoto Miyata","doi":"10.1093/jmicro/dfae023","DOIUrl":"10.1093/jmicro/dfae023","url":null,"abstract":"<p><p>Bacterial spores, known for their complex and resilient structures, have been the focus of visualization using various methodologies. In this study, we applied quick-freeze and replica electron microscopy techniques, allowing observation of Bacillus subtilis spores in high-contrast and three-dimensional detail. This method facilitated visualization of the spore structure with enhanced resolution and provided new insights into the spores and their germination processes. We identified and described five distinct structures: (i) hair-like structures on the spore surface, (ii) spike formation on the surface of lysozyme-treated spores, (iii) the fractured appearance of the spore cortex during germination, (iv) potential connections between small vesicles and the core membrane and (v) the evolving surface structure of nascent vegetative cells during germination.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":"463-472"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11630275/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141180766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Correction to: Observation and quantitative analysis of dislocations in steel using electron channeling contrast imaging method with precise control of electron beam incident direction.","authors":"","doi":"10.1093/jmicro/dfae037","DOIUrl":"10.1093/jmicro/dfae037","url":null,"abstract":"","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":"523"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11630296/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142047619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bayesian inference of atomic column positions in scanning transmission electron microscopy images.","authors":"Yuki Nomura, Satoshi Anada, Shunsuke Kobayashi","doi":"10.1093/jmicro/dfae025","DOIUrl":"10.1093/jmicro/dfae025","url":null,"abstract":"<p><p>Atomic-resolution scanning transmission electron microscopy combined with two-dimensional Gaussian fitting enables the accurate and precise identification of atomic column positions within a few picometers. The measurement performance significantly depends on the signal-to-noise ratio of the atomic columns. In areas with low signal-to-noise ratios, such as near surfaces, the measurement performance was lower than that of the bulk. However, previous studies evaluated the accuracy and precision only in bulk areas, underscoring the need for a method that quantitatively evaluates the accuracy and precision of each atomic column position with various signal-to-noise ratios. This study introduced Bayesian inference to assess the accuracy and precision of determining individual atomic column positions under various signals. We applied this method to simulated and experimental images and demonstrated its effectiveness in identifying statistically significant displacements, particularly near surfaces with signal degradation. The use of vector maps and kernel density estimate plots obtained from Bayesian inference provided a probabilistic understanding of the atom displacement. Therefore, this study highlighted the potential benefits of Bayesian inference in high-resolution imaging to reveal material properties.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":"481-487"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140900800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development of silicon-on-insulator direct electron detector with analog memories in pixels for sub-microsecond imaging.","authors":"Takafumi Ishida, Kosei Sugie, Toshinobu Miyoshi, Yuichi Ishida, Koh Saitoh, Yasuo Arai, Makoto Kuwahara","doi":"10.1093/jmicro/dfae029","DOIUrl":"10.1093/jmicro/dfae029","url":null,"abstract":"<p><p>We have developed a high-speed recordable direct electron detector based on silicon-on-insulator technology. The detector has 16 analog memories in each pixel to record 16 images with sub-microsecond temporal resolution. A dedicated data acquisition system has also been developed to display and record the results on a personal computer. The performance of the direct electron detector as an image sensor is evaluated under electron irradiation with an energy of 30 keV in a low-voltage transmission electron microscope equipped with a photocathode electron gun. We demonstrate that the detector can record images at an exposure time of 100 ns and an interval of 900 ns.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":"511-516"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11630314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141187161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sandwich freezing and freeze substitution of Arabidopsis plant tissues for electron microscopy.","authors":"Masashi Yamaguchi, Mayuko Sato, Azusa Takahashi-Nakaguchi, Michiyo Okamoto, Kiminori Toyooka, Hiroji Chibana","doi":"10.1093/jmicro/dfae032","DOIUrl":"10.1093/jmicro/dfae032","url":null,"abstract":"<p><p>Sandwich freezing is a method of rapid freezing by sandwiching specimens between two copper disks, and it has been used for observing exquisite close-to-native ultrastructure of living yeast and bacteria. Recently, this method has been found to be useful for preserving cell images of glutaraldehyde-fixed cultured cells, as well as animal and human tissues. In the present study, this method was applied to observe the fine structure of living Arabidopsis plant tissues and was found to achieve excellent ultrastructural preservation of cells and tissues. This is the first report of applying the sandwich freezing method to observe plant tissues.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":"517-522"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141728400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fast computational approach with prior dimension reduction for three-dimensional chemical component analysis using CT data of spectral imaging.","authors":"Motoki Shiga, Taisuke Ono, Kenichi Morishita, Keiji Kuno, Nanase Moriguchi","doi":"10.1093/jmicro/dfae027","DOIUrl":"10.1093/jmicro/dfae027","url":null,"abstract":"<p><p>Spectral image (SI) measurement techniques, such as X-ray absorption fine structure (XAFS) imaging and scanning transmission electron microscopy (STEM) with energy-dispersive X-ray spectroscopy (EDS) or electron energy loss spectroscopy (EELS), are useful for identifying chemical structures in composite materials. Machine-learning techniques have been developed for automatic analysis of SI data and their usefulness has been proven. Recently, an extended measurement technique combining SI with a computed tomography (CT) technique (CT-SI), such as CT-XAFS and STEM-EDS/EELS tomography, was developed to identify the three-dimensional (3D) structures of chemical components. CT-SI analysis can be conducted by combining CT reconstruction algorithms and chemical component analysis based on machine-learning techniques. However, this analysis incurs high-computational costs owing to the size of the CT-SI datasets. To address this problem, this study proposed a fast computational approach for 3D chemical component analysis in an unsupervised learning setting. The primary idea for reducing the computational cost involved compressing the CT-SI data prior to CT computation and performing 3D reconstruction and chemical component analysis on the compressed data. The proposed approach significantly reduced the computational cost without losing information about the 3D structure and chemical components. We experimentally evaluated the proposed approach using synthetic and real CT-XAFS data, which demonstrated that our approach achieved a significantly faster computational speed than the conventional approach while maintaining analysis performance. As the proposed procedure can be implemented with any CT algorithm, it is expected to accelerate 3D analyses with sparse regularized CT algorithms in noisy and sparse CT-SI datasets.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":"488-498"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140961075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Wire-tracking of bent electric cable using X-ray CT and deep active learning.","authors":"Yutaka Hoshina, Takuma Yamamoto, Shigeaki Uemura","doi":"10.1093/jmicro/dfae028","DOIUrl":"10.1093/jmicro/dfae028","url":null,"abstract":"<p><p>We have demonstrated a quantification of all component wires in a bent electric cable, which is necessary for discussion of cable products in actual use cases. Quantification became possible for the first time because of our new technologies for image analysis of bent cables. In this paper, various image analysis techniques to detect all wire tracks in a bent cable are demonstrated. Unique cross-sectional image construction and deep active learning schemes are the most important items in this study. These methods allow us to know the actual state of cables under external loads, which makes it possible to elucidate the mechanisms of various phenomena related to cables in the field and further improve the quality of cable products.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":"499-510"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141097016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recent advancement and human tissue applications of volume electron microscopy.","authors":"Makoto Abe, Nobuhiko Ohno","doi":"10.1093/jmicro/dfae047","DOIUrl":"https://doi.org/10.1093/jmicro/dfae047","url":null,"abstract":"<p><p>Structural observations are essential for the advancement of life science. Volume electron microscopy has recently realized remarkable progress in the three-dimensional analyses of biological specimens for elucidating complex ultrastructures in several fields of life science. The advancements in volume electron microscopy technologies have led to improvements, including higher resolution, more stability, and the ability to handle larger volumes. Although human applications of volume electron microscopy remain limited, the reported applications in various organs have already provided previously unrecognized features of human tissues and also novel insights of human diseases. Simultaneously, the application of volume electron microscopy to human studies faces challenges, including ethical and clinical hurdles, costs of data storage and analysis, and efficient and automated imaging methods for larger volume. Solutions including the use of residual clinical specimens and data analysis based on artificial intelligence would address those issues and establish the role of volume electron microscopy in human structural research. Future advancements in volume electron microscopy are anticipated to lead to transformative discoveries in basic research and clinical practice, deepening our understanding of human health and diseases for better diagnostic and therapeutic strategies.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Masami Terauchi, Yohei K Sato, Takaomi D Yokoyama, Takanori Murano
{"title":"Simple derivation of L-absorption spectra of 3d transition metal elements by the self-absorption effect observed in soft X-ray emission spectra.","authors":"Masami Terauchi, Yohei K Sato, Takaomi D Yokoyama, Takanori Murano","doi":"10.1093/jmicro/dfae012","DOIUrl":"10.1093/jmicro/dfae012","url":null,"abstract":"<p><p>This study proposes a simple evaluation method for deriving L-absorption information from two L-emission spectra of 3d transition metal (TM) elements obtained at two different accelerating voltages. This method realizes a spatial identity for X-ray emission and absorption spectroscopies. This method was evaluated for the Fe L-emission spectra of Fe and its oxides and was applied to the TM L-emission spectra of MnO, Co, CoO and NiO. The derived absorption peak positions were consistent with those obtained previously at synchrotron orbital radiation facilities, which considered the core-hole effect. This simple derivation method could be useful for obtaining X-ray absorption spectroscopy distribution images from X-ray emission spectroscopy mapping data obtained by scanning electron microscopy.</p>","PeriodicalId":74193,"journal":{"name":"Microscopy (Oxford, England)","volume":" ","pages":"451-455"},"PeriodicalIF":0.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140029725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}