Microscopy (Oxford, England)最新文献

Recent advancements in imaging technologies have enabled the acquisition of high-quality, voluminous, multidimensional image data. Among these, light-sheet microscopy stands out for its ability to capture dynamic biological processes over extended periods and across large volumes, owing to its exceptional three-dimensional resolution and minimal invasiveness. However, handling and analyzing these vast datasets present significant challenges. Current computing environments struggle with high storage and computational demands, while traditional analysis methods relying heavily on human intervention are proving inadequate. Consequently, there is a growing shift toward automated solutions using artificial intelligence (AI), encompassing machine learning (ML) and other approaches. Although these technologies show promise, their application in extensive light-sheet imaging data analysis remains limited. This review explores the potential of light-sheet microscopy to revolutionize the life sciences through advanced imaging, addresses the primary challenges in data handling and analysis and discusses potential solutions, including the integration of AI and ML technologies.

Three-dimensional (3D) reconstruction is time-consuming owing to segmentation work. We evaluated the accuracy of the artificial intelligence (AI)-based segmentation and tracking model SAM-Track for segmentation of anatomical or histological structures and explored the potential of AI to enhance research efficiency. Images [obtained via computed tomography (CT) and magnetic resonance imaging (MRI)], anatomical sections from a Visible Korean Human open resource, and serial histological section images of cadavers were obtained. Six structures in the CT, MRI, and anatomical sections and seven in the histological sections were segmented using SAM-Track and compared with manual segmentation by calculating the Dice similarity coefficient. Segmented images were then reconstructed three dimensionally. The average Dice scores of CT and MRI results varied (0.13-0.83); anatomical sections showed mostly good accuracy (0.31-0.82). Clear-edged structures, such as the femur and liver, had high scores (0.69-0.83). In contrast, soft tissue structures, such as the rectus femoris and stomach, had variable accuracy (0.38-0.82). Histological sections showed high accuracy, especially for well-delineated tissues, such as the tibia and pancreas (0.95, 0.90). However, the tracking of branching structures, such as arteries and veins, was less successful (0.72, 0.52). In 3D reconstruction, high Dice scores were associated with accurate shapes, whereas low scores indicated discrepancies between the predicted and true shapes. AI-based automatic segmentation using SAM-Track provides moderate-to-good accuracy for anatomical and histological structures and is beneficial for conducting morphological studies involving 3D reconstruction.

Optimum bright-field scanning transmission electron microscopy (OBF STEM) is a recently developed low-dose imaging technique that uses a segmented or pixelated detector. While we previously reported that OBF STEM with a segmented detector has a higher efficiency than conventional STEM techniques such as annular bright field (ABF), the imaging efficiency is expected to be further improved by using a pixelated detector. In this study, we adopted a pixelated detector for the OBF technique and investigated the imaging characteristics. Because OBF imaging is based on the thick weak phase object approximation (tWPOA), a non-zero crystalline sample thickness is considered in addition to the conventional WPOA, where the pixelated OBF method can be regarded as the theoretical extension of single side band (SSB) ptychography. Thus, we compared these two techniques via signal-to-noise ratio transfer functions (SNRTFs), multi-slice image simulations, and experiments, showing how the OBF technique can improve dose efficiency from the conventional WPOA-based ptychographic imaging.

Although modern scanning electron microscope (SEM) possesses several electron detectors, it is not clear what kind of information is contained in a SEM image taken by a certain detector. Specifically, the detectors installed in the objective lens are difficult to know their characters. Thus, we propose a simple method to assess the acceptance of electron detector using a stainless steel sphere. After taking images under certain conditions, say electron beam energy, working distance (WD), etc., the image intensity of each pixel point, which is characterized by coordinate (θ, φ), is evaluated. The advantage of this method is the ease of implementation and the whole information of electron emission from the tilted surfaces is contained in the image. Using this information, the acceptance of the detector can be analyzed systematically. In this paper, the traditional Everhart-Thornley (ET) detector is analyzed with this method. It is demonstrated how the sphere image changes according to the measurement condition. The ET image quality is strongly governed by WD but not so much by the electron beam energy. We propose an alternative method to avoid the ambiguity of WD. Using a needle-type specimen stage, the ET image does not vary so much with WD and the reliability of ET image significantly improves.

A simple method that improves the resolution of phase measurement in differential phase-contrast scanning transmission electron microscopy for closed-type environmental cell applications was developed and tested using a model sample simulating environmental cell observations. Because the top and bottom membranes of an environmental cell are typically far apart, the images from these membranes are shifted widely by tilt-series acquisition, and averaging the images after alignment can effectively eliminate undesired signals from the membranes while improving the signal from the object of interest. It was demonstrated that a phase precision of 2π/100 rad is well achievable using the proposed method for the sample in an environmental cell.

The direct observation of the morphological changes in silicon-based negative electrode (Si-based negative electrode) materials during battery charging and discharging is useful for handling such materials and in electrode plate design. We developed an operando scanning electron microscopy (operando SEM) technique to quantitatively evaluate the expansion and contraction of Si-based negative electrode materials. A small all-solid-state lithium-ion battery was charged and discharged, and the expansion/contraction of particles while harnessing capacity was observed using SEM. We found that in a silicon monosilicate (SiO)/graphite negative electrode, SiO expanded first during charging, and graphite contracted first during discharging. Our study provides insights into the relationship between capacity and expansion and contraction coefficient of Si-based negative electrode materials.

It is challenging to image structures in liquids for electron microscopy (EM); thus, low-temperature imaging has been developed, initially for aqueous systems. Organic liquids (OLs) are widely used as dispersants, although their cryogenic EM (cryo-EM) imaging is less common than that of aqueous systems. This is because the basic properties (e.g. vapor pressure, density and amorphousness) of OL in the solid state have not been extensively investigated, preventing the determination of whether the observed structure is free from artifacts. Herein, I summarized physical data related to the phase change, and the solid density at 77 K and sublimation speed for some OLs were measured independently to discuss the applicability of OLs for cryo-EM. Among various OL properties, the sublimation temperature, pressure and rate and crystallinity are important for cryo-EM. The sublimation-related properties are used to judge whether the OL is stable during storage, observation and sample preparation such as etching. These properties were calculated, and the calculated sublimation speed matched with that measured by cryogenic scanning EM movie imaging. Crystallinity was estimated using the difference between the extrapolated temperature-dependent liquid density and the solid density of frozen OLs measured in liquid nitrogen. Artifacts observed upon freezing were exemplified by focused ion beam cross-sections of OL-in-water emulsions, and cracks, voids and wrinkles are found in the OL phase at a large shrinkage ratio. The study findings show that the applicability of OLs largely differs for structural isomers and that appropriate OLs are required for the cryo-EM imaging of nonaqueous systems.

The anisotropic electronic structure of MgB2C2 was studied using soft X-ray emission spectroscopy electron microscopes. MgB2C2 fragments were selected by examining C K-emission profiles. C and B K-emission and Mg L-emission spectra were obtained, revealing common and distinct structures that reflect the mixing of valence orbitals. Since the material is reported to have two-dimensional B-C honeycomb layers, the orientational dependence of these emission spectra was also examined. Experimental data were compared with the theoretically calculated partial density of states of the valence bands (VBs) of the material. The C K-emission profile showed an apparent orientational dependence, while the B K-emission exhibited minimal dependence. This difference originated from the different energy distributions of C-2pz and B-2pz components in the VBs. The Mg L-emission intensity was very small, likely due to charge transfer from Mg atoms to B-N layers. The Mg L-emission profile showed a peak related to structures in C-K and B-K. An unexpected intensity was observed just above the VBs, which also showed orientational dependence, possibly due to a small deviation from the ideal composition of Mg:B:C = 1:2:2.