Microscopy (Oxford, England)最新文献

Glucose is the most important energy source in all organisms; however, our understanding of the pathways and mechanisms underlying glucose transportation and localization in living cells is incomplete. Here, we prepared two glucose analogs labeled with a dansylamino group at the C-1 (1-Dansyl) or C-2 (2-Dansyl) position; the dansyl group is a highly fluorescent moiety that is characterized by a large Stokes shift between its excitation and emission wavelengths. We then examined the cytotoxicity of the two glucose analogs in mammalian fibroblast cells and in the ciliated protozoan Tetrahymena thermophila. In both cell types, 2-Dansyl had no negative effects on cell growth. The specificity of cellular uptake of glucose analogs was confirmed using an inhibitor of glucose transporter in NIH3T3 cells. In NIH3T3 cells and T. thermophila, fluorescence microscopy revealed that the glucose analogs localized throughout the cytoplasm, but especially at the periphery of the nucleus. In T. thermophila, we also found that swimming speed was comparable in media containing non-labeled glucose or one of the glucose analogs, which provided more evidence not only that the analogs were not cytotoxic in these cells but also that the analogs had no negative effect on the ciliary motion. Together, the present results suggest that the glucose analogs have low toxicity and will be useful for bioimaging of glucose-related systems.

Perovskite oxides, ABO3, are potential catalysts for the oxygen evolution reaction, which is important in the production of hydrogen as a sustainable energy resource. Optimizing the chemical composition of such oxides by substitution or doping with additional elements is an effective approach to improving the activity of such catalysts. Here, we characterized the crystal and electronic structures of fluorine-doped La0.5Sr0.5CoO3-δ particles using scanning transmission electron microscopy (STEM) and electron energy-loss spectroscopy (EELS). High-resolution STEM imaging demonstrated the formation of a disordered surface phase caused by fluorine doping. In addition, spatially resolved EELS data showed that fluorine anions were introduced into the interiors of the particles and that Co ions near the surfaces were slightly reduced by fluorine doping in conjunction with the loss of oxygen ions. Peak fitting of energy-loss near-edge structure data demonstrated an unexpected nanostructure in the vicinity of the surface. An EELS characterization comprising elemental mapping together with an energy-loss near-edge structure analysis indicated that this nanostructure could not be assigned to Co-based materials but rather to the solid electrolyte BaF2. Complementary structural and electronic characterizations using STEM and EELS as demonstrated herein evidently have the potential to play an increasingly important role in elucidating the nanostructures of functional materials.

Nanosized precipitates play a critical role in increasing the strength of metallic alloys. There are many reports that the initial precipitates are metastable phases holding a different composition and crystal structure from the equilibrium precipitate. The metastable precipitate transforms to its stable phase during heat treatment. A transmission electron microscope enables researchers to study the phase transition of metastable precipitates to stable phases due to its fine resolution in identifying crystal structures and chemical compositions. This review introduces the various phase transformation mechanisms of metastable precipitates to stable phases obtained from the analysis using a transmission electron microscope. The role of dislocation movement in the phase transition is further discussed.

We have demonstrated a new data analysis method that enables nondestructive depth profiling of a multilayer thin-film sample from energy-dispersive X-ray spectroscopy (EDX) data without the assumption of initial profiles. This method is based on a quadratic programming problem and allows for three-dimensional elemental mapping in the sample without destroying it, by performing depth profiling for all the pixels in the EDX two-dimensional mapping data. In this paper, first nondestructive depth profiling of two samples with different multilayer structures was performed using the proposed method. The results were compared with those obtained by cross-sectional observation to validate the accuracy and usefulness of the proposed method. Next, an example of the three-dimensional elemental mapping based on the proposed method was demonstrated. This method allows us to nondestructively obtain three-dimensional elemental distribution within a sample over a wide area on the order of mm, which is impossible to obtain using other analytical methods. The way to determine the hyperparameters, which significantly affects the calculation results, is fully described in this paper.

Optical errors, including spherical aberrations, hinder high-resolution imaging of biological samples due to biochemical components and physical properties. We developed the Deep-C microscope system to achieve aberration-free images, employing a motorized correction collar and contrast-based calculations. However, current contrast-maximization techniques, such as the Brenner gradient method, inadequately assess specific frequency bands. The Peak-C method addresses this issue, but its arbitrary neighbor selection and susceptibility to the noise limit its effectiveness. In this paper, we emphasize the importance of a broad spatial frequency range for accurate spherical aberration correction and propose Peak-F. This spatial frequency-based system utilizes a fast Fourier transform as a bandpass filter. This approach overcomes Peak-C's limitations and comprehensively covers the low-frequency domain of image spatial frequencies.

High-speed atomic force microscopy (HS-AFM) is now a widely used technique to study the dynamics of single biomolecules and complex structures. In the past, it has mainly been used to capture surface topography as structural analysis, leading to important discoveries not attainable by other methods. Similar to conventional AFM, the scope of HS-AFM was recently expanded to encompass quantities beyond topography, such as the measurement of mechanical properties. This review delves into various methodologies for assessing mechanical properties, ranging from semi-quantitative approaches to precise force measurements and their corresponding sample responses. We will focus on the application to single proteins such as bridging integrator-1, ion channels such as Piezo1, complex structures such as microtubules and supramolecular fibers. In all these examples, the unique combination of quantifiable force application and high spatiotemporal resolution allows to unravel mechanisms that cannot be investigated by conventional means.

We conducted a comprehensive analysis of the surface microtexture of kefir biofilms grown on Theobroma grandiflorum Shum (cupuaçu) juice using atomic force microscopy. Our goal was to investigate the unique monofractal and multifractal spatial patterns of these biofilms to complement the existing limited literature. The biofilms were prepared dispersing four different concentrations of kefir grains in cupuaçu juice. Our morphological analysis showed that the surface of the obtained biofilms is essentially formed by the presence of cupuaçu fibers and microorganisms like lactobacilli and yeast. The topographic height-based parameter analysis reveals that there is a dependence between surface roughness and the concentration of kefir grains used. The strongly anisotropic well-centralized topographical height distribution of the biofilms also exhibited a quasi-symmetrical and platykurtic pattern. The biofilms exhibit comparable levels of spatial complexity, surface percolation and surface homogeneity, which can be attributed to their similar topographic uniformity. This aspect was further supported by the presence of similar multifractality in the biofilms, suggesting that despite their varying topographic roughness, their vertical growth dynamics follow a similar pattern. Our findings demonstrate that the surface roughness of kefir biofilms cultivated on cupuaçu juice is influenced by the concentration of kefir grains in the precursor solution. However, this dependence follows a consistent pattern across different concentrations. Graphical Abstract.

This article describes a neural network system for predicting the secondary electron yield of metallic materials. For bulk metals, experimental values are used as training data. Due to the strong correlation between the secondary electron yield and the work function, deep learning predicts the secondary electron yield with relatively high accuracy even with a small amount of training data. Our approach demonstrates the importance of the work function in predicting the secondary electron yield. For the secondary electron yield of thin metal films on metal substrates, deep learning predictions are generated using training data obtained by Monte Carlo simulations. The accuracy of the secondary yield predictions of thin films on substrates could be improved by adding experimental values of bulk metals to the training data.

Electron holography is a useful tool for analyzing functional properties, such as electromagnetic fields and strains of materials and devices. The performance of electron holography is limited by the 'shot noise' inherent in electron micrographs (holograms), which are composed of a finite number of electrons. A promising approach for addressing this issue is to use mathematical and machine learning-based image-processing techniques for hologram denoising. With the advancement of information science, denoising methods have become capable of extracting signals that are completely buried in noise, and they are being applied to electron microscopy, including electron holography. However, these advanced denoising methods are complex and have many parameters to be tuned; therefore, it is necessary to understand their principles in depth and use them carefully. Herein, we present an overview of the principles and usage of sparse coding, the wavelet hidden Markov model and tensor decomposition, which have been applied to electron holography. We also present evaluation results for the denoising performance of these methods obtained through their application to simulated and experimentally recorded holograms. Our analysis, review and comparison of the methods clarify the impact of denoising on electron holography research.

Biological nanoparticles, such as bacterial outer membrane vesicles (OMVs), are routinely characterized through transmission electron microscopy (TEM). In this study, we report a novel method to prepare OMVs for TEM imaging. To preserve vesicular shape and structure, we developed a dual fixation protocol involving osmium tetroxide incubation prior to negative staining with uranyl acetate. Combining osmium tetroxide with uranyl acetate resulted in preservation of sub-50 nm vesicles and improved morphological stability, enhancing characterization of lipid-based nanoparticles by TEM.