Conventional Electron Microscopy Research Articles

Ultrastructural 3D Microscopy for Biomedicine: Principles, Applications, and Perspectives.

Modern biomedical research often requires a three-dimensional microscopic analysis of the ultrastructure of biological objects and materials. Conceptual technical and methodological solutions for three-dimensional structure reconstruction are needed to improve the conventional optical, electron, and probe microscopy methods, which to begin with allow one to obtain two-dimensional images and data. This review discusses the principles and potential applications of such techniques as serial section transmission electron microscopy; techniques based on scanning electron microscopy (SEM) (array tomography, focused ion beam SEM, and serial block-face SEM). 3D analysis techniques based on modern super-resolution optical microscopy methods are described (stochastic optical reconstruction microscopy and stimulated emission depletion microscopy), as well as ultrastructural 3D microscopy methods based on scanning probe microscopy and the feasibility of combining them with optical techniques. A comparative analysis of the advantages and shortcomings of the discussed approaches is performed.

A soft touch with electron beams: Digging out structural information of nanomaterials with advanced scanning low energy electron microscopy coupled with deep learning

Nanostructured materials continue to find applications in various electronic and sensing devices, chromatography, separations, drug delivery, renewable energy, and catalysis. While major advancements on the synthesis and characterization of these materials have already been made, getting information about their structures at sub-nanometer resolution remains challenging. It is also unfortunate to find that many emerging or already available powerful analytical methods take time to be fully adopted for characterization of various nanomaterials. The scanning low energy electron microscopy (SLEEM) is a good example to this. In this report, we show how clearer structural and surface information at nanoscale can be obtained by SLEEM, coupled with deep learning. The method is demonstrated using Au nanoparticles-loaded mesoporous silica as a model system. Moreover, unlike conventional scanning electron microscopy (SEM), SLEEM does not require the samples to be coated with conductive films for analysis; thus, not only it is convenient to use but it also does not give artifacts. The results further reveal that SLEEM and deep learning can serve as great tools to analyze materials at nanoscale well. The biggest advantage of the presented method is its availability, as most modern SEMs are able to operate at low energies and deep learning methods are already being widely used in many fields.

Significance of Using Scanning Electron Microscopy with Energy Dispersive X-ray Spectrometry (SEM-EDX) for Analysis of Evidence Material in Forensic Sciences

Forensic applications of Scanning Electron Microscopy (SEM) are found mostly in areas where there is a need for good imaging at relatively high magnifications. SEM enables the forensic scientist to examine specimens at much higher magnification than those possible with optical microscopy and without the difficulties of specimen preparation associated with conventional electron microscope. Physicochemical examinations of gunshot residues, called also chemical ballistics, are helpful, e.g. in identification of damages and injuries as the effect of the use of firearms (with indicating the entrance and exit of projectile), estimation of the shooting distance and also establishing, whether a person has used a firearm. It is discussed in details that Scanning Electron Microscopy with Energy Dispersive X-Ray Spectroscopy (SEM-EDX) can serve as a powerful tool for forensic scientists to classify and discriminate evidence material because they can simultaneously examine the morphology and the elemental composition of objects.

Lift-out cryo-FIBSEM and cryo-ET reveal the ultrastructural landscape of extracellular matrix.

The extracellular matrix (ECM) serves as a scaffold for cells and plays an essential role in regulating numerous cellular processes, including cell migration and proliferation. Due to limitations in specimen preparation for conventional room-temperature electron microscopy, we lack structural knowledge on how ECM components are secreted, remodeled, and interact with surrounding cells. We have developed a 3D-ECM platform compatible with sample thinning by cryo-focused ion beam milling, the lift-out extraction procedure, and cryo-electron tomography. Our workflow implements cell-derived matrices (CDMs) grown on EM grids, resulting in a versatile tool closely mimicking ECM environments. This allows us to visualize ECM for the first time in its hydrated, native context. Our data reveal an intricate network of extracellular fibers, their positioning relative to matrix-secreting cells, and previously unresolved structural entities. Our workflow and results add to the structural atlas of the ECM, providing novel insights into its secretion and assembly.

Non‐Destructive Tomographic Nanoscale Imaging of Ferroelectric Domain Walls

AbstractExtraordinary physical properties arise at polar interfaces in oxide materials, including the emergence of 2D electron gases, sheet‐superconductivity, and multiferroicity. A special type of polar interface is ferroelectric domain walls, where electronic reconstruction phenomena can be driven by bound charges. Great progress has been achieved in the characterization of such domain walls and, over the last decade, their potential for next‐generation nanotechnology has become clear. Established tomography techniques, however, are either destructive or offer insufficient spatial resolution, creating a pressing demand for 3D imaging compatible with future fabrication processes. Here, non‐destructive tomographic imaging of ferroelectric domain walls is demonstrated using secondary electrons. Utilizing conventional scanning electron microscopy (SEM), the position, orientation, and charge state of hidden domain walls are reconstructed at distances up to several hundreds of nanometers away from the surface. A mathematical model is derived that links the SEM intensity variations at the surface to the local domain wall properties, enabling non‐destructive tomography with good noise tolerance on the timescale of seconds. The SEM‐based approach facilitates high‐throughput screening of materials with functional domain walls and domain‐wall‐based devices, which is essential for monitoring during the production of device architectures and quality control in real‐time.

3D porous structure imaging of membranes for medical devices using scanning probe microscopy and electron microscopy: from membrane science points of view.

The evolution of hemodialysis membranes (dialyzer, artificial kidney) was remarkable, since Dow Chemical began manufacturing hollow fiber hemodialyzers in 1968, especially because it involved industrial chemistry, including polymer synthesis and membrane manufacturing process. The development of hemodialysis membranes has brought about the field of medical devices as a major industry. In addition to conventional electron microscopy, scanning probe microscopy (SPM), represented by atomic force microscopy (AFM), has been used in membrane science research on porous membranes for hemodialysis, and membrane science contributes greatly to the hemodialyzer industry. Practical studies of membrane porous structure-function relationship have evolved, and methods for analyzing membrane cross-sectional morphology were developed, such as the ion milling method, which was capable of cutting membrane cross sections on the order of molecular size to obtain smooth surface structures. Recently, following the global pandemic of SARS-CoV-2 infection, many studies on new membranes for extracorporeal membrane oxygenator have been promptly reported, which also utilize membrane science researches. Membrane science is playing a prominent role in membrane-based technologies such as separation and fabrication, for hemodialysis, membrane oxygenator, lithium ion battery separators, lithium recycling, and seawater desalination. These practical studies contribute to the global medical devices industry.

Confocal Scanning Laser Microscopic (CSLM) characterization of volcanic rocks

Optical and microscopical analyses of surficial and internal textures are key elements of volcanic rock characterization. Yet conventional methods for textural analyses often pose challenges and difficulties in terms of sample preparation and/or time and resources consumption, beside their inherent limitations. Here, we performed Confocal Scanning Laser Microscopy (CSLM) to characterize vesicles in volcanic rocks and their experimental analogs and to compare the results to those of conventional Scanning Electron Microscopy (SEM) investigations. Further, we discuss surface roughness analysis as a possible parameter to analyze different vesicle textures. CSLM obviates the need for sample impregnation (using fluorescent resin) and polishing, it enables fast and automated analyses of samples surfaces at lower costs than conventional techniques. Calculated vesicle size distributions and vesicle number densities of the analyzed samples were compared in order to determine the potential and precision of volume and area information directly obtainable from CSLM measurements in 3D. Monodisperse samples with homogeneous vesicle texture show remarkable similarities in vesicle size and volume distribution, when compared directly with the two methods. For all experimental and natural samples, roughly half of them show VNDs and porosity show the same range, which can be explained by vesicle coalescence. After de-coalescing the images of CSLM for FOAMS analysis, these differences vanish almost entirely for most of the sample types. Combining our textural data and our numerical modeling, we present a universal scaling model to link surface roughness with vesicle number density, porosity, and polydispersivity. These results indicate that CSLM can be a powerful tool to investigate vesicle structures from the millimetric to micrometric scale. The resulting data is both quantitatively and qualitatively equivalent to SEM-derived data for a variety of volcanic rock types. This, combined with the simple sample preparation and handling make CSLM a valid alternative to SEM investigations to characterize vesicles, particles, and any sort of rock property that reflects on topography. Surface roughness can become a new key parameter to interpret porous networks in volcanic rocks and can be applied to other geological fields.

Morphomics via next-generation electron microscopy.

The living body is composed of innumerable fine and complex structures. Although these structures have been studied in the past, a vast amount of information pertaining to them still remains unknown. When attempting to observe these ultra-structures, the use of electron microscopy (EM) has become indispensable. However, conventional EM settings are limited to a narrow tissue area, which can bias observations. Recently, new trends in EM research have emerged that provide coverage of far broader, nano-scale fields of view for two-dimensional wide areas and three-dimensional large volumes. Moreover, cutting-edge bioimage informatics conducted via deep learning has accelerated the quantification of complex morphological bioimages. Taken together, these technological and analytical advances have led to the comprehensive acquisition and quantification of cellular morphology, which now arises as a new omics science termed 'morphomics'.

An enhanced visualization image acquisition method for samples with poor conductivity under a conventional scanning electron microscope.

The low-vacuum and low-accelerating-voltage modes are the most simple and practical ways to directly analyze poorly conductive samples in conventional scanning electron microscopy (SEM). However, structural feature information may disappear or be obscured in these imaging modes, making it challenging to identify and analyze some local microstructures of poorly conductive samples. To overcome this challenge, an enhanced visualization image acquisition method for samples with poor conductivity is proposed based on the image registration and multi-sensor fusion technology. Experiments demonstrate that the proposed method can effectively obtain enhanced visualization images containing clearer terrain information than the SEM source images, thereby providing new references for measuring and analyzing microstructures.

Research on the ultrafast laser in microscopy

Ultrafast laser technology has been making a huge difference in different areas, such as material processing, laser surgery, and military usage. In parallel with the development of ultrafast lasers, microscopy also greatly promotes modern science, even though there are still some shortcomings, and one of them is that it is hard to obtain information about dynamic samples. However, this shortcoming can be solved by using ultrafast laser technology. This review will introduce the concept of ultrafast laser technology and electron microscopy, while several limitations of conventional electron microscopy will be mentioned. This paper also introduces two advanced technology in ultrafast microscopy. Nowadays, by taking advantage of ultrafast laser technology, the dynamic sample can be observed with highly improved temporal resolutions, which are basically restricted by the duration of pulses, but the ultrafast laser technology makes the duration even reach the range of attoseconds. However, there are some limitations, such as aberration, still hamper the development of high spatial resolution in microscopy. It is hoped that the ultrafast microscopy will break through the bottleneck of traditional microscopy in the future.

Deep learning image segmentation for the reliable porosity measurement of high-capacity Ni-based oxide cathode secondary particles

The optimization of geometrical pore control in high-capacity Ni-based cathode materials is required to enhance the cyclic performance of lithium-ion batteries. Enhanced porosity improves lithium-ion mobility by increasing the electrode–electrolyte contact area and reducing the number of ion diffusion pathways. However, excessive porosity can diminish capacity, thus necessitating optimizing pore distribution to compromise the trade-off relation. Accordingly, a statistically meaningful porosity estimation of electrode materials is required to engineer the local pore distribution inside the electrode particles. Conventional scanning electron microscopy (SEM) image-based porosity measurement can be used for this purpose. However, it is labor-intensive and subjected to human bias for low-contrast pore images, thereby potentially lowering measurement accuracy. To mitigate these difficulties, we propose an automated image segmentation method for the reliable porosity measurement of cathode materials using deep convolutional neural networks specifically trained for the analysis of porous cathode materials. Combined with the preprocessed SEM image datasets, the model trained for 100 epochs exhibits an accuracy of > 97% for feature segmentation with regard to pore detection on the input datasets. This automated method considerably reduces manual effort and human bias related to the digitization of pore features in serial section SEM image datasets used in 3D electron tomography.Graphical abstract

Investigation of the Efficacy of Lanthanoid Heavy Metal Acetates as Electron Staining Reagents for Biomembrane Vesicles.

Transmission electron microscopy (TEM) has revolutionized our understanding of protein structures by enabling atomic-resolution visualization without the need for crystallography, thanks to advancements in cryo-TEM and single particle analysis methods. However, conventional electron microscopy remains relevant for studying stained samples, as it allows the practical determination of optimal conditions through extensive experimentation. TEM also facilitates the examination of supramolecular complexes encompassing proteins, lipids, and nucleic acids. In this study, we investigated the applicability of lanthanoid reagents as electron-staining alternatives to uranyl acetate, which is globally regulated as a nuclear fuel material. We focus on a model biomembrane vesicle system, the chromatophores from the purple photosynthetic eubacterium Rhodospirillum rubrum, which integrate proteins and lipids. Through density distribution analysis of electron micrographs, we evaluated the efficacy of various lanthanoid acetates and found that triacetates of neodymium, samarium, and gadolinium exhibited similar staining effectiveness to uranyl acetate. Additionally, triacetates of praseodymium, erbium, and lutetium, followed by europium show promising results as secondary candidates. Our findings suggest that lanthanoid transition heavy metal acetates could serve as viable alternatives for electron staining in TEM, offering potential advantages over uranyl acetate.

Super-resolution Fluorescence Imaging of Recycled Polymer Blends via Hydrogen Bond-Assisted Adsorption of a Nile Red Derivative.

A key challenge in the recycling of multilayer plastic films of polyethylene and polyamide, as typically used for food packaging, is to assess and control the phase separation of the two types of polymers in the recycled material, the specifics of which determine the mechanical strength of the recycled material. However, visualizing the polyamide-in-polyethylene domains with conventional fluorescence methods or electron microscopy is challenging. We present a new approach that combines the point accumulation in nanoscale topography (PAINT) super-resolution method with a newly synthesized Nile Red probe (diOHNR) as the fluorescent label. The molecule was modified to undergo a hydrogen bond-assisted interaction with the polyamide phase in the blend due to its two additional hydroxyl groups but preserves the spectral properties of Nile Red. As a result, the localization density of the probe in the PAINT image is 13 times larger at the polyamide phase than at the polyethylene phase, enabling quantitative evaluation of the spatial polyamide/polyethylene distribution down to the nanoscale. The method achieved a spatial resolution of 18.8 nm, and we found that over half of the polyamide particles in a recycled sample were smaller than the optical diffraction limit. Being able to image the blends with nanoscopic resolution can help to optimize the composition and mechanical properties of recycled materials and thus contribute to an increased reuse of plastics.

Mammalian autophagosomes form from finger-like phagophores

The sequence of morphological intermediates that leads to mammalian autophagosome formation and closure is a crucial yet poorly understood issue. Previous studies have shown that yeast autophagosomes evolve from cup-shaped phagophores with only one closure point, and mammalian studies have inferred that mammalian phagophores also have single openings. Our superresolution microscopy studies in different human cell lines in conditions of basal and nutrient-deprivation-induced autophagy identified autophagosome precursors with multifocal origins that evolved into unexpected finger-like phagophores with multiple openings before becoming more spherical structures. Compatible phagophore structures were observed with whole-mount and conventional electron microscopy. This sequence of events was visualized using advanced SIM2 superresolution live microscopy. The finger-shaped phagophore apertures remained open when ESCRT function was compromised. The efficient closure of autophagic structures is important for their release from the recycling endosome. This has important implications for understanding how autophagosomes form and capture various cargoes.

Atomic-scale imaging of polyvinyl alcohol crystallinity using electron ptychography

Polyvinyl alcohol (PVA) is considered to have great potential in medical, pharmaceutical, and packaging applications because of its outstanding biocompatibility, water solubility, low density and relatively low cost. PVA crystallinity, central to the materials properties, has been studied by X-ray diffraction, but two possible crystal structures are mooted. Electron microscopic techniques can potentially image PVA at high resolution. Still, it is challenging for conventional electron microscopies because of the relatively low crystallinity of PVA, its severe beam sensitivity, and the poor contrast of light elements. Electron ptychography makes use of a 4D STEM dataset comprising the intensity in the STEM detector plane recorded as a function of each probe position and has lower sample damage and better phase-contrast compared to traditional techniques. Here, we use electron ptychography to image PVA crystallinity. The reconstructed images, which show good agreement in the unit cell dimension with X-ray diffraction data, can show how the atoms order in the materials, however, deviations from previous models derived from X-ray diffraction are observed. To interpret the data, we propose a series of changes based on previous models to formulate a description of PVA crystal structure. Simulated results from this new model accord well with the experimental images. This study manages to image both carbon and oxygen atoms in PVA, which has not previously been achieved by any conventional method. The results are expected to bring a new and deeper understanding of PVA crystal structure, and illustrate the opportunity presented by this approach for directly imaging molecular order in polymer crystals.

In Situ Nanoindentation at Elevated Humidities

AbstractNanoindentation is one of the most widespread methods to measure the mechanical performance of complex materials systems. As it allows for local characterization of composite architectures with sub‐micron spatial features and a large range of properties, nanoindentation is commonly used to measure the properties of biological materials. In situ nanoindentation, a further development of the approach, is a powerful tool for the analysis of plastic deformation and failure of materials. Here, samples can be mechanically manipulated using the indenter, while their behavior is monitored with the resolution of a scanning electron microscope (SEM). Indeed, numerous studies demonstrate the potential of this approach for studying the most fundamental material characteristics. However, so far, these measurements are performed in high‐vacuum conditions inherent to the conventional electron microscopy method, which are irrelevant when studying biological structures that evolved to perform in hydrated conditions. In this work, the ability to conduct nanoindentation experiments under controlled humidity and temperature inside an environmental SEM is developed. This technique has the potential to become crucial for materials design and characterization in many domains where humidity has a significant impact on performance. These include organic/polymer systems, microelectronic and optoelectronic devices, materials for catalysis, batteries, and many more.

Anatomical damage caused by Bacillus thuringiensis variety israelensis in yellow fever mosquito Aedes aegypti (L.) larvae revealed by micro-computed tomography

With micro-computed tomography techniques, using the single-distance phase-retrieval algorithm phase contrast, we reconstructed enhanced rendered images of soft tissues of Aedes aeqypti fourth instar larvae after Bti treatment. In contrast to previous publications based on conventional microscopy, either optical or electron microscopy, which were limited to partial studies, mostly in the form of histological sections, here we show for the first time the effects of Bti on the complete internal anatomy of an insect. Using 3D rendered images it was possible to study the effect of the bacterium in tissues and organs, not only in sections but also as a whole. We compared the anatomy of healthy larvae with the changes undergone in larvae after being exposed to Bti (for 30 min, 1 h and 6 h) and observed the progressive damage that Bti produce. Damage to the midgut epithelia was confirmed, with progressive swelling of the enterocytes, thickening epithelia, increase of the vacuolar spaces and finally cell lysis, producing openings in the midgut walls. Simultaneously, the larvae altered their motility, making it difficult for them to rise to the surface and position the respiratory siphon properly to break surface tension and breathe. Internally, osmotic shock phenomena were observed, resulting in a deformation of the cross-section shape, producing the appearance of a wide internal space between the cuticle and the internal structures and a progressive collapse of the tracheal trunks. Taken together, these results indicate the death of the larvae, not by starvation as a consequence of the destruction of the epithelia of the digestive tract as previously stated, but due to a synergic catastrophic multifactor process in addition to asphyxia due to a lack of adequate gas exchange.

Recent advances inin-resin correlative light andelectron microscopy ofEpon-embedded cells.

Correlative fluorescent and electron microscopic images of the same section of epoxy (or other polymer)-embedded samples, hereafter referred to as 'in-resin CLEM', have been developed to improve the positional accuracy and Z-axis resolution limitations of conventional correlative light and electron microscopy (CLEM). High-pressure freezing and quick-freezing substitution result in in-resin CLEM of acrylic-based resin-embedded cells expressing green fluorescent protein, yellow fluorescent protein, mVenus and mCherry, which are sensitive to osmium tetroxide. The identification of osmium-resistant fluorescent proteins leads to the development of in-resin CLEM of Epon-embedded cells. Using subtraction-based fluorescence microscopy with a photoconvertible fluorescent protein, mEosEM-E, its green fluorescence can be observed in thin sections of Epon-embedded cells, and two-color in-resin CLEM using mEosEM-E and mScarlet-H can be performed. Green fluorescent proteins, CoGFP variant 0 and mWasabi, and far-red fluorescent proteins, mCherry2 and mKate2, are available for in-resin CLEM of Epon-embedded cells using the standard procedure for Epon-embedding with additional incubation. Proximity labeling is applied to in-resin CLEM to overcome the limitations of fluorescent proteins in epoxy resin. These approaches will contribute significantly to the future of CLEM analysis.

Nondestructive and Quantitative Analysis of Cell Wall Regeneration in the Medicinal Macrofungus Ganoderma lingzhi by a Membrane-Fusing Fluorescent Probe.

Ganoderma is a prize medicinal macrofungus with a broad range of pharmaceutical values. To date, various attempts have been made to cultivate Ganoderma to improve the production of secondary metabolites with pharmacological activity. Among the adopted techniques, protoplast preparation and regeneration are indispensable. However, the evaluation of protoplasts and regenerated cell walls usually relies on electron microscopy assays, which require time-consuming and destructive sample preparation and merely provide localized information in the selected area. In contrast, fluorescence assays enable sensitive real-time detection and imaging in vivo. They can also be applied to flow cytometry, providing a collective overview of every cell in a sample. However, for macrofungi such as Ganoderma, the fluorescence analysis of protoplasts and regenerated cell walls is difficult owing to the hindrance of the homologous fluorescent protein expression and the lack of an appropriate fluorescence marker. Herein, a specific plasma membrane probe, TAMRA perfluorocarbon nucleic acid probe (TPFN), is proposed for the nondestructive and quantitative fluorescence analysis of cell wall regeneration. Exploiting the perfluorocarbon membrane-anchoring chains, hydrophilic nucleic acid linker, and fluorescent dye TAMRA, the probe is proven to be selective, soluble, and stable, enabling rapid fluorescence detection of a protoplast sample free of transgenic expression or immune staining. Based on the TPFN and flow cytometry techniques, a quantitative approach is constructed to monitor the process of cell wall growth in a fast, quantitative, and high-throughout manner, and the obtained results are consistent with those of conventional electron microscopy. In principle, with slight modifications or integration, the proposed probe and approach can be adapted to the preparation of cell protoplasts, inspection of cell wall integrity under environmental stress, and programmable membrane engineering for cytobiology and physiology research.

Maternal antibiotic administration during gestation can affect the memory and brain structure in mouse offspring.

Maternal antibiotics administration (MAA) is among the widely used therapeutic approaches in pregnancy. Although published evidence demonstrates that infants exposed to antibiotics immediately after birth have altered recognition memory responses at one month of age, very little is known about in utero effects of antibiotics on the neuronal function and behavior of children after birth. Therefore, this study aimed to evaluate the impact of MAA at different periods of pregnancy on memory decline and brain structural alterations in young mouse offspring after their first month of life. To study the effects of MAA on 4-week-old offspring, pregnant C57BL/6J mouse dams (2-3-month-old; n = 4/group) were exposed to a cocktail of amoxicillin (205 mg/kg/day) and azithromycin (51 mg/kg/day) in sterile drinking water (daily/1 week) during either the 2nd or 3rd week of pregnancy and stopped after delivery. A control group of pregnant dams was exposed to sterile drinking water alone during all three weeks of pregnancy. Then, the 4-week-old offspring mice were first evaluated for behavioral changes. Using the Morris water maze assay, we revealed that exposure of pregnant mice to antibiotics at the 2nd and 3rd weeks of pregnancy significantly altered spatial reference memory and learning skills in their offspring compared to those delivered from the control group of dams. In contrast, no significant difference in long-term associative memory was detected between offspring groups using the novel object recognition test. Then, we histologically evaluated brain samples from the same offspring individuals using conventional immunofluorescence and electron microscopy assays. To our knowledge, we observed a reduction in the density of the hippocampal CA1 pyramidal neurons and hypomyelination in the corpus callosum in groups of mice in utero exposed to antibiotics at the 2nd and 3rd weeks of gestation. In addition, offspring exposed to antibiotics at the 2nd or 3rd week of gestation demonstrated a decreased astrocyte cell surface area and astrocyte territories or depletion of neurogenesis in the dentate gyrus and hippocampal synaptic loss, respectively. Altogether, this study shows that MAA at different times of pregnancy can pathologically alter cognitive behavior and brain development in offspring at an early age after weaning.