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Electron microscopy of soft and biological materials, or "soft electron microscopy", is essential to the characterization of macromolecules. Soft microscopy is governed by enhancing contrast while maintaining low electron doses, and sample preparation and imaging methodologies are driven by the length scale of features of interest. While cryo-electron microscopy offers the highest resolution, larger structures can be characterized efficiently and with high contrast using low-voltage electron microscopy by performing scanning transmission electron microscopy in a scanning electron microscope (STEM-in-SEM). Here, STEM-in-SEM is demonstrated for a four-lobed protein assembly where the arrangement of the proteins in the construct must be examined. STEM image simulations show the theoretical contrast enhancement at SEM-level voltages for unstained structures, and experimental images with multiple STEM modes exhibit the resolution possible for negative-stained proteins. This technique can be extended to complex protein assemblies, larger structures such as cell sections, and hybrid materials, making STEM-in-SEM a valuable high-throughput imaging method.

High-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) can be acquired together with energy dispersive X-ray (EDX) spectroscopy to give complementary information on the nanoparticles being imaged. Recent deep learning approaches show potential for accurate 3D tomographic reconstruction for these applications, but a large number of high-quality electron micrographs are usually required for supervised training, which may be difficult to collect due to the damage on the particles from the electron beam. To overcome these limitations and enable tomographic reconstruction even in low-dose sparse-view conditions, here we present an unsupervised deep learning method for HAADF-STEM-EDX tomography. Specifically, to improve the EDX image quality from low-dose condition, a HAADF-constrained unsupervised denoising approach is proposed. Additionally, to enable extreme sparse-view tomographic reconstruction, an unsupervised view enrichment scheme is proposed in the projection domain. Extensive experiments with different types of quantum dots show that the proposed method offers a high-quality reconstruction even with only

Here, we demonstrate atomic-resolution scanning transmission electron microscopy (STEM) imaging of light elements in small organic molecules on graphene. We use low-dose, room-temperature, aberration-corrected STEM to image 2D monolayer and bilayer molecular crystals, followed by advanced image processing methods to create high-quality composite images from ∼10

Differential phase contrast (DPC) scanning transmission electron microscopy can directly visualize electromagnetic fields inside a specimen. However, their image contrast is not only sensitive to the electromagnetic fields in the sample, but also the changes in diffraction conditions such as sample bends or thickness changes. These additional contrasts are called diffraction contrasts, and sometimes make it difficult to extract pure electromagnetic field information from the experimental DPC images. In this study, we developed a beam scan system that can acquire many DPC images from the same sample region with arbitrarily varying incident beam tilt angles to the sample. Then, these images are precisely averaged to form tilt-scan averaged DPC images. It is shown that the diffraction contrast can be effectively reduced in the tilt-scan averaged DPC images.

The manipulation of individual atoms has developed from visionary speculation into an established experimental science. Using focused electron irradiation in a scanning transmission electron microscope instead of a physical tip in a scanning probe microscope confers several benefits, including thermal stability of the manipulated structures, the ability to reach into bulk crystals, and the chemical identification of single atoms. However, energetic electron irradiation also presents unique challenges, with an inevitable possibility of irradiation damage. Understanding the underlying mechanisms will undoubtedly continue to play an important role to guide experiments. Great progress has been made in several materials including graphene, carbon nanotubes, and crystalline silicon in the eight years since the discovery of electron-beam manipulation, but the important challenges that remain will determine how far we can expect to progress in the near future.

The use of carbon nanotubes (CNTs) could improve medical diagnosis and treatment provided they show no adverse effects in the organism. In this study, short CNTs with different diameters with and without carboxyl surface functionalisation were assessed. After physicochemical characterisation, cytotoxicity in phagocytic and non-phagocytic cells was determined. The role of oxidative stress was evaluated according to the intracellular glutathione levels and protection by N-acetyl cysteine (NAC). In addition to this, the mode of cell death was also investigated. CNTs

Heat-up and hot-injection methods were employed to synthesize Ni nanoparticles (NPs) with narrow size distribution in the presence of hyperbranched pyridylphenylene polymer (PPP) as a stabilizing agent. It was shown that depending on the synthetic method, Ni NPs were formed either in a cross-linked polymer network or stabilized by a soluble hyperbranched polymer. Ni NPs were characterized by a combination of transmission electron microscopy (TEM), scanning TEM, thermogravimetric analysis, powder X-ray diffraction, X-ray photoelectron spectroscopy, energy dispersive X-ray analysis, and magnetic measurements. The architecture of polymer support was found to significantly effect Ni NPs characteristics and behavior. The Ni NPs demonstrated a high catalytic activity in a model Suzuki–Miyaura cross-coupling reaction. No significant drop in activity was observed upon repeated use after magnetic separation in five consecutive catalytic cycles. We believe that hyperbranched PPP can serve as universal platform for the controllable synthesis of Ni NPs, acting as highly active and stable catalysts.

Physics-driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here we develop and experimentally implement a deep kernel learning workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics-based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure-property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk- and edge plasmon discovery in MnPS3, a lesser-known beam-sensitive layered 2D material. This approach is universal, can be directly used as-is with any specimen, and is expected to be applicable to any probe-based microscopic techniques including other STEM modalities, Scanning Probe Microscopies, chemical, and optical imaging.

Objectives The human adult vocal fold mucosa, especially, superficial layer of the lamina propria (Reinke's space) has attracted notice as an important vibrating structure. However, fine structures of the stratified squamous epithelium of the human adult vocal fold, which is another histological component of the mucosa, remain enigmatic. Methods Three normal human adult vocal folds and epiglottises and three newborn vocal folds were investigated. Observations using transmission electron microscopy and light microscopy including immunohistochemistry were performed. Results The most obvious feature of the epithelium of the human adult vocal folds was that the intercellular spaces between adjacent epithelial cells were large (984 ± 186 nm) compared with the stratified squamous epithelium of the human adult epiglottis and the human newborn vocal fold. Even though intercellular spaces between adjacent epithelial cells of the human adult vocal fold were large, desmosomes at the junctions of two adjacent epithelial cells made firm intercellular adhesion. Tonofilaments composed of the bundles of intermediate filaments anchored to the desmosomes. Desmosomes formed a continuous cytoskeletal network throughout the epithelial cells and epithelium of the human adult vocal fold. In addition, a great deal of E-cadherin (adhesive glycoprotein) was present between epithelial cells especially the lower half of the stratified squamous epithelium of the human adult vocal fold. Conclusions From the functional morphological point of view, stratified squamous epithelium of the human adult vocal fold seems to form a structural framework of tensile strength with pliability suitable structure for vibration.

Chromatin organization over multiple length scales plays a critical role in the regulation of transcription. Deciphering the interplay of these processes requires high-resolution, three-dimensional, quantitative imaging of chromatin structure in vitro. Herein, we introduce ChromSTEM, a method that utilizes high-angle annular dark-field imaging and tomography in scanning transmission electron microscopy combined with DNA-specific staining for electron microscopy. We utilized ChromSTEM for an in-depth quantification of 3D chromatin conformation with high spatial resolution and contrast, allowing for characterization of higher-order chromatin structure almost down to the level of the DNA base pair. Employing mass scaling analysis on ChromSTEM mass density tomograms, we observed that chromatin forms spatially well-defined higher-order domains, around 80 nm in radius. Within domains, chromatin exhibits a polymeric fractal-like behavior and a radially decreasing mass-density from the center to the periphery. Unlike other nanoimaging and analysis techniques, we demonstrate that our unique combination of this high-resolution imaging technique with polymer physics-based analysis enables us to (i) investigate the chromatin conformation within packing domains and (ii) quantify statistical descriptors of chromatin structure that are relevant to transcription. We observe that packing domains have heterogeneous morphological properties even within the same cell line, underlying the potential role of statistical chromatin packing in regulating gene expression within eukaryotic nuclei.

Scanning transmission electron microscopy (STEM) is an indispensable tool for atomic-resolution structural analysis for a wide range of materials. The conventional analysis of STEM images is an extensive hands-on process, which limits efficient handling of high-throughput data. Here, we apply a fully convolutional network (FCN) for identification of important structural features of two-dimensional crystals. ResUNet, a type of FCN, is utilized in identifying sulfur vacancies and polymorph types of MoS

Escherichia coli chaperonin GroEL, which is a large cylindrical protein complex comprising two heptameric rings with cavities of 4.5 nm each in the center, assists in intracellular protein folding with the aid of GroES and adenosine triphosphate (ATP). Here, we investigated the possibility that GroEL can also encapsulate metal nanoparticles (NPs) up to ∼5 nm in diameter into the cavities with the aid of GroES and ATP. The slow ATP-hydrolyzing GroELD52A/D398A mutant, which forms extremely stable complexes with GroES (half-time of ∼6 days), made it possible to analyze GroEL/GroES complexes containing metal NPs. Scanning transmission electron microscopy–energy-dispersive X-ray spectroscopy analysis proved distinctly that FePt NPs and Au NPs were encapsulated in the GroEL/GroES complexes. Dynamic light scattering measurements showed that the NPs in the GroEL/GroES complex were able to maintain their dispersibility in solution. We previously described that the incubation of GroEL and GroES in the presence of ATP·BeFx and adenosine diphosphate·BeFx resulted in the formation of symmetric football-shaped and asymmetric bullet-shaped complexes, respectively. Based on this knowledge, we successfully constructed the football-shaped complex in which two compartments were occupied by Pt or Au NPs (first compartment) and FePt NPs (second compartment). This study showed that metal NPs were sequentially encapsulated according to the GroEL reaction in a step-by-step manner. In light of these results, chaperonin can be used as a tool for handling nanomaterials.

Here, we describe the surprising reactivity between surface-attached (a) 0.9, 1.6, and 4.1 nm diameter weakly stabilized Au nanoparticles (NPs) and aqueous 1.0 × 10-4 M Ag+ solution, and (b) 1.6 and 4.1 nm diameter weakly stabilized Au NPs and aqueous 1.0 × 10-5 M PtCl42-, which are considered to be antigalvanic replacement (AGR) reactions because they are not thermodynamically favorable for bulk-sized Au under these conditions. Anodic Stripping Voltammetry (ASV) and Scanning Transmission Electron Microscopy with Energy-Dispersive X-ray Spectroscopy (STEM-EDS) mapping provide quantitation of the extent of Ag and Pt replacement as a function of Au NP diameter. The extent of the reaction increases as the Au NP size decreases. The percentage of Ag in the AuAg alloy following AGR based on ASV is 17.8 ± 0.6% for 4.1 nm diameter Au NPs, 87.2 ± 2.9% for 1.6 nm Au NPs, and an unprecedented full 100% Ag for 0.9 nm diameter Au NPs. STEM-EDS mapping shows very close agreement with the ASV-determined compositions. In the case of PtCl42-, STEM-EDS mapping shows AuPt alloy NPs with 3.9 ± 1.3% and 41.1 ± 8.7% Pt following replacement with 4.1 and 1.6 nm diameter Au NPs, respectively, consistent with qualitative changes to the ASV. The size-dependent AGR correlates well with the negative shift in the standard potential (E0) for Au oxidation with decreasing NP size.

The complex environment of biological cells and tissues has motivated development of three-dimensional (3D) imaging in both light and electron microscopies. To this end, one of the primary tools in fluorescence microscopy is that of computational deconvolution. Wide-field fluorescence images are often corrupted by haze due to out-of-focus light, i.e., to cross-talk between different object planes as represented in the 3D image. Using prior understanding of the image formation mechanism, it is possible to suppress the cross-talk and reassign the unfocused light to its proper source post facto. Electron tomography based on tilted projections also exhibits a cross-talk between distant planes due to the discrete angular sampling and limited tilt range. By use of a suitably synthesized 3D point spread function, we show here that deconvolution leads to similar improvements in volume data reconstructed from cryoscanning transmission electron tomography (CSTET), namely a dramatic in-plane noise reduction and improved representation of features in the axial dimension. Contrast enhancement is demonstrated first with colloidal gold particles and then in representative cryotomograms of intact cells. Deconvolution of CSTET data collected from the periphery of an intact nucleus revealed partially condensed, extended structures in interphase chromatin.

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) theory exploits the inherent sparse signal structure to efficiently reconstruct three-dimensional (3D) volumes at the nanoscale from undersampled measurements. However, the process bottlenecks 3D reconstruction with computation times that run from hours to days. Here we demonstrate a framework for dynamic compressed sensing that produces a 3D specimen structure that updates in real-time as new specimen projections are collected. Researchers can begin interpreting 3D specimens as data is collected to facilitate high-throughput and interactive analysis. Using scanning transmission electron microscopy (STEM), we show that dynamic compressed sensing accelerates the convergence speed by 3-fold while also reducing its error by 27% for an Au/SrTiO3 nanoparticle specimen. Before a tomography experiment is completed, the 3D tomogram has interpretable structure within 33% of completion and fine details are visible as early as 66%. Upon completion of an experiment, a high-fidelity 3D visualization is produced without further delay. Additionally, reconstruction parameters that tune data fidelity can be manipulated throughout the computation without rerunning the entire process.

Dental enamel is a principal component of teeth.[1] It has evolved to bear large masticatory forces, resist mechanical fatigue, and withstand wear over decades of use.[2] Functional impairment or loss, as a consequence of developmental defects or tooth decay (caries), has a dramatic impact on health and quality of life, with significant costs to society.[3] While the last decade has seen great progress in our understanding of enamel formation (amelogenesis) and the functional properties of mature enamel, attempts to repair enamel lesions or synthesize enamel in vitro have had limited success.[4–6] This is partly due to the highly hierarchical structure of enamel and the additional complexities arising from chemical gradients that we are only beginning to understand.[7–9] Herein, we show, using atomic-scale quantitative imaging and correlative spectroscopies, that the nanoscale crystallites of hydroxylapatite (OHAp; Ca5(PO4)3(OH)) that are the fundamental building blocks of enamel are comprised of two nanometric layers enriched in magnesium flanking a core rich in sodium, fluoride, and carbonate ions; this sandwich core is surrounded by a shell with lower concentration of substitutional defects. A mechanical model based on DFT calculations and X-ray diffraction data predicts that significant residual stresses arise as a consequence of the chemical gradients, in agreement with preferential dissolution of the crystallite core. Further, stresses may impact the mechanical resilience of enamel. Finally, the two additional layers of hierarchy suggest a new model for biological control over crystal growth during amelogenesis and have implications for the preservation of biomarkers during tooth development.

Atypical low-oxidation-state iron phases in Alzheimer’s disease (AD) pathology are implicated in disease pathogenesis, as they may promote elevated redox activity and convey toxicity. However, the origin of low-oxidation-state iron and the pathways responsible for its formation and evolution remain unresolved. Here we investigate the interaction of the AD peptide β-amyloid (Aβ) with the iron storage protein ferritin, to establish whether interactions between these two species are a potential source of low-oxidation-state iron in AD. Using X-ray spectromicroscopy and electron microscopy we found that the co-aggregation of Aβ and ferritin resulted in the conversion of ferritin’s inert ferric core into more reactive low-oxidation-states. Such findings strongly implicate Aβ in the altered iron handling and increased oxidative stress observed in AD pathogenesis. These amyloid-associated iron phases have biomarker potential to assist with disease diagnosis and staging, and may act as targets for therapies designed to lower oxidative stress in AD tissue.

Colloidal crystal engineering with nucleic acid-modified nanoparticles is a powerful way for preparing 3D superlattices, which may be useful in many areas, including catalysis, sensing, and photonics. To date, the building blocks studied have been primarily based upon metals, metal oxides, chalcogenide semiconductors, and proteins. Here, we show that metal–organic framework nanoparticles (MOF NPs) densely functionalized with oligonucleotides can be programmed to crystallize into a diverse set of superlattices with well-defined crystal symmetries and compositions. Electron microscopy and small-angle X-ray scattering characterization confirm the formation of single-component MOF superlattices, binary MOF–Au single crystals, and two-dimensional MOF nanorod assemblies. Importantly, DNA-modified porphyrinic MOF nanorods (PCN-222) were assembled into 2D superlattices and found to be catalytically active for the photooxidation of 2-chloroethyl ethyl sulfide (CEES, a chemical warfare simulant of mustard gas). Taken together, these new materials and methods provide access to colloidal crystals that incorporate particles with the well-established designer properties of MOFs and, therefore, increase the scope of possibilities for colloidal crystal engineering with DNA., Colloidal crystals assembled from nanoscale building blocks are powerful designer materials with diverse functionalities. Here, the authors describe a colloidal crystal engineering strategy to prepare hierarchical structures from metal–organic framework nanoparticles and DNA which retain permanent porosity and catalytic activity.

In this study a high resolution structural analysis revealed that enamel prisms are surrounded by an interface that is discontinuous with frequent mineral to mineral contact separated by gaps. This contact manifests either by crystallites bridging the boundary between prismatic and interprismatic enamel or continuous crystallites curving and bridging the interprismatic enamel to the prisms. The geometrical resolution of this TEM investigation of the interfaces is ≤2 nm as a basis for micromechanical models. Within this resolution, contrary to existing structural descriptions of dental enamel structure in materials science literature, here the crystallites themselves are shown to be either in direct contact with each other, sometimes even fusing together, or are separated by gaps. Image analysis revealed that on average only 57 ± 15% of the interface consists of points of no contact between crystallites. This work reveals structural features of dental enamel that contribute important understanding to both the architecture and mechanical properties of this biological material. A new structural model is proposed and the implications for the mechanical properties of dental enamel are discussed. Statement of significance In this study a high resolution structural analysis, employing focused ion beam and transmission electron microscopy revealed that enamel prisms are surrounded by interfaces that are discontinuous with frequent mineral to mineral contact separated by gaps. Although the interfaces in enamel have been investigated previously, existing studies are lacking in detail considering the geometry and morphology of the interfaces. We think that this result is of great importance when it comes to the understanding of the mechanical properties. In our opinion the concept of soft sheaths is no longer feasible. The resulting observations are included in a new structural model which provides new qualitative insights into the mechanical behavior. Existing analytical models were applied to simulate the new geometrical structure.

The main aspects of material research: material synthesis, material structure, and material properties, are interrelated. Acquiring atomic structure information of electron beam sensitive materials by electron microscope, such as porous zeolites, organic-inorganic hybrid perovskites, metal-organic frameworks, is an important and challenging task. The difficulties in characterization of the structures will inevitably limit the optimization of their synthesis methods and further improve their performance. The emergence of integrated differential phase contrast scanning transmission electron microscopy (iDPC-STEM), a STEM characterization technique capable of obtaining images with high signal-to-noise ratio under lower doses, has made great breakthroughs in the atomic structure characterization of these materials. This article reviews the developments and applications of iDPC-STEM in electron beam sensitive materials, and provides an outlook on its capabilities and development.

Nanoscale tailoring of catalytic materials and Li-battery alternatives has elevated the importance of

A major aim in structural cell biology is to analyze intact cells in three dimensions, visualize subcellular structures, and even localize proteins at the best possible resolution in three dimensions. Though recently developed electron microscopy tools such as electron tomography, or three-dimensional (3D) scanning electron microscopy, offer great resolution in three dimensions, the challenge is that, the better the resolution, usually the smaller the volume under investigation. Several different approaches to overcome this challenge were presented at the Microscopy Conference in Vienna in 2021. These tools include array tomography, batch tomography, or scanning transmission electron tomography, all of which can nowadays be extended toward correlative light and electron tomography, with greatly increased 3D information. Here, we review these tools, describe the underlying procedures, and discuss their advantages and limits.

ToTEM, a multislice-based image simulation software is developed for transmission electron microscope (TEM). This software implements the following major features: (i) capability of assigning three-dimensional potentials of atom into multiple slices and precise introduction of phase shift caused by the sub-pixel atomic position, (ii) employing CUDA coding and graphical processing units (GPU) with multithreading parallel algorithm based on the powerful batch (inverse) fast Fourier transform (FFT), which is especially beneficial for image simulation of scanning transmission electron microscopy (STEM) or (integrated) differential phase contrast (I)DPC, (iii) design for efficiently generating large batch of data set of high-resolution transmission electron microscopy (HRTEM) images. Image simulation acceleration for STEM has been verified by simulating a large-scale SrTiO

Application of scanning transmission electron microscopy (STEM) to in situ observation will be essential in the current and emerging data-driven materials science by taking STEM's high affinity with various analytical options into account. As is well known, STEM's image acquisition time needs to be further shortened to capture a targeted phenomenon in real-time as STEM's current temporal resolution is far below the conventional TEM's. However, rapid image acquisition in the millisecond per frame or faster generally causes image distortion, poor electron signals, and unidirectional blurring, which are obstacles for realizing video-rate STEM observation. Here we show an image correction framework integrating deep learning (DL)-based denoising and image distortion correction schemes optimized for STEM rapid image acquisition. By comparing a series of distortion corrected rapid scan images with corresponding regular scan speed images, the trained DL network is shown to remove not only the statistical noise but also the unidirectional blurring. This result demonstrates that rapid as well as high-quality image acquisition by STEM without hardware modification can be established by the DL. The DL-based noise filter could be applied to in-situ observation, such as dislocation activities under external stimuli, with high spatio-temporal resolution. R3QR Program (Qdai-jump Research Program) [01271]; JSPS KAKENHI [JP21K20491, JP20K21093, JP19H02029, JP20H02479]; Iketani science and technology foundation; Pan Omics Data-Driven Research Innovation Center; Five star Alliance; JST CREST [JPMJCR1994]; Virginia Tech National Center for Earth and Environmental Nanotechnology Infrastructure by NSF [ECCS 1542100, 2025151] Published version This work was supported by R3QR Program (Qdai-jump Research Program) 01271 and JSPS KAKENHI Grant Number (JP21K20491, JP20K21093), Iketani science and technology foundation, Pan Omics Data-Driven Research Innovation Center and Five star Alliance. M.M. greatly appreciates the financial support by the JST CREST (JPMJCR1994), JSPS KAKENHI Grant Numbers (JP19H02029, JP20H02479), Virginia Tech National Center for Earth and Environmental Nanotechnology Infrastructure (NanoEarth), a member of the National Nanotechnology Coordinated Infrastructure (NNCI), supported by NSF (ECCS 1542100 and 2025151).

Preservation of analyte integrity during focused ion beam (FIB) sample preparation is a significant challenge in the scanning transmission electron microscopy (STEM) characterization of plan-view samples with sensitive surface chemistries. This can preclude the characterization of atomic arrangements, nanoscale surface coverages, and distributions and morphologies of functional molecular materials composed of surface-immobilized metal nanoparticles, clusters or coordination complexes. This work demonstrates effective protection of Pt nanoparticle (NP) morphology through a plan-view FIB lift-out and thinning procedure by encapsulating the sample surface in an Al

Since silver ion is known for its antimicrobial function, most of the research has focused mainly on toxicity effects rather than the role of silver ion in general biology and the behind mechanism of actions of silver ion in mammalian cells. Moreover, a conventional in vitro approach to estimate the effects of silver ion on cells does not provide information about the biochemical changes and might accompany artifacts due to invasive and destructive sample preparation processes. In the present study, in-situ real time approaches were applied to evaluate the impact of silver ion (0.57, 1.34, 1.96, 2.33 mg/L) on fibroblast cells. Raman spectroscopy analysis showed that Raman peak intensities of proteins and nucleic acids significantly increased in the cells after exposure to silver ion for 21 h, especially at relatively higher levels 1.34, 1.96, and 2.33 mg/L. Raman peak at 1585 cm

In electron cryomicroscopy (cryo-EM), molecular images of vitrified biological samples are obtained by conventional transmission microscopy (CTEM) using large underfocuses and subsequently computationally combined into a high-resolution three-dimensional structure. Here, we apply scanning transmission electron microscopy (STEM) using the integrated differential phase contrast mode also known as iDPC–STEM to two cryo-EM test specimens, keyhole limpet hemocyanin (KLH) and tobacco mosaic virus (TMV). The micrographs show complete contrast transfer to high resolution and enable the cryo-EM structure determination for KLH at 6.5 Å resolution, as well as for TMV at 3.5 Å resolution using single-particle reconstruction methods, which share identical features with maps obtained by CTEM of a previously acquired same-sized TMV data set. These data show that STEM imaging in general, and in particular the iDPC–STEM approach, can be applied to vitrified single-particle specimens to determine near-atomic resolution cryo-EM structures of biological macromolecules.

Significance Endocytosis transports cargos inside the cell by creating spherical vesicles from the plasma membrane. This membrane remodeling requires proteins to generate force to bend the membrane inwards, overcoming the high-turgor pressure in plant cells. However, as plants create clathrin-coated vesicles without actin, the machinery to bend membranes during endocytosis is entirely unknown and appears distinct from other model systems. Here, we refine the physiological role of the plant-specific and essential endocytic TPLATE complex. We find it localizes outside of clathrin-coated vesicles and mediates membrane bending, contrasting with previous predictions. We further demonstrate that the TPLATE complex contains protein domains which have intrinsic membrane-bending activity; thus, we identify a component of the unique endocytosis membrane-bending machinery in plants., Clathrin-mediated endocytosis is the major route of entry of cargos into cells and thus underpins many physiological processes. During endocytosis, an area of flat membrane is remodeled by proteins to create a spherical vesicle against intracellular forces. The protein machinery which mediates this membrane bending in plants is unknown. However, it is known that plant endocytosis is actin independent, thus indicating that plants utilize a unique mechanism to mediate membrane bending against high-turgor pressure compared to other model systems. Here, we investigate the TPLATE complex, a plant-specific endocytosis protein complex. It has been thought to function as a classical adaptor functioning underneath the clathrin coat. However, by using biochemical and advanced live microscopy approaches, we found that TPLATE is peripherally associated with clathrin-coated vesicles and localizes at the rim of endocytosis events. As this localization is more fitting to the protein machinery involved in membrane bending during endocytosis, we examined cells in which the TPLATE complex was disrupted and found that the clathrin structures present as flat patches. This suggests a requirement of the TPLATE complex for membrane bending during plant clathrin–mediated endocytosis. Next, we used in vitro biophysical assays to confirm that the TPLATE complex possesses protein domains with intrinsic membrane remodeling activity. These results redefine the role of the TPLATE complex and implicate it as a key component of the evolutionarily distinct plant endocytosis mechanism, which mediates endocytic membrane bending against the high-turgor pressure in plant cells.

Environmentally friendly synthesis of Cu(In,Ga)Se

Atomic-resolution electron microscopy imaging of solid-state material is a powerful method for structural analysis. Scanning transmission electron microscopy (STEM) is one of the actively used techniques to directly observe atoms in materials. However, some materials are easily damaged by the electron beam irradiation, and only noisy images are available when we decrease the electron dose to avoid beam damages. Therefore, a denoising process is necessary for precise structural analysis in low-dose STEM. In this study, we propose total variation (TV) denoising algorithm to remove quantum noise in an STEM image. We defined an entropy of STEM image that corresponds to the image contrast to determine a hyperparameter and we found that there is a hyperparameter that maximizes the entropy. We acquired atomic-resolution STEM image of CaF2 viewed along the [001] direction and executed TV denoising. The atomic columns of Ca and F are clearly visualized by the TV denoising, and atomic positions of Ca and F are determined with the error of ±1 pm and ±4 pm, respectively.

Crystallization of biomacromolecules-metal-organic frameworks (BMOFs) allows for orderly assemble of symbiotic hybrids with desirable biological and chemical functions in one voxel. The structure-activity relationship of this symbiotic crystal, however, is still blurred. Here, we directly identify the atomic-level structure of BMOFs, using the integrated differential phase contrast-scanning transmission electron microscopy, cryo-electron microscopy and x-ray absorption fine structure techniques. We discover an obvious difference in the nanoarchitecture of BMOFs under different crystallization pathways that was previously not seen. In addition, we find the nanoarchitecture significantly affects the bioactivity of the BMOFs. This work gives an important insight into the structure-activity relationship of BMOFs synthesized in different scenarios, and may act as a guide to engineer next-generation materials with excellent biological and chemical functions.

This study presents the development of a new correlative workflow to bridge the gap between electron microscopy imaging and genetic analysis of viruses. The workflow enables the assignment of genetic information to a specific biological entity by harnessing the nanodissection capability of focused ion beam (FIB). This correlative workflow is based on scanning transmission electron microscopy (STEM) and FIB followed by a polymerase chain reaction (PCR). For this purpose, we studied the tomato brown rugose fruit virus (ToBRFV) and the adenovirus that have significant impacts on plant integrity and human health, respectively. STEM imaging was used for the identification and localization of virus particles on a transmission electron microscopy (TEM) grid followed by FIB milling of the desired region of interest. The final-milled product was subjected to genetic analysis by the PCR. The results prove that the FIB-milling process maintains the integrity of the genetic material as confirmed by the PCR. We demonstrate the identification of RNA and DNA viruses extracted from a few micrometers of an FIB-milled TEM grid. This workflow enables the genetic analysis of specifically imaged viral particles directly from heterogeneous clinical samples. In addition to viral diagnostics, the ability to isolate and to genetically identify specific submicrometer structures may prove valuable in additional fields, including subcellular organelle and granule research.

Electron microscopy (EM) is the most versatile tool for the study of matter at scales ranging from subatomic to visible. The high vacuum environment and the charged irradiation require careful stabilization of many specimens of interest. Biological samples are particularly sensitive due to their composition of light elements suspended in an aqueous medium. Early investigators developed techniques of embedding and staining with heavy metal salts for contrast enhancement. Indeed, the Nobel Prize in 1974 recognized Claude, de Duve, and Palade for establishment of the field of cell biology, largely due to their developments in separation and preservation of cellular components for electron microscopy. A decade later, cryogenic fixation was introduced. Vitrification of the water avoids the need for dehydration and provides an ideal matrix in which the organic macromolecules are suspended; the specimen represents a native state, suddenly frozen in time at temperatures below -150 °C. The low temperature maintains a low vapor pressure for the electron microscope, and the amorphous nature of the medium avoids diffraction contrast from crystalline ice. Such samples are extremely delicate, however, and cryo-EM imaging is a race for information in the face of ongoing damage by electron irradiation. Through this journey, cryo-EM enhanced the resolution scale from membranes to molecules and most recently to atoms. Cryo-EM pioneers, Dubochet, Frank, and Henderson, were awarded the Nobel Prize in 2017 for high resolution structure determination of biological macromolecules.A relatively untapped feature of cryo-EM is its preservation of composition. Nothing is added and nothing removed. Analytical spectroscopies based on electron energy loss or X-ray emission can be applied, but the very small interaction cross sections conflict with the weak exposures required to preserve sample integrity. To what extent can we interpret quantitatively the pixel intensities in images themselves? Conventional cryo-transmission electron microscopy (TEM) is limited in this respect, due to the strong dependence of the contrast transfer on defocus and the absence of contrast at low spatial frequencies.Inspiration comes largely from a different modality for cryo-tomography, using soft X-rays. Contrast depends on the difference in atomic absorption between carbon and oxygen in a region of the spectrum between their core level ionization energies, the so-called water window. Three dimensional (3D) reconstruction provides a map of the local X-ray absorption coefficient. The quantitative contrast enables the visualization of organic materials without stain and measurement of their concentration quantitatively. We asked, what aspects of the quantitative contrast might be transferred to cryo-electron microscopy?Compositional contrast is accessible in scanning transmission EM (STEM) via incoherent elastic scattering, which is sensitive to the atomic number Z. STEM can be regarded as a high energy, low angle diffraction measurement performed pixel by pixel with a weakly convergent beam. When coherent diffraction effects are absent, that is, in amorphous materials, a dark field signal measures quantitatively the flux scattered from the specimen integrated over the detector area. Learning to interpret these signals will open a new dimension in cryo-EM. This Account describes our efforts so far to introduce STEM for cryo-EM and tomography of biological specimens. We conclude with some thoughts on further developments.

The Athabasca Oil Sands Region (AOSR) in Alberta, Canada, is an important source of atmospheric pollutants, such as aerosols, that have repercussions on both the climate and human health. We show that the mean freezing temperature of snow-borne particles from AOSR was elevated (−7.1 ± 1.8 °C), higher than mineral dust which freezes at ∼ −15 °C and is recognized as one of the most relevant ice nuclei globally. Ice nucleation of nanosized snow samples indicated an elevated freezing ability (−11.6 ± 2.0 °C), which was statistically much higher than snow-borne particles from downtown Montreal. AOSR snow had a higher concentration (∼2 orders of magnitude) of >100 nm particles than Montreal. Triple quadrupole ICP-(QQQ)-MS/MS analysis of AOSR and Montreal snow demonstrated that most concentrations of metals, including those identified as emerging nanoparticulate contaminants, were much more elevated in AOSR in contrast to Montreal: 34.1, 34.1, 16.6, 5.8, 0.3, 0.1, and 9.4 mg/m3 for Cr, Ni, Cu, As, Se, Cd, and Pb respectively, in AOSR and 1.3, 0.3, 2.0

Backgound and aims The low-density lipoprotein receptor-deficient (Ldlr−/−) mouse has been utilized by cardiovascular researchers for more than two decades to study atherosclerosis. However, there has not yet been a systematic effort to document the ultrastructural changes that accompany the progression of atherosclerotic plaque in this model. Methods Employing several different staining and microscopic techniques, including immunohistochemistry, as well as electron and polarized microscopy, we analyzed atherosclerotic lesion development in Ldlr−/− mice fed an atherogenic diet over time. Results Lipid-like deposits occurred in the subendothelial space after only one week of atherogenic diet. At two weeks, cholesterol crystals (CC) formed and increased thereafter. Lipid, CC, vascular smooth muscles cells, and collagen progressively increased over time, while after 4 weeks, relative macrophage content decreased. Accelerated accumulation of plate- and needle-shaped CC accompanied plaque core necrosis. Lastly, CC were surrounded by cholesterol microdomains, which co-localized with CC through all stages of atherosclerosis, indicating that the cholesterol microdomains may be a source of CC. Conclusions Here, we have documented, for the first time in a comprehensive way, atherosclerotic plaque morphology and composition from early to advanced stages in the Ldlr−/− mouse, one of the most commonly used animal models utilized in atherosclerosis research.

In sample preparation of biological samples for electron microscopy, many types of embedding media are widely used. Unfortunately, none of them is perfectly resistant to beam induced damage. The article is focused on mass loss measuring of pure epoxy resin EMbed 812 that replaced Epon – the most widely used embedding resin for biological electron microscopy, in a form of ultrathin sections with thicknesses ranging from 30 to 100 nm. The STEM imaging was performed in a quantitative way which allowed us to estimate the mass loss directly up to the total dose of 3000 e−/nm2. For data acquisition we used SEM equipped with a commercial STEM detector working at a relatively low acceleration voltage of 30 kV. In this study we estimated the influence of various factors which can affect the endurance of the epoxy resin EMbed 812 ultrathin sections under an electron beam, such as the sample aging, differences between storing the samples in forms of ultrathin sections and whole blocks, ultrathin sections thicknesses, temperature of the sample, probe current, and one or two-sided carbon coating of ultrathin sections. The aim of this work is to investigate beam induced mass loss at electron energies of SEM and find out how to reduce the mass loss.

Tissue regeneration has become a promising strategy for repairing damaged skin tissues. Among the hydrogels for tissue regeneration applications, topical hydrogels have demonstrated great potential for use as 3D-scaffolds in the burn wound healing process. Currently, no report has been published specifically on icariin-loaded polyvinyl alcohol (PVA)/agar hydrogel on full-thickness burn wounds. In the present study, burn tissue regeneration based on biomimetic hydrogel scaffolds was used for repairing damaged extracellular matrix. Furthermore, a skin burn model was developed in rats, and the icariin-loaded PVA/agar hydrogels were implanted into the damaged portions. The regeneration of the damaged tissues with the help of the icariin-loaded hydrogel group exhibited new translucent skin tissues and repaired extracellular matrix, indicating that the hydrogel can enhance the wound healing process. Moreover, characterization studies such as X-ray diffraction, Fourier-transformed infrared spectroscopy, and differential scanning calorimetry reported the extent of compatibility between icariin and its polymers. Results of the field emission scanning electron microscopy images revealed the extent of the spread of icariin within the polymer-based hydrogel. Furthermore, the wound healing potential, confirmed by histopathological and histochemical findings at the end of 21 days, revealed the visual evidence for the biomimetic property of icariin-loaded PVA/agar hydrogel scaffolds with the extracellular matrix for tissue regeneration.

The C-terminally truncated Y145Stop variant of prion protein (PrP23-144), which is associated with heritable PrP cerebral amyloid angiopathy in humans and also capable of triggering a transmissible prion disease in mice, serves as a useful in vitro model for investigating the molecular and structural basis of amyloid strains and cross-seeding specificities. Here, we determine the protein-solvent interfaces in human PrP23-144 amyloid fibrils generated from recombinant (13)C,(15)N-enriched protein and incubated in aqueous solution containing paramagnetic Cu(II)-EDTA, by measuring residue-specific (15)N longitudinal paramagnetic relaxation enhancements using two-dimensional magic-angle spinning solid-state NMR spectroscopy. To further probe the interactions of the amyloid core residues with solvent molecules we perform complementary measurements of amide hydrogen/deuterium exchange detected by solid-state NMR and solution NMR methods. The solvent accessibility data are evaluated in the context of the structural model for human PrP23-144 amyloid.

Intra-neuronal aggregation of alpha-synuclein into fibrils is the molecular basis for alpha-synucleinopathies, such as Parkinson's disease. The atomic structure of human alpha-synuclein (hAS) fibrils was recently determined by Tuttle et al. using solid-state NMR (ssNMR). The previous study found that hAS fibrils are composed of a single protofilament. Here, we have investigated the structure of mouse alpha-synuclein (mAS) fibrils by STEM and isotope-dilution ssNMR experiments. We found that in contrast to hAS, mAS fibrils consist of two or even three protofilaments which are connected by rather weak interactions in between them. Although the number of protofilaments appears to be different between hAS and mAS, we found that they have a remarkably similar secondary structure and protofilament 3D structure as judged by secondary chemical shifts and intra-molecular distance restraints. We conclude that the two mutant sites between hAS and mAS (positions 53 and 87) in the fibril core region are crucial for determining the quaternary structure of alpha-synuclein fibrils.

In the use of solution-based 3D nanoarchitectures for optics, drug delivery, and cancer treatment, the precise nanoparticle architecture morphologies, architecture sizes, interparticle distances, and the assembly stability are all critical to their functionality. 3D nanoparticle architectures in solution are difficult to characterize, as few techniques can provide individualized information on interparticle spacing (defined by linkage molecule), nanoparticle assembly size, morphology, and identification of false aggregation. Bulk characterization techniques, including small angle x-ray scattering, can provide architecture sizes, though they are unable to precisely measure differences within interparticle spacings for individual architectures and can falsely measure assemblies caused by non-linkage grouped nanoparticles. Two solution-based characterization techniques were used to determine which assembly type and linkage length would produce the fastest assembly rate for large DNA-directed gold nanoparticle assemblies. In-situ liquid-cell scanning transmission electron microscopy (LC-STEM), measured interparticle spacings between DNA-functionalized nanoparticles, and fluorescence correlation spectroscopy provided the bulk volume fraction of large and small assemblies for nanoparticle architectures that were assembled using two different types: (1) the hybrid assemblies join two complementary single-stranded DNA linkages, and (2) the bridged assemblies are comprised of single-stranded DNA (bridging component) that is double the length of two different complementary single-stranded DNA-functionalized gold nanoparticles. Assembly times were tested at 24-hrs intervals over 3 days. Statistics derived from the in-situ LC-STEM images provided data for interparticle distance measurements, which identified the fraction of nanoparticles within the images acquired that were at the expected double-stranded DNA-binding distance of the linkages (varied in three distances for each of the two different architectures). In general, longer linkage lengths assembled in the shortest amount of time. The bridged assemblies formed fewer large architectures at 24-hrs but ultimately assembled a greater fraction of nanoparticles, which was due to the longer functionalized DNA lengths for individual nanoparticles. Fluorescence correlation spectroscopy provided a bulk average of the gold nanoparticle assembly sizes over time, which supported the conclusions drawn from the in-situ LC-STEM data. The microscopy provided sub-2 nm precision in the interparticle distances between gold nanoparticles in a solution environment. This coupled microscopy and spectroscopy characterization approach can provide more detailed information than bulk characterization methods.