An introduction to scanning transmission electron microscopy for the study of protozoans.

Since its inception in the 1930s, transmission electron microscopy (TEM) has been a powerful method to explore the cellular structure of parasites. TEM usually requires samples of <100 nm thick and with protozoans being larger than 1 µm, their study requires resin embedding and ultrathin sectioning. During the past decade, several new methods have been developed to improve, facilitate, and speed up the structural characterisation of biological samples, offering new imaging modalities for the study of protozoans. In particular, scanning transmission electron microscopy (STEM) can be used to observe sample sections as thick as 1 µm thus becoming an alternative to conventional TEM. STEM can also be performed under cryogenic conditions in combination with cryo-electron tomography providing access to the study of thicker samples in their native hydrated states in 3D. This method, called cryo-scanning transmission electron tomography (cryo-STET), was first developed in 2014. This review presents the basic concepts and benefits of STEM methods and provides examples to illustrate the potential for new insights into the structure and ultrastructure of protozoans.

Caracterização de cubossomos não-iônicos em presença de proteínas modelo: uma abordagem estrutural e funcional / Characterization of non-ionic cubosomes in the presence of model pro­teins: a structural and functional approach

Uma área de pesquisa que vem ganhando muita atenção nos últimos anos é a nanome­dicina, com especial atenção para os sistemas com entrega controlada de fármacos, ou drug delivery. Dentre as diversas nanopartículas utilizadas para este fim, destacam-se os sistemas formados por lipídeos e polímeros, como por exemplo os lipossomos e os cubossomos. Neste trabalho, é estudada a influência estrutural da lisozima e da curcumina, proteínas modelo. A lisozima é uma enzima antimicrobiana produzida por animais e que faz parte do sistema imunológico. Ela é uma hidrolase glicosídica que catalisa a hidrólise dos componentes da parede celular de bactérias gram-positivas. Esta hidrólise, por sua vez, compromete a integridade das paredes celulares, causando a lise (e como consequência a morte) das bactérias. Curcumina é um composto cristalino de cor amarelada brilhante, encontrada no caule da Curcuma longa (ou açafrão), que tem sido utilizada como corante ou até mesmo como aditivo alimentar. Este composto tem sido uma grande aposta no tratamento de doenças crônicas como inflamação, artrite, síndrome metabólica, doença hepática, obesidade, doenças neurodegenerativas e principalmente canceres, sendo também utilizada em estudos como potencial agente antibacteriano. O principal objetivo deste trabalho é construir sistemas nanoestruturados com potencial de atuarem como sistemas antimicrobianos, com a liberação controlada de ambos dos fármacos. Estes sistemas são compostos por cubossomos de fitantriol (PHY) em ausência e presença da lisozima, da curcumina e de suas combinações, a fim de analisar ação antimicrobiana conjunta da lisozima e da curcumina. As técnicas biofísicas utilizadas para caracterizar essas partículas são SAXS (espalhamento de raios-X em baixos ângulos), DLS (espalhamento dinâmico de luz), Cryo-TEM (criomicroscopia eletrônica de transmissão) e NTA (análise de rastreamento de nanopartículas). Foi possível verificar que as formulações lipídicas são eficazes na formação de estruturas cúbicas com estabilidade desejável. As nanopartículas cúbicas demonstraram alta capacidade de encapsulação da lisozima e da curcumina. A cinética de liberação desses medicamentos mostrou-se promissora, sugerindo que a encapsulação dos fármacos é eficaz, bem como a liberação controlada e direcionada. Duas linhagens de bactérias foram estudadas, sendo que a E. coli, não sofreu nenhum dano citotóxico, enquanto a Bacillus subtilis sim. Tal resultado indica o potencial antimicrobiano do sistema para alguns tipos de bactérias

An area of research that has gained significant attention in recent years is nanomedicine, with a particular focus on drug delivery systems. Among the various nanoparticles used for this purpose, lipid and polymer-based systems, such as liposomes and cubosomes stand out. This study investigate the structural influence of encapsulating lysozyme and curcumin, model compounds. Lysozyme is an antimicrobial enzyme produced by animals and is part of the immune system. It is a glycosidic hydrolase that catalyzes the hydrolysis of components in the cell walls of gram-positive bacteria. This hydrolysis compromises the integrity of cell walls, leading to the lysis (and consequently the death) of bacteria. Curcumin is a bright yellow crystalline compound found in the stem of Curcuma longa (or turmeric), commonly used as a dye or even as a food additive. It has been a significant focus in the treatment of chronic diseases such as inflammation, arthritis, metabolic syndrome, liver disease, obesity, neurodegenerative diseases, and especially cancers. It is also studied as a potential antibacterial agent. The main objective of this study is to construct nanostructured systems with the potential to act as antimicrobial agents, with controlled release of both drugs. These systems consist of phytantriol (PHY) cubosomes in the absence and presence of lysozyme, curcumin, and their combinations to analyze the joint antimicrobial action of lysozyme and curcumin. Biophysical techniques used for characterization include Small-Angle X-ray Scattering (SAXS), Dynamic Light Scattering (DLS), Cryo-Transmission Electron Microscopy (Cryo-TEM), and Nanoparticle Tracking Analysis (NTA). It was observed that lipid formulations are effective in forming cubic structures with desirable stability. Cubic nanoparticles have demonstrated a high encapsulation capacity for lysozyme and curcumin. The release kinetics of these drugs have shown promise, suggesting that drug encapsulation is effective, as well as their controlled and targeted release. Two bacterial strains were studied, with E. coli showing no cytotoxic damage, while Bacillus subtilis did. This result indicates the antimicrobial potential of the system against types of bacteria

Dynamical scattering in ice-embedded proteins in conventional and scanning transmission electron microscopy.

Structure determination of biological macromolecules using cryogenic electron microscopy is based on applying the phase object (PO) assumption and the weak phase object (WPO) approximation to reconstruct the 3D potential density of the molecule. To enhance the understanding of image formation of protein complexes embedded in glass-like ice in a transmission electron microscope, this study addresses multiple scattering in tobacco mosaic virus (TMV) specimens. This includes the propagation inside the molecule while also accounting for the effect of structural noise. The atoms in biological macromolecules are light but are distributed over several nanometres. Commonly, PO and WPO approximations are used in most simulations and reconstruction models. Therefore, dynamical multislice simulations of TMV specimens embedded in glass-like ice were performed based on fully atomistic molecular-dynamics simulations. In the first part, the impact of multiple scattering is studied using different numbers of slices. In the second part, different sample thicknesses of the ice-embedded TMV are considered in terms of additional ice layers. It is found that single-slice models yield full frequency transfer up to a resolution of 2.5 Å, followed by attenuation up to 1.4 Å. Three slices are sufficient to reach an information transfer up to 1.0 Å. In the third part, ptychographic reconstructions based on scanning transmission electron microscopy (STEM) and single-slice models are compared with conventional TEM simulations. The ptychographic reconstructions do not need the deliberate introduction of aberrations, are capable of post-acquisition aberration correction and promise benefits for information transfer, especially at resolutions beyond 1.8 Å.

Low-energy scanning transmission electron microscopy applied to ice-embedded biological macromolecules.

In this report, we applied annular bright-field and annular dark-field low-energy (30 keV) scanning transmission electron microscopy imaging to a vitreous ice-embedded biological macromolecule, T4 phage, to investigate the applicability of these methods for morphological investigation and sample screening. Multiple camera lengths were examined to find the optimal acceptance angle for both modes. Image clarity differed substantially between the modes, with the presence of ice also strongly influencing the quality of acquired micrographs. In annular dark-field mode, the proper discrimination of electrons scattered by the specimen from those scattered by the background ice was found to be difficult due to the severe overlap of the scattered electrons. The resulting micrographs lacked clarity, and the ice-embedded phage particles could only be discerned after post-processing image adjustment. However, in annular bright-field mode, despite similar overlapping of the scattered electrons, it was possible to assess the morphology and intactness of the specimen in the embedding ice, suggesting that this mode may find utility in low-energy cryo-scanning transmission electron microscopy imaging methods.

Near-real-time diagnosis of electron optical phase aberrations in scanning transmission electron microscopy using an artificial neural network.

The key to optimizing spatial resolution in a state-of-the-art scanning transmission electron microscope is the ability to measure and correct for electron optical aberrations of the probe-forming lenses precisely. Several diagnostic methods for aberration measurement and correction have been proposed, albeit often at the cost of relatively long acquisition times. Here, we illustrate how artificial intelligence can be used to provide near-real-time diagnosis of aberrations from individual Ronchigrams. The demonstrated speed of aberration measurement is important because microscope conditions can change rapidly. It is also important for the operation of MEMS-based hardware correction elements, which have less intrinsic stability than conventional electromagnetic lenses.

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy.

Physics-driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) 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 (BO) 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.

Scanning Transmission Electron Microscopy in a Scanning Electron Microscope for the High-Throughput Imaging of Biological Assemblies.

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.

The Development of iDPC-STEM and Its Application in Electron Beam Sensitive Materials.

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.

Low-Dose Sparse-View HAADF-STEM-EDX Tomography of Nanocrystals Using Unsupervised Deep Learning.

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 three projection views recorded under low-dose conditions.

Effects of the Encapsulation Membrane in Operando Scanning Transmission Electron Microscopy.

Nanoscale tailoring of catalytic materials and Li-battery alternatives has elevated the importance of in situ gas-phase electron microscopy. Such advanced techniques are often performed using an environmental cell inserted into a conventional S/TEM setup, as this method facilitates concurrent electrochemical and temperature stimulations in a convenient and cost-effective manner. However, these cells are made by encapsulating gas between two insulating membranes, which introduces additional electron scattering. We have evaluated strengths and limitations of the gas-phase E-cell S/TEM technique, both experimentally and through simulations, across a variety of practical parameters. We reveal the degradation of image quality in an E-cell setup from various components and explore opportunities to improve imaging quality through intelligent choice of experimental parameters. Our results underscore the benefits of using an E-cell STEM technique, due to its versatility and excellent ability to suppress the exotic contributions from the membrane device.

ToTEM: A software for fast TEM image simulation.

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 SrTiO3 . Additionally, iDPC image of MFI-type zeolites with xylene molecules encapsulated in straight channels demonstrates the advantage of iDPC in detecting light molecules.

Atomic-Resolution Imaging of Small Organic Molecules on Graphene.

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 ∼102-104 individual molecules. In metalated porphyrin and phthalocyanine derivatives, these images contain an elementally sensitive contrast with up to 1.3 Å resolution─sufficient to distinguish individual carbon and nitrogen atoms. Importantly, our methods can be applied to molecules with low masses (∼0.6 kDa) and nanocrystalline domains containing just a few hundred molecules, making it possible to study systems for which large crystals cannot easily be grown. Our approach is enabled by low-background graphene substrates, which we show increase the molecules' critical dose by 2-7×. These results indicate a new route for low-dose, atomic-resolution electron microscopy imaging to solve the structures of small organic molecules.

Imaging biological samples by integrated differential phase contrast (iDPC) STEM technique.

Scanning transmission electron microscopy (STEM) is a powerful imaging technique and has been widely used in current material science research. The attempts of applying STEM (annual dark field (ADF)-STEM or annular bright field (ABF)-STEM) into biological research have been going on for decades while applications have still been limited because of the existing bottlenecks in dose efficiency and non-linearity in contrast. Recently, integrated differential phase contrast (iDPC) STEM technique emerged and achieved a linear phase contrast imaging condition, while resolving signals of light elements next to heavy ones even at low electron dose. This enables successful investigation of beam sensitive materials. Here, we investigate iDPC-STEM advantages in biology, in particular, chemically fixed and resin embedded biological tissues. By comparing results to the conventional TEM, we have found that iDPC-STEM not only shows better contrast but also resolves more structural details at molecular level, including conditions of extremely low dose and minimal heavy-atom staining. We also compare iDPC-STEM with ABF-STEM and found that contrast of iDPC-STEM is even further improved, moderately in lower frequency domains while highly with preserving high frequency biological structural details. For thick sample sections, iDPC-STEM is particularly advantageous. It avoids contrast inversion canceling effects, and by adjusting the depth of focus, fully preserves the contrast of structural details along with the sample. In addition, using depth-sectioning, iDPC-STEM enables resolving in-depth structural variation. Our results suggest that iDPC-STEM have the place and advantages within the future biological research.

Development of tilt-scan system for differential phase contrast scanning transmission electron microscopy.

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.

Tetradenia riparia leaves, flower buds, and stem essential oils to control of Aedes aegypti larvae

Abstract Tetradenia riparia (Hochst.) Codd (Lamiaceae) is a species native to the African continent and used as an insect repellent. The objective of the study was to evaluate the larvicidal potential of essential oils (EOs) from the leaves, flower buds, and stem of T. riparia, collected in winter against Aedes aegypti larvae. The EOs were extracted by hydrodistillation (3 h) and identified by GC/MS. The EOs were tested against larvae of A. aegypti at concentrations ranging from 12500 to 1.5 µg/mL for 24 h. The insecticide activity was evaluated by probit analysis, and the anticholinesterase activity was determined by bioautographic method. The results of the class projection indicated sesquiterpenes as the majority class, corresponding to 60.66% (leaves), 64.70% (flower buds) and 83.99% (stem), and the bioassays on A. aegypti larvae indicated LC50 of 1590, 675 and 665 µg/mL, respectively. The anticholinesterase activity indicated that the EO of the leaves inhibited the enzyme at a concentration of 780 µg/mL, and those from the flower buds and stem inhibited up to 1560 µg/mL. The results indicated weak activity of essential oils against A. aegypti larvae.

Essential Oil from the Stem Bark of Casuarina equisetifolia Exerts Anti-inflammatory and Anti-nociceptive Activities in Rats

Abstract Herein the chemical constituents and the anti-pain properties of the essential oil from the stem bark of Casuarina equisetifolia L. (Casuarinaceae) grown in Nigeria were evaluated. The essential oil was obtained by hydrodistillation method in an all glass Clevenger-type apparatus, and characterized by gas chromatography (GC-FID) and gas chromatography-mass spectrometry (GC-MS). The hot plate method was used to determine the anti-nociceptive property whereas the anti-inflammatory activity was evaluated by carrageenan-induced and formalin experimental models. The pale-yellow essential oil was obtained in yield of 0.21% (v/w), calculated on a dry weight basis. The main constituents of the essential oil were methyl salicylate (30.4%), a-zingiberene (15.5%), (E)-anethole (9.5%), b-bisabolene (8.6%), b- sesquiphellandrene (6.9%), and ar-curcumene (6.2%). In the anti-nociceptive study, the rate of inhibition increases as the doses of essential oil increases with optimum activity at the 30th and 60th min for all tested doses. The essential oil displayed anti-nociceptive activity independently of reaction time at the highest tested dose (200 mg/kg). The essential oil of C. equisetifolia moderately reduced pain responses in early and late phases of the formalin test. The oil inhibited the paw licking in the neurogenic phase (60-63%) compared to the late phase of the formalin test. The carrageenan- induced oedema model revealed the suppression of inflammatory mediators within the 1st - 3rd h. Thus, C. equisetifolia essential oil displayed both anti-nociceptive and anti-inflammatory activities independent of the dose tested. The anti-inflammatory and anti-nociceptive activities of C. equisetifolia essential oil are herein reported for the first time

Cepstral scanning transmission electron microscopy imaging of severe lattice distortions.

The development of four-dimensional (4D) scanning transmission electron microscopy (STEM) using fast detectors has opened-up new avenues for addressing some of longstanding challenges in electron imaging. One of these challenges is how to image severely distorted crystal lattices, such as at a dislocation core. Here we develop a new 4D-STEM technique, called Cepstral STEM, for imaging disordered crystals using electron diffuse scattering. In contrast to analysis based on Bragg diffraction, which measures the average and periodic scattering potential, electron diffuse scattering can detect fluctuations caused by crystal disorder. Local fluctuations of diffuse scattering are captured by scanning electron nanodiffraction (SEND) using a coherent probe. The harmonic signals in electron diffuse scattering are detected through Cepstral analysis and used for imaging. By integrating Cepstral analysis with 4D-STEM, we demonstrate that information about the distortive part of electron scattering potential can be separated and imaged at nm spatial resolution. We apply the technique to the analysis of a dislocation core in SiGe and lattice distortions in a high entropy alloy.

ab initio description of bonding for transmission electron microscopy.

The simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret their contrast and extract specimen features. This is especially true for high-resolution phase-contrast imaging of materials, but electron scattering simulations based on atomistic models are widely used in materials science and structural biology. Since electron scattering is dominated by the nuclear cores, the scattering potential is typically described by the widely applied independent atom model. This approximation is fast and fairly accurate, especially for scanning TEM (STEM) annular dark-field contrast, but it completely neglects valence bonding and its effect on the transmitting electrons. However, an emerging trend in electron microscopy is to use new instrumentation and methods to extract the maximum amount of information from each electron. This is evident in the increasing popularity of techniques such as 4D-STEM combined with ptychography in materials science, and cryogenic microcrystal electron diffraction in structural biology, where subtle differences in the scattering potential may be both measurable and contain additional insights. Thus, there is increasing interest in electron scattering simulations based on electrostatic potentials obtained from first principles, mainly via density functional theory, which was previously mainly required for holography. In this Review, we discuss the motivation and basis for these developments, survey the pioneering work that has been published thus far, and give our outlook for the future. We argue that a physically better justified ab initio description of the scattering potential is both useful and viable for an increasing number of systems, and we expect such simulations to steadily gain in popularity and importance.

Dynamic compressed sensing for real-time tomographic reconstruction.

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) 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 a 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 re-running the entire process.

Three-dimensional deconvolution processing for STEM cryotomography.

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.