Fast auto-acquisition tomography tilt series by using HD video camera in ultra-high voltage electron microscope.

Automatic system for electron tomography data collection in the ultra-high voltage electron microscope

The modulation transfer function (MTF) and the geometric errors of two flatbed scanners, a slow-scan CCD (SSC) camera and film, have been measured and compared. The geometric errors of the SSC camera and film have been measured using diffraction spots from a lipid crystal. The SSC camera was shown to have the smallest geometric errors while film had the best MTF. Even though film had the best MTF, this is significantly reduced when scanning the film, so that the MTF of the film and scanner combined are comparable to the MTF of the SSC camera.

Electron detection characteristics are summarized for the slow scan CCD (SSC) camera, imaging plates, and film. The advantage of each detector is demonstrated with the selected examples of electron diffraction and imaging. The Richardson-Lucy algorithm for image restoration is described and tested for images recorded with the SSC camera. The effectiveness of image restoration is demonstrated for the recorded high-resolution lattice image, energy-loss spectrum, and convergent beam electron diffraction (CBED) pattern.

A heterotrophic organism 1–2 billion years ago enslaved a cyanobacterium to become the first photosynthetic eukaryote, and has diverged globally. The primary phototrophs, glaucophytes, are thought to retain ancestral features of the first photosynthetic eukaryote, but examining the protoplast ultrastructure has previously been problematic in the coccoid glaucophyte Glaucocystis due to its thick cell wall. Here, we examined the three-dimensional (3D) ultrastructure in two divergent species of Glaucocystis using ultra-high voltage electron microscopy. Three-dimensional modelling of Glaucocystis cells using electron tomography clearly showed that numerous, leaflet-like flattened vesicles are distributed throughout the protoplast periphery just underneath a single-layered plasma membrane. This 3D feature is essentially identical to that of another glaucophyte genus Cyanophora, as well as the secondary phototrophs in Alveolata. Thus, the common ancestor of glaucophytes and/or the first photosynthetic eukaryote may have shown similar 3D structures.

Aerosols affect the climate system through various physical processes as they can scatter and absorb solar radiation, emit thermal radiation, or act as cloud condensation nuclei that modify the cloudiness coverage, changing then its albedo. Carbonaceous solid aerosols resulting either from anthropogenic processes or biomass burning are one of the most significant contributors to global climate change [1] with respect to their impact on radiative forcing. They are constituted by tiny primary spherules having a diameter typically ranging from a few nanometers to dozens nanometers. These spherules are aggregated to form particles of larger sizes (0.1 to 1 micrometre) showing a complex morphology (Figure 1) that plays an important role on their radiative and transport properties. These soot aggregates are commonly characterized from 2D transmission electron microscopy (TEM) images and their 3D shape is then deduced from TEM projections assuming geometrical models of spheres, cylinders or spheroids. In order to check the validity of the 2D to 3D transition of these geometrical models we investigated bright field (BF) TEM tomography and directly determine 3D soot morphological characteristics. To be suitable for tomographic reconstruction, images of the tilt series must fulfill the projection requirement and BF TEM images of amorphous specimen, which are dominated by mass‐thickness contrast, can satisfy this assumption. We show in this work that attention must be paid on the influence of defocus, responsible of the appearance of Fresnel fringes, which do not answer the projection requirement and can lead to artefacts that do not ensure a realistic reconstruction of soot aggregates. To do so, we analyse the effect of defocus both on real and numerical soot particles. Thus the same real soot aggregate is reconstructed (with the SIRT algorithm) from different tilt series obtained at different defocus values. Its surface area and volume are determined by using the Amira software suite after a segmentation step based on the method of Adachi et al [2]. The same procedure (reconstruction, segmentation, surface area measurement) is then applied on an amorphous numerical particle, which is generated using a tight binding model [3] processed with the Nanofabric software developed by Y.Lebouar. Projection series are simulated with the EMS software based on the multislice method [4]. Both experimental and numerical approaches show that defocus drastically modifies the intensity profile of primary particles along their diameter and subsequently affects the shape of the reconstructed aggregate (Figure 2) and leads to overestimated values of their surface area and volume.

EPiK-a Workflow for Electron Tomography in Kepler

Electron tomography (ET) is an outstanding technique to access information about nanoparticles whose properties are critically dependent on their 3D shape and structure. A particularly relevant application of ET concerns plasmonic chiral nanoparticles, which exhibit strong correlation between optical activity and asymmetric morphology. Thus, it is crucial to go beyond qualitative visual inspection of ET reconstructions and extract quantitative shape or chirality descriptors. However, the time‐consuming nature of conventional ET, where a series of 2D projection images is used for one 3D reconstruction, makes it challenging to collect statistically representative data. A recently proposed semi‐automated approach for the acquisition of the required tilt series can reduce the data collection time from typically ≈ 45 minutes–1 hour to less than 10 minutes. What remains unclear is how this method influences the quality of the reconstruction and the accuracy of the samples’ quantitative descriptors. Here, two sets of chiral gold nanoparticles with wrinkled or twisted morphological chirality are used. It is demonstrated that the fast tilt series acquisitions yield results that are consistent with conventional ET, provided a standardized data processing protocol is used. Finally, a practical example of how fast ET can be used to obtain more statistically relevant measurements is presented.

During the last decade, computation of a three-dimensional image from a tilt series (3D reconstruction) has become a well established method, of which a variety of implementations are available. The term “electron tomography” is now generally used for this type of data acquisition and 3D reconstruction. An overview over the techniques involved is given in. With the introduction of micro-processor-controlled TEMs and cooled slow-scan CCD cameras and with the progress in performance of high-speed computers, automation of complex imaging procedures became mainly a task of developing appropriate software, using the control facilities of the microscope. in this way, automated electron tomography was realized in 1990 at the Max- Planck-Institute for Biochemistry in Martinsried, and at about the same time at the University of California in San Francisco (UCSF). New techniques for automatic focusing and alignment, developed somewhat earlier, have been integrated in these automated tomography procedures. in the following we discuss the requirements of automatic data acquisition and the present implementation for several TEMs.

Electron tomography (ET) is a method for three-dimensional (3-D) reconstruction of single, transparent objects from a series of images (i.e., a tilt series) recorded with a transmission electron microscope (EM) (Fig. 4.1). The method is related to the procedures used in medical tomography. The 3-D reconstructions are usually computed from the digitized tilt series after a radial weighting scheme has been applied to the Fourier-transformed data. The ET method can be used to reconstruct in 3-D any object that is transparent enough for projection imaging with the transmission EM. This means that specimens of biological origin are usually available for ET 3-D reconstruction, whereas, e.g., colloidal gold particles are not. An ET-calculated 3-D map could be based on projections from objects that have been visualized by EM in several different ways, i.e., from stained or unstained objects, objects visualized at different energy loss levels or objects embedded in different media. The combined analysis of the 3-D structure, imaged in different ways, could thus become very informative. The general applicability also means that it is not restricted to symmetrical or regularly arranged objects, nor to objects with preferred orientations on a support grid. In its present state, the ET method allows reproducible 3-D reconstructions of single molecular objects, with a resolution in the range of 5 nm, of complex cellular specimens. For isolated objects, free of interfering cellular substances, a somewhat higher resolution can be achieved. The ET method covers the intermediate resolution range where there is no other physical technique available to analyze single molecular complexes.

Image quality of microns-thick specimens in the ultra-high voltage electron microscope

3D quantitative characterization of metal catalysts supported on heavy oxides by High Angle Annular Dark Field (HAADF) STEM electron tomography (ET) is a very challenging task. Noble metal nanoparticles (Au, Ru) supported on ceria or ceria mixed oxides illustrates the case. The difference, very small in some cases, between the atomic number (Z) of metal and support (Z Ru =44, Z Au =79, Z Ce =58) complicates the discrimination of the small particles. This makes that each step, acquisition, alignment, reconstruction and segmentation, has to be carefully optimized not only to improve the visualization of the nanoparticles but also to extract relevant quantitative results, e.g . metal loading, specific surface area, or particle size distribution. In this work, we have combined advanced image processing algorithms, based on undecimated wavelets transform (UWT) [1], to improve the contrast and denoising the tilt series projections, with new reconstruction algorithms, based on compressed sensing (CS) [2], to study a series of catalysts with a high potential in different processes related to the production of hydrogen, as CeO 2 Nanorods, Au/CeO 2 Nanocubes or Ru/Ce 2 Z 2 O 8 . The results obtained by ET have been compared to those determined by macroscopic characterization techniques as Inductively Coupled Plasma (ICP) or Brunauer, Emmett and Teller (BET) isotherm method. HAADF‐STEM ET has been carried out using a FEI TITAN 3 THEMIS 60‐300 operated at 200kV recently installed at Cadiz University. Data collections were obtained by tilting the specimen about a single axis perpendicular to the electron beam. Series of projections were acquired between ‐70º and +70° either every 2° or 5º. The images series were aligned using Inspect3D and TomoJ and reconstructed using the ASTRA Toolbox implemented in Matlab [3]. In the particular case of CS, Total Variation Minimization (TVM) was carried by using the TVAL3 solver [2]. Figure 1 shows the 3D‐rendered voxel of a catalyst consisting of Au nanoparticles supported on CeO 2 Nanocubes after reconstructing the raw tilt series by SIRT (Figure 1a) and TVM (Figure 1b) and after denoising the tilt series projections by UWT and reconstructed by SIRT (Figure 1c) and TVM (Figure1d). Note how in the case of UWT‐TVM reconstruction an important improvement in terms of morphology of the support and visualization of nanoparticles is obtained. The 3D rendered surface of a similar sample and the 3D quantifications of relevant properties as metal loading, specific surface area and average particle size are shown in Figure 2. It is important to point out how the values are quite similar to those determined by macroscopic characterization techniques. These results indicate that this combination of techniques allows determining nanostructural features representative of the catalysts at macroscopic level.

The end goal of the projects under the Philippine Institute of Volcanology and Seismology – Japan International Cooperation Agency – Japan Science and Technology Agency – Science and Technology Research Partnership for Sustainable Development (PHIVOLCS-JICA-JST-SATREPS) Program on Enhancement of Earthquake and Volcano Monitoring and Effective Utilization of Disaster Mitigation Information in the Philippines is to provide rapid, reliable and usable information on earthquakes, tsunamis, and volcanoes to the public. Component 4 of this program involves the provision of disaster mitigation information and promotion of utilization. Practical tools for the evaluation of vulnerability and safety of houses in the Philippines were developed in this component. Two tools were developed during the project; a 12-point questionnaire for self-check for earthquake safety of concrete hollow block houses in the Philippines (Tool 1) and a software program to evaluate the safety and earthquake vulnerability of houses (Tool 2). These tools aim to raise the awareness of stakeholders such as house owners, local engineers, building officials, and local government units, as well as function as an educational tool for the quick and simple evaluation of the vulnerability and safety of houses. The tools were disseminated to the specific users for enabling the effective utilization of disaster mitigation information. Various strategies were implemented for disseminating these tools: a launch activity was conducted during PHIVOLCS InfoSentro, an activity implemented by PHIVOLCS to update the public on its recent programs, projects, and activities; a copy of Tool 1 was uploaded on the PHIVOLCS website; training modules were developed; and training programs and workshops were conducted for users.

Electron tomography (ET) offers a unique capacity to image biological structures in situ. However, the resolution of ET reconstructed tomograms is not comparable to that of the single-particle cryo-EM. If many copies of the object of interest are present in the tomograms, their structures can be reconstructed in the tomogram, picked, aligned and averaged to increase the signal-to-noise ratio and improve the resolution, which is known as the subtomogram averaging. To date, the resolution improvement of the subtomogram averaging is still limited because each reconstructed subtomogram is of low reconstruction quality due to the missing wedge issue. In this article, we propose a novel computational model, the constrained reconstruction model (CRM), to better recover the information from the multiple subtomograms and compensate for the missing wedge issue in each of them. CRM is supposed to produce a refined reconstruction in the final turn of subtomogram averaging after alignment, instead of directly taking the average. We first formulate the averaging method and our CRM as linear systems, and prove that the solution space of CRM is no larger, and in practice much smaller, than that of the averaging method. We then propose a sparse Kaczmarz algorithm to solve the formulated CRM, and further extend the solution to the simultaneous algebraic reconstruction technique (SART). Experimental results demonstrate that CRM can significantly alleviate the missing wedge issue and improve the final reconstruction quality. In addition, our model is robust to the number of images in each tilt series, the tilt range and the noise level. The codes of CRM-SIRT and CRM-SART are available at https://github.com/icthrm/CRM. Supplementary data are available at Bioinformatics online.

Night imaging with modern smartphone cameras is troublesome due to low photon count and unavoidable noise in the imaging system. Directly adjusting exposure time and ISO ratings cannot obtain sharp and noise-free images at the same time in low-light conditions. Though many methods have been proposed to enhance noisy or blurry night images, their performances on real-world night photos are still unsatisfactory due to two main reasons: 1) Limited information in a single image and 2) Domain gap between synthetic training images and real-world photos (e.g., differences in blur area and resolution). To exploit the information from successive long- and short-exposure images, we propose a learning-based pipeline to fuse them. A D2HNet framework is developed to recover a high-quality image by deblurring and enhancing a long-exposure image under the guidance of a short-exposure image. To shrink the domain gap, we leverage a two-phase DeblurNet-EnhanceNet architecture, which performs accurate blur removal on a fixed low resolution so that it is able to handle large ranges of blur in different resolution inputs. In addition, we synthesize a D2-Dataset from HD videos and experiment on it. The results on the validation set and real photos demonstrate our methods achieve better visual quality and state-of-the-art quantitative scores. The D2HNet codes and D2-Dataset can be found at https://github.com/zhaoyuzhi/D2HNet.KeywordsNight image restorationImage denoisingImage deblurringDomain gap issue

Electron microscope tomography is a useful method for deriving three-dimensional (3-D) structures from tilt series. We used an intermediate, high-voltage electron microscope operated at 400 kV to study the 3-D structure of selectively stained or labeled mitochondria from diverse sources. We have examined the structure of neuronal mitochondria and mitochondria from brown adipose tissue (BAT) employing either single-axis or double-axis techniques over a tilt range of ±60° with 1° or 2° angular increments (Fig. 1). Although BAT mitochondria contains only lamellar cristae with no tubular cristae as we have observed in neuronal mitochondria, we found that the inner membrane of BAT mitochondria invaginates to form cristae only through narrow, tubular openings or crista junctions (Fig. 2). Recent interest in the possibility of structural artifacts in chemically fixed mitochondria imaged in situ motivated us to perform electron tomography on cryofixed brain and brown fat tissue.