Fast pixelated detectors incorporating direct electron detection (DED) technology are increasingly being regarded as universal detectors for scanning transmission electron microscopy (STEM), capable of imaging under multiple modes of operation. However, several issues remain around the post-acquisition processing and visualization of the often very large multidimensional STEM datasets produced by them. We discuss these issues and present open source software libraries to enable efficient processing and visualization of such datasets. Throughout, we provide examples of the analysis methodologies presented, utilizing data from a 256 × 256 pixel Medipix3 hybrid DED detector, with a particular focus on the STEM characterization of the structural properties of materials. These include the techniques of virtual detector imaging; higher-order Laue zone analysis; nanobeam electron diffraction; and scanning precession electron diffraction. In the latter, we demonstrate a nanoscale lattice parameter mapping with a fractional precision ≤6 × 10−4 (0.06%).

Concurrent three-dimensional imaging of the renal vascular and tubular systems on the whole-kidney scale with capillary level resolution is labor-intensive and technically difficult. Approaches based on vascular corrosion casting and X-ray micro computed tomography (μCT), for example, suffer from vascular filling artifacts and necessitate imaging with an additional modality to acquire tubules. In this work, we report on a new sample preparation, image acquisition, and quantification protocol for simultaneous vascular and tubular μCT imaging of whole, uncorroded mouse kidneys. The protocol consists of vascular perfusion with the water-soluble, aldehyde-fixable, polymeric X-ray contrast agent XlinCA, followed by laboratory-source μCT imaging and structural analysis using the freely available Fiji/ImageJ software. We achieved consistent filling of the entire capillary bed and staining of the tubules in the cortex and outer medulla. After imaging at isotropic voxel sizes of 3.3 and 4.4 μm, we segmented vascular and tubular systems and quantified luminal volumes, surface areas, diffusion distances, and vessel path lengths. This protocol permits the analysis of vascular and tubular parameters with higher reliability than vascular corrosion casting, less labor than serial sectioning and leaves tissue intact for subsequent histological examination with light and electron microscopy.

Finasteride is commonly used in the management of alopecia and nodular prostatic hyperplasia. It was reported to have a harmful effect on spermatogenesis with subsequent infertility. Thus, this research was to determine the ameliorative effect of resveratrol against testicular damage caused by finasteride. Forty adult male rats were randomly divided into four main groups: group I acted as the control, group II was administrated resveratrol 20 mg/kg/day, group III was administrated finasteride 5 mg/kg/day, and group IV was administrated finasteride and resveratrol as in the previous groups. Finasteride induced a significant decrement in the testosterone and dihydrotestosterone levels. The level of malondialdehyde significantly increased, while the levels of glutathione peroxidase, superoxide dismutase, and catalase significantly decreased in the finasteride-administrated rats. Variable histopathological alterations in the testes were revealed in the form of irregular seminiferous tubules. Some seminiferous tubules appeared with degenerated germinal epithelium. Others showed detachment of their germinal epithelium. Congested blood vessels and homogeneous acidophilic substance in-between tubules were also detected. A significant decrement in PCNA positive cells and a significant increment in Bax expression were demonstrated. Ultrastructural examination showed Sertoli cells with rarefied cytoplasm. Vacuolated cytoplasm, shrunken nuclei, and dilated perinuclear spaces were also revealed in the spermatogonia, primary spermatocytes, and early spermatids. On the contrary, few changes were noticed in rats received resveratrol concomitant with finasteride. This study indicated that resveratrol exerted a potent ameliorative effect against testicular injury caused by finasteride.

Accurate elemental quantification of materials by X-ray detection techniques in electron microscopes or microprobes can only be carried out if the appropriate mass absorption coefficients (MACs) are known. With continuous advancements in experimental techniques, databases of MACs must be expanded in order to account for new detection limits. Soft X-ray emission spectroscopy (SXES) is a characterization technique that can detect emitted X-rays whose energies are in the range of 10 eV to 2 keV by using a varied-line-spaced grating. Transitions producing soft X-rays can be detected and accurate MACs are required for use in quantification. This work uses Monte Carlo modeling coupled with multivoltage SXES measurements in an electron probe micro-analyzer (EPMA) to compute MACs for the L2,3-M and Li Kα transitions in a variety of aluminum alloys. Electron depth distribution curves obtained by the software MC X-ray are used in a parametrized fitting equation. The MACs are calculated using a least-squares regression analysis. It is shown that X-ray distribution cross-sections at such low energies need to take into account additional contributions, such as Coster–Kronig transitions, Auger yields, and wave function effects in order to be accurate.

We describe a method to estimate background noise in atom probe tomography (APT) mass spectra and to use this information to enhance both background correction and quantification. Our approach is mathematically general in form for any detector exhibiting Poisson noise with a fixed data acquisition time window, at voltages varying through the experiment. We show that this accurately estimates the background observed in real experiments. The method requires, as a minimum, the z-coordinate and mass-to-charge-state data as input and can be applied retrospectively. Further improvements are obtained with additional information such as acquisition voltage. Using this method allows for improved estimation of variance in the background, and more robust quantification, with quantified count limits at parts-per-million concentrations. To demonstrate applications, we show a simple peak detection implementation, which quantitatively suppresses false positives arising from random noise sources. We additionally quantify the detectability of 121-Sb in a standardized-doped Si microtip as (1.5 × 10−5, 3.8 × 10−5) atomic fraction, α = 0.95. This technique is applicable to all modes of APT data acquisition and is highly general in nature, ultimately allowing for improvements in analyzing low ionic count species in datasets.

Hypoxia and nutrient deprivation are responsible for inducing malignant behavior in neoplastic cells. In these conditions, metabolic stress leads the cells to enhance their autophagic flux and to activate key molecules for homeostasis maintenance. Galectin-3 (Gal-3) is upregulated in pancreatic cancer and it is activated under the hypoxic atmosphere. We aimed to analyze the most effective autophagic-inducing conditions in pancreatic ductal adenocarcinoma cells and the effect exerted under these conditions in association with hypoxia on the Gal-3 expression. Gal-3 and the microtubule-associated protein light chain 3 beta (LC3) were accessed through western blot and immunofluorescence. Degradative vacuole quantification was analyzed by transmission electronic microscopy, and inhibition of Gal-3 was performed using siRNA. According to the analyses, the most effective conditions in the inducement of autophagy for PANC-1 and MIA PaCa-2 cells were nutritional deprivation and complete amino acid/glucose deprivation, respectively. PANC-1 cells presented higher Gal-3 when they were submitted to 24 h of nutritional deprivation alone and simultaneously nutritional and oxygen deprivation. Inhibition of Gal-3 causes a decrease of LC3 levels in all experimental conditions. These results confirm that Gal-3 is modulated by microenvironment factors and the possibility of Gal-3 participating in an adaptive response from PDAC cells to extreme conditions.

Atom probe tomography (APT) is used to quantify atomic-scale elemental and isotopic compositional variations within a very small volume of material (typically <0.01 µm3). The small analytical volume ideally contains specific compositional or microstructural targets that can be placed within the context of the previously characterized surface in order to facilitate a correct interpretation of APT data. In this regard, careful targeting and preparation are paramount to ensure that the desired target, which is often smaller than 100 nm, is optimally located within the APT specimen. Needle-shaped specimens required for atom probe analysis are commonly prepared using a focused ion beam scanning electron microscope (FIB-SEM). Here, we utilize FIB-SEM-based time-of-flight secondary ion mass spectrometry (ToF-SIMS) to illustrate a novel approach to targeting <100 nm compositional and isotopic variations that can be used for targeting regions of interest for subsequent lift-out and APT analysis. We present a new method for high-spatial resolution targeting of small features that involves using FIB-SEM-based electron deposition of platinum “buttons” prior to standard lift-out and sharpening procedures for atom probe specimen manufacture. In combination, FIB-ToF-SIMS analysis and application of the “button” method ensure that even the smallest APT targets can be successfully captured in extracted needles.

Symmetry is omnipresent in nature and we encounter symmetry routinely in our everyday life. It is also common on the microscopic level, where symmetry is often key to the proper function of core biological processes. The human brain is exquisitely well suited to recognize such symmetrical features with ease. In contrast, computational recognition of such patterns in images is still surprisingly challenging. In this paper we describe a mathematical approach to identifying smaller local symmetrical structures within larger images. Our algorithm attributes a local symmetry score to each image pixel, which subsequently allows the identification of the symmetrical centers of an object. Though there are already many methods available to detect symmetry in images, to the best of our knowledge, our algorithm is the first that is easily applicable in ImageJ/FIJI. We have created an interactive plugin in FIJI that allows the detection and thresholding of local symmetry values. The plugin combines the different reflection symmetry axis of a square to get a good coverage of reflection symmetry in all directions. To demonstrate the plugins potential, we analyzed images of bacterial chemoreceptor arrays and intracellular vesicle trafficking events, which are two prominent examples of biological systems with symmetrical patterns.