The shape- and structure-directing ability of capping agents, namely, acetic acid (AA) and folic acid (FA), has been analyzed in the synthesis of hollow plasmonic nanostructures via the nanoscale Kirkendall effect. FA was found to possess both shape-directing and structure-directing abilities when spherical solid Ag2O nanoparticles were transformed into hollow silver nanocubes (HAgNCs). In contrast, AA acted only as a structure-directing agent in the transformation from solid Ag2O nanospheres to hollow Ag nanospheres (HAgNSs). FA capping leads to enhanced plasmon tunability range from 535 to 640 nm in the hollow silver nanostructures. The size and shape of nanostructures were analyzed by high-resolution transmission electron microscopy (HRTEM). HRTEM revealed that the outer diameter of AA-capped HAgNSs is 50 ± 10 nm while edge-length for FA-capped HAgNCs is 100 ± 15 nm. The diameter of inner void space was found to be 30 ± 5 and 43 ± 5 nm for HAgNSs and HAgNCs, respectively. The phase purity of the hollow nanostructures was confirmed by X-ray diffraction and energy dispersive X-ray measurements. Due to unique structural and plasmonic features, FA-capped HAgNCs are well-suited for biomedical applications.

This study aimed to compare three methods of cell death assessment [trypan blue exclusion (TBE), propidium iodide viability assay (PIVA), and transmission electron microscopy] to evaluate fresh and frozen–thawed chicken primordial germ cells (PGCs). For this study, chicken PGCs were collected from ROSS 908 and Oravka breed hens, cryopreserved-thawed according to the protocol, and submitted for different cell death assessments. We observed significant differences between TBE and PIVA techniques in the detectable proportion of dead cells in fresh (14.14 ± 1.27 versus 7.16 ± 1.02%, respectively) and frozen–thawed (44.00 ± 2.11 versus 33.33 ± 1.67%, respectively) samples of the Oravka breed. Moreover, significant differences (p < 0.05) between TBE and PIVA techniques in the detectable proportion of dead cells in fresh (9.20 ± 0.60 versus 5.37 ± 0.51%) samples of ROSS 908 breed were recorded. Differences may be due to methodological, sensitivity, and toxicity features of each technique tested, where TB stains cell cytoplasm of dead cells and PI penetrates and intercalates into DNA of dead cells. Therefore, we suggest using a more precise and sensitive PIVA for viability evaluation of PGCs. Further research is needed to apply various fluorochromes for more detailed cell viability evaluation.

The fraction of organic matter present affects the fragmentation behavior of sialoliths; thus, pretherapeutic information on the degree of mineralization is relevant for a correct selection of lithotripsy procedures. This work proposes a methodology for in vivo characterization of salivary calculi in the pretherapeutic context. Sialoliths were characterized in detail by X-ray computed microtomography (μCT) in combination with atomic emission spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, and transmission electron microscopy. Correlative analysis of the same specimens was performed by in vivo and ex vivo helical computed tomography (HCT) and ex vivo μCT. The mineral matter in the sialoliths consisted essentially of apatite (89 vol%) and whitlockite (11 vol%) with average density of 1.8 g/cm3. In hydrated conditions, the mineral mass prevailed with 53 ± 13 wt%, whereas the organic matter, with a density of 1.2 g/cm3, occupied 65 ± 10% of the sialoliths’ volume. A quantitative relation between sialoliths mineral density and X-ray attenuation is proposed for both HCT and μCT.

In this work, we demonstrate a new system for the examination of gas interactions with surfaces via atom probe tomography. This system provides capability of examining the surface and subsurface interactions of gases with a wide range of specimens, as well as a selection of input gas types. This system has been primarily developed to aid the investigation of hydrogen interactions with metallurgical samples, to better understand the phenomenon of hydrogen embrittlement. In its current form, it is able to operate at pressures from 10−6 to 1000 mbar (abs), can use a variety of gasses, and is equipped with heating and cryogenic quenching capabilities. We use this system to examine the interaction of hydrogen with Pd, as well as the interaction of water vapor and oxygen in Mg samples.

The gray level co-occurrence matrix (GLCM) algorithm is a contemporary computational biology method which, today, is frequently used to detect small changes in texture that are not visible using conventional techniques. We demonstrate that the toxic compound 6-hydroxydopamine (6-OHDA) and iron oxide nanoparticles (IONPS) have opposite effects on GLCM features of cell nuclei. Saccharomyces cerevisiae yeast cells were treated with 6-OHDA and IONPs, and imaging with GLCM analysis was performed at three different time points: 30 min, 60 min, and 120 min after the treatment. A total of 200 cell nuclei were analyzed, and for each nucleus, 5 GLCM parameters were calculated: Angular second moment (ASM), Inverse difference moment (IDM), Contrast (CON), Correlation (COR) and Sum Variance (SVAR). Exposure to IONPs was associated with the increase of ASM and IDM while the values of SVAR and COR were reduced. Treatment with 6-OHDA was associated with the increase of SVAR and CON, while the values of nuclear ASM and IDM were reduced. This is the first study to indicate that IONPs and 6-OHDA have opposite effects on nuclear texture. Also, to the best of our knowledge, this is the first study to apply the GLCM algorithm in Saccharomyces cerevisiae yeast cells in this experimental setting.

Analysis of numerous filamentous structures in an image is often limited by the ability of algorithms to accurately segment complex structures or structures within a dense population. It is even more problematic if these structures continuously grow when recording a time-series of images. To overcome these issues we present DSeg; an image analysis program designed to process time-series image data, as well as single images, to segment filamentous structures. The program includes a robust binary level-set algorithm modified to use size constraints, edge intensity, and past information. We verify our algorithms using synthetic data, differential interference contrast images of filamentous prokaryotes, and transmission electron microscopy images of bacterial adhesion fimbriae. DSeg includes automatic segmentation, tools for analysis, and drift correction, and outputs statistical data such as persistence length, growth rate, and growth direction. The program is available at Sourceforge.

Several microscopy methods have been developed to assess the morphological changes in cells in the investigations of the mode of cell death in response to a stimulus. Our recent finding on the treatment of the IC50 concentration (26.67 μg/mL) of Polyalthia longifolia leaf extract indicated the induction of apoptotic cell death via the regulation of miRNA in HeLa cells. Hence, the current study was conducted to validate the function of these downregulated microRNAs in P. longifolia-treated HeLa cells using microscopic approaches. These include scanning electron microscope (SEM), transmission electron microscope (TEM), and acridine orange/propidium iodide (AO/PI)-based fluorescent microscopy techniques by observing the morphological alterations to cells after transfection with mimic miRNA. Interestingly, the morphological changes observed in this study demonstrated the apoptotic hallmarks, for instance, cell blebbing, cell shrinkage, cytoplasmic and nuclear condensation, vacuolization, cytoplasmic extrusion, and the formation of apoptotic bodies, which proved the role of dysregulated miRNAs in apoptotic HeLa cell death after treatment with the P. longifolia leaf extract. Conclusively, the current study proved the crucial role of downregulated miR-484 and miR-221-5p in the induction of apoptotic cell death in P. longifolia-treated HeLa cells using three approaches—SEM, TEM, and AO/PI-based fluorescent microscope.

Here, different tissue surfaces of tomato root were characterized employing atomic force microscopy on day 7 and day 21 of growth through Young's modulus and plasticity index. These parameters provide quantitative information regarding the mechanical behavior of the tomato root under fresh conditions in different locations of the cross-section of root [cell surface of the epidermis, parenchyma (Pa), and vascular bundles (Vb)]. The results show that the mechanical parameters depend on the indented region, tissue type, and growth time. Thereby, the stiffness increases in the cell surface of epidermal tissue with increasing growth time (from 9.19 ± 0.68 to 13.90 ± 1.68 MPa) and the cell surface of Pa tissue displays the opposite behavior (from 1.74 ± 0.49 to 0.48 ± 0.55); the stiffness of cell surfaces of Vb tissue changes from 10.60 ± 0.58 to 6.37 ± 0.53 MPa, all cases showed a statistical difference (p < 0.05). Viscoelastic behavior dominates the mechanical forces in the tomato root. The current study is a contribution to a better understanding of the cell mechanics behavior of different tomato root tissues during growth.

We have studied Bi2Se3 at its 2D-limit using scanning tunneling spectroscopy (STS). Bulk Bi2Se3 is a well-known topological insulator having gapless surface states. In the 2D limit, the interior of the material exhibits a band gap, whereas the periphery shows a gapless metallic state having a Dirac point. We demonstrate a method to tune the Fermi energy and hence the Dirac point of Bi2Se3 nanoplates through doping at the anionic site. For this purpose, STS measurements were carried out on the Bi2Se3 system. We have used bromide as a dopant, which turns the material to n-type in nature. As a result, STS studies infer that the Fermi energy (EF) shifted toward the conduction band and consequently the Dirac point could be found to move away from Fermi energy. Through STS measurements, we have demonstrated a correlation between the shift of Dirac point position and the dopant content. The size, shape, and compositions of Bi2Se3 nanoflakes and concentration of bromine in the doped nanostructures were determined using transmission electron microscopy, associated energy dispersive X-ray spectroscopy analysis, and X-ray diffraction.

In this paper, prediction models are proposed which allow the mineralogical characterization of particle systems observed by X-ray micro tomography (XMT). The models are calibrated using 2D image data obtained by a combination of scanning electron microscopy and energy dispersive X-ray spectroscopy in a planar cross-section of the XMT data. To reliably distinguish between different minerals the models are based on multidimensional distributions of certain particle characteristics describing, for example, their size, shape, and texture. These multidimensional distributions are modeled using parametric Archimedean copulas which are able to describe the correlation structure of complex multidimensional distributions with only a few parameters. Furthermore, dimension reduction of the multidimensional vectors of particle characteristics is utilized to make non-parametric approaches such as the computation of distributions via kernel density estimation viable. With the help of such distributions the proposed prediction models are able to distinguish between different types of particles among the entire XMT image.

Due to the low capacity of contemporary position-sensitive detectors in atom probe tomography (APT) to detect multiple events, material analyses that exhibit high numbers of multiple events are the most subject to compositional biases. To solve this limitation, some researchers have developed statistical correction algorithms. However, those algorithms are only efficient when one is confronted with homogeneous materials having nearly the same evaporation field between elements. Therefore, dealing with more complex materials must be accompanied by a better understanding of the signal loss mechanism during APT experiments. By modeling the evaporation mechanism and the whole APT detection system, it may be possible to predict compositional and spatial biases induced by the detection system. This paper introduces a systematic study of the impact of the APT detection system on material analysis through the development of a simulation tool.

In the context of microbiology, recent studies show the importance of ribonucleo-protein aggregates (RNPs) for the understanding of mechanisms involved in cell responses to specific environmental conditions. The assembly and disassembly of aggregates is a dynamic process, the characterization of the stage of their evolution can be performed by the evaluation of their number. The aim of this study is to propose a method to automatically determine the count of RNPs. We show that the determination of a precise count is an issue by itself and hence, we propose three textural approaches: a classical point of view using Haralick features, a frequency point of view with generalized Fourier descriptors, and a structural point of view with Zernike moment descriptors (ZMD). These parameters are then used as inputs for a supervised classification in order to determine the most relevant. An experiment using a specific Saccharomyces cerevisiae strain presenting a fusion between a protein found in RNPs (PAB1) and the green fluorescent protein was performed to benchmark this approach. The fluorescence was observed with two-photon fluorescence microscopy. Results show that the textural approach, by mixing ZMD with Haralick features, allows for the characterization of the number of RNPs.

Specimen survivability is a primary concern to those who utilize atom probe tomography (APT) for materials analysis. The state-of-the-art in understanding survivability might best be described as common-sense application of basic physics principles to describe failure mechanisms. For example, APT samples are placed under near-failure mechanical-stress conditions, so reduction in the force required to initiate field evaporation must provide for higher survivability—a common sense explanation of survivability. However, the interplay of various analytical conditions (or instrumentation) and how they influence survivability (e.g., decreasing the applied evaporation field improves survivability), and which factors have more impact than others has not been studied. In this paper, we report on the systematic analysis of a material composed of a silicon-dioxide layer surrounded on two sides by silicon. In total, 261 specimens were fabricated and analyzed under a variety of conditions to correlate statistically significant survivability trends with analysis conditions and other specimen characteristics. The primary result suggests that, while applied field/force plays an obvious role in survivability for this material, the applied field alone does not predict survivability trends for silicon/silicon-dioxide interfaces. The rate at which ions are extracted from the specimen (both in terms of ions-per-pulse and pulse-frequency) has similar importance.

Phototrophic microorganisms are the dominant populations in microbial mats, which play an important role in stabilizing sediments, such as happens in the Ebro Delta. These microorganisms are exposed to low metal concentrations over a long period of time. Distinct methods have been used to evaluate their toxic effect on the preservation of these ecosystems. Nevertheless, most of these techniques are difficult to apply in isolated phototrophs because (i) they usually form consortia with heterotrophic bacteria, (ii) are difficult to obtain in axenic cultures, and (iii) do not grow on solid media.

In this study, and for the first time, a combination of fast, non-invasive, and in vivo Confocal Laser Scanning Microscopy (CLSM) techniques were applied in a consortium of Scenedesmus sp. DE2009 to analyze its physiological state and viability under metal stress conditions. Microalga was more resistant to Pb followed by Cr and Cu. However, in multimetal combinations, the presence of Cu negatively affected microalga growth. Additionally, the inhibitory concentration (IC) values were also calculated by CLSM pigment analysis. The result determines a higher degree of toxicity for Cu and Cr in comparison to Pb. The high sensitivity of these CLSM-methods to detect low concentrations allows consideration of Scenedesmus sp. DE2009 as a good bioindicator of metal pollution in natural environments.

The difference in the defect structures produced by different ion masses in a tungsten lattice is investigated using 80 MeV Au7+ ions and 10 MeV B3+ ions. The details of the defects produced by ions in recrystallized tungsten foil samples are studied using transmission electron microscopy. Dislocations of type b = 1/2[111] and [001] were observed in the analysis. While highly energetic gold ion produced small clusters of defects with very few dislocation lines, boron has produced large and sparse clusters with numerous dislocation lines. The difference in the defect structures could be due to the difference in separation between primary knock-on atoms produced by gold and boron ions.