Microscopy and Microanalysis最新文献

Aging is a biological process with gradual decrease of cell function. Kidneys are one of the organs with higher susceptibility to the development of age-dependent tissue damage. Intermittent fasting has several beneficial effects on age-related degenerative changes. The aim of this study was to investigate the possible beneficial effect of intermittent fasting in delaying age-related renal changes and the possible mechanisms of this effect. Thirty male albino rats were classified into three groups: control, adult rats aged 3 months; aged group, 15-month-old rats and maintained until the age of 18 months; and intermittent fasting-aged groups, 15-month-old rats maintained on intermittent fasting for 3 months. Kidneys were processed for histological and immunohistochemical study. Aging resulted in a significant reduction in renal function and significant several degenerative changes in renal corpuscles and tubules which showed abnormal histological structure with increased collagen deposition. Aging caused significant reduction in the expression of autophagic marker light chain 3 with increased expression of active caspase-3 and inducible nitric oxide synthase. Intermittent fasting significantly improved these age-related renal changes. Intermittent fasting effectively prevents age-related renal changes through the reduction of age-related oxidative stress, inflammation, apoptosis, and activation of autophagy.

This comprehensive study delved into the detrimental effects of cadmium (Cd), a toxic heavy metal, on the testicular lamina propria (LP), a key player in spermatogenesis, and the maintenance of testicular stem cell niches. Utilizing transmission electron microscopy, immunohistochemistry, and double-labeling immunofluorescence, the research characterized the structural and cellular components of mouse testicular LP under Cd exposure and investigated the protective effects of quercetin. The findings illustrated that Cd exposure results in significant morphological and cellular modifications within the LP, including the apoptosis of peritubular myoid cells, an upsurge in CD34+ stromal cells displaying anti-apoptotic behaviors, and an excessive production of collagen Type I fibers and extracellular matrix. Remarkably, quercetin effectively counteracted these adverse changes by reversing apoptosis, reducing the proliferation of CD34+ stromal cells, and addressing fibrosis markers, thereby mitigating the cellular damage induced by Cd. This study not only highlighted the critical impact of apoptosis and fibrosis in Cd-related testicular damage but also elucidated the protective mechanism of quercetin, laying the groundwork for future clinical applications in addressing testicular damage from heavy metal poisoning through cellular therapeutics and pharmacological interventions.

The first attempts of bacteria observation started with the use of glass lenses to generate magnified images of specimens. This technique is constrained by the principal limit to the resolution of any optical system. Besides optical microscopy, other imaging techniques emerged to reveal more levels of details. The more the achievable resolution, the more complex the imaging systems, and at the same time, the more potentially cell-killing or DNA-damaging they may become. This article provides a state of the art of nonconventional sensor techniques that have been used in applications related to bacteria imaging, for the purpose of comparing the information they provide and determine their suitability or find out if their combination can yield new results without compromising the ability to keep the cells alive.

Integrating deep learning into image analysis for transmission electron microscopy (TEM) holds significant promise for advancing materials science and nanotechnology. Deep learning is able to enhance image quality, to automate feature detection, and to accelerate data analysis, addressing the complex nature of TEM datasets. This capability is crucial for precise and efficient characterization of details on the nano-and microscale, e.g., facilitating more accurate and high-throughput analysis of nanoparticle structures. This study investigates the influence of batch normalization (BN) and instance normalization (IN) on the performance of deep learning models for semantic segmentation of high-resolution TEM images. Using U-Net and ResNet architectures, we trained models on two different datasets. Our results demonstrate that IN consistently outperforms BN, yielding higher Dice scores and Intersection over Union metrics. These findings underscore the necessity of selecting appropriate normalization methods to maximize the performance of deep learning models applied to TEM images.

We report a large-angle rocking beam electron diffraction (LARBED) technique for electron diffraction analysis. Diffraction patterns are recorded in a scanning transmission electron microscope (STEM) using a direct electron detector with large dynamical range and fast readout. We use a nanobeam for diffraction and perform the beam double rocking by synchronizing the detector with the STEM scan coils for the recording. Using this approach, large-angle convergent beam electron diffraction (LACBED) patterns of different reflections are obtained simultaneously. By using a nanobeam, instead of a focused beam, the LARBED technique can be applied to beam-sensitive crystals as well as crystals with large unit cells. This paper describes the implementation of LARBED and evaluates the performance using silicon and gadolinium gallium garnet crystals as test samples. We demonstrate that our method provides an effective and robust way for recording LARBED patterns and paves the way for quantitative electron diffraction of large unit cell and beam-sensitive crystals.

The Bayesian genetic algorithm (BGA) is a powerful tool to reconstruct the 3D structure of mono-atomic single-crystalline metallic nanoparticles imaged using annular dark field scanning transmission electron microscopy. The number of atoms in a projected atomic column in the image is used as input to obtain an accurate and atomically precise reconstruction of the nanoparticle, taking prior knowledge and the finite precision of atom counting into account. However, as the number of parameters required to describe a nanoparticle with atomic detail rises quickly with the size of the studied particle, the computational costs of the BGA rise to prohibitively expensive levels. In this study, we investigate these computational costs and propose methods and control parameters for efficient application of the algorithm to nanoparticles of at least up to 10 nm in size.

Ten years ago, the term "resolution revolution" was used for the first time to describe how cryogenic electron microscopy (cryo-EM) marked the beginning of a new era in the field of structural biology, enabling the investigation of previously unsolvable protein targets. The success of cryo-EM was recognized with the 2017 Chemistry Nobel Prize and has become a widely used method for the structural characterization of biological macromolecules, quickly catching up to x-ray crystallography. Bioenergetics is the division of biochemistry that studies the mechanisms of energy conversion in living organisms, strongly focused on the molecular machines (enzymes) that carry out these processes in cells. As bioenergetic enzymes can be arranged in complexes characterized by conformational heterogeneity/flexibility, they represent challenging targets for structural investigation by crystallography. Over the last decade, cryo-EM has therefore become a powerful tool to investigate the structure and function of bioenergetic complexes; here, we provide an overview of the main achievements enabled by the technique. We first summarize the features of cryo-EM and compare them to x-ray crystallography, and then, we present the exciting discoveries brought about by cryo-EM, particularly but not exclusively focusing on the oxidative phosphorylation system, which is a crucial energy-converting mechanism in humans.

Atom probe tomography data are composed of a list of coordinates of the reconstructed atoms in the probed volume. The elemental identity of each atom is derived from time-of-flight mass spectrometry, with no local chemical information readily available. In this study, we use a data processing technique referred to as field evaporation energy loss spectroscopy (FEELS), which analyzes the tails of mass peaks. FEELS was used to extract critical energetic parameters that are related to the activation energy for atoms to escape from the surface under intense electrostatic field and dependent of the path followed by the departing atoms. We focused our study on pure face-centered cubic metals. We demonstrate that the energetic parameters can be mapped in two-dimensional with nanometric resolution. A dependence on the considered crystallographic planes is observed, with sets of planes of low Miller indices showing a lower sensitivity to the field. The temperature is also an important parameter in particular for aluminum, which we attribute to an energetic transition between two paths of field evaporation between 25 and 60 K close to (002) pole. This paper shows that the information that can be retrieved from the measured energy loss of surface atoms is important both experimentally and theoretically.

As hydrogen is touted as a key player in the decarbonization of modern society, it is critical to enable quantitative hydrogen (H) analysis at high spatial resolution and, if possible, at the atomic scale. H has a known deleterious impact on the mechanical properties (strength, ductility, toughness) of most materials that can hinder their use as part of the infrastructure of a hydrogen-based economy. Enabling H mapping including local hydrogen concentration analyses at specific microstructural features is essential for understanding the multiple ways that H affect the properties of materials including embrittlement mechanisms and their synergies. In addition, spatial mapping and quantification of hydrogen isotopes is essential to accurately predict tritium inventory of future fusion power plants thus ensuring their safe and efficient operation. Atom probe tomography (APT) has the intrinsic capability to detect H and deuterium (D), and in principle the capacity for performing quantitative mapping of H within a material's microstructure. Yet, the accuracy and precision of H analysis by APT remain affected by complex field evaporation behavior and the influence of residual hydrogen from the ultrahigh vacuum chamber that can obscure the signal of H from within the material. The present article reports a summary of discussions at a focused workshop held at the Max-Planck Institute for Sustainable Materials in April 2024. The workshop was organized to pave the way to establishing best practices in reporting APT data for the analysis of H. We first summarize the key aspects of the intricacies of H analysis by APT and then propose a path for better reporting of the relevant data to support interpretation of APT-based H analysis in materials.

The biocompatibility and resorption characteristics of β-tricalcium phosphate (β-TCP, Ca3(PO4)2) have made it a coveted alternative for bone grafts. However, the underlying mechanisms governing the biological interactions between β-tricalcium phosphate and osteoclasts remain elusive. It has been speculated that the composition at grain boundaries might vary and affect β-TCP resorption properties. Atom probe tomography (APT) offers a quantitative approach to assess the composition of the grain boundaries, and thus advance our comprehension of the biological responses within the microstructure and chemical composition at the nanoscale. The precise quantitative analysis of chemical composition remains a notable challenge in APT, primarily due to the influence of measurement conditions on compositional accuracy. In this study, we investigated the impact of laser pulse energy on the composition of β-TCP using APT, aiming for the most precise Ca:P ratio and consistent results across multiple analyses performed with different sets of analysis conditions and on two different instruments.