Microscopy and Microanalysis最新文献

Accurate identification of local phases in nanocrystalline materials is essential for understanding their functional properties, but it remains a significant challenge for polymorphic materials to locally differentiate them at nanoscale. This challenge is further compounded in polycrystalline materials with randomly oriented grains and the coexistence of multiple phases. In this report, we present a methodology for phase and orientation identification at the nanoscale by leveraging vector pair correlation functions extracted from atomically resolved scanning transmission electron microscopy (STEM) images. We demonstrate the accuracy of the methodology on both simulated and experimental data from HfO2-based films, a material that exhibits multiple coexisting phases in films with thicknesses ranging from 5 to 20 nm. While demonstrated on HfO2 films, the methodology can be extended to other polymorphic nanocrystalline systems with complex phase coexistence.

The dermal arteries of the finger are organized in discrete units. We hypothesized that the anatomy of the dermal arterial units and the number and complexity of dermal Sucquet-Hoyer canals (SHCs) differ between the tip and center of the pad of the thumb. To test this, digital HREM volume datasets (voxel dimensions of 1-3 μm³) were created from biopsies harvested from the thumb tip and pad of six body donors. They were analyzed using virtual sectioning and three-dimensional (3D) surface and volume models. In the tip samples, two to six arteries entered the dermis via a square of 4 mm2 of the dermo-hypodermal junction. They supplied 1.16 mm2 surface and connected to ∼5.5 SHCs. Conversely, in 50% of pad samples, no dermal artery entered via the dermo-hypodermal junction. In the remaining 50%, one or two arteries supplied an average surface of 2.08 mm2 and fed ∼2.5 SHCs. SHC tortuosity and the number of arterio-arterial bridge anastomoses were similar in the tip and pad. Our results support the concept of discrete dermal arterial units. The differences in the dermal microanatomy between the thumb's tip and pad are of particular significance, since they may reflect distinct functional requirements and different reactions to injury and pathogens.

In forensic science, determining the postmortem interval (PMI) is considered a continuing challenge. Herein, 36 male albino rats were categorized into six equal groups. The study investigated the postmortem (PM) changes in the prostate at different time points (0, 0.5, 6, 24, 48, and 72 h) through assessment of DNA fragmentation, western blotting of caspase 3, immunohistochemistry (IHC) of Bax/Bcl2 and caspase 3, and histopathological changes. Each PMI showed a significant decrease (p < 0.05) in the mean DNA optical density versus the immediate postmortem group. Additionally, a time-dependent rise (p < 0.05) in the expression of the apoptotic markers Bax and caspase 3 was observed. The anti-apoptotic Bcl2 immunostaining showed strong positive immune expression within the nuclei of basal acinar cells from the moment of death until 6 h PM. The Bcl2 immunoreactivity decreased noticeably after 6 h and then gradually at 24, 48, and 72 h after death. The 72-h postmortem prostate displayed the highest expression of Bax and caspase 3, but the maximal fragmentation of DNA was noted at 0 h. We conclude that the determination of the PMI in the prostate tissues could be accomplished via assessment of the histopathological alterations, DNA fragmentation, and pro-/anti-apoptotic indicators.

Noise in scanning electron microscopy (SEM) often obscures details critical for accurate wafer defect inspection. Deep learning-based denoising methods have been widely used to address this problem, but they have two major limitations in SEM image denoising: lack of both efficient and powerful denoising methods, and poor generalization to image structures that are unseen during training. To this end, we propose Relaxed Noise2Noise with Input dropout (ReNIn), which includes components that address the above two issues. Firstly, our Relaxed Noise2Noise framework provides a much better trade-off between denoising performance and training data collection cost; namely, it shows nearly on-par denoising performance with much lower data collection cost than ordinary supervised learning-based methods. Secondly, we propose to apply the input dropout to boost generalization ability. It improves the performance of the images that are structurally different from the training images without compromising the performance of the normally structured images, thereby increasing the overall denoising performance. Consequently, our method supports downstream inspection tasks by reducing the failure rate in circle detection, which is a critical preprocessing step for circle-shaped product analysis. Overall, our ReNIn attains efficient training data collection cost with competitive denoising performance and enhances generalization capability across various structures.

Here, we explore the atomic number (Z) dependence of multislice electron ptychography and approaches to optimize Z sensitivity. Specifically, we show that ptychography's Z-dependence is highly dependent on the integrated area of an atom column considered. A monotonic Z-dependence is found when the reconstructed projected atomic potentials are integrated over a small region. When increasing the integration area, Z-contrast changes significantly, becoming highly nonmonotonic and following trends in the orbital shell-structure. Moreover, the reconstructed projected potential aligns with the transmission function phase with an overall deviation of only 2.4%. The nonmonotonic Z-dependence is further shown to be useful to accentuate contrast between certain elements, allowing for distinguishability of elements that are only a single atomic number apart, and even in > 20 nm thick samples. This is demonstrated for β-CuZn (Z=29 and 30), with the differentiability between the elements explored for different signal quantification methods. The impact of electron dose and finite effective source size are also considered. These results demonstrate that the atom column integration area can optimize ptychographic Z-contrast for specific applications and experimental conditions.

The performance of an integrated parallel beam wavelength-dispersive/energy-dispersive microanalysis system mounted on a field emission scanning electron microscope has been compared with that of a conventional electron microprobe, using the same reference samples and as close as possible operational conditions. Tests on standards of known composition reveal internally consistent results for the former, and no obvious advantage of wavelength-dispersive over energy-dispersive spectroscopy has emerged for major elements without peak overlaps. Rather, because an energy-dispersive spectrometer can acquire all energies of the X-ray spectrum concurrently, conveying a lower electron dose per atom, it has the advantage of being faster and milder to minerals. In all cases, however, element migration may be significant, especially for monovalent, large ionic radius elements such as K and Na.

The emission-based fluorescence resonance energy transfer (E-FRET), renowned for its rapid detection, noninvasiveness towards fluorophores, and compatibility with both wide-field and confocal microscopy, is extensively employed in dynamically monitoring intermolecular interactions within living cells. However, E-FRET requires manual screening of hundreds to thousands of images for regions meeting specific criteria, a labor-intensive process devoid of mature automation solutions. In this article, we introduce AutoFRET, the automated and efficient solution tailored for E-FRET experimentation. AutoFRET harnesses image processing algorithms to swiftly and precisely identify target regions amidst vast image datasets. Furthermore, to mitigate the impact of dead cells in images on experimental results, we devise a novel cell morphology-based approach for their identification and exclusion. AutoFRET significantly reduces the time commitment for E-FRET experimental data analysis, condensing the entire process to the minute level. Comprehensive experimental evaluations reveal an average accuracy exceeding 95% for AutoFRET. This research presents a highly automated and reliable platform that expeditiously quantifies molecular interactions in living cells leveraging FRET technology, poised to contribute to advancements in quantitative biological research.

Maintaining a strong immune system and protecting the body from chemicals is essential for overall well-being. The exploitation of the major plant-derived bioactive compounds potentially accounts for prospective immunomodulators. The advantages of plant protein and/or branched-chain amino acids (BCAAs) likely suggest their potential as effective alternative treatment against sustainable chemical damage; existing research regarding their biological impact remains inconclusive. Specifically, limited clarity on the effects of plant protein alone or in combination with BCAAs on the toxic model of carbon tetrachloride (CCl4) on tissue structure and apoptosis-related caspase-3 expression. The concern of this study was with the effectiveness of a plant protein composite with BCAAs in mitigating CCl4-induced histo-immunocytotoxicity using experimental rats (n = 28). Wistar rats were randomly divided into four groups (n = 7 each): Group 1 was control; group 2 was CCl4 only; group 3 was CCl4+BCAAs; while group 4 was CCl4+plant protein. CCl4 model was performed through intraperitoneal injection of l mL/kg b.wt. for three consecutive weeks. However, combined treatment by BCAAs or dietary protein groups exploited 30 g for seven consecutive weeks. Systemic evaluations focused on cell integrity and apoptosis-related gene expression, using Toluidine blue stain and caspase-3 immunohistochemistry, respectively. Histomorphological analysis confirmed tissue distortion significantly induced by CCl4. Immunohistochemical assessment accentuated that the apoptotic index regarding CCl4-treated organs was significantly higher (p < 0.05) than that of CCl4 + BCAAs, indicating the suppressive expression of caspase-3. Contradictory findings by co-administration of dietary protein and BCAAs with CCl4 protruded more substantial protective effects compared to combined BCAAs alone, indicating augmented protection against CCl4-induced immunotoxicity and cellular damage. In conclusion, dietary protein rich with BCAAs exhibited immunomodulatory properties and effectively preserved cellular integrity, particularly when challenged with CCl4. Our findings can serve as a valuable reference for future research aimed at refining recommendations on how dietary protein in combination with BCAAs specifically constrains cancer risks.

Atom probe tomography provides compositional mapping of materials at the nanoscale, and in that sense accurate reconstruction of the atomic positions is crucial for precise and accurate analysis. Here, we introduce the "APT Calibrator," developed in C#, a software tool that aids in the calibration of atom probe tomography reconstructions. It integrates essential calibration methods proposed over the past two decades to derive the key hyperparameters, such as the image compression factor and field reduction factor, allows for dynamic reconstruction of the data using a newly introduced method based on the use of fiducial markers that we refer to as "golden seed," and facilitates atom probe crystallographic analysis of microstructural defects. The software features a straightforward interface, simplifying the calibration process and making it more accessible.