Applied Microscopy最新文献

Spider capture silk is a natural scaffolding material that outperforms most synthetic materials in terms of its combination of strength and elasticity. Among the various kinds of silk threads, cribellar thread is the most primitive prey-capturing type of spider web material. We analyzed the functional organization of the sieve-like cribellum spigots and specialized calamistral comb bristles for capture thread production by the titanoecid spider Nurscia albofasciata. The outer cribellar surface is covered with thousands of tiny spigots, and the cribellar plate produces non-sticky threads composed of thousands of fine nanofibers. N. albofasciata cribellar spigots are typically about 10?μm long, and each spigot appears as a long individual shaft with a pagoda-like tiered tip. The five distinct segments comprising each spigot is a defining characteristic of this spider. This segmented and flexible structure not only allows for spigots to bend individually and join with adjacent spigots, but it also enables spigots to draw the silk fibrils from their cribella with rows of calamistral leg bristles to form cribellar prey-capture threads.

We investigate the sensitivity of symmetry quantification algorithms based on the profile R-factor (R_p) and the normalized cross-correlation (NCC) coefficient (γ). A DM (Digital Micrograph^?) script embedded in the Gatan digital microscopy software is used to develop the symmetry quantification program. Using the Bloch method, a variety of CBED patterns are simulated and used to investigate the sensitivity of symmetry quantification algorithms. The quantification results show that two symmetry quantification coefficients are significantly sensitive to structural changes even for small strain values of <?1%.

Brain disorders seriously affect life quality. Therefore, non-invasive neuroimaging has received attention to monitoring and early diagnosing neural disorders to prevent their progress to a severe level. This short review briefly describes the current MRI and PET/CT techniques developed for non-invasive neuroimaging and the future direction of optical imaging techniques to achieve higher resolution and specificity using the second near-infrared (NIR-II) region of wavelength with organic molecules.

Growing demands for comprehending complicated nano-scale phenomena in atomic resolution has attracted in-situ transmission electron microscopy (TEM) techniques for understanding their dynamics. However, simple to safe TEM sample preparation for in-situ observation has been limited. Here, we suggested the optical microscopy based micro-manipulating system for transferring TEM samples. By adopting our manipulator system, several types of samples from nano-wires to plate-like thin samples were transferred on micro-electro mechanical systems (MEMS) chip in a single step. Furthermore, the control of electrostatic force between the sample and the probe tip is found to be a key role in transferring process.

Neuromorphic systems require integrated structures with high-density memory and selector devices to avoid interference and recognition errors between neighboring memory cells. To improve the performance of a selector device, it is important to understand the characteristics of the switching process. As changes by switching cycle occur at local nanoscale areas, a high-resolution analysis method is needed to investigate this phenomenon. Atomic force microscopy (AFM) is used to analyze the local changes because it offers nanoscale detection with high-resolution capabilities. This review introduces various types of AFM such as conductive AFM (C-AFM), electrostatic force microscopy (EFM), and Kelvin probe force microscopy (KPFM) to study switching behaviors.

Histopathology is a well-established standard diagnosis employed for the majority of malignancies, including breast cancer. Nevertheless, despite training and standardization, it is considered operator-dependent and errors are still a concern. Fractal dimension analysis is a computational image processing technique that allows assessing the degree of complexity in patterns. We aimed here at providing a robust and easily attainable method for introducing computer-assisted techniques to histopathology laboratories. Slides from two databases were used: A) Breast Cancer Histopathological; and B) Grand Challenge on Breast Cancer Histology. Set A contained 2480 images from 24 patients with benign alterations, and 5429 images from 58 patients with breast cancer. Set B comprised 100 images of each type: normal tissue, benign alterations, in situ carcinoma, and invasive carcinoma. All images were analyzed with the FracLac algorithm in the ImageJ computational environment to yield the box count fractal dimension (Db) results. Images on set A on 40x magnification were statistically different (p?=?0.0003), whereas images on 400x did not present differences in their means. On set B, the mean Db values presented promissing statistical differences when comparing. Normal and/or benign images to in situ and/or invasive carcinoma (all p?<?0.0001). Interestingly, there was no difference when comparing normal tissue to benign alterations. These data corroborate with previous work in which fractal analysis allowed differentiating malignancies. Computer-aided diagnosis algorithms may beneficiate from using Db data; specific Db cut-off values may yield ~?99% specificity in diagnosing breast cancer. Furthermore, the fact that it allows assessing tissue complexity, this tool may be used to understand the progression of the histological alterations in cancer.