Cryo-electron tomography (cryo-ET) is a powerful technique that can provide unprecedented insight into protein-protein interactions and molecular machinery in a near-native state. The adoption of cryo-ET by life science research groups is hampered by the challenges associated with cryo-ET sample preparation. The current sample preparation process has many steps at which ice contamination may occur to negatively affect the final sample and data quality. A survey was conducted to better understand the effects and impact of ice contamination to the cryo-ET outcome. Over 80 cryo-electron microscopy users worldwide participated in our survey. The results are presented in this article. We furthermore discussed the currently available solutions that can alleviate the ice contamination problems to increase the sample yield and cryo-ET data output.

Although scanning transmission electron microscopy (STEM) images of individual heavy atoms were reported 50 years ago, the applications of atomic-resolution STEM imaging became wide spread only after the practical realization of aberration correctors on field-emission STEM/TEM instruments to form sub-Ångstrom electron probes. The innovative designs and advances of electron optical systems, the fundamental understanding of electron–specimen interaction processes, and the advances in detector technology all played a major role in achieving the goal of atomic-resolution STEM imaging of practical materials. It is clear that tremendous advances in computer technology and electronics, image acquisition and processing algorithms, image simulations, and precision machining synergistically made atomic-resolution STEM imaging routinely accessible. It is anticipated that further hardware/software development is needed to achieve three-dimensional atomic-resolution STEM imaging with single-atom chemical sensitivity, even for electron-beam-sensitive materials. Artificial intelligence, machine learning, and big-data science are expected to significantly enhance the impact of STEM and associated techniques on many research fields such as materials science and engineering, quantum and nanoscale science, physics and chemistry, and biology and medicine. This review focuses on advances of STEM imaging from the invention of the field-emission electron gun to the realization of aberration-corrected and monochromated atomic-resolution STEM and its broad applications.

Nanosized Platinum (Pt) nanocrystals (NCs) have been extensively investigated in catalytic fields because of their high reactivity due to the unique electron structure. However, the rarity and the high cost of Pt limit its applications in industry. To reduce the usage of Pt in catalytic industry, research interests have been extended to Pt-based nanoalloys. Among various nanostructures, nanoframes (NFs) showed promising catalytic performance even with a lower metallic loading dose. Herein, we report a facile and robust method to transfer the Pt-Ni tetrahexahedral (THH) NCs into THH NFs in which carbon monoxide (CO) plays a role of the “etching reagent”. The driving force of the etching is a formation of gaseous metallic complex, Ni(CO)4, known as Mond Process, preferentially dealloying nickel atoms along <100> directions of the Pt-Ni THH NCs. It is determined that the resultant Pt-Ni THH NFs possess an open, stable and high-index preserved nanostructure, in which the outside atomic layers are composed of only Pt atoms with surface strains. Compared to a solution-based etching process, this approach requires less etching time and generates a well-defined structure. The associated thermal annealing operation also releases extra internal stress, making the NFs more stable with fewer surface defects. Such Pt-Ni THH NFs show interesting potentials in the improvement of stability and activity as advanced catalysts.

Objectives: Huntington’s disease (HD) is a debilitating genetic disorder characterized by motor, cognitive and psychiatric abnormalities associated with neuropathological decline. HD pathology is the result of an extended chain of CAG (cytosine, adenine, guanine) trinucleotide repetitions in the HTT gene. Clinical diagnosis of HD requires the presence of an otherwise unexplained extrapyramidal movement disorder in a participant at risk for HD. Over the past 15 years, evidence has shown that cognitive, psychiatric, and subtle motor dysfunction is evident decades before traditional motor diagnosis. This study examines the relationships among subcortical brain volumes and measures of emerging disease phenotype in prodromal HD, before clinical diagnosis. Methods: The dataset includes 34 cognitive, motor, psychiatric, and functional variables and five subcortical brain volumes from 984 prodromal HD individuals enrolled in the PREDICT HD study. Using cluster analyses, seven distinct clusters encompassing cognitive, motor, psychiatric, and functional domains were identified. Individual cluster scores were then regressed against the subcortical brain volumetric measurements. Results: Accounting for site and genetic burden (the interaction of age and CAG repeat length) smaller caudate and putamen volumes were related to clusters reflecting motor symptom severity, cognitive control, and verbal learning. Conclusions: Variable reduction of the HD phenotype using cluster analysis revealed biologically related domains of HD and are suitable for future research with this population. Our cognitive control cluster scores show sensitivity to changes in basal ganglia both within and outside the striatum that may not be captured by examining only motor scores. (JINS, 2017, 23, 159–170)