Electron tomography imaging methods with diffraction contrast for materials research

MT-TN mutations lead to progressive mitochondrial encephalopathy and promotes mitophagy

Mitochondrial encephalopathy is a neurological disorder caused by impaired mitochondrial function and energy production. One of the genetic causes of this condition is the mutation of MT-TN, a gene that encodes the mitochondrial transfer RNA (tRNA) for asparagine. MT-TN mutations affect the stability and structure of the tRNA, resulting in reduced protein synthesis and complex enzymatic deficiency of the mitochondrial respiratory chain. Our patient cohort manifests with epileptic encephalopathy, ataxia, hypotonia, and bilateral basal ganglia calcification, which differs from previously reported cases. MT-TN mutation deficiency leads to decreased basal and maximal oxygen consumption rates, disrupted spare respiratory capacity, declined mitochondrial membrane potential, and impaired ATP production. Moreover, MT-TN mutations promote mitophagy, a process of selective degradation of damaged mitochondria by autophagy. Excessive mitophagy further leads to mitochondrial biogensis as a compensatory mechanism. In this study, we provided evidence of pathogenicity for two MT-TN mutations, m.5688 T > C and m.G5691A, explored the molecular mechanisms, and summarized the clinical manifestations of MT-TN mutations. Our study expanded the genotype and phenotypic spectrum and provided new insight into mt-tRNA (Asn)-associated mitochondrial encephalopathy.

A new method for obtaining the magnetic shape anisotropy directly from electron tomography images

A new methodology to obtain magnetic information on magnetic nanoparticle (MNP) systems via electron tomography techniques is reported in this work. The new methodology is implemented in an under-development software package called Magn3t, written in Python and C++. A novel image-filtering technique that reduces the highly undesired diffraction effects in the tomography tilt-series has been also developed in order to increase the reliability of the correlations between morphology and magnetism. Using the Magn3t software, the magnetic shape anisotropy magnitude and direction of magnetite nanoparticles has been extracted for the first time directly from transmission electron tomography.

Semi-Automated, Object-Based Tomography of Dislocation Structures

The characterization of the three-dimensional arrangement of dislocations is important for many analyses in materials science. Dislocation tomography in transmission electron microscopy is conventionally accomplished through intensity-based reconstruction algorithms. Although such methods work successfully, a disadvantage is that they require many images to be collected over a large tilt range. Here, we present an alternative, semi-automated object-based approach that reduces the data collection requirements by drawing on the prior knowledge that dislocations are line objects. Our approach consists of three steps: (1) initial extraction of dislocation line objects from the individual frames, (2) alignment and matching of these objects across the frames in the tilt series, and (3) tomographic reconstruction to determine the full three-dimensional configuration of the dislocations. Drawing on innovations in graph theory, we employ a node-line segment representation for the dislocation lines and a novel arc-length mapping scheme to relate the dislocations to each other across the images in the tilt series. We demonstrate the method for a dataset collected from a dislocation network imaged by diffraction-contrast scanning transmission electron microscopy. Based on these results and a detailed uncertainty analysis for the algorithm, we discuss opportunities for optimizing data collection and further automating the method.