Evidence for hard and soft substructures in thermoelectric SnSe

SnSe is a topical thermoelectric material with a low thermal conductivity which is linked to its unique crystal structure. We use low-temperature heat capacity measurements to demonstrate the presence of two characteristic vibrational energy scales in SnSe with Debye temperatures thetaD1 = 345(9) K and thetaD2 = 154(2) K. These hard and soft substructures are quantitatively linked to the strong and weak Sn-Se bonds in the crystal structure. The heat capacity model predicts the temperature evolution of the unit cell volume, confirming that this two-substructure model captures the basic thermal properties. Comparison with phonon calculations reveals that the soft substructure is associated with the low energy phonon modes that are responsible for the thermal transport. This suggests that searching for materials containing highly divergent bond distances should be a fruitful route for discovering low thermal conductivity materials.Comment: Accepted by Applied Physics Letter

To Learn or Not to Learn Features for Deformable Registration?

Feature-based registration has been popular with a variety of features ranging from voxel intensity to Self-Similarity Context (SSC). In this paper, we examine the question on how features learnt using various Deep Learning (DL) frameworks can be used for deformable registration and whether this feature learning is necessary or not. We investigate the use of features learned by different DL methods in the current state-of-the-art discrete registration framework and analyze its performance on 2 publicly available datasets. We draw insights into the type of DL framework useful for feature learning and the impact, if any, of the complexity of different DL models and brain parcellation methods on the performance of discrete registration. Our results indicate that the registration performance with DL features and SSC are comparable and stable across datasets whereas this does not hold for low level features.Comment: 9 pages, 4 figure

Different Quaternary Structures of Human RECQ1 Are Associated with Its Dual Enzymatic Activity

RecQ helicases are essential for the maintenance of chromosome stability. In addition to DNA unwinding, some RecQ enzymes have an intrinsic DNA strand annealing activity. The function of this dual enzymatic activity and the mechanism that regulates it is, however, unknown. Here, we describe two quaternary forms of the human RECQ1 helicase, higher-order oligomers consistent with pentamers or hexamers, and smaller oligomers consistent with monomers or dimers. Size exclusion chromatography and transmission electron microscopy show that the equilibrium between the two assembly states is affected by single-stranded DNA (ssDNA) and ATP binding, where ATP or ATPγS favors the smaller oligomeric form. Our three-dimensional electron microscopy reconstructions of human RECQ1 reveal a complex cage-like structure of approximately 120 Å × 130 Å with a central pore. This oligomeric structure is stabilized under conditions in which RECQ1 is proficient in strand annealing. In contrast, competition experiments with the ATPase-deficient K119R and E220Q mutants indicate that RECQ1 monomers, or tight binding dimers, are required for DNA unwinding. Collectively, our findings suggest that higher-order oligomers are associated with DNA strand annealing, and lower-order oligomers with DNA unwinding

Heterologous production of curcuminoids

Curcuminoids, components of the rhizome of turmeric, show several beneficial biological activities, including anticarcinogenic, antioxidant, anti-inflammatory, and antitumor activities. Despite their numerous pharmaceutically important properties, the low natural abundance of curcuminoids represents a major drawback for their use as therapeutic agents. Therefore, they represent attractive targets for heterologous production and metabolic engineering. The understanding of biosynthesis of curcuminoids in turmeric made remarkable advances in the last decade, and as a result, several efforts to produce them in heterologous organisms have been reported. The artificial biosynthetic pathway (e.g., in Escherichia coli) can start with the supplementation of the amino acid tyrosine or phenylalanine or of carboxylic acids and lead to the production of several natural curcuminoids. Unnatural carboxylic acids can also be supplemented as precursors and lead to the production of unnatural compounds with possibly novel therapeutic properties. In this paper, we review the natural conversion of curcuminoids in turmeric and their production by E. coli using an artificial biosynthetic pathway. We also explore the potential of other enzymes discovered recently or already used in other similar biosynthetic pathways, such as flavonoids and stilbenoids, to increase curcuminoid yield and activity.We acknowledge financial support from the Strategic Project PEst-OE/EQB/LA0023/2013, project reference RECI/BBB-EBI/0179/2012 (project number FCOMP-01-0124-FEDER-027462), project SYNBIOBACTHER (PTDC/EBB-BIO/102863/2008), and a doctoral grant (SFRH/BD/51187/ 2010) to J. L. Rodrigues, funded by Fundacao para a Ciencia e a Tecnologia. We thank the MIT-Portugal Program for support given to J. L. Rodrigues

Substantially thinner internal granular layer and reduced molecular layer surface in the cerebellum of the Tc1 mouse model of Down Syndrome - a comprehensive morphometric analysis with active staining contrast-enhanced MRI

Down Syndrome is a chromosomal disorder that affects the development of cerebellar cortical lobules. Impaired neurogenesis in the cerebellum varies among different types of neuronal cells and neuronal layers. In this study, we developed an imaging analysis framework that utilizes gadolinium-enhanced ex vivo mouse brain MRI. We extracted the middle Purkinje layer of the mouse cerebellar cortex, enabling the estimation of the volume, thickness, and surface area of the entire cerebellar cortex, the internal granular layer, and the molecular layer in the Tc1 mouse model of Down Syndrome. The morphometric analysis of our method revealed that a larger proportion of the cerebellar thinning in this model of Down Syndrome resided in the inner granule cell layer, while a larger proportion of the surface area shrinkage was in the molecular layer

Study the Longitudinal in vivo and Cross-Sectional ex vivo Brain Volume Difference for Disease Progression and Treatment Effect on Mouse Model of Tauopathy Using Automated MRI Structural Parcellation

Brain volume measurements extracted from structural MRI data sets are a widely accepted neuroimaging biomarker to study mouse models of neurodegeneration. Whether to acquire and analyze data in vivo or ex vivo is a crucial decision during the phase of experimental designs, as well as data analysis. In this work, we extracted the brain structures for both longitudinal in vivo and single-time-point ex vivo MRI acquired from the same animals using accurate automatic multi-atlas structural parcellation, and compared the corresponding statistical and classification analysis. We found that most gray matter structures volumes decrease from in vivo to ex vivo, while most white matter structures volume increase. The level of structural volume change also varies between different genetic strains and treatment. In addition, we showed superior statistical and classification power of ex vivo data compared to the in vivo data, even after resampled to the same level of resolution. We further demonstrated that the classification power of the in vivo data can be improved by incorporating longitudinal information, which is not possible for ex vivo data. In conclusion, this paper demonstrates the tissue-specific changes, as well as the difference in statistical and classification power, between the volumetric analysis based on the in vivo and ex vivo structural MRI data. Our results emphasize the importance of longitudinal analysis for in vivo data analysis

G-Quadruplex DNA Sequences Are Evolutionarily Conserved and Associated with Distinct Genomic Features in Saccharomyces cerevisiae

G-quadruplex DNA is a four-stranded DNA structure formed by non-Watson-Crick base pairing between stacked sets of four guanines. Many possible functions have been proposed for this structure, but its in vivo role in the cell is still largely unresolved. We carried out a genome-wide survey of the evolutionary conservation of regions with the potential to form G-quadruplex DNA structures (G4 DNA motifs) across seven yeast species. We found that G4 DNA motifs were significantly more conserved than expected by chance, and the nucleotide-level conservation patterns suggested that the motif conservation was the result of the formation of G4 DNA structures. We characterized the association of conserved and non-conserved G4 DNA motifs in Saccharomyces cerevisiae with more than 40 known genome features and gene classes. Our comprehensive, integrated evolutionary and functional analysis confirmed the previously observed associations of G4 DNA motifs with promoter regions and the rDNA, and it identified several previously unrecognized associations of G4 DNA motifs with genomic features, such as mitotic and meiotic double-strand break sites (DSBs). Conserved G4 DNA motifs maintained strong associations with promoters and the rDNA, but not with DSBs. We also performed the first analysis of G4 DNA motifs in the mitochondria, and surprisingly found a tenfold higher concentration of the motifs in the AT-rich yeast mitochondrial DNA than in nuclear DNA. The evolutionary conservation of the G4 DNA motif and its association with specific genome features supports the hypothesis that G4 DNA has in vivo functions that are under evolutionary constraint