Adolf Hitler's Decision to Invade the Soviet Union

This study makes use not only of German documents captured during the Second World War but of personal accounts of major figures of the Third Reich and their testimony at the Nuremberg Trials. Organized into five chapters, this study surveys Nazi- Soviet relations from 1939 to 1941, from the German viewpoint, with emphasis on Adolf Hitler's assessment of Russian policies and Germany's wartime situation, both of which factors shaped his decision to invade the USSR. The conclusion is that Hitler saw his attack on the Soviet Union as a preventive war, carried out to destroy a growing threat to the Reich. He interpreted Russian activities during the period 1939-1941 as designed to strengthen the USSR strategically against Germany in preparation for intervention in the ongoing conflict with Britain

Molecular Mechanics of the α-Actinin Rod Domain: Bending, Torsional, and Extensional Behavior

α-Actinin is an actin crosslinking molecule that can serve as a scaffold and maintain dynamic actin filament networks. As a crosslinker in the stressed cytoskeleton, α-actinin can retain conformation, function, and strength. α-Actinin has an actin binding domain and a calmodulin homology domain separated by a long rod domain. Using molecular dynamics and normal mode analysis, we suggest that the α-actinin rod domain has flexible terminal regions which can twist and extend under mechanical stress, yet has a highly rigid interior region stabilized by aromatic packing within each spectrin repeat, by electrostatic interactions between the spectrin repeats, and by strong salt bridges between its two anti-parallel monomers. By exploring the natural vibrations of the α-actinin rod domain and by conducting bending molecular dynamics simulations we also predict that bending of the rod domain is possible with minimal force. We introduce computational methods for analyzing the torsional strain of molecules using rotating constraints. Molecular dynamics extension of the α-actinin rod is also performed, demonstrating transduction of the unfolding forces across salt bridges to the associated monomer of the α-actinin rod domain

Heritable Epigenetic Variation among Maize Inbreds

Epigenetic variation describes heritable differences that are not attributable to changes in DNA sequence. There is the potential for pure epigenetic variation that occurs in the absence of any genetic change or for more complex situations that involve both genetic and epigenetic differences. Methylation of cytosine residues provides one mechanism for the inheritance of epigenetic information. A genome-wide profiling of DNA methylation in two different genotypes of Zea mays (ssp. mays), an organism with a complex genome of interspersed genes and repetitive elements, allowed the identification and characterization of examples of natural epigenetic variation. The distribution of DNA methylation was profiled using immunoprecipitation of methylated DNA followed by hybridization to a high-density tiling microarray. The comparison of the DNA methylation levels in the two genotypes, B73 and Mo17, allowed for the identification of approximately 700 differentially methylated regions (DMRs). Several of these DMRs occur in genomic regions that are apparently identical by descent in B73 and Mo17 suggesting that they may be examples of pure epigenetic variation. The methylation levels of the DMRs were further studied in a panel of near-isogenic lines to evaluate the stable inheritance of the methylation levels and to assess the contribution of cis- and trans- acting information to natural epigenetic variation. The majority of DMRs that occur in genomic regions without genetic variation are controlled by cis-acting differences and exhibit relatively stable inheritance. This study provides evidence for naturally occurring epigenetic variation in maize, including examples of pure epigenetic variation that is not conditioned by genetic differences. The epigenetic differences are variable within maize populations and exhibit relatively stable trans-generational inheritance. The detected examples of epigenetic variation, including some without tightly linked genetic variation, may contribute to complex trait variation

Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD. © 2013 Liu et al

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

Recombinase technology: applications and possibilities

The use of recombinases for genomic engineering is no longer a new technology. In fact, this technology has entered its third decade since the initial discovery that recombinases function in heterologous systems (Sauer in Mol Cell Biol 7(6):2087–2096, 1987). The random insertion of a transgene into a plant genome by traditional methods generates unpredictable expression patterns. This feature of transgenesis makes screening for functional lines with predictable expression labor intensive and time consuming. Furthermore, an antibiotic resistance gene is often left in the final product and the potential escape of such resistance markers into the environment and their potential consumption raises consumer concern. The use of site-specific recombination technology in plant genome manipulation has been demonstrated to effectively resolve complex transgene insertions to single copy, remove unwanted DNA, and precisely insert DNA into known genomic target sites. Recombinases have also been demonstrated capable of site-specific recombination within non-nuclear targets, such as the plastid genome of tobacco. Here, we review multiple uses of site-specific recombination and their application toward plant genomic engineering. We also provide alternative strategies for the combined use of multiple site-specific recombinase systems for genome engineering to precisely insert transgenes into a pre-determined locus, and removal of unwanted selectable marker genes

THE SAMI GALAXY SURVEY: REVISITING GALAXY CLASSIFICATION THROUGH HIGH-ORDER STELLAR KINEMATICS

Recent cosmological hydrodynamical simulations suggest that integral field spectroscopy can connect the high-order stellar kinematic moments h3 (~skewness) and h4 (~kurtosis) in galaxies to their cosmological assembly history. Here, we assess these results by measuring the stellar kinematics on a sample of 315 galaxies, without a morphological selection, using 2D integral field data from the SAMI Galaxy Survey. A proxy for the spin parameter ($\lambda_{R_e}$) and ellipticity ($\epsilon_e$) are used to separate fast and slow rotators; there exists a good correspondence to regular and non-regular rotators, respectively, as also seen in earlier studies. We confirm that regular rotators show a strong h3 versus $V/\sigma$ anti-correlation, whereas quasi-regular and non-regular rotators show a more vertical relation in h3 and $V/\sigma$. Motivated by recent cosmological simulations, we develop an alternative approach to kinematically classify galaxies from their individual h3 versus $V/\sigma$ signatures. We identify five classes of high-order stellar kinematic signatures using Gaussian mixture models. Class 1 corresponds to slow rotators, whereas Classes 2-5 correspond to fast rotators. We find that galaxies with similar $\lambda_{R_e}-\epsilon_e$ values can show distinctly different h3-$V/\sigma$ signatures. Class 5 objects are previously unidentified fast rotators that show a weak h3 versus $V/\sigma$ anti-correlation. These objects are predicted to be disk-less galaxies formed by gas-poor mergers. From morphological examination, however, there is evidence for large stellar disks. Instead, Class 5 objects are more likely disturbed galaxies, have counter-rotating bulges, or bars in edge-on galaxies. Finally, we interpret the strong anti-correlation in h3 versus $V/\sigma$ as evidence for disks in most fast rotators, suggesting a dearth of gas-poor mergers among fast rotators.Comment: Accepted for Publication in The Astrophysical Journal. 35 pages and 30 figures, abstract abridged for arXiv submission. The key figures of the paper are: 7, 11, 12 , and 1

PHYSICOCHEMICAL CHARACTERIZATION OF LARGE UNILAMELLAR PHOSPHOLIPID-VESICLES PREPARED BY REVERSE-PHASE EVAPORATION

Properties of large unilamellar vesicles (LUV), composed of phosphatidylcholine and prepared by reverse-phase evaporation and subsequent extrusion through Unipore polycarbonate membranes, have been investigated and compared with those of small unilamellar vesicles (SUV) and of multilamellar vesicles (MLV). The unilamellar nature of the LUV is shown by 1H-NMR using Pr3+ as a shift reagent. The gel to liquid-crystalline phase transition of LUV composed of dipalmitoylphosphatidylcholine (DPPC) monitored by differential scanning calorimetry, fluorescence polarization of diphenylhexatriene and 90° light scattering, occurs at a slightly lower temperature (40.8°C) than that of MLV (42°C) and is broadened by about 50%. The phase transition of SUV is shifted to considerably lower temperatures (mid-point, 38°C) and extends over a wide temperature range. In LUV a well-defined pretransition is not observed. The permeability of LUV (DPPC) monitored by leakage of carboxyfluorescein, increases sharply at the phase transition temperature, and the extent of release is greater than that from MLV. Leakage from SUV occurs in a wide temperature range. Freeze-fracture electron microscopy of LUV (DPPC) reveals vesicles of 0.1-0.2 μm diameter with mostly smooth fracture faces. At temperatures below the phase transition, the larger vesicles in the population have angled faces, as do extruded MLV. A banded pattern, seen in MLV at temperatures between the pretransition and the main transition, is not observed in the smaller LUV, although the larger vesicles reveal a dimpled appearance. © 1983