Offspring of parents with recurrent depression: which features of parent depression index risk for offspring psychopathology?

Background: Parental depression is associated with an increased risk of psychiatric disorder in offspring, although outcomes vary. At present relatively little is known about how differences in episode timing, severity, and course of recurrentdepression relate to risk in children. The aim of this study was to consider the offspring of parents with recurrentdepression and examine whether a recent episode of parental depressionindexesrisk for offspringpsychopathology over and above these other parental depressionfeatures. <p/>Methods: Three hundred and thirty seven recurrently depressed parents and their offspring (aged 9–17) were interviewed as part of an ongoing study, the ‘Early Prediction of Adolescent Depression Study’. The Child and Adolescent Psychiatric Assessment was used to assess two child outcomes; presence of a DSM-IV psychiatric disorder and number of DSM-IV child-rated depression symptoms. <p/>Results: Children whose parents had experienced a recent episode of depression reported significantly more depression symptoms, and odds of child psychiatric disorder were doubled relative to children whose parents had not experienced a recent episode of depression. Past severity of parental depression was also significantly associated with child depression symptoms. <p/>Limitations: Statistical analyses preclude causal conclusions pertaining to parental depression influences on offspringpsychopathology; several features of parental depression were recalled retrospectively. <p/>Conclusions: This study suggests that particular features of parental depression, specifically past depression severity and presence of a recent episode, may be important indicators of risk for child psychiatric disorder and depressive symptoms

Bibliography on the Scyphozoa with selected references on Hydrozoa and Anthozoa

Our goal in assembling this bibliography has been to bring together literature references on all aspects of scyphozoan research. Compilation was begun in 1967 as a card file of references to publications on the Scyphozoa; selected references to hydrozoan and anthozoan studies that were considered relevant to the study of scyphozoans were included. In 1968, a major research program on the jellyfish of Chesapeake Bay was initiated at the Virginia Institute of Marine Science (VIMS) under Dr. E. B. Joseph, and work on the bibliography became an integral part of the program. In 1969 we began converting the bibliography into a form suitable for wider distribution, and in February 1970 a preliminary draft was completed. The present bibliography is an expanded and revised version of the preliminary draft

A Multi-level Algorithm for Quantum-impurity Models

A continuous-time path integral Quantum Monte Carlo method using the directed-loop algorithm is developed to simulate the Anderson single-impurity model in the occupation number basis. Although the method suffers from a sign problem at low temperatures, the new algorithm has many advantages over conventional algorithms. For example, the model can be easily simulated in the Kondo limit without time discretization errors. Further, many observables including the impurity susceptibility and a variety of fermionic observables can be calculated efficiently. Finally the new approach allows us to explore a general technique, called the multi-level algorithm, to solve the sign problem. We find that the multi-level algorithm is able to generate an exponentially large number of configurations with an effort that grows as a polynomial in inverse temperature such that configurations with a positive sign dominate over those with negative signs. Our algorithm can be easily generalized to other multi-impurity problems.Comment: 9 pages, 8 figure

Reports of Committees

Contains reports from the following committees of the Washington State Bar Association: Annotations to the Restatement of Law, Cooperation with American Bar Association, Corporation Law, Discipline and Disbarment, Judicial Administration, Law Enforcement, Law Examiners, Legislative Committee, Public Relations, Selection of Judges, and Unauthorized Practice of Law. Includes the auditor\u27s report

Host-Derived Artificial MicroRNA as an Alternative Method to Improve Soybean Resistance to Soybean Cyst Nematode

Citation: Tian, B., Li, J. R., Oakley, T. R., Todd, T. C., & Trick, H. N. (2016). Host-Derived Artificial MicroRNA as an Alternative Method to Improve Soybean Resistance to Soybean Cyst Nematode. Genes, 7(12), 13. doi:10.3390/genes7120122Citation: Tian, B., . . . & Trick, H. (2016). Host-Derived Artificial MicroRNA as an Alternative Method to Improve Soybean Resistance to Soybean Cyst Nematode. Genes, 7(12), 13. https://doi.org/10.3390/genes7120122The soybean cyst nematode (SCN), Heterodera glycines, is one of the most important pests limiting soybean production worldwide. Novel approaches to managing this pest have focused on gene silencing of target nematode sequences using RNA interference (RNAi). With the discovery of endogenous microRNAs as a mode of gene regulation in plants, artificial microRNA (amiRNA) methods have become an alternative method for gene silencing, with the advantage that they can lead to more specific silencing of target genes than traditional RNAi vectors. To explore the application of amiRNAs for improving soybean resistance to SCN, three nematode genes (designated as J15, J20, and J23) were targeted using amiRNA vectors. The transgenic soybean hairy roots, transformed independently with these three amiRNA vectors, showed significant reductions in SCN population densities in bioassays. Expression of the targeted genes within SCN eggs were downregulated in populations feeding on transgenic hairy roots. Our results provide evidence that host-derived amiRNA methods have great potential to improve soybean resistance to SCN. This approach should also limit undesirable phenotypes associated with off-target effects, which is an important consideration for commercialization of transgenic crops

Statistics of Wave Functions in Disordered Systems with Applications to Coulomb Blockade Peak Spacing

Despite considerable work on the energy-level and wavefunction statistics of disordered quantum systems, numerical studies of those statistics relevant for electron-electron interactions in mesoscopic systems have been lacking. We plug this gap by using a tight-binding model to study a wide variety of statistics for the two-dimensional, disordered quantum system in the diffusive regime. Our results are in good agreement with random matrix theory (or its extensions) for simple statistics such as the probability distribution of energy levels or spatial correlation of a wavefunction. However, we see substantial disagreement in several statistics which involve both integrating over space and different energy levels, indicating that disordered systems are more complex than previously thought. These are exactly the quantities relevant to electron-electron interaction effects in quantum dots; in fact, we apply these results to the Coulomb blockade, where we find altered spacings between conductance peaks and wider spin distributions than traditionally expected.Comment: Accepted for publication in Phys Rev

Discovery of Novel Nonactive Site Inhibitors of the Prothrombinase Enzyme Complex

© 2016 American Chemical Society. The risk of serious bleeding is a major liability of anticoagulant drugs that are active-site competitive inhibitors targeting the Factor Xa (FXa) prothrombin (PT) binding site. The present work identifies several new classes of small molecule anticoagulants that can act as nonactive site inhibitors of the prothrombinase (PTase) complex composed of FXa and Factor Va (FVa). These new classes of anticoagulants were identified, using a novel agnostic computational approach to identify previously unrecognized binding pockets at the FXa-FVa interface. From about three million docking calculations of 281 128 compounds in a conformational ensemble of FXa heavy chains identified by molecular dynamics (MD) simulations, 97 compounds and their structural analogues were selected for experimental validation, through a series of inhibition assays. The compound selection was based on their predicted binding affinities to FXa and their ability to successfully bind to multiple protein conformations while showing selectivity for particular binding sites at the FXa/FVa interface. From these, thirty-one (31) compounds were experimentally identified as nonactive site inhibitors. Concentration-based assays further identified 10 compounds represented by four small-molecule families of inhibitors that achieve dose-independent partial inhibition of PTase activity in a nonactive site-dependent and self-limiting mechanism. Several compounds were identified for their ability to bind to protein conformations only seen during MD, highlighting the importance of accounting for protein flexibility in structure-based drug discovery approaches