Adaptive genetic markers discriminate migratory runs of Chinook salmon (Oncorhynchus tshawytscha) amid continued gene flow

Neutral genetic markers are routinely used to define distinct units within species that warrant discrete management. Human-induced changes to gene flow however may reduce the power of such an approach. We tested the efficiency of adaptive versus neutral genetic markers in differentiating temporally divergent migratory runs of Chinook salmon (Oncorhynchus tshawytscha) amid high gene flow owing to artificial propagation and habitat alteration. We compared seven putative migration timing genes to ten microsatellite loci in delineating three migratory groups of Chinook in the Feather River, CA: offspring of fall-run hatchery broodstock that returned as adults to freshwater in fall (fall run), spring-run offspring that returned in spring (spring run), and fall-run offspring that returned in spring (FRS). We found evidence for significant differentiation between the fall and federally listed threatened spring groups based on divergence at three circadian clock genes (OtsClock1b, OmyFbxw11, and Omy1009UW), but not neutral markers. We thus demonstrate the importance of genetic marker choice in resolving complex life history types. These findings directly impact conservation management strategies and add to previous evidence from Pacific and Atlantic salmon indicating that circadian clock genes influence migration timing.Keywords: conservation genetics, ecological genetics, captive populations, conservation biology, life history evolution, hybridization, population genetics, fisheries managemen

Thermodynamically Important Contacts in Folding of Model Proteins

We introduce a quantity, the entropic susceptibility, that measures the thermodynamic importance-for the folding transition-of the contacts between amino acids in model proteins. Using this quantity, we find that only one equilibrium run of a computer simulation of a model protein is sufficient to select a subset of contacts that give rise to the peak in the specific heat observed at the folding transition. To illustrate the method, we identify thermodynamically important contacts in a model 46-mer. We show that only about 50% of all contacts present in the protein native state are responsible for the sharp peak in the specific heat at the folding transition temperature, while the remaining 50% of contacts do not affect the specific heat.Comment: 5 pages, 5 figures; to be published in PR

Platform Dependent Verification: On Engineering Verification Tools for 21st Century

The paper overviews recent developments in platform-dependent explicit-state LTL model checking.Comment: In Proceedings PDMC 2011, arXiv:1111.006

Compact Difference Bound Matrices

The Octagon domain, which tracks a restricted class of two variable inequality, is the abstract domain of choice for many applications because its domain operations are either quadratic or cubic in the number of program variables. Octagon constraints are classically represented using a Difference Bound Matrix (DBM), where the entries in the DBM store bounds c for inequalities of the form x_i - x_j <= c, x_i + x_j <= c or -x_i - x_j <= c. The size of such a DBM is quadratic in the number of variables, giving a representation which can be excessively large for number systems such as rationals. This paper proposes a compact representation for DBMs, in which repeated numbers are factored out of the DBM. The paper explains how the entries of a DBM are distributed, and how this distribution can be exploited to save space and significantly speed-up long-running analyses. Moreover, unlike sparse representations, the domain operations retain their conceptually simplicity and ease of implementation whilst reducing memory usage

Elevated Stress-Hemoconcentration in Major Depression Is Normalized by Antidepressant Treatment: Secondary Analysis from a Randomized, Double-Blind Clinical Trial and Relevance to Cardiovascular Disease Risk

Major depressive disorder (MDD) is an independent risk factor for cardiovascular disease (CVD); the presence of MDD symptoms in patients with CVD is associated with a higher incidence of cardiac complications following acute myocardial infarction (MI). Stress-hemoconcentration, a result of psychological stress that might be a risk factor for the pathogenesis of CVD, has been studied in stress-challenge paradigms but has not been systematically studied in MDD.Secondary analysis of stress hemoconcentration was performed on data from controls and subjects with mild to moderate MDD participating in an ongoing pharmacogenetic study of antidepressant treatment response to desipramine or fluoxetine. Hematologic and hemorheologic measures of stress-hemoconcentration included blood cell counts, hematocrit, hemoglobin, total serum protein, and albumin, and whole blood viscosity.Subjects with mild to moderate MDD had significantly increased hemorheologic measures of stress-hemoconcentration and blood viscosity when compared to controls; these measures were correlated with depression severity. Measures of stress-hemoconcentration improved significantly after 8 weeks of antidepressant treatment. Improvements in white blood cell count, red blood cell measures and plasma volume were correlated with decreased severity of depression.Our secondary data analyses support that stress-hemoconcentration, possibly caused by decrements in plasma volume during psychological stress, is present in Mexican-American subjects with mild to moderate MDD at non-challenged baseline conditions. We also found that after antidepressant treatment hemorheologic measures of stress-hemoconcentration are improved and are correlated with improvement of depressive symptoms. These findings suggest that antidepressant treatment may have a positive impact in CVD by ameliorating increased blood viscosity. Physicians should be aware of the potential impact of measures of hemoconcentration and consider the implications for cardiovascular risk in depressed patients

Self-help groups challenge health care systems in the US and UK

Purpose: This research considers how self-help groups (SHGs) and self- help organizations (SHOs) contribute to consumerist trends in two different societies: United States and United Kingdom. How do the health care systems and the voluntary sectors affect the kinds of social changes that SHGs/SHOs make? Methodology/approach: A review of research on the role of SHGs/SHOs in contributing to national health social movements in the UK and US was made. Case studies of the UK and the US compare the characteristics of their health care systems and their voluntary sector. Research reviews of two community level self-help groups in each country describe the kinds of social changes they made. Findings: The research review verified that SHGs/SHOs contribute to national level health social movements for patient consumerism. The case studies showed that community level SHGs/SHOs successfully made the same social changes but on a smaller scale as the national movements, and the health care system affects the kinds of community changes made. Research limitations: A limited number of SHGs/SHOs within only two societies were studied. Additional SHGs/SHOs within a variety of societies need to be studied. Originality/value of chapter Community SHGs/SHOs are often trivialized by social scientists as just inward-oriented support groups, but this chapter shows that local groups contribute to patient consumerism and social changes but in ways that depend on the kind of health care system and societal context

Implications from a Network-Based Topological Analysis of Ubiquitin Unfolding Simulations

BACKGROUND: The architectural organization of protein structures has been the focus of intense research since it can hopefully lead to an understanding of how proteins fold. In earlier works we had attempted to identify the inherent structural organization in proteins through a study of protein topology. We obtained a modular partitioning of protein structures with the modules correlating well with experimental evidence of early folding units or "foldons". Residues that connect different modules were shown to be those that were protected during the transition phase of folding. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we follow the topological path of ubiquitin through molecular dynamics unfolding simulations. We observed that the use of recurrence quantification analysis (RQA) could lead to the identification of the transition state during unfolding. Additionally, our earlier contention that the modules uncovered through our graph partitioning approach correlated well with early folding units was vindicated through our simulations. Moreover, residues identified from native structure as connector hubs and which had been shown to be those that were protected during the transition phase of folding were indeed more stable (less flexible) well beyond the transition state. Further analysis of the topological pathway suggests that the all pairs shortest path in a protein is minimized during folding. CONCLUSIONS: We observed that treating a protein native structure as a network by having amino acid residues as nodes and the non-covalent interactions among them as links allows for the rationalization of many aspects of the folding process. The possibility to derive this information directly from 3D structure opens the way to the prediction of important residues in proteins, while the confirmation of the minimization of APSP for folding allows for the establishment of a potentially useful proxy for kinetic optimality in the validation of sequence-structure predictions

Computational Fragment-Based Binding Site Identification by Ligand Competitive Saturation

Fragment-based drug discovery using NMR and x-ray crystallographic methods has proven utility but also non-trivial time, materials, and labor costs. Current computational fragment-based approaches circumvent these issues but suffer from limited representations of protein flexibility and solvation effects, leading to difficulties with rigorous ranking of fragment affinities. To overcome these limitations we describe an explicit solvent all-atom molecular dynamics methodology (SILCS: Site Identification by Ligand Competitive Saturation) that uses small aliphatic and aromatic molecules plus water molecules to map the affinity pattern of a protein for hydrophobic groups, aromatic groups, hydrogen bond donors, and hydrogen bond acceptors. By simultaneously incorporating ligands representative of all these functionalities, the method is an in silico free energy-based competition assay that generates three-dimensional probability maps of fragment binding (FragMaps) indicating favorable fragment∶protein interactions. Applied to the two-fold symmetric oncoprotein BCL-6, the SILCS method yields two-fold symmetric FragMaps that recapitulate the crystallographic binding modes of the SMRT and BCOR peptides. These FragMaps account both for important sequence and structure differences in the C-terminal halves of the two peptides and also the high mobility of the BCL-6 His116 sidechain in the peptide-binding groove. Such SILCS FragMaps can be used to qualitatively inform the design of small-molecule inhibitors or as scoring grids for high-throughput in silico docking that incorporate both an atomic-level description of solvation and protein flexibility