Determinism and boundedness of self-assembling structures.

Self-assembly processes are widespread in nature and lie at the heart of many biological and physical phenomena. The characteristics of self-assembly building blocks determine the structures that they form. Two crucial properties are the determinism and boundedness of the self-assembly. The former tells us whether the same set of building blocks always generates the same structure, and the latter whether it grows indefinitely. These properties are highly relevant in the context of protein structures, as the difference between deterministic protein self-assembly and nondeterministic protein aggregation is central to a number of diseases. Here we introduce a graph theoretical approach that can determine the determinism and boundedness for several geometries and dimensionalities of self-assembly more accurately and quickly than conventional methods. We apply this methodology to a previously studied lattice self-assembly model and discuss generalizations to a wide range of other self-assembling systems

Emerging technologies in physics education

Three emerging technologies in physics education are evaluated from the interdisciplinary perspective of cognitive science and physics education research. The technologies - Physlet Physics, the Andes Intelligent Tutoring System (ITS), and Microcomputer-Based Laboratory (MBL) Tools - are assessed particularly in terms of their potential at promoting conceptual change, developing expert-like problem-solving skills, and achieving the goals of the traditional physics laboratory. Pedagogical methods to maximize the potential of each educational technology are suggested.Comment: Accepted for publication in the Journal of Science Education and Technology; 20 page

Time for T? Immunoinformatics addresses the challenges of vaccine design for neglected tropical and emerging infectious diseases

Vaccines have been invaluable for global health, saving lives and reducing healthcare costs, while also raising the quality of human life. However, newly emerging infectious diseases (EID) and more well-established tropical disease pathogens present complex challenges to vaccine developers; in particular, neglected tropical diseases, which are most prevalent among the world’s poorest, include many pathogens with large sizes, multistage life cycles and a variety of nonhuman vectors. EID such as MERS-CoV and H7N9 are highly pathogenic for humans. For many of these pathogens, while their genomes are available, immune correlates of protection are currently unknown. These complexities make developing vaccines for EID and neglected tropical diseases all the more difficult. In this review, we describe the implementation of an immunoinformatics-driven approach to systematically search for key determinants of immunity in newly available genome sequence data and design vaccines. This approach holds promise for the development of 21st century vaccines, improving human health everywhere

Flavor conversion of cosmic neutrinos from hidden jets

High energy cosmic neutrino fluxes can be produced inside relativistic jets under the envelopes of collapsing stars. In the energy range E ~ (0.3 - 1e5) GeV, flavor conversion of these neutrinos is modified by various matter effects inside the star and the Earth. We present a comprehensive (both analytic and numerical) description of the flavor conversion of these neutrinos which includes: (i) oscillations inside jets, (ii) flavor-to-mass state transitions in an envelope, (iii) loss of coherence on the way to observer, and (iv) oscillations of the mass states inside the Earth. We show that conversion has several new features which are not realized in other objects, in particular interference effects ("L- and H- wiggles") induced by the adiabaticity violation. The neutrino-neutrino scattering inside jet and inelastic neutrino interactions in the envelope may produce some additional features at E > 1e4 GeV. We study dependence of the probabilities and flavor ratios in the matter-affected region on angles theta13 and theta23, on the CP-phase delta, as well as on the initial flavor content and density profile of the star. We show that measurements of the energy dependence of the flavor ratios will, in principle, allow to determine independently the neutrino and astrophysical parameters.Comment: 56 pages, 19 figures. Minor changes. Accepted by JHEP

A Spatial Analysis of Rift Valley Fever Virus Seropositivity in Domestic Ruminants in Tanzania

Rift Valley fever (RVF) is an acute arthropod-borne viral zoonotic disease primarily occurring in Africa. Since RVF-like disease was reported in Tanzania in 1930, outbreaks of the disease have been reported mainly from the eastern ecosystem of the Great Rift Valley. This cross-sectional study was carried out to describe the variation in RVF virus (RVFV) seropositivity in domestic ruminants between selected villages in the eastern and western Rift Valley ecosystems in Tanzania, and identify potential risk factors. Three study villages were purposively selected from each of the two Rift Valley ecosystems. Serum samples from randomly selected domestic ruminants (n = 1,435) were tested for the presence of specific immunoglobulin G (IgG) and M (IgM), using RVF enzyme-linked immunosorbent assay methods. Mixed effects logistic regression modelling was used to investigate the association between potential risk factors and RVFV seropositivity. The overall RVFV seroprevalence (n = 1,435) in domestic ruminants was 25.8% and species specific seroprevalence was 29.7%, 27.7% and 22.0% in sheep (n = 148), cattle (n = 756) and goats (n = 531), respectively. The odds of seropositivity were significantly higher in animals sampled from the villages in the eastern than those in the western Rift Valley ecosystem (OR = 1.88, CI: 1.41, 2.51; p<0.001), in animals sampled from villages with soils of good than those with soils of poor water holding capacity (OR = 1.97; 95% CI: 1.58, 3.02; p< 0.001), and in animals which had been introduced than in animals born within the herd (OR = 5.08, CI: 2.74, 9.44; p< 0.001). Compared with animals aged 1-2 years, those aged 3 and 4-5 years had 3.40 (CI: 2.49, 4.64; p< 0.001) and 3.31 (CI: 2.27, 4.82, p< 0.001) times the odds of seropositivity. The findings confirm exposure to RVFV in all the study villages, but with a higher prevalence in the study villages from the eastern Rift Valley ecosystem

Depression and sickness behavior are Janus-faced responses to shared inflammatory pathways

It is of considerable translational importance whether depression is a form or a consequence of sickness behavior. Sickness behavior is a behavioral complex induced by infections and immune trauma and mediated by pro-inflammatory cytokines. It is an adaptive response that enhances recovery by conserving energy to combat acute inflammation. There are considerable phenomenological similarities between sickness behavior and depression, for example, behavioral inhibition, anorexia and weight loss, and melancholic (anhedonia), physio-somatic (fatigue, hyperalgesia, malaise), anxiety and neurocognitive symptoms. In clinical depression, however, a transition occurs to sensitization of immuno-inflammatory pathways, progressive damage by oxidative and nitrosative stress to lipids, proteins, and DNA, and autoimmune responses directed against self-epitopes. The latter mechanisms are the substrate of a neuroprogressive process, whereby multiple depressive episodes cause neural tissue damage and consequent functional and cognitive sequelae. Thus, shared immuno-inflammatory pathways underpin the physiology of sickness behavior and the pathophysiology of clinical depression explaining their partially overlapping phenomenology. Inflammation may provoke a Janus-faced response with a good, acute side, generating protective inflammation through sickness behavior and a bad, chronic side, for example, clinical depression, a lifelong disorder with positive feedback loops between (neuro)inflammation and (neuro)degenerative processes following less well defined triggers

Scaling of the surface vasculature on the human placenta

The networks of veins and arteries on the chorionic plate of the human placenta are analyzed in terms of Voronoi cells derived from these networks. Two groups of placentas from the United States are studied: a population cohort with no prescreening, and a cohort from newborns with an elevated risk of developing autistic spectrum disorder. Scaled distributions of the Voronoi cell areas in the two cohorts collapse onto a single distribution, indicating common mechanisms for the formation of the complete vasculatures, but which have different levels of activity in the two cohorts

A computational approach to chemical etiologies of diabetes.

Computational meta-analysis can link environmental chemicals to genes and proteins involved in human diseases, thereby elucidating possible etiologies and pathogeneses of non-communicable diseases. We used an integrated computational systems biology approach to examine possible pathogenetic linkages in type 2 diabetes (T2D) through genome-wide associations, disease similarities, and published empirical evidence. Ten environmental chemicals were found to be potentially linked to T2D, the highest scores were observed for arsenic, 2,3,7,8-tetrachlorodibenzo-p-dioxin, hexachlorobenzene, and perfluorooctanoic acid. For these substances we integrated disease and pathway annotations on top of protein interactions to reveal possible pathogenetic pathways that deserve empirical testing. The approach is general and can address other public health concerns in addition to identifying diabetogenic chemicals, and offers thus promising guidance for future research in regard to the etiology and pathogenesis of complex diseases

What we talk about when we talk about "global mindset": managerial cognition in multinational corporations

Recent developments in the global economy and in multinational corporations have placed significant emphasis on the cognitive orientations of managers, giving rise to a number of concepts such as “global mindset” that are presumed to be associated with the effective management of multinational corporations (MNCs). This paper reviews the literature on global mindset and clarifies some of the conceptual confusion surrounding the construct. We identify common themes across writers, suggesting that the majority of studies fall into one of three research perspectives: cultural, strategic, and multidimensional. We also identify two constructs from the social sciences that underlie the perspectives found in the literature: cosmopolitanism and cognitive complexity and use these two constructs to develop an integrative theoretical framework of global mindset. We then provide a critical assessment of the field of global mindset and suggest directions for future theoretical and empirical research

Development and Validation of an Epitope Prediction Tool for Swine (PigMatrix) Based on the Pocket Profile Method

Background: T cell epitope prediction tools and associated vaccine design algorithms have accelerated the development of vaccines for humans. Predictive tools for swine and other food animals are not as well developed, primarily because the data required to develop the tools are lacking. Here, we overcome a lack of T cell epitope data to construct swine epitope predictors by systematically leveraging available human information. Applying the “pocket profile method”, we use sequence and structural similarities in the binding pockets of human and swine major histocompatibility complex proteins to infer Swine Leukocyte Antigen (SLA) peptide binding preferences. We developed epitope-prediction matrices (PigMatrices), for three SLA class I alleles (SLA-1*0401, 2*0401 and 3*0401) and one class II allele (SLA-DRB1*0201), based on the binding preferences of the best-matched Human Leukocyte Antigen (HLA) pocket for each SLA pocket. The contact residues involved in the binding pockets were defined for class I based on crystal structures of either SLA (SLA-specific contacts, Ssc) or HLA supertype alleles (HLA contacts, Hc); for class II, only Hc was possible. Different substitution matrices were evaluated (PAM and BLOSUM) for scoring pocket similarity and identifying the best human match. The accuracy of the PigMatrices was compared to available online swine epitope prediction tools such as PickPocket and NetMHCpan. Results: PigMatrices that used Ssc to define the pocket sequences and PAM30 to score pocket similarity demonstrated the best predictive performance and were able to accurately separate binders from random peptides. For SLA-1*0401 and 2*0401, PigMatrix achieved area under the receiver operating characteristic curves (AUC) of 0.78 and 0.73, respectively, which were equivalent or better than PickPocket (0.76 and 0.54) and NetMHCpan version 2.4 (0.41 and 0.51) and version 2.8 (0.72 and 0.71). In addition, we developed the first predictive SLA class II matrix, obtaining an AUC of 0.73 for existing SLA-DRB1*0201 epitopes. Notably, PigMatrix achieved this level of predictive power without training on SLA binding data. Conclusions: Overall, the pocket profile method combined with binding preferences from HLA binding data shows significant promise for developing T cell epitope prediction tools for pigs. When combined with existing vaccine design algorithms, PigMatrix will be useful for developing genome-derived vaccines for a range of pig pathogens for which no effective vaccines currently exist (e.g. porcine reproductive and respiratory syndrome, influenza and porcine epidemic diarrhea)