Project description:Why do members of some species live in groups while others are solitary? Group living (sociality) has often been studied from an evolutionary perspective, but less is known about the neurobiology of affiliation outside the realms of mating and parenting. Colonial species offer a valuable opportunity to study nonsexual affiliative behavior between adult peers. Meadow voles (Microtus pennsylvanicus) display environmentally induced variation in social behavior, maintaining exclusive territories in summer months, but living in social groups in winter. Research on peer relationships in female meadow voles demonstrates that these selective preferences are mediated differently than mate relationships in socially monogamous prairie voles, but are also impacted by oxytocin and HPA axis signaling. This review addresses day-length dependent variation in physiology and behavior, and presents the current understanding of the mechanisms supporting selective social relationships in meadow voles, with connections to lessons from other species.
Project description:Following the 2007-2009 financial crisis, governments around the world passed laws that marked the beginning of new period of enhanced regulation of the financial industry. These laws called for a myriad of new regulations, which in the U.S. are created through the so-called notice-and-comment process. Through examining the text documents generated through this process, we study the formation of regulations to gain insight into how new regulatory regimes are implemented following major laws like the landmark Dodd-Frank Wall Street Reform and Consumer Protection Act. Due to the variety of constituent preferences and political pressures, we find evidence that the government implements rules strategically to extend the regulatory boundary by first pursuing procedural rules that establish how economic activities will be regulated, followed by specifying who is subject to the procedural requirements. Our findings together with the unique nature of the Dodd-Frank Act translate to a number of stylized facts that should guide development of formal models of the rule-making process.
Project description:The Dodd Frank Act was passed by the US Congress in July 2010 and included a provision-Section 1502-that aimed to break the link between conflict and minerals in the Eastern Democratic Republic of Congo. To date there is only one rigorous quantitative analysis that investigates the impact of Dodd-Frank on local conflict events. Looking at the short-term impact (2011-2012), it finds that the policy backfired. This study builds on a larger, more representative, dataset of mining sites and extends the time horizon by three years (2013-2015). The results indicate that the policy also backfired in the longer run, especially in areas home to gold mines. For territories with the average number of gold mines, the introduction of Dodd-Frank increased the incidence of battles with 44%; looting with 51% and violence against civilians with 28%, compared to pre-Dodd Frank averages. Delving deeper into the impact of the conflict minerals legislation is important, as President Trump suspended the legislation in February 2017 for a two-year period, ordering his administration to replace it with another policy.
Project description:With increasingly "big" data available in biomedical research, deriving accurate and reproducible biology knowledge from such big data imposes enormous computational challenges. In this paper, motivated by recently developed stochastic block coordinate algorithms, we propose a highly scalable randomized block coordinate Frank-Wolfe algorithm for convex optimization with general compact convex constraints, which has diverse applications in analyzing biomedical data for better understanding cellular and disease mechanisms. We focus on implementing the derived stochastic block coordinate algorithm to align protein-protein interaction networks for identifying conserved functional pathways based on the IsoRank framework. Our derived stochastic block coordinate Frank-Wolfe (SBCFW) algorithm has the convergence guarantee and naturally leads to the decreased computational cost (time and space) for each iteration. Our experiments for querying conserved functional protein complexes in yeast networks confirm the effectiveness of this technique for analyzing large-scale biological networks.
Project description:Frank-Kasper (F-K) and quasicrystal phases were originally identified in metal alloys and only sporadically reported in soft materials. These unconventional sphere-packing schemes open up possibilities to design materials with different properties. The challenge in soft materials is how to correlate complex phases built from spheres with the tunable parameters of chemical composition and molecular architecture. Here, we report a complete sequence of various highly ordered mesophases by the self-assembly of specifically designed and synthesized giant surfactants, which are conjugates of hydrophilic polyhedral oligomeric silsesquioxane cages tethered with hydrophobic polystyrene tails. We show that the occurrence of these mesophases results from nanophase separation between the heads and tails and thus is critically dependent on molecular geometry. Variations in molecular geometry achieved by changing the number of tails from one to four not only shift compositional phase boundaries but also stabilize F-K and quasicrystal phases in regions where simple phases of spheroidal micelles are typically observed. These complex self-assembled nanostructures have been identified by combining X-ray scattering techniques and real-space electron microscopy images. Brownian dynamics simulations based on a simplified molecular model confirm the architecture-induced sequence of phases. Our results demonstrate the critical role of molecular architecture in dictating the formation of supramolecular crystals with "soft" spheroidal motifs and provide guidelines to the design of unconventional self-assembled nanostructures.
Project description:Although the clinical high risk for psychosis (CHR) paradigm has become well-established over the past two decades, one key component has received surprisingly little investigative attention: the predictive validity of the criteria for conversion or transition to frank psychosis. The current study evaluates the predictive validity of the transition to psychosis as measured by the Structured Interview for Psychosis-Risk Syndromes (SIPS) in CHR individuals. Participants included 33 SIPS converters and 399 CHR non-converters both from the North American Prodromal Longitudinal Study (NAPLS-2), as well as a sample of 67 separately ascertained first-episode psychosis (FEP) patients from the STEP program. Comparisons were made at baseline and one-year follow-up on demographic, diagnostic stability (SCID), and available measurement domains relating to severity of illness (psychotropic medication, psychosocial treatment, and resource utilization). Principal findings are: 1) a large majority of cases in both SIPS converters (n = 27/33, 81.8%) and FEP (n = 57/67, 85.1%) samples met criteria for continued psychosis at one-year follow-up; 2) follow-up prescription rates for current antipsychotic medication were higher in SIPS converters (n = 17/32, 53.1%) compared to SIPS non-converters (n = 81/397, 20.4%), and similar as compared to FEP cases (n = 39/65, 60%); and 3) at follow-up, SIPS converters had higher rates of resource utilization (psychiatric hospitalizations, day hospital admissions, and ER visits) than SIPS non-converters and were similar to FEP in most categories. The results suggest that the SIPS definition of psychosis onset carries substantial predictive validity. Limitations and future directions are discussed.
Project description:Using computer simulations, the structural properties of solvation water of three model hydrophobic molecules, methane and two fullerenes (C60 and C80), were studied. Systems were simulated at temperatures in the range of 250-298 K. By analyzing both the local ordering of the molecules of water in the solvation layers and the structure of hydrogen bond network, it is shown that in the solvation layer of hydrophobic molecules, ordered aggregates consisting of water molecules are formed. Even though it is difficult to define the exact structure of these aggregates, their existence alone is clearly noticeable. Moreover, these aggregates become more pronounced with the decrease of temperature. The existence of the ordered aggregates around the hydrophobic solutes complies with the concept of "icebergs" proposed by Frank and Evans.
Project description:Single molecular species can self-assemble into Frank-Kasper (FK) phases, finite approximants of dodecagonal quasicrystals, defying intuitive notions that thermodynamic ground states are maximally symmetric. FK phases are speculated to emerge as the minimal-distortional packings of space-filling spherical domains, but a precise measure of this distortion and how it affects assembly thermodynamics remains ambiguous. We use two complementary approaches to demonstrate that the principles driving FK lattice formation in diblock copolymers emerge directly from the strong-stretching theory of spherical domains, in which a minimal interblock area competes with a minimal stretching of space-filling chains. The relative stability of FK lattices is studied first using a diblock foam model with unconstrained particle volumes and shapes, which correctly predicts not only the equilibrium ? lattice but also the unequal volumes of the equilibrium domains. We then provide a molecular interpretation for these results via self-consistent field theory, illuminating how molecular stiffness increases the sensitivity of the intradomain chain configurations and the asymmetry of local domain packing. These findings shed light on the role of volume exchange on the formation of distinct FK phases in copolymers and suggest a paradigm for formation of FK phases in soft matter systems in which unequal domain volumes are selected by the thermodynamic competition between distinct measures of shape asymmetry.