Acting out our dam future: science-based role-play simulations as mechanisms for learning and natural resource planning

Science often does not make its way into decisions, leading to a problematic gap between scientific and societal progress. To tackle this issue, our research tests a novel science-based negotiation simulation that integrates a role-play simulation (RPS) with a system dynamics model (SDM). In RPSs, stakeholders engage in a mock decision-making process (reflecting real-life institutional arrangements and scientific knowledge) for a set period. System dynamics models (SDMs) are visual tools used to simulate the interactions and feedback within a complex system. We test the integration of the two approaches with stakeholders in New England via a series of two consecutive workshops across two states. The workshops engage stakeholders from diverse groups to foster dialogue, learning, and creativity. Participants discuss a hypothetical (yet realistic) decision scenario to consider scientific information and explore dam management options that meet one another\u27s interests. In the first workshop, participants contributed to the design of the fictionalized dam decision scenario and the SDM. In the second workshop, participants assumed another representative\u27s role and discussed dam management options for the fictionalized scenario. This presentation will briefly report on the practical design of this science-based role-play, and particularly emphasize preliminary results of workshop outcomes, which were evaluated using debriefing sessions, surveys, concept mapping exercises, and interviews. Results will determine the extent to which this new knowledge production process leads to learning, use of science, and more collaborative decision-making about dams in New England and beyond

Higher excitations of ω\omega and ϕ\phi in dilepton spectra

We consider lepton pair production via two-hadron annihilation through various isoscalar vector mesons within hot, baryon-free matter. This is tantamount to constructing effective form factors which we model using a vector-meson-dominance approach and compare with experiment. In particular, we consider the reactions $\pi\rho\to e^+e^-$ and $\bar K K^{*}(892)$ + c.c. $\to e^+e^-$. We find that $\omega(1390)$ and $\phi(1680)$ are visible in the mass spectrum for the thermal production rate above the $\pi^{+}\pi^{-} \to e^+e^-$ tail and even above the $\pi a_{1}\to e^+e^-$ results---both of which were considered important in their respective mass regions.Comment: RevTeX, 9 pages, 6 (uuencoded) figures; to appear in Phys. Rev

Glycan Reader: Automated Sugar Identification and Simulation Preparation for Carbohydrates and Glycoproteins

This is the peer reviewed version of the following article: Jo, S., Song, K. C., Desaire, H., MacKerell, A. D., & Im, W. (2011). Glycan Reader: Automated Sugar Identification and Simulation Preparation for Carbohydrates and Glycoproteins. Journal of Computational Chemistry, 32(14), 3135–3141. http://doi.org/10.1002/jcc.21886, which has been published in final form at http://doi.org/10.1002/jcc.21886. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Understanding how glycosylation affects protein structure, dynamics, and function is an emerging and challenging problem in biology. As a first step toward glycan modeling in the context of structural glycobiology, we have developed Glycan Reader and integrated it into the CHARMMGUI, http://www.charmm-gui.org/input/glycan. Glycan Reader greatly simplifies the reading of PDB structure files containing glycans through (i) detection of carbohydrate molecules, (ii) automatic annotation of carbohydrates based on their three-dimensional structures, (iii) recognition of glycosidic linkages between carbohydrates as well as N-/O-glycosidic linkages to proteins, and (iv) generation of inputs for the biomolecular simulation program CHARMM with the proper glycosidic linkage setup. In addition, Glycan Reader is linked to other functional modules in CHARMM-GUI, allowing users to easily generate carbohydrate or glycoprotein molecular simulation systems in solution or membrane environments and visualize the electrostatic potential on glycoprotein surfaces. These tools are useful for studying the impact of glycosylation on protein structure and dynamics

Orientation of Fluorescent Lipid Analog BODIPY-PC to Probe Lipid Membrane Properties: Insights from Molecular Dynamics Simulations

Single-molecule fluorescence measurements have been used to characterize membrane properties, and recently showed a linear evolution of the fluorescent lipid analog BODIPY-PC towards small tilt angles in Langmuir-Blodgett monolayers as the lateral surface pressure is increased. In this work, we have performed comparative molecular dynamics (MD) simulations of BODIPY-PC in DPPC (dipalmitoylphosphatidylcholine) monolayers and bilayers at three surface pressures (3, 10, and 40 mN/m) to explore 1) the microscopic correspondence between monolayer and bilayer structures, 2) the fluorophore’s position within the membrane, and 3) the microscopic driving forces governing the fluorophore’s tilting. The MD simulations reveal very close agreement between the monolayer and bilayer systems in terms of the fluorophore’s orientation and lipid chain order, suggesting that monolayer experiments can be used to approximate bilayer systems. The simulations capture the trend of reduced tilt angle of the fluorophore with increasing surface pressure as seen in the experimental results, and provide detailed insights into fluorophore location and orientation, not obtainable in the experiments. The simulations also reveal that the enthalpic contribution is dominant at 40 mN/m resulting in smaller tilt angles of the fluorophore, and the entropy contribution is dominant at lower pressures resulting in larger tilt angles

Regional multi-compartment ecological risk assessment:establishing cadmium pollution risk in the northern Bohai Rim, China

Ecological risk assessment (ERA) has been widely applied in characterizing the risk of chemicals to organisms and ecosystems. The paucity of toxicity data on local biota living in the different compartments of an ecosystem and the absence of a suitable methodology for multi-compartment spatial risk assessment at the regional scale has held back this field. The major objective of this study was to develop a methodology to quantify and distinguish the spatial distribution of risk to ecosystems at a regional scale. A framework for regional multi-compartment probabilistic ecological risk assessment (RMPERA) was constructed and corroborated using a bioassay of a local species. The risks from cadmium (Cd) pollution in river water, river sediment, coastal water, coastal surface sediment and soil in northern Bohai Rim were examined. The results indicated that the local organisms in soil, river, coastal water, and coastal sediment were affected by Cd. The greatest impacts from Cd were identified in the Tianjin and Huludao areas. The overall multi-compartment risk was 31.4% in the region. The methodology provides a new approach for regional multi-compartment ecological risk assessment

Micro-Environment Causes Reversible Changes in DNA Methylation and mRNA Expression Profiles in Patient-Derived Glioma Stem Cells

In vitro and in vivo models are widely used in cancer research. Characterizing the similarities and differences between a patient\u27s tumor and corresponding in vitro and in vivo models is important for understanding the potential clinical relevance of experimental data generated with these models. Towards this aim, we analyzed the genomic aberrations, DNA methylation and transcriptome profiles of five parental tumors and their matched in vitro isolated glioma stem cell (GSC) lines and xenografts generated from these same GSCs using high-resolution platforms. We observed that the methylation and transcriptome profiles of in vitro GSCs were significantly different from their corresponding xenografts, which were actually more similar to their original parental tumors. This points to the potentially critical role of the brain microenvironment in influencing methylation and transcriptional patterns of GSCs. Consistent with this possibility, ex vivo cultured GSCs isolated from xenografts showed a tendency to return to their initial in vitro states even after a short time in culture, supporting a rapid dynamic adaptation to the in vitro microenvironment. These results show that methylation and transcriptome profiles are highly dependent on the microenvironment and growth in orthotopic sites partially reverse the changes caused by in vitro culturing

Studying genetic determinants of natural variation in human gene expression using Bayesian ANOVA

Standard genetic mapping techniques scan chromosomal segments for location of genetic linkage and association signals. The majority of these methods consider only correlations at single markers and/or phenotypes with explicit detailing of the genetic structure. These methods tend to be limited by their inability to consider the effect of large numbers of model variables jointly. In contrast, we propose a Bayesian analysis of variance (ANOVA) method to categorize individuals based on similarity of multidimensional profiles and attempt to analyze all variables simultaneously. Using Problem 1 of the Genetic Analysis Workshop 15 data set, we demonstrate the method's utility for joint analysis of gene expression levels and single-nucleotide polymorphism genotypes. We show that the method extracts similar information to that of previous genetic mapping analyses, and suggest extensions of the method for mining unique information not previously found

Photons from axial-vector radiative decay in a hadron gas

Strange and non-strange axial-vector meson radiative decays contribute to photon production in hadron gas. One- and two-hadron radiative decay modes of $b_{1}(1235)$, $a_{1}(1260)$ and $K_{1}(1270)$ are studied. At 200 MeV temperature and for a narrow range in photon energies they contribute more to the net thermal photon production rate than $\pi\rho\rightarrow \pi\gamma$, $\pi\pi\rightarrow \rho\gamma$ or $\rho\rightarrow\pi\pi\gamma$. They provide significant contribution to the rate for photon energies as high as 1.5--2.0 GeV. For higher energies they are less important.Comment: 10 pages + 7 figures uuencoded in separate file, MSUCL-92