Duties of a Conference Leader

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GeoZui3D: Data Fusion for Interpreting Oceanographic Data

GeoZui3D stands for Geographic Zooming User Interface. It is a new visualization software system designed for interpreting multiple sources of 3D data. The system supports gridded terrain models, triangular meshes, curtain plots, and a number of other display objects. A novel center of workspace interaction method unifies a number of aspects of the interface. It creates a simple viewpoint control method, it helps link multiple views, and is ideal for stereoscopic viewing. GeoZui3D has a number of features to support real-time input. Through a CORBA interface external entities can influence the position and state of objects in the display. Extra windows can be attached to moving objects allowing for their position and data to be monitored. We describe the application of this system for heterogeneous data fusion, for multibeam QC and for ROV/AUV monitoring

In-cell thermodynamics and a new role for protein surfaces

Understanding protein thermodynamics as it occurs inside cells is a fundamental goal of biophysics, and, from a practical point of view, will facilitate the design and improvement of protein-based drugs and catalysts. By measuring the temperature dependence of protein stability inside Escherichia coli cells, we show, contrary to predictions, that proteins are not necessarily stabilized inside cells compared with buffer alone. We also show that crowding-induced charge–charge interactions slow folding because of preferential interactions with the unfolded ensemble, and reducing these interactions increases protein stability

Co-benefits of global and regional greenhouse gas mitigation for US air quality in 2050

Policies to mitigate greenhouse gas (GHG) emissions will not only slow climate change but can also have ancillary benefits of improved air quality. Here we examine the co-benefits of both global and regional GHG mitigation for US air quality in 2050 at fine resolution, using dynamical downscaling methods, building on a previous global co-benefits study (West et al., 2013). The co-benefits for US air quality are quantified via two mechanisms: through reductions in co-emitted air pollutants from the same sources and by slowing climate change and its influence on air quality, following West et al. (2013). Additionally, we separate the total co-benefits into contributions from domestic GHG mitigation vs. mitigation in foreign countries. We use the Weather Research and Forecasting (WRF) model to dynamically downscale future global climate to the regional scale and the Sparse Matrix Operator Kernel Emissions (SMOKE) program to directly process global anthropogenic emissions to the regional domain, and we provide dynamical boundary conditions from global simulations to the regional Community Multi-scale Air Quality (CMAQ) model. The total co-benefits of global GHG mitigation from the RCP4.5 scenario compared with its reference are estimated to be higher in the eastern US (ranging from 0.6 to 1.0 µg m−3) than the west (0–0.4 µg m−3) for fine particulate matter (PM2.5), with an average of 0.47 µg m−3 over the US; for O3, the total co-benefits are more uniform at 2–5 ppb, with a US average of 3.55 ppb. Comparing the two mechanisms of co-benefits, we find that reductions in co-emitted air pollutants have a much greater influence on both PM2.5 (96 % of the total co-benefits) and O3 (89 % of the total) than the second co-benefits mechanism via slowing climate change, consistent with West et al. (2013). GHG mitigation from foreign countries contributes more to the US O3 reduction (76 % of the total) than that from domestic GHG mitigation only (24 %), highlighting the importance of global methane reductions and the intercontinental transport of air pollutants. For PM2.5, the benefits of domestic GHG control are greater (74 % of total). Since foreign contributions to co-benefits can be substantial, with foreign O3 benefits much larger than those from domestic reductions, previous studies that focus on local or regional co-benefits may greatly underestimate the total co-benefits of global GHG reductions. We conclude that the US can gain significantly greater domestic air quality co-benefits by engaging with other nations to control GHGs.</html

Lactate, a product of glycolytic metabolism, inhibits histone deacetylase activity and promotes changes in gene expression

Chemical inhibitors of histone deacetylase (HDAC) activity are used as experimental tools to induce histone hyperacetylation and deregulate gene transcription, but it is not known whether the inhibition of HDACs plays any part in the normal physiological regulation of transcription. Using both in vitro and in vivo assays, we show that lactate, which accumulates when glycolysis exceeds the cell’s aerobic metabolic capacity, is an endogenous HDAC inhibitor, deregulating transcription in an HDAC-dependent manner. Lactate is a relatively weak inhibitor (IC(50) 40 mM) compared to the established inhibitors trichostatin A and butyrate, but the genes deregulated overlap significantly with those affected by low concentrations of the more potent inhibitors. HDAC inhibition causes significant up and downregulation of genes, but genes that are associated with HDAC proteins are more likely to be upregulated and less likely to be downregulated than would be expected. Our results suggest that the primary effect of HDAC inhibition by endogenous short-chain fatty acids like lactate is to promote gene expression at genes associated with HDAC proteins. Therefore, we propose that lactate may be an important transcriptional regulator, linking the metabolic state of the cell to gene transcription

Report on the 2013 Rapid Assessment Survey of Marine Species at New England Bays and Harbors

Introduced species (i.e., non-native species that have become established in a new location) have increasingly been recognized as a concern as they have become more prevalent in marine and terrestrial environments (Mooney and Cleland 2001; Simberloff et al. 2005). The ability of introduced species to alter population, community, and ecosystem structure and function, as well as cause significant economic damage is well documented (Carlton 1989, 1996b, 2000; Cohen and Carlton 1995; Cohen et al. 1995; Elton 1958; Meinesz et al. 1993; Occhipinti-Ambrogi and Sheppard 2007; Pimentel et al. 2005; Thresher 2000). The annual economic costs incurred from managing the approximately 50,000 introduced species in the United States alone are estimated to be over $120 billion (Pimentel et al. 2005). Having a monitoring network in place to track new introductions and distributional changes of introduced species is critical for effective management, as these efforts may be more successful when species are detected before they have the chance to become established. A rapid assessment survey is one such method for early detection of introduced species. With rapid assessment surveys, a team of taxonomic experts record and monitor marine species–providing a baseline inventory of native, introduced, and cryptogenic (i.e., unknown origin) species (as defined by Carlton 1996a)–and document range expansions of previously identified species. Since 2000, five rapid assessment surveys have been conducted in New England. These surveys focus on recording species at marinas, which often are in close proximity to transportation vectors (i.e., recreational boats). Species are collected from floating docks and piers because these structures are accessible regardless of the tidal cycle. Another reason for sampling floating docks and other floating structures is that marine introduced species are often found to be more prevalent on artificial surfaces than natural surfaces (Glasby and Connell 2001; Paulay et al. 2002). The primary objectives of these surveys are to: (1) identify native, introduced, and cryptogenic marine species, (2) expand on data collected in past surveys, (3) assess the introduction status and range extensions of documented introduced species, and (4) detect new introductions. This report presents the introduced, cryptogenic, and native species recorded during the 2013 survey

Use of Risk Models to Predict Death in the Next Year Among Individual Ambulatory Patients With Heart Failure

Importance: The clinical practice guidelines for heart failure recommend the use of validated risk models to estimate prognosis. Understanding how well models identify individuals who will die in the next year informs decision making for advanced treatments and hospice. Objective: To quantify how risk models calculated in routine practice estimate more than 50% 1-year mortality among ambulatory patients with heart failure who die in the subsequent year. Design, Setting, and Participants: Ambulatory adults with heart failure from 3 integrated health systems were enrolled between 2005 and 2008. The probability of death was estimated using the Seattle Heart Failure Model (SHFM) and the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk calculator. Baseline covariates were collected from electronic health records. Missing covariates were imputed. Estimated mortality was compared with actual mortality at both population and individual levels. Main Outcomes and Measures: One-year mortality. Results: Among 10930 patients with heart failure, the median age was 77 years, and 48.0% of these patients were female. In the year after study enrollment, 1661 patients died (15.9% by life-table analysis). At the population level, 1-year predicted mortality among the cohort was 9.7% for the SHFM (C statistic of 0.66) and 17.5% for the MAGGIC risk calculator (C statistic of 0.69). At the individual level, the SHFM predicted a more than 50% probability of dying in the next year for 8 of the 1661 patients who died (sensitivity for 1-year death was 0.5%) and for 5 patients who lived at least a year (positive predictive value, 61.5%). The MAGGIC risk calculator predicted a more than 50% probability of dying in the next year for 52 of the 1661 patients who died (sensitivity, 3.1%) and for 63 patients who lived at least a year (positive predictive value, 45.2%). Conversely, the SHFM estimated that 8496 patients (77.8%) had a less than 15% probability of dying at 1 year, yet this lower-risk end of the score range captured nearly two-thirds of deaths (n = 997); similarly, the MAGGIC risk calculator estimated a probability of dying of less than 25% for the majority of patients who died at 1 year (n = 914). Conclusions and Relevance: Although heart failure risk models perform reasonably well at the population level, they do not reliably predict which individual patients will die in the next year

Sparse and Distributed Coding of Episodic Memory in Neurons of the Human Hippocampus

Neurocomputational models hold that sparse distributed coding is the most efficient way for hippocampal neurons to encode episodic memories rapidly. We investigated the representation of episodic memory in hippocampal neurons of nine epilepsy patients undergoing intracranial monitoring as they discriminated between recently studied words (targets) and new words (foils) on a recognition test. On average, single units and multiunits exhibited higher spike counts in response to targets relative to foils, and the size of this effect correlated with behavioral performance. Further analyses of the spike-count distributions revealed that (i) a small percentage of recorded neurons responded to any one target and (ii ) a small percentage of targets elicited a strong response in any one neuron. These findings are consistent with the idea that in the human hippocampus episodic memory is supported by a sparse distributed neural code