Showing papers by "University of Rhode Island published in 2016"
TL;DR: The Global Burden of Disease 2015 Study provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015, finding several countries in sub-Saharan Africa had very large gains in life expectancy, rebounding from an era of exceedingly high loss of life due to HIV/AIDS.
4,804 citations
TL;DR: In this paper, the authors present a spatial analysis of 2013-2015 national drinking water PFAS concentrations from the U.S. Environmental Protection Agency's (US EPA) third Unregulated Contaminant Monitoring Rule (UCMR3) program.
Abstract: Drinking water contamination with poly- and perfluoroalkyl substances (PFASs) poses risks to the developmental, immune, metabolic, and endocrine health of consumers. We present a spatial analysis of 2013–2015 national drinking water PFAS concentrations from the U.S. Environmental Protection Agency’s (US EPA) third Unregulated Contaminant Monitoring Rule (UCMR3) program. The number of industrial sites that manufacture or use these compounds, the number of military fire training areas, and the number of wastewater treatment plants are all significant predictors of PFAS detection frequencies and concentrations in public water supplies. Among samples with detectable PFAS levels, each additional military site within a watershed’s eight-digit hydrologic unit is associated with a 20% increase in PFHxS, a 10% increase in both PFHpA and PFOA, and a 35% increase in PFOS. The number of civilian airports with personnel trained in the use of aqueous film-forming foams is significantly associated with the detection of ...
744 citations
TL;DR: The development of an underwater gripper that utilizes soft robotics technology to delicately manipulate and sample fragile species on the deep reef is presented, making it the first use of soft robotics in the deep sea for the nondestructive sampling of benthic fauna.
Abstract: This article presents the development of an underwater gripper that utilizes soft robotics technology to delicately manipulate and sample fragile species on the deep reef. Existing solutions for deep sea robotic manipulation have historically been driven by the oil industry, resulting in destructive interactions with undersea life. Soft material robotics relies on compliant materials that are inherently impedance matched to natural environments and to soft or fragile organisms. We demonstrate design principles for soft robot end effectors, bench-top characterization of their grasping performance, and conclude by describing in situ testing at mesophotic depths. The result is the first use of soft robotics in the deep sea for the nondestructive sampling of benthic fauna.
580 citations
TL;DR: The analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient.
441 citations
University of Florida1, University of Minnesota2, University of Oklahoma3, United States Department of Agriculture4, Donald Danforth Plant Science Center5, Stony Brook University6, Eckerd College7, Purdue University8, Cold Spring Harbor Laboratory9, University of Rhode Island10, University of California, Berkeley11, Colorado State University12, University of California, Riverside13, University of California, Davis14, Boyce Thompson Institute for Plant Research15, Stanford University16, Iowa State University17, University of Missouri18, University of Tennessee19
TL;DR: The state of plant transformation is reviewed and innovations needed to enable genome editing in crops are pointed to, including a potential game-changer in crop genetics when plant transformation systems are optimized.
Abstract: Plant transformation has enabled fundamental insights into plant biology and revolutionized commercial agriculture. Unfortunately, for most crops, transformation and regeneration remain arduous even after more than thirty years of technological advances. Genome editing provides new opportunities to enhance crop productivity, but relies on genetic transformation and plant regeneration, which are bottlenecks in the process. Herein we review the state of plant transformation and point to innovations needed to enable genome editing in crops. Plant tissue culture methods need optimization and simplification for efficiency and minimize time in culture. Currently, specialized facilities exist for crop transformation. Single cell and robotic techniques should be developed for high throughput genomic screens. Utilization of plant genes involved in developmental reprogramming, wound response, and/or homologous recombination could boost recovery of transformed plants. Engineering universal Agrobacterium strains and recruitment of other microbes, such as Ensifer or Rhizobium, could facilitate delivery of DNA and proteins into plant cells. Synthetic biology should be employed for de novo design of transformation systems. Genome editing is a potential game-changer in crop genetics when plant transformation systems are optimized.
419 citations
TL;DR: It is found that pre-colonization of surfaces by S4Sm was critical for this bacterium to inhibit pathogen colonization and growth, and involves contributions from both biofilm formation and the production of the antibiotic TDA.
Abstract: Background: The probiotic bacterium Phaeobacter inhibens strain S4Sm, isolated from the inner shell surface of a healthy oyster, secretes the antibiotic tropodithietic acid (TDA), is an excellent biofilm former, and increases oyster larvae survival when challenged with bacterial pathogens. In this study, we investigated the specific roles of TDA secretion and biofilm formation in the probiotic activity of S4Sm. Results: Mutations in clpX (ATP-dependent ATPase) and exoP (an exopolysaccharide biosynthesis gene) were created by insertional mutagenesis using homologous recombination. Mutation of clpX resulted in the loss of TDA production, no decline in biofilm formation, and loss of the ability to inhibit the growth of Vibrio tubiashii and Vibrio anguillarum in co-colonization experiments. Mutation of exoP resulted in a ~60 % decline in biofilm formation, no decline in TDA production, and delayed inhibitory activity towards Vibrio pathogens in co-colonization experiments. Both clpX and exoP mutants exhibited reduced ability to protect oyster larvae from death when challenged by Vibrio tubiashii. Complementation of the clpX and exoP mutations restored the wild type phenotype. We also found that pre-colonization of surfaces by S4Sm was critical for this bacterium to inhibit pathogen colonization and growth. Conclusions: Our observations demonstrate that probiotic activity by P. inhibens S4Sm involves contributions from both biofilm formation and the production of the antibiotic TDA. Further, probiotic activity also requires colonization of surfaces by S4Sm prior to the introduction of the pathogen.
362 citations
TL;DR: In this article, the products of fluoroethylene carbonate (FEC) and vinylene carbonates (VC) via lithium naphthalenide reduction were synthesized.
Abstract: We have synthesized the products of fluoroethylene carbonate (FEC) and vinylene carbonate (VC) via lithium naphthalenide reduction. By analyzing the resulting solid precipitates and gas evolution, our results confirm that both FEC and VC decomposition products include HCO2Li, Li2C2O4, Li2CO3, and polymerized VC. For FEC, our experimental data supports a reduction mechanism where FEC reduces to form VC and LiF, followed by subsequent VC reduction. In the FEC reduction product, HCO2Li, Li2C2O4, and Li2CO3 were found in smaller quantities than in the VC reduction product, with no additional fluorine environments being detected by solid-state nuclear magnetic resonance or X-ray photoelectron spectroscopy analysis. With these additives being practically used in higher (FEC) and lower (VC) concentrations in the base electrolytes of lithium-ion batteries, our results suggest that the different relative ratios of the inorganic and organic reduction products formed by their decomposition may be relevant to the che...
311 citations
TL;DR: Investigation of the effects of different binders on the cycling performance and solid electrolyte interphase (SEI) formation on silicon nanoparticle electrodes found the Lewis basic -CO2Na of CMC was found to scavenge HF in electrolyte.
Abstract: The effects of different binders, polyvinylidene difluoride (PVdF), poly(acrylic acid) (PAA), sodium carboxymethyl cellulose (CMC), and cross-linked PAA–CMC (c–PAA–CMC), on the cycling performance and solid electrolyte interphase (SEI) formation on silicon nanoparticle electrodes have been investigated. Electrodes composed of Si–PAA, Si–CMC, and Si–PAA–CMC exhibit a specific capacity ≥3000 mAh/g after 20 cycles while Si–PVdF electrodes have a rapid capacity fade to 1000 mAh/g after just 10 cycles. Infrared spectroscopy (IR) and X-ray photoelectron spectroscopy (XPS) reveal that PAA and CMC react with the surface of the Si nanoparticles during electrode fabrication. The fresh Si–CMC electrode has a thicker surface coating of SiOx than Si–PAA and Si–PAA–CMC electrodes, due to the formation of thicker SiOx during electrode preparation, which leads to lower cyclability. The carboxylic acid functional groups of the PAA binder are reactive toward the electrolyte, causing the decomposition of LiPF6 and dissoluti...
199 citations
TL;DR: This paper identifies key ecosystem needs in fisheries management and indicates which types of models can meet these needs and illuminate the characteristics, capabilities and short-comings of the various modelling approaches being proposed for ecosystem-based fisheries management.
Abstract: The advent of an ecosystem-based approach dramatically expanded the scope of fisheries management, creating a critical need for new kinds of data and quantitative approaches that could be integrated into the management system. Ecosystem models are needed to codify the relationships among drivers, pressures and resulting states, and to quantify the trade-offs between conflicting objectives. Incorporating ecosystem considerations requires moving from the single-species models used in stock assessments, to more complex models that include species interactions, environmental drivers and human consequences. With this increasing model complexity, model fit can improve, but parameter uncertainty increases. At intermediate levels of complexity, there is a ‘sweet spot’ at which the uncertainty in policy indicators is at a minimum. Finding the sweet spot in models requires compromises: for example, to include additional component species, the models of each species have in some cases been simplified from age-structured to logistic or bioenergetic models. In this paper, we illuminate the characteristics, capabilities and short-comings of the various modelling approaches being proposed for ecosystem-based fisheries management. We identify key ecosystem needs in fisheries management and indicate which types of models can meet these needs. Ecosystem models have been playing strategic roles by providing an ecosystem context for single-species management decisions. However, conventional stock assessments are being increasingly challenged by changing natural mortality rates and environmentally driven changes in productivity that are observed in many fish stocks. Thus, there is a need for more tactical ecosystem models that can respond dynamically to changing ecological and environmental conditions.
198 citations
TL;DR: In this paper, the authors presented a novel and efficient feature selection framework based on the information theory, which aims to rank the features with their discriminative capacity for classification, and proposed a new divergence measure, called Jeffreys-Multi-Hypothesis (JMH) divergence, to measure multi-distribution divergence for multi-class classification.
Abstract: Automated feature selection is important for text categorization to reduce the feature size and to speed up the learning process of classifiers. In this paper, we present a novel and efficient feature selection framework based on the Information Theory, which aims to rank the features with their discriminative capacity for classification. We first revisit two information measures: Kullback-Leibler divergence and Jeffreys divergence for binary hypothesis testing, and analyze their asymptotic properties relating to type I and type II errors of a Bayesian classifier. We then introduce a new divergence measure, called Jeffreys-Multi-Hypothesis (JMH) divergence, to measure multi-distribution divergence for multi-class classification. Based on the JMH-divergence, we develop two efficient feature selection methods, termed maximum discrimination ($MD$) and $MD-\chi^2$ methods, for text categorization. The promising results of extensive experiments demonstrate the effectiveness of the proposed approaches.
193 citations
Hunter College1, Lincoln Park Zoo2, University of Arizona3, University of Rhode Island4, Duke University5, Loyola University Chicago6, University of Wisconsin-Madison7, Kwame Nkrumah University of Science and Technology8, University of Lausanne9, University of the West Indies10, University of Cape Town11, University of New Mexico12, Krasnow Institute for Advanced Study13, Indianapolis Zoo14, Indiana University15
TL;DR: Water measurements of total energy expenditure in humans, chimpanzees, bonobos, gorillas and orangutans are used to test the hypothesis that the human lineage has experienced an acceleration in metabolic rate, providing energy for larger brains and faster reproduction without sacrificing maintenance and longevity.
Abstract: Humans are distinguished from the other living apes in having larger brains and an unusual life history that combines high reproductive output with slow childhood growth and exceptional longevity. This suite of derived traits suggests major changes in energy expenditure and allocation in the human lineage, but direct measures of human and ape metabolism are needed to compare evolved energy strategies among hominoids. Here we used doubly labelled water measurements of total energy expenditure (TEE; kcal day(-1)) in humans, chimpanzees, bonobos, gorillas and orangutans to test the hypothesis that the human lineage has experienced an acceleration in metabolic rate, providing energy for larger brains and faster reproduction without sacrificing maintenance and longevity. In multivariate regressions including body size and physical activity, human TEE exceeded that of chimpanzees and bonobos, gorillas and orangutans by approximately 400, 635 and 820 kcal day(-1), respectively, readily accommodating the cost of humans' greater brain size and reproductive output. Much of the increase in TEE is attributable to humans' greater basal metabolic rate (kcal day(-1)), indicating increased organ metabolic activity. Humans also had the greatest body fat percentage. An increased metabolic rate, along with changes in energy allocation, was crucial in the evolution of human brain size and life history.
TL;DR: In this paper, the authors used meta-analysis approaches to evaluate the nitrate removal rate of denitrifying woodchip bioreactors and found that hydraulic retention times were significantly lower in beds with <6-h hydraulic retention time than those with ≥6h retention times.
Abstract: Meta-analysis approaches were used in this first quantitative synthesis of denitrifying woodchip bioreactors. Nitrate removal across environmental and design conditions was assessed from 26 published studies, representing 57 separate bioreactor units (i.e., walls, beds, and laboratory columns). Effect size calculations weighted the data based on variance and number of measurements for each bioreactor unit. Nitrate removal rates in bed and column studies were not significantly different, but both were significantly higher than wall studies. In denitrifying beds, wood source did not significantly affect nitrate removal rates. Nitrate removal (mass per volume) was significantly lower in beds with <6-h hydraulic retention times, which argues for ensuring that bed designs incorporate sufficient time for nitrate removal. Rates significantly declined after the first year of bed operation but then stabilized. Nitrogen limitation significantly affected bed nitrate removal. Categorical and linear assessments found significant nitrate removal effects with bed temperature; a of 2.15 was quite similar to other studies. Lessons from this meta-analysis can be incorporated into bed designs, especially extending hydraulic retention times to increase nitrate removal under low temperature and high flow conditions. Additional column studies are warranted for comparative assessments, as are field-based studies for assessing in situ conditions, especially in aging beds, with careful collection and reporting of design and environmental data. Future assessment of these systems might take a holistic view, reviewing nitrate removal in conjunction with other processes, including greenhouse gas and other unfavorable by-product production.
Lancaster University1, Stanford University2, James Cook University3, San Diego State University4, University of Michigan5, Duke University6, National Oceanic and Atmospheric Administration7, University of Alaska Fairbanks8, United States Department of Agriculture9, Northumbria University10, University of Washington11, University of Rhode Island12, Conservation International13, University of British Columbia14, Rutgers University15
TL;DR: This work identifies seven key social concepts that are largely absent from many efforts to pursue sustainability goals and presents existing and emerging well-tested indicators and proposes priority areas for conceptual and methodological development.
Abstract: With humans altering climate processes, biogeochemical cycles, and ecosystem functions (1), governments and societies confront the challenge of shaping a sustainable future for people and nature. Policies and practices to address these challenges must draw on social sciences, along with natural sciences and engineering (2). Although various social science approaches can enable and assess progress toward sustainability, debate about such concrete engagement is outpacing actual use. To catalyze uptake, we identify seven key social concepts that are largely absent from many efforts to pursue sustainability goals. We present existing and emerging well-tested indicators and propose priority areas for conceptual and methodological development.
TL;DR: The mean depth-independent, or barotropic transport, determined from the near-bottom current meter records was 45.6 Sv with an uncertainty of 8.9 Sv as mentioned in this paper.
Abstract: The Antarctic Circumpolar Current is an important component of the global climate system connecting the major ocean basins as it flows eastward around Antarctica, yet due to the paucity of data it remains unclear how much water is transported by the current. Between 2007 and 2011 flow through Drake Passage was continuously monitored with a line of moored instrumentation with unprecedented horizontal and temporal resolution. Annual mean near-bottom currents are remarkably stable from year to year. The mean depth-independent, or barotropic transport, determined from the near-bottom current meter records was 45.6 Sv with an uncertainty of 8.9 Sv. Summing the mean barotropic transport with the mean baroclinic transport relative to zero at the seafloor of 127.7 Sv gives a total transport through Drake Passage of 173.3 Sv. This new measurement is 30% larger than the canonical value often used as the benchmark for global circulation and climate models.
Ali H. Mokdad1, Mohammad H. Forouzanfar2, Farah Daoud2, Charbel El Bcheraoui2 +185 more•Institutions (92)
TL;DR: The eastern Mediterranean region is going through a crucial health phase, and the Arab uprisings and the wars that followed, coupled with ageing and population growth, will have a major impact on the region's health and resources.
TL;DR: In this paper, the authors explored the potential effects of financial education on the financial capability of American consumers and found that respondents who ever received financial education had higher scores in all financial capability indicators.
Abstract: The purpose of this study was to explore potential effects of financial education on the financial capability of American consumers. Data from the 2012 National Financial Capability Study were used to test the hypothesis that financial education is positively associated with financial capability. Four financial literacy and behaviour variables were used to form a financial capability index. Multivariate linear regression results showed that, after controlling for demographic and financial variables, respondents who ever received financial education had higher scores in all financial capability indicators (objective financial literacy, subjective financial literacy, desirable financial behaviour, perceived financial capability and the financial capability index). In addition, high school, college and workplace financial education variables showed positive associations with these financial capability indicators. Additional state comparison analyses provided evidence suggesting high school financial education may have direct impacts and spillover effects on consumer financial capability.
TL;DR: These results are consistent with (i) dispersal of marine sedimentary bacteria via the ocean, and (ii) selection of the subseafloor sedimentary community from within the community present in shallow sediment.
Abstract: We investigated compositional relationships between bacterial communities in the water column and those in deep-sea sediment at three environmentally distinct Pacific sites (two in the Equatorial Pacific and one in the North Pacific Gyre). Through pyrosequencing of the v4-v6 hypervariable regions of the 16S ribosomal RNA gene, we characterized 450,104 pyrotags representing 29,814 operational taxonomic units (OTUs, 97% similarity). Hierarchical clustering and non-metric multidimensional scaling partition the samples into four broad groups, regardless of geographic location: a photic-zone community, a subphotic community, a shallow sedimentary community and a subseafloor sedimentary community (⩾1.5 meters below seafloor). Abundance-weighted community compositions of water-column samples exhibit a similar trend with depth at all sites, with successive epipelagic, mesopelagic, bathypelagic and abyssopelagic communities. Taxonomic richness is generally highest in the water-column O2 minimum zone and lowest in the subseafloor sediment. OTUs represented by abundant tags in the subseafloor sediment are often present but represented by few tags in the water column, and represented by moderately abundant tags in the shallow sediment. In contrast, OTUs represented by abundant tags in the water are generally absent from the subseafloor sediment. These results are consistent with (i) dispersal of marine sedimentary bacteria via the ocean, and (ii) selection of the subseafloor sedimentary community from within the community present in shallow sediment.
TL;DR: A probe that uses a pH low insertion peptide to locate a pH-sensing dye at acidic cell surfaces is developed and it is found that the probe can measure surface pH, which is correlated with tumor aggressiveness and is sensitive to cell glycolytic activity.
Abstract: We have developed a way to measure cell surface pH by positioning a pH-sensitive fluorescent dye, seminaphtharhodafluor (SNARF), conjugated to the pH low insertion peptide (pHLIP). It has been observed that many diseased tissues are acidic and that tumors are especially so. A combination of effects acidifies tumor cell interiors, and cells pump out lactic acid and protons to maintain intracellular pH, acidifying the extracellular space. Overexpression of carbonic anhydrases on cell surfaces further contributes to acidification. Thus, the pH near tumor cell surfaces is expected to be low and to increase with distance from the membrane, so bulk pH measurements will not report surface acidity. Our new surface pH-measurement tool was validated in cancer cells grown in spheroids, in mouse tumor models in vivo, and in excised tumors. We found that the surface pH is sensitive to cell glycolytic activity: the pH decreases in high glucose and increases if glucose is replaced with nonmetabolized deoxyglucose. For highly metastatic cancer cells, the pH measured at the surface was 6.7-6.8, when the surrounding external pH was 7.4. The approach is sensitive enough to detect 0.2-0.3 pH unit changes in vivo in tumors induced by i.p. injection of glucose. The pH at the surfaces of highly metastatic cells within tumors was found to be about 6.1-6.4, whereas in nonmetastatic tumors, it was 6.7-6.9, possibly creating a way to distinguish more aggressive from less aggressive tumors. Other biological roles of surface acidity may be found, now that targeted measurements are possible.
TL;DR: Urolithins are the possible brain absorbable compounds which contribute to pomegranate's anti-AD effects warranting further in vivo studies on these compounds.
Abstract: Pomegranate shows neuroprotective effects against Alzheimer's disease (AD) in several reported animal studies. However, whether its constituent ellagitannins and/or their physiologically relevant gut microbiota-derived metabolites, namely, urolithins (6H-dibenzo[b,d]pyran-6-one derivatives), are the responsible bioactive constituents is unknown. Therefore, from a pomegranate extract (PE), previously reported by our group to have anti-AD effects in vivo, 21 constituents, which were primarily ellagitannins, were isolated and identified (by HPLC, NMR, and HRESIMS). In silico computational studies, used to predict blood-brain barrier permeability, revealed that none of the PE constituents, but the urolithins, fulfilled criteria required for penetration. Urolithins prevented β-amyloid fibrillation in vitro and methyl-urolithin B (3-methoxy-6H-dibenzo[b,d]pyran-6-one), but not PE or its predominant ellagitannins, had a protective effect in Caenorhabditis elegans post induction of amyloid β(1-42) induced neurotoxicity and paralysis. Therefore, urolithins are the possible brain absorbable compounds which contribute to pomegranate's anti-AD effects warranting further in vivo studies on these compounds.
TL;DR: Improved transmission electron microscopy images and image averages of the rosette-type CSC are obtained, revealing the frequent triangularity and average cross-sectional area in the plasma membrane of its individual lobes and multifaceted data support a rosettes CSC with 18 CESAs that mediates the synthesis of a fundamental microfibril composed of 18 glucan chains.
Abstract: A six-lobed membrane spanning cellulose synthesis complex (CSC) containing multiple cellulose synthase (CESA) glycosyltransferases mediates cellulose microfibril formation. The number of CESAs in the CSC has been debated for decades in light of changing estimates of the diameter of the smallest microfibril formed from the β-1,4 glucan chains synthesized by one CSC. We obtained more direct evidence through generating improved transmission electron microscopy (TEM) images and image averages of the rosette-type CSC, revealing the frequent triangularity and average cross-sectional area in the plasma membrane of its individual lobes. Trimeric oligomers of two alternative CESA computational models corresponded well with individual lobe geometry. A six-fold assembly of the trimeric computational oligomer had the lowest potential energy per monomer and was consistent with rosette CSC morphology. Negative stain TEM and image averaging showed the triangularity of a recombinant CESA cytosolic domain, consistent with previous modeling of its trimeric nature from small angle scattering (SAXS) data. Six trimeric SAXS models nearly filled the space below an average FF-TEM image of the rosette CSC. In summary, the multifaceted data support a rosette CSC with 18 CESAs that mediates the synthesis of a fundamental microfibril composed of 18 glucan chains.
TL;DR: ERA-EDTA-based prevalence estimates and application of a uniform definition of prevalence to population-based studies consistently indicate that the ADPKD point prevalence is <5/10 000, the threshold for rare disease in the EU.
Abstract: Background Autosomal dominant polycystic kidney disease (ADPKD) is a leading cause of end-stage renal disease, but estimates of its prevalence vary by >10-fold. The objective of this study was to examine the public health impact of ADPKD in the European Union (EU) by estimating minimum prevalence (point prevalence of known cases) and screening prevalence (minimum prevalence plus cases expected after population-based screening). Methods A review of the epidemiology literature from January 1980 to February 2015 identified population-based studies that met criteria for methodological quality. These examined large German and British populations, providing direct estimates of minimum prevalence and screening prevalence. In a second approach, patients from the 2012 European Renal Association‒European Dialysis and Transplant Association (ERA-EDTA) Registry and literature-based inflation factors that adjust for disease severity and screening yield were used to estimate prevalence across 19 EU countries (N = 407 million). Results Population-based studies yielded minimum prevalences of 2.41 and 3.89/10 000, respectively, and corresponding estimates of screening prevalences of 3.3 and 4.6/10 000. A close correspondence existed between estimates in countries where both direct and registry-derived methods were compared, which supports the validity of the registry-based approach. Using the registry-derived method, the minimum prevalence was 3.29/10 000 (95% confidence interval 3.27-3.30), and if ADPKD screening was implemented in all countries, the expected prevalence was 3.96/10 000 (3.94-3.98). Conclusions ERA-EDTA-based prevalence estimates and application of a uniform definition of prevalence to population-based studies consistently indicate that the ADPKD point prevalence is <5/10 000, the threshold for rare disease in the EU.
TL;DR: This position statement provides a classification system for older adults in LTC settings, describes how diabetes goals and management should be tailored based on comorbidities, delineates key issues to consider when using glucose-lowering agents in this population, and provides recommendations on how to replace SSI in L TC facilities.
Abstract: Diabetes is more common in older adults, has a high prevalence in long-term care (LTC) facilities, and is associated with significant disease burden and higher cost. The heterogeneity of this population with regard to comorbidities and overall health status is critical to establishing personalized goals and treatments for diabetes. The risk of hypoglycemia is the most important factor in determining glycemic goals due to the catastrophic consequences in this population. Simplified treatment regimens are preferred, and the sole use of sliding scale insulin (SSI) should be avoided. This position statement provides a classification system for older adults in LTC settings, describes how diabetes goals and management should be tailored based on comorbidities, delineates key issues to consider when using glucose-lowering agents in this population, and provides recommendations on how to replace SSI in LTC facilities. As these patients transition from one setting to another, or from one provider to another, their risk for adverse events increases. Strategies are presented to reduce these risks and ensure safe transitions. This article addresses diabetes management at end of life and in those receiving palliative and hospice care. The integration of diabetes management into LTC facilities is important and requires an interprofessional team approach. To facilitate this approach, acceptance by administrative personnel is needed, as are protocols and possibly system changes. It is important for clinicians to understand the characteristics, challenges, and barriers related to the older population living in LTC facilities as well as the proper functioning of the facilities themselves. Once these challenges are identified, individualized approaches can be designed to improve diabetes management while lowering the risk of hypoglycemia and ultimately improving quality of life.
Kansas State University1, Oklahoma State University–Stillwater2, Boyce Thompson Institute for Plant Research3, University of Rhode Island4, Max Planck Society5, University of Sydney6, Human Genome Sequencing Center7, University of Kansas8, Massachusetts Institute of Technology9, University of Barcelona10, China Agricultural University11, François Rabelais University12, Commonwealth Scientific and Industrial Research Organisation13, University of Oxford14, Academy of Athens15, University of Copenhagen16, Columbia University17, Southwest University18, Reed College19, Fraunhofer Society20, Donghua University21, Northwest A&F University22, University of Texas Southwestern Medical Center23, University of Southern Maine24, University of California, Irvine25, Anhui Agricultural University26, University of Rochester27, Northeastern University28, Cornell University29, Chinese Academy of Sciences30, Hamilton College31, University of Hamburg32, Ghent University33, National and Kapodistrian University of Athens34, University of Wisconsin-Madison35, North Carolina State University36, University of Siegen37, Oregon Health & Science University38, University of Cambridge39, University of Massachusetts Amherst40, College of Charleston41, University of Giessen42, University of South Carolina43, University of Missouri–Kansas City44, Rothamsted Research45
TL;DR: The sequence and annotation of the M. sexta genome, and a survey of gene expression in various tissues and developmental stages, provide an important new resource from a well-studied model insect species and will facilitate further biochemical and mechanistic experimental studies of many biological systems in insects.
TL;DR: A Bayesian classification approach for automatic text categorization using class-specific features so that most feature selection criteria, such as Information Gain and Maximum Discrimination, can be easily incorporated into this approach.
Abstract: In this paper, we present a Bayesian classification approach for automatic text categorization using class-specific features. Unlike conventional text categorization approaches, our proposed method selects a specific feature subset for each class. To apply these class-specific features for classification, we follow Baggenstoss's PDF Projection Theorem (PPT) to reconstruct the PDFs in raw data space from the class-specific PDFs in low-dimensional feature subspace, and build a Bayesian classification rule. One noticeable significance of our approach is that most feature selection criteria, such as Information Gain (IG) and Maximum Discrimination (MD), can be easily incorporated into our approach. We evaluate our method's classification performance on several real-world benchmarks, compared with the state-of-the-art feature selection approaches. The superior results demonstrate the effectiveness of the proposed approach and further indicate its wide potential applications in data mining.
TL;DR: In this paper, a series of lithium alkyl trimethyl borates and lithium aryl tricarborates were used as cathode film forming additive for high voltage graphite/LiNi0.5Mn1.5O4 cells.
Abstract: A novel series of lithium alkyl trimethyl borates and lithium aryl trimethyl borates have been prepared and investigated as cathode film forming additives. The borates are prepared via the reaction of lithium alkoxides or lithium phenoxides with trimethyl borate. Incorporation of 0.5–2.0% (wt) of the lithium borates to a baseline electrolyte (1.0 M LiPF6 in 3 : 7 (EC/EMC)) results in improved capacity retention and efficiency of high voltage graphite/LiNi0.5Mn1.5O4 cells especially upon cycling at elevated temperature (55 °C). The improved performance results from the sacrificial oxidation of the lithium borate on the cathode surface to generate a cathode passivation film. The lithium borates can be readily structurally modified to act as a functional group delivery agent to modify the cathode surface. Ex situ surface analysis of the electrodes after cycling confirms that the lithium borates modify the cathode surface and generate a borate rich surface film which inhibits electrolyte oxidation and Mn dissolution.
National Oceanic and Atmospheric Administration1, University of Washington2, Duke University3, University of Alaska Fairbanks4, United States Forest Service5, Northumbria University6, University of Rhode Island7, Stanford University8, James Cook University9, San Diego State University10, Conservation International11, University of British Columbia12, Rutgers University13
TL;DR: In this paper, a conceptual framework of human wellbeing is proposed to guide the development of indicators and a complementary social science research agenda for ecosystem-based management, and four major social science-based constituents of wellbeing: connections, capabilities, conditions, and cross-cutting domains.
TL;DR: In this paper, the authors proposed a service-oriented architecture for fog computing, where the embedded computer collects the sensed data as time series, analyzes it, and finds similar patterns present.
Abstract: The size of multi-modal, heterogeneous data collected through various sensors is growing exponentially. It demands intelligent data reduction, data mining and analytics at edge devices. Data compression can reduce the network bandwidth and transmission power consumed by edge devices. This paper proposes, validates and evaluates Fog Data, a service-oriented architecture for Fog computing. The center piece of the proposed architecture is a low power embedded computer that carries out data mining and data analytics on raw data collected from various wearable sensors used for telehealth applications. The embedded computer collects the sensed data as time series, analyzes it, and finds similar patterns present. Patterns are stored, and unique patterns are transmited. Also, the embedded computer extracts clinically relevant information that is sent to the cloud. A working prototype of the proposed architecture was built and used to carry out case studies on telehealth big data applications. Specifically, our case studies used the data from the sensors worn by patients with either speech motor disorders or cardiovascular problems. We implemented and evaluated both generic and application specific data mining techniques to show orders of magnitude data reduction and hence transmission power savings. Quantitative evaluations were conducted for comparing various data mining techniques and standard data compression techniques. The obtained results showed substantial improvement in system efficiency using the Fog Data architecture.
TL;DR: In this article, two information measures, Kullback-Leibler divergence and Jeffreys divergence, were revisited for binary hypothesis testing, and analyzed their asymptotic properties relating to type I and type II errors of a Bayesian classifier.
Abstract: Automated feature selection is important for text categorization to reduce feature size and to speed up learning process of classifiers. In this paper, we present a novel and efficient feature selection framework based on the Information Theory, which aims to rank the features with their discriminative capacity for classification. We first revisit two information measures: Kullback-Leibler divergence and Jeffreys divergence for binary hypothesis testing, and analyze their asymptotic properties relating to type I and type II errors of a Bayesian classifier. We then introduce a new divergence measure, called Jeffreys-Multi-Hypothesis (JMH) divergence, to measure multi-distribution divergence for multi-class classification. Based on the JMH-divergence, we develop two efficient feature selection methods, termed maximum discrimination ( $MD$ ) and methods, for text categorization. The promising results of extensive experiments demonstrate the effectiveness of the proposed approaches.
TL;DR: It is demonstrated that FANCD2 protein is required to ensure efficient CFS replication and mechanistic insight into how FAN CD2 regulates CFS stability is provided.
07 Apr 2016
TL;DR: In this paper, the state of the art in current uses of Fourier transform infrared (FTIR) for the elucidation of bacteria-nanoparticle interactions is described, including advantages for the application of FTIR in the field of nanotoxicology, including higher signal-to-noise ratio, high energy throughput, as well as high accuracy and stability which are applicable to solid phase samples but not recommended for assays in the liquid phase.
Abstract: Fourier transform infrared (FTIR) is a spectroscopy method that can identify variations in the total composition of microorganisms through the determination of changes in functional groups in biomolecules. FTIR measures the vibration and rotation of molecules influenced by infrared radiation at a specific wavelength. This technique allows the identification of structural changes in the molecular binding between microorganisms and metal atoms, which can provide information about the nature of their interactions. In this review article, we will describe the state of the art in current uses of FTIR for the elucidation of bacteria–nanoparticle interactions. We will describe advantages for the application of FTIR in the field of nanotoxicology, including higher signal-to-noise ratio, high energy throughput, as well as high accuracy and stability which are applicable to solid phase samples but not recommended for assays in the liquid phase. Limitations such as multiple background scans and post-processing analysis are not deniable. Comparison of FTIR with other commonly used tools such as Raman spectroscopy, mass spectrometry, nuclear magnetic resonance spectroscopy, and X-ray photoelectron spectroscopy is also discussed. Finally, we present an application of FTIR for the assessment of bacterial changes in response to the exposure to silver nanoparticles (AgNPs). The results showed that the AgNPs-induced structural changes in the peptide and amino acids region may lead to alterations of conformation and/or composition of Amid B and Amid III. These results showed that bacteria developed resistance toward AgNPs and resulted in changes in the genotype and expression in the phenotype. Here, ATR–FTIR provided the evidence of the AgNPs cytotoxicity-induced intracellular level alterations in bacteria.