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Sample records for metabolism predicts ecological

  1. Predictive systems ecology.

    Science.gov (United States)

    Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G

    2013-11-22

    Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

  2. Metabolic theory predicts animal self-thinning.

    Science.gov (United States)

    Jonsson, Tomas

    2017-05-01

    The metabolic theory of ecology (MTE) predicts observed patterns in ecology based on metabolic rates of individuals. The theory is influential but also criticized for a lack of firm empirical evidence confirming MTE's quantitative predictions of processes, e.g. outcome of competition, at population or community level. Self-thinning is a well-known population level phenomenon among plants, but a much less studied phenomenon in animal populations and no consensus exists on what a universal thinning slope for animal populations might be, or if it exists. The goal of this study was to use animal self-thinning as a tool to test population-level predictions from MTE, by analysing (i) if self-thinning can be induced in populations of house crickets (Acheta domesticus) and (ii) if the resulting thinning trajectories can be predicted from metabolic theory, using estimates of the species-specific metabolic rate of A. domesticus. I performed a laboratory study where the growth of A. domesticus was followed, from hatching until emergence as adults, in 71 cohorts of five different starting densities. Ninety-six per cent of all cohorts in the three highest starting densities showed evidence of self-thinning, with estimated thinning slopes in general being remarkably close to that expected under metabolic constraints: A cross-sectional analysis of all data showing evidence of self-thinning produced an ordinary least square (OLS) slope of -1·11, exactly that predicted from specific metabolic allometry of A. domesticus. This result is furthermore supported by longitudinal analyses, allowing for independent responses within cohorts, producing a mean OLS slope across cohorts of -1·13 and a fixed effect linear mixed effects models slope of -1·09. Sensitivity analysis showed that these results are robust to how the criterion for on-going self-thinning was defined. Finally, also as predicted by metabolic theory, temperature had a negative effect on the thinning intercept, producing

  3. Ecological network analysis of China's societal metabolism.

    Science.gov (United States)

    Zhang, Yan; Liu, Hong; Li, Yating; Yang, Zhifeng; Li, Shengsheng; Yang, Naijin

    2012-01-01

    Uncontrolled socioeconomic development has strong negative effects on the ecological environment, including pollution and the depletion and waste of natural resources. These serious consequences result from the high flows of materials and energy through a socioeconomic system produced by exchanges between the system and its surroundings, causing the disturbance of metabolic processes. In this paper, we developed an ecological network model for a societal system, and used China in 2006 as a case study to illustrate application of the model. We analyzed China's basic metabolic processes and used ecological network analysis to study the network relationships within the system. Basic components comprised the internal environment, five sectors (agriculture, exploitation, manufacturing, domestic, and recycling), and the external environment. We defined 21 pairs of ecological relationships in China's societal metabolic system (excluding self-mutualism within a component). Using utility and throughflow analysis, we found that exploitation, mutualism, and competition relationships accounted for 76.2, 14.3, and 9.5% of the total relationships, respectively. In our trophic level analysis, the components were divided into producers, consumers, and decomposers according to their positions in the system. Our analyses revealed ways to optimize the system's structure and adjust its functions, thereby promoting healthier socioeconomic development, and suggested ways to apply ecological network analysis in future socioeconomic research. Copyright © 2011 Elsevier Ltd. All rights reserved.

  4. Unifying elemental stoichiometry and metabolic theory in predicting species abundances

    NARCIS (Netherlands)

    Ott, David; Digel, Christoph; Rall, Björn Christian; Maraun, Mark; Scheu, Stefan; Brose, Ulrich

    2014-01-01

    While metabolic theory predicts variance in population density within communities depending on population average body masses, the ecological stoichiometry concept relates density variation across communities to varying resource stoichiometry. Using a data set including biomass densities of 4959

  5. 2007 Archaea: Ecology, Metabolism and Molecular Biology

    Energy Technology Data Exchange (ETDEWEB)

    Imke Schroeder

    2008-09-18

    The Archaea are a fascinating and diverse group of prokaryotic organisms with deep roots overlapping those of eukaryotes. The focus of this GRC conference, 'Archaea: Ecology Metabolism & Molecular Biology', expands on a number of emerging topics highlighting the evolution and composition of microbial communities and novel archaeal species, their impact on the environment, archaeal metabolism, and research that stems from sequence analysis of archaeal genomes. The strength of this conference lies in its ability to couple reputable areas with new scientific topics in an atmosphere of stimulating exchange. This conference remains an excellent opportunity for younger scientists to interact with world experts in this field.

  6. 2011 Archaea: Ecology, Metabolism, & Molecular Biology

    Energy Technology Data Exchange (ETDEWEB)

    Keneth Stedman

    2011-08-05

    Archaea, one of three major evolutionary lineages of life, are a fascinating and diverse group of microbes with deep roots overlapping those of eukaryotes. The focus of the 'Archaea: Ecology Metabolism & Molecular Biology' GRC conference expands on a number of emerging topics highlighting new paradigms in archaeal metabolism, genome function and systems biology; information processing; evolution and the tree of life; the ecology and diversity of archaea and their viruses. The strength of this conference lies in its ability to couple a field with a rich history in high quality research with new scientific findings in an atmosphere of stimulating exchange. This conference remains an excellent opportunity for younger scientists to interact with world experts in this field.

  7. 2009 Archaea: Ecology, Metabolism & Molecular Biology GRC

    Energy Technology Data Exchange (ETDEWEB)

    Furlow, Julie Maupin- [Univ. of Florida, Gainesville, FL (United States)

    2009-07-26

    Archaea, one of three major evolutionary lineages of life, are a fascinating and diverse group of microbes with deep roots overlapping those of eukaryotes. The focus of the 'Archaea: Ecology Metabolism & Molecular Biology' GRC conference expands on a number of emerging topics highlighting new paradigms in archaeal metabolism, genome function and systems biology; information processing; evolution and the tree of life; the ecology and diversity of archaea and their viruses; and industrial applications. The strength of this conference lies in its ability to couple a field with a rich history in high quality research with new scientific findings in an atmosphere of stimulating exchange. This conference remains an excellent opportunity for younger scientists to interact with world experts in this field.

  8. Soil-covered strategy for ecological restoration alters the bacterial community structure and predictive energy metabolic functions in mine tailings profiles.

    Science.gov (United States)

    Li, Yang; Sun, Qingye; Zhan, Jing; Yang, Yang; Wang, Dan

    2017-03-01

    Native soil amendment has been widely used to stabilize mine tailings and speed up the development of soil biogeochemical functions before revegetation; however, it remains poorly understood about the response of microbial communities to ecological restoration of mine tailings with soil-covered strategy. In this study, microbial communities along a 60-cm profile were investigated in mine tailings during ecological restoration of two revegetation strategies (directly revegetation and native soil covered) with different plant species. The mine tailings were covered by native soils as thick as 40 cm for more than 10 years, and the total nitrogen, total organic carbon, water content, and heavy metal (Fe, Cu, and Zn) contents in the 0-40 cm intervals of profiles were changed. In addition, increased microbial diversity and changed microbial community structure were also found in the 10-40 cm intervals of profiles in soil-covered area. Soil-covered strategy rather than plant species and soil depth was the main factor influencing the bacterial community, which explained the largest portion (29.96%) of the observed variation. Compared directly to revegetation, soil-covered strategy exhibited the higher relative abundance of Acidobacteria and Deltaproteobacteria and the lower relative abundance of Bacteroidetes, Gemmatimonadetes, Betaproteobacteria, and Gammaproteobacteria. PICRUSt analysis further demonstrated that soil-covered caused energy metabolic functional changes in carbon, nitrogen, and sulfur metabolism. Given all these, the soil-covered strategy may be used to fast-track the establishment of native microbial communities and is conducive to the rehabilitation of biogeochemical processes for establishing native plant species.

  9. The role of Dynamic Energy Budget theory in predictive modeling of stressor impacts on ecological systems. Comment on: ;Physics of metabolic organization; by Marko Jusup et al.

    Science.gov (United States)

    Galic, Nika; Forbes, Valery E.

    2017-03-01

    Human activities have been modifying ecosystems for centuries, from pressures on wild populations we harvest to modifying habitats through urbanization and agricultural activities. Changes in global climate patterns are adding another layer of, often unpredictable, perturbations to ecosystems on which we rely for life support [1,2]. To ensure the sustainability of ecosystem services, especially at this point in time when the human population is estimated to grow by another 2 billion by 2050 [3], we need to predict possible consequences of our actions and suggest relevant solutions [4,5]. We face several challenges when estimating adverse impacts of our actions on ecosystems. We describe these in the context of ecological risk assessment of chemicals. Firstly, when attempting to assess risk from exposure to chemicals, we base our decisions on a very limited number of species that are easily cultured and kept in the lab. We assume that preventing risk to these species will also protect all of the untested species present in natural ecosystems [6]. Secondly, although we know that chemicals interact with other stressors in the field, the number of stressors that we can test is limited due to logistical and ethical reasons. Similarly, empirical approaches are limited in both spatial and temporal scale due to logistical, financial and ethical reasons [7,8]. To bypass these challenges, we can develop ecological models that integrate relevant life history and other information and make testable predictions across relevant spatial and temporal scales [8-10].

  10. Ecological implications of metabolic compensation at low temperatures in salamanders.

    Science.gov (United States)

    Catenazzi, Alessandro

    2016-01-01

    Global warming is influencing the biology of the world's biota. Temperature increases are occurring at a faster pace than that experienced by organisms in their evolutionary histories, limiting the organisms' response to new conditions. Mechanistic models that include physiological traits can help predict species' responses to warming. Changes in metabolism at high temperatures are often examined; yet many species are behaviorally shielded from high temperatures. Salamanders generally favor cold temperatures and are one of few groups of metazoans to be most species-rich in temperate regions. I examined variation in body temperature, behavioral activity, and temperature dependence of resting heart rate, used as a proxy for standard metabolic rate, in fire salamanders (Salamandra salamandra). Over 26 years, I found that salamanders are behaviorally active at temperatures as low as 1 °C, and aestivate at temperatures above 16 °C. Infrared thermography indicates limited thermoregulation opportunities for these nocturnal amphibians. Temperature affects resting heart rate, causing metabolic depression above 11 °C, and metabolic compensation below 8 °C: heart rate at 3 °C is 224% the expected heart rate. Thus, salamanders operating at low temperatures during periods of peak behavioral activity are able to maintain a higher metabolic rate than the rate expected in absence of compensation. This compensatory mechanism has important ecological implications, because it increases estimated seasonal heart rates. Increased heart rate, and thus metabolism, will require higher caloric intake for field-active salamanders. Thus, it is important to consider a species performance breadth over the entire temperature range, and particularly low temperatures that are ecologically relevant for cold tolerant species such as salamanders.

  11. Ecological implications of metabolic compensation at low temperatures in salamanders

    Directory of Open Access Journals (Sweden)

    Alessandro Catenazzi

    2016-05-01

    Full Text Available Global warming is influencing the biology of the world’s biota. Temperature increases are occurring at a faster pace than that experienced by organisms in their evolutionary histories, limiting the organisms’ response to new conditions. Mechanistic models that include physiological traits can help predict species’ responses to warming. Changes in metabolism at high temperatures are often examined; yet many species are behaviorally shielded from high temperatures. Salamanders generally favor cold temperatures and are one of few groups of metazoans to be most species-rich in temperate regions. I examined variation in body temperature, behavioral activity, and temperature dependence of resting heart rate, used as a proxy for standard metabolic rate, in fire salamanders (Salamandra salamandra. Over 26 years, I found that salamanders are behaviorally active at temperatures as low as 1 °C, and aestivate at temperatures above 16 °C. Infrared thermography indicates limited thermoregulation opportunities for these nocturnal amphibians. Temperature affects resting heart rate, causing metabolic depression above 11 °C, and metabolic compensation below 8 °C: heart rate at 3 °C is 224% the expected heart rate. Thus, salamanders operating at low temperatures during periods of peak behavioral activity are able to maintain a higher metabolic rate than the rate expected in absence of compensation. This compensatory mechanism has important ecological implications, because it increases estimated seasonal heart rates. Increased heart rate, and thus metabolism, will require higher caloric intake for field-active salamanders. Thus, it is important to consider a species performance breadth over the entire temperature range, and particularly low temperatures that are ecologically relevant for cold tolerant species such as salamanders.

  12. Saccharomyces cerevisiae metabolism in ecological context

    Science.gov (United States)

    Jouhten, Paula; Ponomarova, Olga; Gonzalez, Ramon

    2016-01-01

    The architecture and regulation of Saccharomyces cerevisiae metabolic network are among the best studied owing to its widespread use in both basic research and industry. Yet, several recent studies have revealed notable limitations in explaining genotype–metabolic phenotype relations in this yeast, especially when concerning multiple genetic/environmental perturbations. Apparently unexpected genotype–phenotype relations may originate in the evolutionarily shaped cellular operating principles being hidden in common laboratory conditions. Predecessors of laboratory S. cerevisiae strains, the wild and the domesticated yeasts, have been evolutionarily shaped by highly variable environments, very distinct from laboratory conditions, and most interestingly by social life within microbial communities. Here we present a brief review of the genotypic and phenotypic peculiarities of S. cerevisiae in the context of its social lifestyle beyond laboratory environments. Accounting for this ecological context and the origin of the laboratory strains in experimental design and data analysis would be essential in improving the understanding of genotype–environment–phenotype relationships. PMID:27634775

  13. 2003 Archaea: Ecology, Metabolism and Molecular Biology

    Energy Technology Data Exchange (ETDEWEB)

    Richard F. Shand

    2004-09-21

    The Gordon Research Conference (GRC) on 2003 Archaea: Ecology, Metabolism and Molecular Biology was held at Proctor Academy, Andover, NH from August 3-8, 2003. The Conference was well-attended with 150 participants (attendees list attached). The attendees represented the spectrum of endeavor in this field coming from academia, industry, and government laboratories, both U.S. and foreign scientists, senior researchers, young investigators, and students. In designing the formal speakers program, emphasis was placed on current unpublished research and discussion of the future target areas in this field. There was a conscious effort to stimulate lively discussion about the key issues in the field today. Time for formal presentations was limited in the interest of group discussions. In order that more scientists could communicate their most recent results, poster presentation time was scheduled. Attached is a copy of the formal schedule and speaker program and the poster program. In addition to these formal interactions, ''free time'' was scheduled to allow informal discussions. Such discussions are fostering new collaborations and joint efforts in the field. I want to personally thank you for your support of this Conference. As you know, in the interest of promoting the presentation of unpublished and frontier-breaking research, Gordon Research Conferences does not permit publication of meeting proceedings. If you wish any further details, please feel free to contact me. Thank you, Dr. Richard F. Shand, 2003 Conference Chair.

  14. Predicting drug metabolism: Concepts and challenges

    OpenAIRE

    Testa, B.; Balmat, A.-L; Long, Anthony

    2017-01-01

    The paper begins with a discussion of the needs and goals of metabolic predictions in early drug research. Major difficulties toward this objective are examined, mainly the various substrate and product selectivities characteristic of drug metabolism. In a second part, we classify and summarize the major in silico methods used to predict drug metabolism. A discrimination is thus made between "local ”and "global ”systems. In the last part of the paper, the program METEOR is presented and evalu...

  15. Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

    Energy Technology Data Exchange (ETDEWEB)

    Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.; Borenstein, Elhanan; Sanchez, Laura M.

    2015-12-22

    ABSTRACT

    Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in

  16. Plant interactions alter the predictions of metabolic scaling theory

    DEFF Research Database (Denmark)

    Lin, Yue; Berger, Uta; Grimm, Volker

    2013-01-01

    produced variable results, and the validity of MST is intensely debated. MST focuses on organisms’ internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model....... Slopes were significantly shallower than 24/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic...... processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive....

  17. From metabolism to ecology: cross-feeding interactions shape the balance between polymicrobial conflict and mutualism.

    Science.gov (United States)

    Estrela, Sylvie; Trisos, Christopher H; Brown, Sam P

    2012-11-01

    Polymicrobial interactions are widespread in nature and play a major role in maintaining human health and ecosystems. Whenever one organism uses metabolites produced by another organism as energy or nutrient sources, it is called cross-feeding. The ecological outcomes of cross-feeding interactions are poorly understood and potentially diverse: mutualism, competition, exploitation, or commensalism. A major reason for this uncertainty is the lack of theoretical approaches linking microbial metabolism to microbial ecology. To address this issue, we explore the dynamics of a one-way interspecific cross-feeding interaction in which food can be traded for a service (detoxification). Our results show that diverse ecological interactions (competition, mutualism, exploitation) can emerge from this simple cross-feeding interaction and can be predicted by the metabolic, demographic, and environmental parameters that govern the balance of the costs and benefits of association. In particular, our model predicts stronger mutualism for intermediate by-product toxicity because the resource-service exchange is constrained to the service being neither too vital (high toxicity impairs resource provision) nor dispensable (low toxicity reduces need for service). These results support the idea that bridging microbial ecology and metabolism is a critical step toward a better understanding of the factors governing the emergence and dynamics of polymicrobial interactions.

  18. Plant interactions alter the predictions of metabolic scaling theory.

    Directory of Open Access Journals (Sweden)

    Yue Lin

    Full Text Available Metabolic scaling theory (MST is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of -4/3 between mean individual biomass and density during density-dependent mortality (self-thinning. Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms' internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric, and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than -4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.

  19. Predicting Ecological Roles in the Rhizosphere Using Metabolome and Transportome Modeling.

    Science.gov (United States)

    Larsen, Peter E; Collart, Frank R; Dai, Yang

    2015-01-01

    The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. However, new algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad's ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism's transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.

  20. Predicting Ecological Roles in the Rhizosphere Using Metabolome and Transportome Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, Peter E.; Collart, Frank R.; Dai, Yang; Blanchard, Jeffrey L.

    2015-09-02

    The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. However, new algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad's ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism's transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.

  1. An urban metabolism and ecological footprint assessment of Metro Vancouver.

    Science.gov (United States)

    Moore, Jennie; Kissinger, Meidad; Rees, William E

    2013-07-30

    As the world urbanizes, the role of cities in determining sustainability outcomes grows in importance. Cities are the dominant form of human habitat, and most of the world's resources are either directly or indirectly consumed in cities. Sustainable city analysis and management requires understanding the demands a city places on a wider geographical area and its ecological resource base. We present a detailed, integrated urban metabolism of residential consumption and ecological footprint analysis of the Vancouver metropolitan region for the year 2006. Our overall goal is to demonstrate the application of a bottom-up ecological footprint analysis using an urban metabolism framework at a metropolitan, regional scale. Our specific objectives are: a) to quantify energy and material consumption using locally generated data and b) to relate these data to global ecological carrying capacity. Although water is the largest material flow through Metro Vancouver (424,860,000 m(3)), it has the smallest ecological footprint (23,100 gha). Food (2,636,850 tonnes) contributes the largest component to the ecological footprint (4,514,400 gha) which includes crop and grazing land as well as carbon sinks required to sequester emissions from food production and distribution. Transportation fuels (3,339,000 m(3)) associated with motor vehicle operation and passenger air travel comprises the second largest material flow through the region and the largest source of carbon dioxide emissions (7,577,000 tonnes). Transportation also accounts for the second largest component of the EF (2,323,200 gha). Buildings account for the largest electricity flow (17,515,150 MWh) and constitute the third largest component of the EF (1,779,240 gha). Consumables (2,400,000 tonnes) comprise the fourth largest component of the EF (1,414,440 gha). Metro Vancouver's total Ecological Footprint in 2006 was 10,071,670 gha, an area approximately 36 times larger than the region itself. The EFA reveals that

  2. Machine learning methods for metabolic pathway prediction

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2010-01-01

    Full Text Available Abstract Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations.

  3. Machine learning methods for metabolic pathway prediction

    Science.gov (United States)

    2010-01-01

    Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML) methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations. PMID:20064214

  4. Thermodynamics predicts density-dependent energy use in organisms and ecological communities.

    Science.gov (United States)

    Yen, Jian D L; Paganin, David M; Thomson, James R; Mac Nally, Ralph

    2015-04-01

    Linking our knowledge of organisms to our knowledge of ecological communities and ecosystems is a key challenge for ecology. Individual size distributions (ISDs) link the size of individual organisms to the structure of ecological communities, so that studying ISDs might provide insight into how organism functioning affects ecosystems. Similarly shaped ISDs among ecosystems, coupled with allometric links between organism size and resource use, suggest the possibility of emergent resource-use patterns in ecological communities. We drew on thermodynamics to develop a maximization principle that predicted both organism and community energy use. These predictions highlighted the importance of density-dependent metabolic rates and were able to explain nonlinear relationships between community energy use and community biomass. We analyzed data on fish community energy use and biomass and found evidence of nonlinear scaling, which was predicted by the thermodynamic principle developed here and is not explained by other theories of ISDs. Detailed measurements of organism energy use will clarify the role of density dependence in driving metabolic rates and will further test our derived thermodynamic principle. Importantly, our study highlights the potential for fundamental links between ecology and thermodynamics.

  5. Population FBA predicts metabolic phenotypes in yeast.

    Directory of Open Access Journals (Sweden)

    Piyush Labhsetwar

    2017-09-01

    Full Text Available Using protein counts sampled from single cell proteomics distributions to constrain fluxes through a genome-scale model of metabolism, Population flux balance analysis (Population FBA successfully described metabolic heterogeneity in a population of independent Escherichia coli cells growing in a defined medium. We extend the methodology to account for correlations in protein expression arising from the co-regulation of genes and apply it to study the growth of independent Saccharomyces cerevisiae cells in two different growth media. We find the partitioning of flux between fermentation and respiration predicted by our model agrees with recent 13C fluxomics experiments, and that our model largely recovers the Crabtree effect (the experimentally known bias among certain yeast species toward fermentation with the production of ethanol even in the presence of oxygen, while FBA without proteomics constraints predicts respirative metabolism almost exclusively. The comparisons to the 13C study showed improvement upon inclusion of the correlations and motivated a technique to systematically identify inconsistent kinetic parameters in the literature. The minor secretion fluxes for glycerol and acetate are underestimated by our method, which indicate a need for further refinements to the metabolic model. For yeast cells grown in synthetic defined (SD medium, the calculated broad distribution of growth rates matches experimental observations from single cell studies, and we characterize several metabolic phenotypes within our modeled populations that make use of diverse pathways. Fast growing yeast cells are predicted to perform significant amount of respiration, use serine-glycine cycle and produce ethanol in mitochondria as opposed to slow growing cells. We use a genetic algorithm to determine the proteomics constraints necessary to reproduce the growth rate distributions seen experimentally. We find that a core set of 51 constraints are essential but

  6. The SMARTCyp cytochrome P450 metabolism prediction server

    DEFF Research Database (Denmark)

    Rydberg, Patrik; Gloriam, David Erik Immanuel; Olsen, Lars

    2010-01-01

    The SMARTCyp server is the first web application for site of metabolism prediction of cytochrome P450-mediated drug metabolism.......The SMARTCyp server is the first web application for site of metabolism prediction of cytochrome P450-mediated drug metabolism....

  7. Ecological relationship analysis of the urban metabolic system of Beijing, China

    International Nuclear Information System (INIS)

    Li Shengsheng; Zhang Yan; Yang Zhifeng; Liu Hong; Zhang Jinyun

    2012-01-01

    Cities can be modelled as giant organisms, with their own metabolic processes, and can therefore be studied using the same tools used for biological metabolic systems. The complicated distribution of compartments within these systems and the functional relationships among them define the system's network structure. Taking Beijing as an example, we divided the city's internal system into metabolic compartments, then used ecological network analysis to calculate a comprehensive utility matrix for the flows between compartments within Beijing's metabolic system from 1998 to 2007 and to identify the corresponding functional relationships among the system's compartments. Our results show how ecological network analysis, utility analysis, and relationship analysis can be used to discover the implied ecological relationships within a metabolic system, thereby providing insights into the system's internal metabolic processes. Such analyses provide scientific support for urban ecological management. - Highlights: ► Urban metabolic processes can be analyzed by treating cities as superorganisms. ► We developed an ecological network model for an urban system. ► We studied the system's network relationships using ecological network analysis. ► We developed indices for judging the system's synergism and degree of stability. - Using Beijing as an example of an urban superorganism, we used ecological network analysis to describe the ecological relationships among the urban metabolic system's compartments.

  8. Twitter Predicts Citation Rates of Ecological Research.

    Directory of Open Access Journals (Sweden)

    Brandon K Peoples

    Full Text Available The relationship between traditional metrics of research impact (e.g., number of citations and alternative metrics (altmetrics such as Twitter activity are of great interest, but remain imprecisely quantified. We used generalized linear mixed modeling to estimate the relative effects of Twitter activity, journal impact factor, and time since publication on Web of Science citation rates of 1,599 primary research articles from 20 ecology journals published from 2012-2014. We found a strong positive relationship between Twitter activity (i.e., the number of unique tweets about an article and number of citations. Twitter activity was a more important predictor of citation rates than 5-year journal impact factor. Moreover, Twitter activity was not driven by journal impact factor; the 'highest-impact' journals were not necessarily the most discussed online. The effect of Twitter activity was only about a fifth as strong as time since publication; accounting for this confounding factor was critical for estimating the true effects of Twitter use. Articles in impactful journals can become heavily cited, but articles in journals with lower impact factors can generate considerable Twitter activity and also become heavily cited. Authors may benefit from establishing a strong social media presence, but should not expect research to become highly cited solely through social media promotion. Our research demonstrates that altmetrics and traditional metrics can be closely related, but not identical. We suggest that both altmetrics and traditional citation rates can be useful metrics of research impact.

  9. Twitter Predicts Citation Rates of Ecological Research.

    Science.gov (United States)

    Peoples, Brandon K; Midway, Stephen R; Sackett, Dana; Lynch, Abigail; Cooney, Patrick B

    2016-01-01

    The relationship between traditional metrics of research impact (e.g., number of citations) and alternative metrics (altmetrics) such as Twitter activity are of great interest, but remain imprecisely quantified. We used generalized linear mixed modeling to estimate the relative effects of Twitter activity, journal impact factor, and time since publication on Web of Science citation rates of 1,599 primary research articles from 20 ecology journals published from 2012-2014. We found a strong positive relationship between Twitter activity (i.e., the number of unique tweets about an article) and number of citations. Twitter activity was a more important predictor of citation rates than 5-year journal impact factor. Moreover, Twitter activity was not driven by journal impact factor; the 'highest-impact' journals were not necessarily the most discussed online. The effect of Twitter activity was only about a fifth as strong as time since publication; accounting for this confounding factor was critical for estimating the true effects of Twitter use. Articles in impactful journals can become heavily cited, but articles in journals with lower impact factors can generate considerable Twitter activity and also become heavily cited. Authors may benefit from establishing a strong social media presence, but should not expect research to become highly cited solely through social media promotion. Our research demonstrates that altmetrics and traditional metrics can be closely related, but not identical. We suggest that both altmetrics and traditional citation rates can be useful metrics of research impact.

  10. Twitter predicts citation rates of ecological research

    Science.gov (United States)

    Peoples, Brandon K.; Midway, Stephen R.; Sackett, Dana K.; Lynch, Abigail; Cooney, Patrick B.

    2016-01-01

    The relationship between traditional metrics of research impact (e.g., number of citations) and alternative metrics (altmetrics) such as Twitter activity are of great interest, but remain imprecisely quantified. We used generalized linear mixed modeling to estimate the relative effects of Twitter activity, journal impact factor, and time since publication on Web of Science citation rates of 1,599 primary research articles from 20 ecology journals published from 2012–2014. We found a strong positive relationship between Twitter activity (i.e., the number of unique tweets about an article) and number of citations. Twitter activity was a more important predictor of citation rates than 5-year journal impact factor. Moreover, Twitter activity was not driven by journal impact factor; the ‘highest-impact’ journals were not necessarily the most discussed online. The effect of Twitter activity was only about a fifth as strong as time since publication; accounting for this confounding factor was critical for estimating the true effects of Twitter use. Articles in impactful journals can become heavily cited, but articles in journals with lower impact factors can generate considerable Twitter activity and also become heavily cited. Authors may benefit from establishing a strong social media presence, but should not expect research to become highly cited solely through social media promotion. Our research demonstrates that altmetrics and traditional metrics can be closely related, but not identical. We suggest that both altmetrics and traditional citation rates can be useful metrics of research impact.

  11. Metabolic theory predicts whole-ecosystem properties.

    Science.gov (United States)

    Schramski, John R; Dell, Anthony I; Grady, John M; Sibly, Richard M; Brown, James H

    2015-02-24

    Understanding the effects of individual organisms on material cycles and energy fluxes within ecosystems is central to predicting the impacts of human-caused changes on climate, land use, and biodiversity. Here we present a theory that integrates metabolic (organism-based bottom-up) and systems (ecosystem-based top-down) approaches to characterize how the metabolism of individuals affects the flows and stores of materials and energy in ecosystems. The theory predicts how the average residence time of carbon molecules, total system throughflow (TST), and amount of recycling vary with the body size and temperature of the organisms and with trophic organization. We evaluate the theory by comparing theoretical predictions with outputs of numerical models designed to simulate diverse ecosystem types and with empirical data for real ecosystems. Although residence times within different ecosystems vary by orders of magnitude-from weeks in warm pelagic oceans with minute phytoplankton producers to centuries in cold forests with large tree producers-as predicted, all ecosystems fall along a single line: residence time increases linearly with slope = 1.0 with the ratio of whole-ecosystem biomass to primary productivity (B/P). TST was affected predominantly by primary productivity and recycling by the transfer of energy from microbial decomposers to animal consumers. The theory provides a robust basis for estimating the flux and storage of energy, carbon, and other materials in terrestrial, marine, and freshwater ecosystems and for quantifying the roles of different kinds of organisms and environments at scales from local ecosystems to the biosphere.

  12. Predicting novel metabolic pathways through subgraph mining.

    Science.gov (United States)

    Sankar, Aravind; Ranu, Sayan; Raman, Karthik

    2017-12-15

    The ability to predict pathways for biosynthesis of metabolites is very important in metabolic engineering. It is possible to mine the repertoire of biochemical transformations from reaction databases, and apply the knowledge to predict reactions to synthesize new molecules. However, this usually involves a careful understanding of the mechanism and the knowledge of the exact bonds being created and broken. There is a need for a method to rapidly predict reactions for synthesizing new molecules, which relies only on the structures of the molecules, without demanding additional information such as thermodynamics or hand-curated reactant mapping, which are often hard to obtain accurately. We here describe a robust method based on subgraph mining, to predict a series of biochemical transformations, which can convert between two (even previously unseen) molecules. We first describe a reliable method based on subgraph edit distance to map reactants and products, using only their chemical structures. Having mapped reactants and products, we identify the reaction centre and its neighbourhood, the reaction signature, and store this in a reaction rule network. This novel representation enables us to rapidly predict pathways, even between previously unseen molecules. We demonstrate this ability by predicting pathways to molecules not present in the KEGG database. We also propose a heuristic that predominantly recovers natural biosynthetic pathways from amongst hundreds of possible alternatives, through a directed search of the reaction rule network, enabling us to provide a reliable ranking of the different pathways. Our approach scales well, even to databases with >100 000 reactions. A Java-based implementation of our algorithms is available at https://github.com/RamanLab/ReactionMiner. sayanranu@cse.iitd.ac.in or kraman@iitm.ac.in. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For

  13. Transitioning a Chesapeake Bay Ecological Prediction System to Operations

    Science.gov (United States)

    Brown, C.; Green, D. S.; Eco Forecasters

    2011-12-01

    Ecological prediction of the impacts of physical, chemical, biological, and human-induced change on ecosystems and their components, encompass a wide range of space and time scales, and subject matter. They vary from predicting the occurrence and/or transport of certain species, such harmful algal blooms, or biogeochemical constituents, such as dissolved oxygen concentrations, to large-scale ecosystem responses and higher trophic levels. The timescales of ecological prediction, including guidance and forecasts, range from nowcasts and short-term forecasts (days), to intraseasonal and interannual outlooks (weeks to months), to decadal and century projections in climate change scenarios. The spatial scales range from small coastal inlets to basin and global scale biogeochemical and ecological forecasts. The types of models that have been used include conceptual, empirical, mechanistic, and hybrid approaches. This presentation will identify the challenges and progress toward transitioning experimental model-based ecological prediction into operational guidance and forecasting. Recent efforts are targeting integration of regional ocean, hydrodynamic and hydrological models and leveraging weather and water service infrastructure to enable the prototyping of an operational ecological forecast capability for the Chesapeake Bay and its tidal tributaries. A path finder demonstration predicts the probability of encountering sea nettles (Chrysaora quinquecirrha), a stinging jellyfish. These jellyfish can negatively impact safety and economic activities in the bay and an impact-based forecast that predicts where and when this biotic nuisance occurs may help management effects. The issuance of bay-wide nowcasts and three-day forecasts of sea nettle probability are generated daily by forcing an empirical habitat model (that predicts the probability of sea nettles) with real-time and 3-day forecasts of sea-surface temperature (SST) and salinity (SSS). In the first demonstration

  14. Predicting phenology by integrating ecology, evolution and climate science

    Science.gov (United States)

    Pau, Stephanie; Wolkovich, Elizabeth M.; Cook, Benjamin I.; Davies, T. Jonathan; Kraft, Nathan J.B.; Bolmgren, Kjell; Betancourt, Julio L.; Cleland, Elsa E.

    2011-01-01

    Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology — the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

  15. QNA-Based Prediction of Sites of Metabolism

    OpenAIRE

    Olga Tarasova; Anastassia Rudik; Alexander Dmitriev; Alexey Lagunin; Dmitry Filimonov; Vladimir Poroikov

    2017-01-01

    Metabolism of xenobiotics (Greek xenos: exogenous substances) plays an essential role in the prediction of biological activity and testing for the subsequent research and development of new drug candidates. Integration of various methods and techniques using different computational and experimental approaches is one of the keys to a successful metabolism prediction. While multiple structure-based and ligand-based approaches to metabolism prediction exist, the most important problem arises at ...

  16. Elucidating the global elapid (Squamata) richness pattern under metabolic theory of ecology

    Science.gov (United States)

    Braga, Rosana Talita; Oliveira de Grande, Thallita; de Souza Barreto, Bruno; Felizola Diniz-Filho, José Alexandre; Terribile, Levi Carina

    2014-04-01

    Environmental determinants of global patterns in species richness are still uncertain. The Metabolic Theory of Ecology (MTE) proposes that species richness patterns can be explained by environmental temperature acting on the metabolism of ectothermic organisms. However, the generality of this theory has been questioned due to its low fit to the geographic variation in species richness of different taxonomic groups. Here, we investigated whether the MTE drives elapid richness, testing the non-stationarity of the relationship between the natural logarithm of species richness (ln S) and the inverse function of temperature (1/kT) using a geographically weighted regression (GWR). The relationship between ln S and 1/kT varied systematically over space and showed non-stationarity. Few tropical locations were consistent with MTE predictions, whereas other regions fitted differently. Although the slope of the GWR model ranged from low to high, the temperature did not predict species richness strongly on average and did not limit the upper values of richness. The response of richness to temperature in some areas might reflect a recent history of colonization and diversification of species across tropical and subtropical regions. In regions not affected by temperature, species richness should be structured by other biotic and abiotic interactions. This scenario reveals that the non-stationarity of the relationship would be linked to idiosyncrasies in the sample sites, which can drift the magnitude or change the relationship between species richness and temperature throughout space.

  17. Comparative metabolic ecology of tropical herbivorous echinoids on a coral reef.

    Science.gov (United States)

    Lewis, Levi S; Smith, Jennifer E; Eynaud, Yoan

    2018-01-01

    The metabolic rate of consumers is a key driver of ecosystem dynamics. On coral reefs, herbivorous echinoids consume fleshy algae, facilitating the growth of reef-building calcified organisms; however, little is known about differences among species in their metabolic and functional ecology. Here, we used log-linear (log-log) regression models to examine the allometric scaling of mass and routine metabolic rate for five common herbivorous echinoids on a Hawaiian coral reef: Echinothrix calamaris, E. diadema, Echinometra matthaei, Heterocentrotus mammillatus, and Tripneustes gratilla. Scaling relationships were then contrasted with empirical observations of echinoid ecology and general metabolic theory to broaden our understanding of diversity in the metabolic and functional ecology of tropical herbivorous echinoids. Test diameter and species explained 98% of the variation in mass, and mass and species explained 92.4% and 87.5% of the variation in individual (I) and mass-specific (B) metabolic rates, respectively. Scaling exponents did not differ for mass or metabolism; however, normalizing constants differed significantly among species. Mass varied as the cube of test diameter (b = 2.9), with HM exhibiting a significantly higher normalizing constant than other species, likely due to its heavily-calcified spines and skeleton. Individual metabolic rate varied approximately as the 2/5 power of mass (γ = 0.44); significantly smaller than the 3/4 universal scaling coefficient, but inclusive of 2/3 scaling. E. calamaris and H. mammillatus exhibited the lowest normalizing constants, corresponding with their slow-moving, cryptic, rock-boring life-history. In contrast, E. calamaris, E. diadema, and T. gratilla, exhibited higher metabolic rates, likely reflecting their higher levels of activity and ability to freely browse for preferred algae due to chemical anti-predator defenses. Thus, differences in metabolic scaling appeared to correspond with differences in phylogeny

  18. Evolution of specialization and ecological character displacement: metabolic plasticity matters.

    NARCIS (Netherlands)

    Egas, C.J.M.; Reydon, Th.A.C.; Hemerik, L.

    2005-01-01

    An important question in evolutionary biology, especially with respect to herbivorous arthropods, is the evolution of specialization. In a previous paper, the combined evolutionary dynamics of specialization and ecological character displacement was studied, focusing on the role of herbivore

  19. Does fish ecology predict dispersal across a river drainage divide?

    Science.gov (United States)

    Burridge, Christopher P; Craw, Dave; Jack, Daniel C; King, Tania M; Waters, Jonathan M

    2008-06-01

    Obligate freshwater taxa are frequently distributed among catchments isolated by marine and terrestrial barriers. Such distributions can arise through vicariant changes in drainage geometry, or dispersal via intermittent freshwater connections. We employed two adjacent rivers in southern New Zealand to test for interdrainage dispersal while controlling for historical drainage geometry, and analyzed four ecologically distinct freshwater-limited fish taxa to assess any relationship with habitat preference. Individuals from the Mararoa and Oreti catchments (n >100 per species) were sequenced for a minimum of 1297 bp of mitochondrial DNA (cytochrome b and control region). Phylogeographic relationships were consistent with ecological expectations of interdrainage dispersal capability, with the two obligate riverine taxa each exhibiting reciprocal monophyly between catchments, whereas the two facultative swamp dwellers revealed paraphyletic relationships, one of which shared a haplotype between catchments. Statistical phylogeography, accommodating taxon-specific mutation rates and the known age of the last major riverine connection between these catchments, rejected complete isolation of populations for one of the swamp dwellers. Therefore, dispersal across a young (145-240 kyr) drainage divide is inferred for one species, and can be predicted to some extent by species ecology. Moreover, our study highlights the importance of historical drainage geometry when assessing the causes of contemporary genetic structuring in freshwater taxa.

  20. Sleep symptoms predict the development of the metabolic syndrome.

    Science.gov (United States)

    Troxel, Wendy M; Buysse, Daniel J; Matthews, Karen A; Kip, Kevin E; Strollo, Patrick J; Hall, Martica; Drumheller, Oliver; Reis, Steven E

    2010-12-01

    Sleep complaints are highly prevalent and associated with cardiovascular disease (CVD) morbidity and mortality. This is the first prospective study to report the association between commonly reported sleep symptoms and the development of the metabolic syndrome, a key CVD risk factor. Participants were from the community-based Heart Strategies Concentrating on Risk Evaluation study. The sample was comprised of 812 participants (36% African American; 67% female) who were free of metabolic syndrome at baseline, had completed a baseline sleep questionnaire, and had metabolic syndrome evaluated 3 years after baseline. Apnea-hypopnea index (AHI) was measured cross-sectionally using a portable monitor in a subset of 290 participants. Logistic regression examined the risk of developing metabolic syndrome and its components according to individual sleep symptoms and insomnia syndrome. Specific symptoms of insomnia (difficulty falling asleep [DFA] and "unrefreshing" sleep), but not a syndromal definition of insomnia, were significant predictors of the development of metabolic syndrome. Loud snoring more than doubled the risk of developing the metabolic syndrome and also predicted specific metabolic abnormalities (hyperglycemia and low high-density lipoprotein cholesterol). With further adjustment for AHI or the number of metabolic abnormalities at baseline, loud snoring remained a significant predictor of metabolic syndrome, whereas DFA and unrefreshing sleep were reduced to marginal significance. Difficulty falling asleep, unrefreshing sleep, and, particularly, loud snoring, predicted the development of metabolic syndrome in community adults. Evaluating sleep symptoms can help identify individuals at risk for developing metabolic syndrome.

  1. Predicting the binding modes and sites of metabolism of xenobiotics.

    Science.gov (United States)

    Mukherjee, Goutam; Lal Gupta, Pancham; Jayaram, B

    2015-07-01

    Metabolism studies are an essential integral part of ADMET profiling of drug candidates to evaluate their safety and efficacy. Cytochrome P-450 (CYP) metabolizes a wide variety of xenobiotics/drugs. The binding modes of these compounds with CYP and their intrinsic reactivities decide the metabolic products. We report here a novel computational protocol, which comprises docking of ligands to heme-containing CYPs and prediction of binding energies through a newly developed scoring function, followed by analyses of the docked structures and molecular orbitals of the ligand molecules, for predicting the sites of metabolism (SOM) of ligands. The calculated binding free energies of 121 heme-containing protein-ligand docked complexes yielded a correlation coefficient of 0.84 against experiment. Molecular orbital analyses of the resultant top three unique poses of the docked complexes provided a success rate of 87% in identifying the experimentally known sites of metabolism of the xenobiotics. The SOM prediction methodology is freely accessible at .

  2. 2001 Gordon Research Conference on Archaea: Ecology [sic], Metabolism. Final progress report [agenda and attendee list

    Energy Technology Data Exchange (ETDEWEB)

    Daniels, Charles

    2001-08-10

    The Gordon Research Conference on Archaea: Ecology, Metabolism [and Molecular Biology] was held at Proctor Academy, Andover, New Hampshire, August 5-10, 2001. The conference was attended by 135 participants. The attendees represented the spectrum of endeavor in this field, coming from academia, industry, and government laboratories, and included US and foreign scientists, senior researchers, young investigators, and students. Emphasis was placed on current unpublished research and discussion of the future target areas in this field. There was a conscious effort to stimulate discussion about the key issues in the field today. Session topics included the following: Ecology and genetic elements; Genomics and evolution; Ecology, genomes and gene regulation; Replication and recombination; Chromatin and transcription; Gene regulation; Post-transcription processing; Biochemistry and metabolism; Proteomics and protein structure; Metabolism and physiology. The featured speaker addressed the topic: ''Archaeal viruses, witnesses of prebiotic evolution?''

  3. Fast prediction of cytochrome P450 mediated drug metabolism

    DEFF Research Database (Denmark)

    Rydberg, Patrik Åke Anders; Poongavanam, Vasanthanathan; Oostenbrink, Chris

    2009-01-01

    Cytochrome P450 mediated metabolism of drugs is one of the major determinants of their kinetic profile, and prediction of this metabolism is therefore highly relevant during the drug discovery and development process. A new rule-based method, based on results from density functional theory...

  4. Predicting drug metabolism by cytochrome P450 2C9

    DEFF Research Database (Denmark)

    Rydberg, Patrik; Olsen, Lars

    2012-01-01

    By the use of knowledge gained through modeling of drug metabolism mediated by the cytochrome P450 2D6 and 3A4 isoforms, we constructed a 2D-based model for site-of-metabolism prediction for the cytochrome P450 2C9 isoform. The similarities and differences between the models for the 2C9 and 2D6...

  5. Risperidone and Venlafaxine Metabolic Ratios Strongly Predict a CYP2D6 Poor Metabolizing Genotype.

    Science.gov (United States)

    Mannheimer, Buster; Haslemo, Tore; Lindh, Jonatan D; Eliasson, Erik; Molden, Espen

    2016-02-01

    To investigate the predictive value of the risperidone and venlafaxine metabolic ratios and CYP2D6 genotype. The determination of risperidone, 9-hydroxyrisperidone, and venlafaxine, O-desmethylvenlafaxine, N-desmethylvenlafaxine and CYP2D6 genotype was performed in 425 and 491 patients, respectively. The receiver operator characteristic method and the area under the receiver operator characteristic curve were used to illustrate the predictive value of risperidone metabolic ratio for the individual CYP2D6 genotype. To evaluate the proposed cutoff levels of >1 to identify individuals with a poor CYP2D6 genotype, the sensitivity, specificity, positive predictive values, and negative predictive values were calculated. Area under the receiver operator characteristic curve to predict poor metabolizers for risperidone/9-hydroxyrisperidone and N-desmethylvenlafaxine/O-desmethylvenlafaxine ratios was 93% and 99%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value (confidence interval) of a risperidone/9-hydroxyrisperidone ratio >1 to predict a CYP2D6 poor metabolizer genotype were 91% (76%-97%), 86% (83%-89%), 35% (26%-46%), and 99% (97%-100%), respectively. The corresponding measures for N-desmethylvenlafaxine/O-desmethylvenlafaxine were 93% (76%-97%), 87% (83%-89%), 40% (32%-51%), and 99% (98%-100%). Risperidone/9-hydroxyrisperidone and N-desmethylvenlafaxine/O-desmethylvenlafaxine metabolic ratios >1 strongly predict individuals with poor metabolizer genotype, which could guide psychotropic drug treatment to avoid adverse drug reactions and to increase their therapeutic efficacy in patients prescribed these drugs.

  6. Temperature dependence of evolutionary diversification: differences between two contrasting model taxa support the metabolic theory of ecology.

    Science.gov (United States)

    Machac, A; Zrzavý, J; Smrckova, J; Storch, D

    2012-12-01

    Biodiversity patterns are largely determined by variation of diversification rates across clades and geographic regions. Although there are multiple reasons for this variation, it has been hypothesized that metabolic rate is the crucial driver of diversification of evolutionary lineages. According to the metabolic theory of ecology (MTE), metabolic rate - and consequently speciation - is driven mainly by body size and environmental temperature. As environmental temperature affects metabolic rate in ecto- and endotherms differently, its impact on diversification rate should also differ between the two types of organisms. Employing two independent approaches, we analysed correlates of speciation rates and, ultimately, net diversification rates for two contrasting taxa: plethodontid salamanders and carnivoran mammals. Whereas in the ectothermic plethodontids speciation rates positively correlated with environmental temperature, in the endothermic carnivorans a reverse, negative correlation was detected. These findings comply with predictions of the MTE and suggest that similar geographic patterns of biodiversity across taxa (e.g. ecto- and endotherms) might have been generated by different ecological and evolutionary processes. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

  7. Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

    Science.gov (United States)

    Takemoto, Kazuhiro; Aie, Kazuki

    2017-05-25

    Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

  8. Prediction of cytochrome P450 mediated metabolism

    DEFF Research Database (Denmark)

    Olsen, Lars; Oostenbrink, Chris; Jørgensen, Flemming Steen

    2015-01-01

    Cytochrome P450 enzymes (CYPs) form one of the most important enzyme families involved in the metabolism of xenobiotics. CYPs comprise many isoforms, which catalyze a wide variety of reactions, and potentially, a large number of different metabolites can be formed. However, it is often hard...

  9. Springs as Model Systems for Aquatic Ecosystems Ecology: Stoichiometry, Metabolism and Nutrient Limitation

    Science.gov (United States)

    Cohen, M. J.; Nifong, R. L.; Kurz, M. J.; Martin, J. B.; Cropper, W. P.; Korhnak, L. V.

    2013-12-01

    Springs have been called nature's chemostats, where low variation in discharge, temperature and chemistry creates a natural laboratory in which to address basic questions about aquatic ecosystems. Ecological stoichiometry posits that patterns of metabolism, trophic energy transfer and community structure arise in response to coupled elemental cycles. In this work we synthesize several recent studies in Florida's iconic springs to explore the overarching hypothesis that stoichiometry can be used to indicate the nutrient limitation status of autotrophs and ecosystem metabolism. Of foremost importance is that the chemically stable conditions observed in springs ensures that autotroph tissue elemental composition, which is thought to vary with environmental supply, is near steady state. Moreover, the elemental ratios of discharging water vary dramatically across our study springs (for example, molar N:P ranges from 0.4:1 to 400:1), subjecting the communities of autotrophs, which are largely conserved across systems, to dramatically different nutrient supply. At the scale of whole ecosystem metabolism, we show that C:N:P ratios are strongly conserved across a wide gradient of environmental supplies, counter to the prediction of stoichiometric plasticity. Moreover, the absence of a relationship between gross primary production and nutrient concentrations or stoichiometry suggests that metabolic homeostasis may be a diagnostic symptom of nutrient saturation. At the scale of individual autotrophs, both submerged vascular plants and filamentous algae, this finding is strongly reinforced, with remarkable within-species tissue C:N:P homeostasis over large gradients, and no statistically significant evidence that gradients in nutrient supply affect autotroph composition. Expanding the suite of elements for which contemporaneous environment and tissue measurements are available to include 19 metals and micronutrients revealed that, while plants were homeostatic across large N

  10. Social network models predict movement and connectivity in ecological landscapes

    Science.gov (United States)

    Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  11. Social network models predict movement and connectivity in ecological landscapes.

    Science.gov (United States)

    Fletcher, Robert J; Acevedo, Miguel A; Reichert, Brian E; Pias, Kyle E; Kitchens, Wiley M

    2011-11-29

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  12. Critical PO2 is size-independent in insects: implications for the metabolic theory of ecology.

    Science.gov (United States)

    Harrison, Jon F; Klok, C J; Waters, James S

    2014-10-01

    Insects, and all animals, exhibit hypometric scaling of metabolic rate, with larger species having lower mass-specific metabolic rates. The metabolic theory of ecology (MTE) is based on models ascribing hypometric scaling of metabolic rate to constrained O 2 supply systems in larger animals. We compiled critical PO 2 of metabolic and growth rates for more than 40 insect species with a size range spanning four orders of magnitude. Critical PO 2 values vary from far below 21kPa for resting animals to near 21kPa for growing or flying animals and are size-independent, demonstrating that supply capacity matches oxygen demand. These data suggest that hypometric scaling of resting metabolic rate in insects is not driven by constraints on oxygen availability. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Bioinformatics tools in predictive ecology: applications to fisheries

    Science.gov (United States)

    Tucker, Allan; Duplisea, Daniel

    2012-01-01

    There has been a huge effort in the advancement of analytical techniques for molecular biological data over the past decade. This has led to many novel algorithms that are specialized to deal with data associated with biological phenomena, such as gene expression and protein interactions. In contrast, ecological data analysis has remained focused to some degree on off-the-shelf statistical techniques though this is starting to change with the adoption of state-of-the-art methods, where few assumptions can be made about the data and a more explorative approach is required, for example, through the use of Bayesian networks. In this paper, some novel bioinformatics tools for microarray data are discussed along with their ‘crossover potential’ with an application to fisheries data. In particular, a focus is made on the development of models that identify functionally equivalent species in different fish communities with the aim of predicting functional collapse. PMID:22144390

  14. Ecological opportunity and sexual selection together predict adaptive radiation.

    Science.gov (United States)

    Wagner, Catherine E; Harmon, Luke J; Seehausen, Ole

    2012-07-19

    A fundamental challenge to our understanding of biodiversity is to explain why some groups of species undergo adaptive radiations, diversifying extensively into many and varied species, whereas others do not. Both extrinsic environmental factors (for example, resource availability, climate) and intrinsic lineage-specific traits (for example, behavioural or morphological traits, genetic architecture) influence diversification, but few studies have addressed how such factors interact. Radiations of cichlid fishes in the African Great Lakes provide some of the most dramatic cases of species diversification. However, most cichlid lineages in African lakes have not undergone adaptive radiations. Here we compile data on cichlid colonization and diversification in 46 African lakes, along with lake environmental features and information about the traits of colonizing cichlid lineages, to investigate why adaptive radiation does and does not occur. We find that extrinsic environmental factors related to ecological opportunity and intrinsic lineage-specific traits related to sexual selection both strongly influence whether cichlids radiate. Cichlids are more likely to radiate in deep lakes, in regions with more incident solar radiation and in lakes where there has been more time for diversification. Weak or negative associations between diversification and lake surface area indicate that cichlid speciation is not constrained by area, in contrast to diversification in many terrestrial taxa. Among the suite of intrinsic traits that we investigate, sexual dichromatism, a surrogate for the intensity of sexual selection, is consistently positively associated with diversification. Thus, for cichlids, it is the coincidence between ecological opportunity and sexual selection that best predicts whether adaptive radiation will occur. These findings suggest that adaptive radiation is predictable, but only when species traits and environmental factors are jointly considered.

  15. Metabolic flux prediction in cancer cells with altered substrate uptake.

    Science.gov (United States)

    Schwartz, Jean-Marc; Barber, Michael; Soons, Zita

    2015-12-01

    Proliferating cells, such as cancer cells, are known to have an unusual metabolism, characterized by an increased rate of glycolysis and amino acid metabolism. Our understanding of this phenomenon is limited but could potentially be used in order to develop new therapies. Computational modelling techniques, such as flux balance analysis (FBA), have been used to predict fluxes in various cell types, but remain of limited use to explain the unusual metabolic shifts and altered substrate uptake in human cancer cells. We implemented a new flux prediction method based on elementary modes (EMs) and structural flux (StruF) analysis and tested them against experimentally measured flux data obtained from (13)C-labelling in a cancer cell line. We assessed the quality of predictions using different objective functions along with different techniques in normalizing a metabolic network with more than one substrate input. Results show a good correlation between predicted and experimental values and indicate that the choice of cellular objective critically affects the quality of predictions. In particular, lactate gives an excellent correlation and correctly predicts the high flux through glycolysis, matching the observed characteristics of cancer cells. In contrast with FBA, which requires a priori definition of all uptake rates, often hard to measure, atomic StruFs (aStruFs) are able to predict uptake rates of multiple substrates. © 2015 Authors; published by Portland Press Limited.

  16. Bridging food webs, ecosystem metabolism, and biogeochemistry using ecological stoichiometry theory

    DEFF Research Database (Denmark)

    Welti, Nina; Striebel, Maren; Ulseth, Amber J.

    2017-01-01

    stoichiometry is important for both biogeochemical and ecological research. Nonetheless, assessments of ecological stoichiometry (ES) often focus on the elemental content of biota rather than taking a more holistic view by examining both elemental pools and fluxes (e. g., organismal stoichiometry and ecosystem...... process rates). ES theory holds the promise to be a unifying concept to link across hierarchical scales of patterns and processes in ecology, but this has not been fully achieved. Therefore, we propose connecting the expertise of aquatic ecologists and biogeochemists with ES theory as a common currency...... to connect food webs, ecosystem metabolism, and biogeochemistry, as they are inherently concatenated by the transfer of carbon, nitrogen, and phosphorous through biotic and abiotic nutrient transformation and fluxes. Several new studies exist that demonstrate the connections between food web ecology...

  17. Scaling up from traits to communities to ecosystems across broad climate gradients: Testing Metabolic Scaling Theories predictions for forests

    Science.gov (United States)

    Enquist, B. J.; Michaletz, S. T.; Buzzard, V.

    2015-12-01

    Key insights in global ecology will come from mechanistically linking pattern and process across scales. Macrosystems ecology specifically attempts to link ecological processes across spatiotemporal scales. The goal s to link the processing of energy and nutrients from cells all the way ecosystems and to understand how shifting climate influences ecosystem processes. Using new data collected from NSF funded Macrosystems project we report on new findings from forests sites across a broad temperature gradient. Our study sites span tropical, temperate, and high elevation forests we assess several key predictions and assumptions of Metabolic Scaling Theory (MST) as well as several other competing hypotheses for the role of climate, light, and plant traits on influencing forest demography and forest ecosystems. Specifically, we assess the importance of plant size, light limitation, size structure, and various climatic factors on forest growth, demography, and ecosystem functioning. We provide some of the first systematic tests of several key predictions from MST. We show that MST predictions are largely upheld and that new insights from assessing theories predictions yields new observations and findings that help modify and extend MST's predictions and applicability. We discuss how theory is critically needed to further our understanding of how to scale pattern and process in ecology - from traits to ecosystems - in order to develop a more predictive global change biology.

  18. Validated Predictions of Metabolic Energy Consumption for Submaximal Effort Movement.

    Directory of Open Access Journals (Sweden)

    George A Tsianos

    2016-06-01

    Full Text Available Physical performance emerges from complex interactions among many physiological systems that are largely driven by the metabolic energy demanded. Quantifying metabolic demand is an essential step for revealing the many mechanisms of physical performance decrement, but accurate predictive models do not exist. The goal of this study was to investigate if a recently developed model of muscle energetics and force could be extended to reproduce the kinematics, kinetics, and metabolic demand of submaximal effort movement. Upright dynamic knee extension against various levels of ergometer load was simulated. Task energetics were estimated by combining the model of muscle contraction with validated models of lower limb musculotendon paths and segment dynamics. A genetic algorithm was used to compute the muscle excitations that reproduced the movement with the lowest energetic cost, which was determined to be an appropriate criterion for this task. Model predictions of oxygen uptake rate (VO2 were well within experimental variability for the range over which the model parameters were confidently known. The model's accurate estimates of metabolic demand make it useful for assessing the likelihood and severity of physical performance decrement for a given task as well as investigating underlying physiologic mechanisms.

  19. Predicting selective drug targets in cancer through metabolic networks

    Science.gov (United States)

    Folger, Ori; Jerby, Livnat; Frezza, Christian; Gottlieb, Eyal; Ruppin, Eytan; Shlomi, Tomer

    2011-01-01

    The interest in studying metabolic alterations in cancer and their potential role as novel targets for therapy has been rejuvenated in recent years. Here, we report the development of the first genome-scale network model of cancer metabolism, validated by correctly identifying genes essential for cellular proliferation in cancer cell lines. The model predicts 52 cytostatic drug targets, of which 40% are targeted by known, approved or experimental anticancer drugs, and the rest are new. It further predicts combinations of synthetic lethal drug targets, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection. Finally, potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled. PMID:21694718

  20. Ecological Relevance of Memory Tests and the Prediction of Relapse in Alcoholics.

    Science.gov (United States)

    Sussman, Steve; And Others

    Recent research suggests that alcoholic inpatients' performance on neuropsychological tests is predictive of their drinking status following discharge from alcohol rehabilitation programs, although no single test itself has been predictive of relapse. This study seeks to develop a ecologically relevant memory test that would predict relapse and…

  1. Do daily fluctuations in inhibitory control predict alcohol consumption? : An ecological momentary assessment study

    NARCIS (Netherlands)

    Jones, Andrew; Tiplady, Brian; Houben, Katrijn; Nederkoorn, Chantal; Field, Matt

    2018-01-01

    RATIONALE: Deficient inhibitory control is predictive of increased alcohol consumption in the laboratory; however, little is known about this relationship in naturalistic, real-world settings. OBJECTIVES: In the present study, we implemented ecological momentary assessment methods to investigate the

  2. Locating Pleistocene Refugia: Comparing Phylogeographic and Ecological Niche Model Predictions

    Science.gov (United States)

    2007-07-01

    how well ‘back- casting ’ of ecological niche models can complement phylogeo- graphic approaches in identifying refugia. A clear advantage of the ENM...records: a test case using cryptic geckos in Madagascar. Journal of Biogeography 34: 102–117. 47. Araújo MB, Whittaker RJ, Ladle RJ, Erhard M (2005

  3. Predicting basal metabolic rates in Malaysian adult elite athletes.

    Science.gov (United States)

    Wong, Jyh Eiin; Poh, Bee Koon; Nik Shanita, Safii; Izham, Mohd Mohamad; Chan, Kai Quin; Tai, Meng De; Ng, Wei Wei; Ismail, Mohd Noor

    2012-11-01

    This study aimed to measure the basal metabolic rate (BMR) of elite athletes and develop a gender specific predictive equation to estimate their energy requirements. 92 men and 33 women (aged 18-31 years) from 15 sports, who had been training six hours daily for at least one year, were included in the study. Body composition was measured using the bioimpedance technique, and BMR by indirect calorimetry. The differences between measured and estimated BMR using various predictive equations were calculated. The novel equation derived from stepwise multiple regression was evaluated using Bland and Altman analysis. The predictive equations of Cunningham and the Food and Agriculture Organization/World Health Organization/United Nations University either over- or underestimated the measured BMR by up to ± 6%, while the equations of Ismail et al, developed from the local non-athletic population, underestimated the measured BMR by 14%. The novel predictive equation for the BMR of athletes was BMR (kcal/day) = 669 + 13 (weight in kg) + 192 (gender: 1 for men and 0 for women) (R2 0.548; standard error of estimates 163 kcal). Predicted BMRs of elite athletes by this equation were within 1.2% ± 9.5% of the measured BMR values. The novel predictive equation presented in this study can be used to calculate BMR for adult Malaysian elite athletes. Further studies may be required to validate its predictive capabilities for other sports, nationalities and age groups.

  4. Predicting and detecting reciprocity between indirect ecological interactions and evolution.

    Science.gov (United States)

    Estes, James A; Brashares, Justin S; Power, Mary E

    2013-05-01

    Living nature can be thought of as a tapestry, defined not only by its constituent parts but also by how these parts are woven together. The weaving of this tapestry is a metaphor for species interactions, which can be divided into three broad classes: competitive, mutualistic, and consumptive. Direct interactions link together as more complex networks, for example, the joining of consumptive interactions into food webs. Food web dynamics are driven, in turn, by changes in the abundances of web members, whose numbers or biomass respond to bottom-up (resource limitation) and top-down (consumer limitation) forcing. The relative strengths of top-down and bottom-up forcing on the abundance of a given web member depend on its ecological context, including its topological position within the food web. Top-down effects by diverse consumers are nearly ubiquitous, in many cases influencing the structure and operation of ecosystems. While the ecological effects of such interactions are well known, far less is known of their evolutionary consequences. In this essay, we describe sundry consequences of these interaction chains on species and ecosystem processes, explain several known or suspected evolutionary effects of consumer-induced interaction chains, and identify areas where reciprocity between ecology and evolution involving the indirect effects of consumer-prey interaction chains might be further explored.

  5. Drought prediction and sustainable development of the ecological environment.

    Science.gov (United States)

    Xu, X H; Lv, Z Q; Zhou, X Y; Jiang, N

    2017-12-01

    In the 1990s ecological early warning research began with the aim of elucidating the effect of drought in dry regions of the world. Drought has been a prevalent natural disaster, ravaging the Yun'nan province of China for over 5 years since 2009. Due to the extensive range, depth and devastating losses, the drought has reached a once-in-a-century severity. Yun'nan province suffered particularly badly from the drought, which took its toll on both the ecological environment and the sustainable economic development of the province. We chose to study Pu'er city in Yun'nun province for this research, and analysed the drought traits of Pu'er city utilizing geographic information technology. We applied the Mann-Kendall test for trend, linear tendency estimation and percentage of precipitation anomalies, as well as using combinations of monthly data searches of meteorological reports from 1980-2010. The results showed that except for a small rise in spring precipitation, the overall rainfall of Pu'er city showed a decreasing trend. The results of this study can provide an adequate and reliable theoretical basis and technological methods for use in government decision making, and promote research into early warning ecology.

  6. Bridging Food Webs, Ecosystem Metabolism, and Biogeochemistry Using Ecological Stoichiometry Theory

    Science.gov (United States)

    Welti, Nina; Striebel, Maren; Ulseth, Amber J.; Cross, Wyatt F.; DeVilbiss, Stephen; Glibert, Patricia M.; Guo, Laodong; Hirst, Andrew G.; Hood, Jim; Kominoski, John S.; MacNeill, Keeley L.; Mehring, Andrew S.; Welter, Jill R.; Hillebrand, Helmut

    2017-01-01

    Although aquatic ecologists and biogeochemists are well aware of the crucial importance of ecosystem functions, i.e., how biota drive biogeochemical processes and vice-versa, linking these fields in conceptual models is still uncommon. Attempts to explain the variability in elemental cycling consequently miss an important biological component and thereby impede a comprehensive understanding of the underlying processes governing energy and matter flow and transformation. The fate of multiple chemical elements in ecosystems is strongly linked by biotic demand and uptake; thus, considering elemental stoichiometry is important for both biogeochemical and ecological research. Nonetheless, assessments of ecological stoichiometry (ES) often focus on the elemental content of biota rather than taking a more holistic view by examining both elemental pools and fluxes (e.g., organismal stoichiometry and ecosystem process rates). ES theory holds the promise to be a unifying concept to link across hierarchical scales of patterns and processes in ecology, but this has not been fully achieved. Therefore, we propose connecting the expertise of aquatic ecologists and biogeochemists with ES theory as a common currency to connect food webs, ecosystem metabolism, and biogeochemistry, as they are inherently concatenated by the transfer of carbon, nitrogen, and phosphorous through biotic and abiotic nutrient transformation and fluxes. Several new studies exist that demonstrate the connections between food web ecology, biogeochemistry, and ecosystem metabolism. In addition to a general introduction into the topic, this paper presents examples of how these fields can be combined with a focus on ES. In this review, a series of concepts have guided the discussion: (1) changing biogeochemistry affects trophic interactions and ecosystem processes by altering the elemental ratios of key species and assemblages; (2) changing trophic dynamics influences the transformation and fluxes of matter

  7. Importance of metabolism in pharmacological studies: possible in vitro predictability

    Energy Technology Data Exchange (ETDEWEB)

    Delaforge, M

    1998-11-01

    Metabolic transformation of drug leads to the formation of a large number of secondary compounds. These metabolites may (a) participate to the elimination of the patent drug, (b) have similar or different therapeutic effects compared to the parent drug (c) exert toxic effects. Cytochromes P450 are the main enzymes involved in the biotransformation of exogenous drugs, leading to oxidized, reduced or peroxidized metabolites. Different isozymes of P450 are present in already all the organs and differ by their affinity for substrate families. P450 3A is the most abundant P450 protein in the adult human liver and is able to transform hundreds of substrates into either drugs or endogenous compounds such as testosterone. Its catalytic activities are regulated either by induction or by inhibition. Attempts to predict metabolic transformation of a given drug are based on the amount of P450 expressed in heterologous systems, induction, and inhibition experiments and by comparison to classical P450 substrates. Erythromycin metabolism and its P450 effects are used to illustrate the complexity and the consequences of metabolic transformation of a given drug.

  8. Metabolic syndrome and atypical antipsychotics: Possibility of prediction and control.

    Science.gov (United States)

    Franch Pato, Clara M; Molina Rodríguez, Vicente; Franch Valverde, Juan I

    Schizophrenia and other psychotic disorders are associated with high morbidity and mortality, due to inherent health factors, genetic factors, and factors related to psychopharmacological treatment. Antipsychotics, like other drugs, have side-effects that can substantially affect the physical health of patients, with substantive differences in the side-effect profile and in the patients in which these side-effects occur. To understand and identify these risk groups could help to prevent the occurrence of the undesired effects. A prospective study, with 24 months follow-up, was conducted in order to analyse the physical health of severe mental patients under maintenance treatment with atypical antipsychotics, as well as to determine any predictive parameters at anthropometric and/or analytical level for good/bad outcome of metabolic syndrome in these patients. There were no significant changes in the physical and biochemical parameters individually analysed throughout the different visits. The baseline abdominal circumference (lambda Wilks P=.013) and baseline HDL-cholesterol levels (lambda Wilks P=.000) were the parameters that seem to be more relevant above the rest of the metabolic syndrome constituents diagnosis criteria as predictors in the long-term. In the search for predictive factors of metabolic syndrome, HDL-cholesterol and abdominal circumference at the time of inclusion were selected, as such that the worst the baseline results were, the higher probability of long-term improvement. Copyright © 2016 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

  9. PREDICTS: Projecting Responses of Ecological Diversity in Changing Terrestrial Systems

    Directory of Open Access Journals (Sweden)

    Georgina Mace

    2012-12-01

    Full Text Available The PREDICTS project (www.predicts.org.uk is a three-year NERC-funded project to model and predict at a global scale how local terrestrial diversity responds to human pressures such as land use, land cover, pollution, invasive species and infrastructure. PREDICTS is a collaboration between Imperial College London, the UNEP World Conservation Monitoring Centre, Microsoft Research Cambridge, UCL and the University of Sussex. In order to meet its aims, the project relies on extensive data describing the diversity and composition of biological communities at a local scale. Such data are collected on a vast scale through the committed efforts of field ecologists. If you have appropriate data that you would be willing to share with us, please get in touch (enquiries@predicts.org.uk. All contributions will be acknowledged appropriately and all data contributors will be included as co-authors on an open-access paper describing the database.

  10. Frost tolerance in wild potatoes : Assessing the predictivity of taxonomic, geographic and ecological factors

    NARCIS (Netherlands)

    Hijmans, R.J.; Jacobs, M.; Bamberg, J.B.; Spooner, D.M.

    2003-01-01

    The use of genetic resources could be more effective and efficient if we were able to predict the presence or absence of useful traits in different populations or accessions. We analyzed the extent to which taxonomic, geographic and ecological factors can predict the presence of frost tolerance in

  11. The database of the PREDICTS (Projecting Responses of Ecological Diversity in Changing Terrestrial Systems) project

    DEFF Research Database (Denmark)

    Hudson, Lawrence N; Newbold, Tim; Contu, Sara

    2017-01-01

    The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity ...

  12. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    NARCIS (Netherlands)

    Hudson, Lawrence N; Newbold, Tim; Contu, Sara; Hill, Samantha L L; Lysenko, Igor; De Palma, Adriana; Phillips, Helen R P; Alhusseini, Tamera I; Bedford, Felicity E; Bennett, Dominic J; Booth, Hollie; Burton, Victoria J; Chng, Charlotte W T; Choimes, Argyrios; Correia, David L P; Day, Julie; Echeverría-Londoño, Susy; Emerson, Susan R; Gao, Di; Garon, Morgan; Harrison, Michelle L K; Ingram, Daniel J; Jung, Martin; Kemp, Victoria; Kirkpatrick, Lucinda; Martin, Callum D; Pan, Yuan; Pask-Hale, Gwilym D; Pynegar, Edwin L; Robinson, Alexandra N; Sanchez-Ortiz, Katia; Senior, Rebecca A; Simmons, Benno I; White, Hannah J; Zhang, Hanbin; Aben, Job; Abrahamczyk, Stefan; Adum, Gilbert B; Aguilar-Barquero, Virginia; Aizen, Marcelo A; Albertos, Belén; Alcala, E L; Del Mar Alguacil, Maria; Alignier, Audrey; Ancrenaz, Marc; Andersen, Alan N; Arbeláez-Cortés, Enrique; Armbrecht, Inge; Arroyo-Rodríguez, Víctor; Aumann, Tom; Axmacher, Jan C; Azhar, Badrul; Azpiroz, Adrián B; Baeten, Lander; Bakayoko, Adama; Báldi, András; Banks, John E; Baral, Sharad K; Barlow, Jos; Barratt, Barbara I P; Barrico, Lurdes; Bartolommei, Paola; Barton, Diane M; Basset, Yves; Batáry, Péter; Bates, Adam J; Baur, Bruno; Bayne, Erin M; Beja, Pedro; Benedick, Suzan; Berg, Åke; Bernard, Henry; Berry, Nicholas J; Bhatt, Dinesh; Bicknell, Jake E; Bihn, Jochen H; Blake, Robin J; Bobo, Kadiri S; Bóçon, Roberto; Boekhout, Teun; Böhning-Gaese, Katrin; Bonham, Kevin J; Borges, Paulo A V; Borges, Sérgio H; Boutin, Céline; Bouyer, Jérémy; Bragagnolo, Cibele; Brandt, Jodi S; Brearley, Francis Q; Brito, Isabel; Bros, Vicenç; Brunet, Jörg; Buczkowski, Grzegorz; Buddle, Christopher M; Bugter, Rob; Buscardo, Erika; Buse, Jörn; Cabra-García, Jimmy; Cáceres, Nilton C; Cagle, Nicolette L; Calviño-Cancela, María; Cameron, Sydney A; Cancello, Eliana M; Caparrós, Rut; Cardoso, Pedro; Carpenter, Dan; Carrijo, Tiago F; Carvalho, Anelena L; Cassano, Camila R; Castro, Helena; Castro-Luna, Alejandro A; Rolando, Cerda B; Cerezo, Alexis; Chapman, Kim Alan; Chauvat, Matthieu; Christensen, Morten; Clarke, Francis M; Cleary, Daniel F R; Colombo, Giorgio; Connop, Stuart P; Craig, Michael D; Cruz-López, Leopoldo; Cunningham, Saul A; D'Aniello, Biagio; D'Cruze, Neil; da Silva, Pedro Giovâni; Dallimer, Martin; Danquah, Emmanuel; Darvill, Ben; Dauber, Jens; Davis, Adrian L V; Dawson, Jeff; de Sassi, Claudio; de Thoisy, Benoit; Deheuvels, Olivier; Dejean, Alain; Devineau, Jean-Louis; Diekötter, Tim; Dolia, Jignasu V; Domínguez, Erwin; Dominguez-Haydar, Yamileth; Dorn, Silvia; Draper, Isabel; Dreber, Niels; Dumont, Bertrand; Dures, Simon G; Dynesius, Mats; Edenius, Lars; Eggleton, Paul; Eigenbrod, Felix; Elek, Zoltán; Entling, Martin H; Esler, Karen J; de Lima, Ricardo F; Faruk, Aisyah; Farwig, Nina; Fayle, Tom M; Felicioli, Antonio; Felton, Annika M; Fensham, Roderick J; Fernandez, Ignacio C; Ferreira, Catarina C; Ficetola, Gentile F; Fiera, Cristina; Filgueiras, Bruno K C; Fırıncıoğlu, Hüseyin K; Flaspohler, David; Floren, Andreas; Fonte, Steven J; Fournier, Anne; Fowler, Robert E; Franzén, Markus; Fraser, Lauchlan H; Fredriksson, Gabriella M; Freire, Geraldo B; Frizzo, Tiago L M; Fukuda, Daisuke; Furlani, Dario; Gaigher, René; Ganzhorn, Jörg U; García, Karla P; Garcia-R, Juan C; Garden, Jenni G; Garilleti, Ricardo; Ge, Bao-Ming; Gendreau-Berthiaume, Benoit; Gerard, Philippa J; Gheler-Costa, Carla; Gilbert, Benjamin; Giordani, Paolo; Giordano, Simonetta; Golodets, Carly; Gomes, Laurens G L; Gould, Rachelle K; Goulson, Dave; Gove, Aaron D; Granjon, Laurent; Grass, Ingo; Gray, Claudia L; Grogan, James; Gu, Weibin; Guardiola, Moisès; Gunawardene, Nihara R; Gutierrez, Alvaro G; Gutiérrez-Lamus, Doris L; Haarmeyer, Daniela H; Hanley, Mick E; Hanson, Thor; Hashim, Nor R; Hassan, Shombe N; Hatfield, Richard G; Hawes, Joseph E; Hayward, Matt W; Hébert, Christian; Helden, Alvin J; Henden, John-André; Henschel, Philipp; Hernández, Lionel; Herrera, James P; Herrmann, Farina; Herzog, Felix; Higuera-Diaz, Diego; Hilje, Branko; Höfer, Hubert; Hoffmann, Anke; Horgan, Finbarr G; Hornung, Elisabeth; Horváth, Roland; Hylander, Kristoffer; Isaacs-Cubides, Paola; Ishida, Hiroaki; Ishitani, Masahiro; Jacobs, Carmen T; Jaramillo, Víctor J; Jauker, Birgit; Hernández, F Jiménez; Johnson, McKenzie F; Jolli, Virat; Jonsell, Mats; Juliani, S Nur; Jung, Thomas S; Kapoor, Vena; Kappes, Heike; Kati, Vassiliki; Katovai, Eric; Kellner, Klaus; Kessler, Michael; Kirby, Kathryn R; Kittle, Andrew M; Knight, Mairi E; Knop, Eva; Kohler, Florian; Koivula, Matti; Kolb, Annette; Kone, Mouhamadou; Kőrösi, Ádám; Krauss, Jochen; Kumar, Ajith; Kumar, Raman; Kurz, David J; Kutt, Alex S; Lachat, Thibault; Lantschner, Victoria; Lara, Francisco; Lasky, Jesse R; Latta, Steven C; Laurance, William F; Lavelle, Patrick; Le Féon, Violette; LeBuhn, Gretchen; Légaré, Jean-Philippe; Lehouck, Valérie; Lencinas, María V; Lentini, Pia E; Letcher, Susan G; Li, Qi; Litchwark, Simon A; Littlewood, Nick A; Liu, Yunhui; Lo-Man-Hung, Nancy; López-Quintero, Carlos A; Louhaichi, Mounir; Lövei, Gabor L; Lucas-Borja, Manuel Esteban; Luja, Victor H; Luskin, Matthew S; MacSwiney G, M Cristina; Maeto, Kaoru; Magura, Tibor; Mallari, Neil Aldrin; Malone, Louise A; Malonza, Patrick K; Malumbres-Olarte, Jagoba; Mandujano, Salvador; Måren, Inger E; Marin-Spiotta, Erika; Marsh, Charles J; Marshall, E J P; Martínez, Eliana; Martínez Pastur, Guillermo; Moreno Mateos, David; Mayfield, Margaret M; Mazimpaka, Vicente; McCarthy, Jennifer L; McCarthy, Kyle P; McFrederick, Quinn S; McNamara, Sean; Medina, Nagore G; Medina, Rafael; Mena, Jose L; Mico, Estefania; Mikusinski, Grzegorz; Milder, Jeffrey C; Miller, James R; Miranda-Esquivel, Daniel R; Moir, Melinda L; Morales, Carolina L; Muchane, Mary N; Muchane, Muchai; Mudri-Stojnic, Sonja; Munira, A Nur; Muoñz-Alonso, Antonio; Munyekenye, B F; Naidoo, Robin; Naithani, A; Nakagawa, Michiko; Nakamura, Akihiro; Nakashima, Yoshihiro; Naoe, Shoji; Nates-Parra, Guiomar; Navarrete Gutierrez, Dario A; Navarro-Iriarte, Luis; Ndang'ang'a, Paul K; Neuschulz, Eike L; Ngai, Jacqueline T; Nicolas, Violaine; Nilsson, Sven G; Noreika, Norbertas; Norfolk, Olivia; Noriega, Jorge Ari; Norton, David A; Nöske, Nicole M; Nowakowski, A Justin; Numa, Catherine; O'Dea, Niall; O'Farrell, Patrick J; Oduro, William; Oertli, Sabine; Ofori-Boateng, Caleb; Oke, Christopher Omamoke; Oostra, Vicencio; Osgathorpe, Lynne M; Otavo, Samuel Eduardo; Page, Navendu V; Paritsis, Juan; Parra-H, Alejandro; Parry, Luke; Pe'er, Guy; Pearman, Peter B; Pelegrin, Nicolás; Pélissier, Raphaël; Peres, Carlos A; Peri, Pablo L; Persson, Anna S; Petanidou, Theodora; Peters, Marcell K; Pethiyagoda, Rohan S; Phalan, Ben; Philips, T Keith; Pillsbury, Finn C; Pincheira-Ulbrich, Jimmy; Pineda, Eduardo; Pino, Joan; Pizarro-Araya, Jaime; Plumptre, A J; Poggio, Santiago L; Politi, Natalia; Pons, Pere; Poveda, Katja; Power, Eileen F; Presley, Steven J; Proença, Vânia; Quaranta, Marino; Quintero, Carolina; Rader, Romina; Ramesh, B R; Ramirez-Pinilla, Martha P; Ranganathan, Jai; Rasmussen, Claus; Redpath-Downing, Nicola A; Reid, J Leighton; Reis, Yana T; Rey Benayas, José M; Rey-Velasco, Juan Carlos; Reynolds, Chevonne; Ribeiro, Danilo Bandini; Richards, Miriam H; Richardson, Barbara A; Richardson, Michael J; Ríos, Rodrigo Macip; Robinson, Richard; Robles, Carolina A; Römbke, Jörg; Romero-Duque, Luz Piedad; Rös, Matthias; Rosselli, Loreta; Rossiter, Stephen J; Roth, Dana S; Roulston, T'ai H; Rousseau, Laurent; Rubio, André V; Ruel, Jean-Claude; Sadler, Jonathan P; Sáfián, Szabolcs; Saldaña-Vázquez, Romeo A; Sam, Katerina; Samnegård, Ulrika; Santana, Joana; Santos, Xavier; Savage, Jade; Schellhorn, Nancy A; Schilthuizen, Menno; Schmiedel, Ute; Schmitt, Christine B; Schon, Nicole L; Schüepp, Christof; Schumann, Katharina; Schweiger, Oliver; Scott, Dawn M; Scott, Kenneth A; Sedlock, Jodi L; Seefeldt, Steven S; Shahabuddin, Ghazala; Shannon, Graeme; Sheil, Douglas; Sheldon, Frederick H; Shochat, Eyal; Siebert, Stefan J; Silva, Fernando A B; Simonetti, Javier A; Slade, Eleanor M; Smith, Jo; Smith-Pardo, Allan H; Sodhi, Navjot S; Somarriba, Eduardo J; Sosa, Ramón A; Soto Quiroga, Grimaldo; St-Laurent, Martin-Hugues; Starzomski, Brian M; Stefanescu, Constanti; Steffan-Dewenter, Ingolf; Stouffer, Philip C; Stout, Jane C; Strauch, Ayron M; Struebig, Matthew J; Su, Zhimin; Suarez-Rubio, Marcela; Sugiura, Shinji; Summerville, Keith S; Sung, Yik-Hei; Sutrisno, Hari; Svenning, Jens-Christian; Teder, Tiit; Threlfall, Caragh G; Tiitsaar, Anu; Todd, Jacqui H; Tonietto, Rebecca K; Torre, Ignasi; Tóthmérész, Béla; Tscharntke, Teja; Turner, Edgar C; Tylianakis, Jason M; Uehara-Prado, Marcio; Urbina-Cardona, Nicolas; Vallan, Denis; Vanbergen, Adam J; Vasconcelos, Heraldo L; Vassilev, Kiril; Verboven, Hans A F; Verdasca, Maria João; Verdú, José R; Vergara, Carlos H; Vergara, Pablo M; Verhulst, Jort; Virgilio, Massimiliano; Vu, Lien Van; Waite, Edward M; Walker, Tony R; Wang, Hua-Feng; Wang, Yanping; Watling, James I; Weller, Britta; Wells, Konstans; Westphal, Catrin; Wiafe, Edward D; Williams, Christopher D; Willig, Michael R; Woinarski, John C Z; Wolf, Jan H D; Wolters, Volkmar; Woodcock, Ben A; Wu, Jihua; Wunderle, Joseph M; Yamaura, Yuichi; Yoshikura, Satoko; Yu, Douglas W; Zaitsev, Andrey S; Zeidler, Juliane; Zou, Fasheng; Collen, Ben; Ewers, Rob M; Mace, Georgina M; Purves, Drew W; Scharlemann, Jörn P W; Purvis, Andy

    The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of

  13. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    Science.gov (United States)

    Lawrence N. Hudson; Joseph Wunderle M.; And Others

    2016-01-01

    The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to...

  14. Prediction of residual metabolic activity after treatment in NSCLC patients

    International Nuclear Information System (INIS)

    Rios Velazquez, Emmanuel; Aerts, Hugo J.W.L.; Oberije, Cary; Ruysscher, Dirk De; Lambin, Philippe

    2010-01-01

    Purpose. Metabolic response assessment is often used as a surrogate of local failure and survival. Early identification of patients with residual metabolic activity is essential as this enables selection of patients who could potentially benefit from additional therapy. We report on the development of a pre-treatment prediction model for metabolic response using patient, tumor and treatment factors. Methods. One hundred and one patients with inoperable NSCLC (stage I-IV), treated with 3D conformal radical (chemo)-radiotherapy were retrospectively included in this study. All patients received a pre and post-radiotherapy fluorodeoxyglucose positron emission tomography-computed tomography FDG-PET-CT scan. The electronic medical record system and the medical patient charts were reviewed to obtain demographic, clinical, tumor and treatment data. Primary outcome measure was examined using a metabolic response assessment on a post-radiotherapy FDG-PET-CT scan. Radiotherapy was delivered in fractions of 1.8 Gy, twice a day, with a median prescribed dose of 60 Gy. Results. Overall survival was worse in patients with residual metabolic active areas compared with the patients with a complete metabolic response (p=0.0001). In univariate analysis, three variables were significantly associated with residual disease: larger primary gross tumor volume (GTVprimary, p=0.002), higher pre-treatment maximum standardized uptake value (SUV max , p=0.0005) in the primary tumor and shorter overall treatment time (OTT, p=0.046). A multivariate model including GTVprimary, SUV max , equivalent radiation dose at 2 Gy corrected for time (EQD2, T) and OTT yielded an area under the curve assessed by the leave-one-out cross validation of 0.71 (95% CI, 0.65-0.76). Conclusion. Our results confirmed the validity of metabolic response assessment as a surrogate of survival. We developed a multivariate model that is able to identify patients at risk of residual disease. These patients may benefit from

  15. Predicting Metabolic Syndrome Using the Random Forest Method

    Directory of Open Access Journals (Sweden)

    Apilak Worachartcheewan

    2015-01-01

    Full Text Available Aims. This study proposes a computational method for determining the prevalence of metabolic syndrome (MS and to predict its occurrence using the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III criteria. The Random Forest (RF method is also applied to identify significant health parameters. Materials and Methods. We used data from 5,646 adults aged between 18–78 years residing in Bangkok who had received an annual health check-up in 2008. MS was identified using the NCEP ATP III criteria. The RF method was applied to predict the occurrence of MS and to identify important health parameters surrounding this disorder. Results. The overall prevalence of MS was 23.70% (34.32% for males and 17.74% for females. RF accuracy for predicting MS in an adult Thai population was 98.11%. Further, based on RF, triglyceride levels were the most important health parameter associated with MS. Conclusion. RF was shown to predict MS in an adult Thai population with an accuracy >98% and triglyceride levels were identified as the most informative variable associated with MS. Therefore, using RF to predict MS may be potentially beneficial in identifying MS status for preventing the development of diabetes mellitus and cardiovascular diseases.

  16. Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways

    KAUST Repository

    Saidi, Rabie

    2017-08-28

    It is becoming more evident that computational methods are needed for the identification and the mapping of pathways in new genomes. We introduce an automatic annotation system (ARBA4Path Association Rule-Based Annotator for Pathways) that utilizes rule mining techniques to predict metabolic pathways across wide range of prokaryotes. It was demonstrated that specific combinations of protein domains (recorded in our rules) strongly determine pathways in which proteins are involved and thus provide information that let us very accurately assign pathway membership (with precision of 0.999 and recall of 0.966) to proteins of a given prokaryotic taxon. Our system can be used to enhance the quality of automatically generated annotations as well as annotating proteins with unknown function. The prediction models are represented in the form of human-readable rules, and they can be used effectively to add absent pathway information to many proteins in UniProtKB/TrEMBL database.

  17. Anthropometric Indicators Predict Metabolic Syndrome Diagnosis in Maintenance Hemodialysis Patients.

    Science.gov (United States)

    Vogt, Barbara Perez; Ponce, Daniela; Caramori, Jacqueline Costa Teixeira

    2016-06-01

    Obesity has been considered the key in metabolic syndrome (MetS) development, and fat accumulation may be responsible for the occurrence of metabolic abnormalities in hemodialysis patients. The use of gold-standard methods to evaluate obesity is limited, and anthropometric measures may be the simplest methods. However, no study has investigated the association between anthropometric indexes and MetS in these patients. Therefore, the aim was to determine which anthropometric indexes had the best association and prediction for MetS in patients undergoing hemodialysis. Cross-sectional study that included patients older than 18 years, undergoing hemodialysis for at least 3 months. Patients with liver disease and cancer or those receiving corticosteroids or antiretroviral therapy were excluded. Diagnostic criteria from Harmonizing Metabolic Syndrome were used for the diagnosis of MetS. Anthropometric indexes evaluated were body mass index (BMI); percent standard of triceps skinfold thickness and of middle arm muscle circumference; waist circumference (WC); sagittal abdominal diameter; neck circumference; waist-to-hip, waist-to-thigh, and waist-to-height ratios; sagittal index; conicity index; and body fat percentage. Ninety-eight patients were included, 54.1% male, and mean age was 57.8 ± 12.9 years. The prevalence of MetS was 74.5%. Individuals with MetS had increased accumulation of abdominal fat and general obesity. Waist-to-height ratio was the variable independently associated with MetS diagnosis (odds ratio, 1.21; 95% confidence interval, 1.09-1.34; P < .01) and that better predicts MetS, followed by WC and BMI (area under the curve of 0.840, 0.836, and 0.798, respectively, P < .01). Waist-to-height ratio was the best anthropometric predictor of MetS in maintenance hemodialysis patients. © 2015 American Society for Parenteral and Enteral Nutrition.

  18. At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration.

    Science.gov (United States)

    Stegen, James C

    2018-01-01

    To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modeling frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. We can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.

  19. Integration of research infrastructures and ecosystem models toward development of predictive ecology

    Science.gov (United States)

    Luo, Y.; Huang, Y.; Jiang, J.; MA, S.; Saruta, V.; Liang, G.; Hanson, P. J.; Ricciuto, D. M.; Milcu, A.; Roy, J.

    2017-12-01

    The past two decades have witnessed rapid development in sensor technology. Built upon the sensor development, large research infrastructure facilities, such as National Ecological Observatory Network (NEON) and FLUXNET, have been established. Through networking different kinds of sensors and other data collections at many locations all over the world, those facilities generate large volumes of ecological data every day. The big data from those facilities offer an unprecedented opportunity for advancing our understanding of ecological processes, educating teachers and students, supporting decision-making, and testing ecological theory. The big data from the major research infrastructure facilities also provides foundation for developing predictive ecology. Indeed, the capability to predict future changes in our living environment and natural resources is critical to decision making in a world where the past is no longer a clear guide to the future. We are living in a period marked by rapid climate change, profound alteration of biogeochemical cycles, unsustainable depletion of natural resources, and deterioration of air and water quality. Projecting changes in future ecosystem services to the society becomes essential not only for science but also for policy making. We will use this panel format to outline major opportunities and challenges in integrating research infrastructure and ecosystem models toward developing predictive ecology. Meanwhile, we will also show results from an interactive model-experiment System - Ecological Platform for Assimilating Data into models (EcoPAD) - that have been implemented at the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in Northern Minnesota and Montpellier Ecotron, France. EcoPAD is developed by integrating web technology, eco-informatics, data assimilation techniques, and ecosystem modeling. EcoPAD is designed to streamline data transfer seamlessly from research infrastructure

  20. Thermodynamic principles governing metabolic operation : inference, analysis, and prediction

    NARCIS (Netherlands)

    Niebel, Bastian

    2015-01-01

    The principles governing metabolic flux are poorly understood. Because diverse organisms show similar metabolic flux patterns, we hypothesized that fundamental thermodynamic constraints might shape cellular metabolism. We developed a constraint-based model for Saccharomyces cerevisiae that included

  1. Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

    Science.gov (United States)

    Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

    2018-01-01

    Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

  2. Reducing the risk of metabolic syndrome at the worksite: preliminary experience with an ecological approach.

    Science.gov (United States)

    Lucini, Daniela; Zanuso, Silvano; Solaro, Nadia; Vigo, Chiara; Malacarne, Mara; Pagani, Massimo

    2016-02-01

    Given the time spent at work, the workplace represents an ideal setting to implement preventive programs for non-communicable diseases, the major cause of mortality and morbidity in Western and developing countries. We sought to verify if an ecological approach based on corporate culture, employees' education and concrete modifications of workplace environment, offering easy opportunity to assume healthy lifestyle, could be associated with reduced cardiometabolic risk. The study involved 1089 workers in two multinational companies following different workplace health promotion policies. Company A offered to all employees the opportunity to access a web platform dedicated to general information on health and diseases. Company B implemented an ecological model encompassing company culture, employees' education and concrete modifications of workplace environment, giving to all employees the opportunity to adopt healthy solutions throughout daily living at workplace. Participants volunteered self-reported clinical information using an IT tool. Numbers of Metabolic Syndrome components (MetS) were taken as proxy of cardiometabolic risk. MetS probability obtained via statistical modeling was lower in company B as compared to company A, and absenteeism was also lower in company B. Our study shows that a work environment favoring assumption of healthy lifestyle, as in company B, is associated with a lower percentage of employees with MetS components and lower absenteeism. Moreover, statistical modeling shows that individual probabilities of being without MetS elements, controlling for age and gender, is remarkably higher in company B. Our data suggest that ecological approaches might be useful in worksite prevention policies.

  3. Citric Acid Metabolism in Resistant Hypertension: Underlying Mechanisms and Metabolic Prediction of Treatment Response.

    Science.gov (United States)

    Martin-Lorenzo, Marta; Martinez, Paula J; Baldan-Martin, Montserrat; Ruiz-Hurtado, Gema; Prado, Jose Carlos; Segura, Julian; de la Cuesta, Fernando; Barderas, Maria G; Vivanco, Fernando; Ruilope, Luis Miguel; Alvarez-Llamas, Gloria

    2017-11-01

    Resistant hypertension (RH) affects 9% to 12% of hypertensive adults. Prolonged exposure to suboptimal blood pressure control results in end-organ damage and cardiovascular risk. Spironolactone is the most effective drug for treatment, but not all patients respond and side effects are not negligible. Little is known on the mechanisms responsible for RH. We aimed to identify metabolic alterations in urine. In addition, a potential capacity of metabolites to predict response to spironolactone was investigated. Urine was collected from 29 patients with RH and from a group of 13 subjects with pseudo-RH. For patients, samples were collected before and after spironolactone administration and were classified in responders (n=19) and nonresponders (n=10). Nuclear magnetic resonance was applied to identify altered metabolites and pathways. Metabolites were confirmed by liquid chromatography-mass spectrometry. Citric acid cycle was the pathway most significantly altered ( P citric acid cycle and deregulation of reactive oxygen species homeostasis control continue its activation after hypertension was developed. A metabolic panel showing alteration before spironolactone treatment and predicting future response of patients is shown. These molecular indicators will contribute optimizing the rate of control of RH patients with spironolactone. © 2017 American Heart Association, Inc.

  4. The metabolic and ecological interactions of oxalate-degrading bacteria in the Mammalian gut.

    Science.gov (United States)

    Miller, Aaron W; Dearing, Denise

    2013-12-06

    Oxalate-degrading bacteria comprise a functional group of microorganisms, commonly found in the gastrointestinal tract of mammals. Oxalate is a plant secondary compound (PSC) widely produced by all major taxa of plants and as a terminal metabolite by the mammalian liver. As a toxin, oxalate can have a significant impact on the health of mammals, including humans. Mammals do not have the enzymes required to metabolize oxalate and rely on their gut microbiota for this function. Thus, significant metabolic interactions between the mammalian host and a complex gut microbiota maintain the balance of oxalate in the body. Over a dozen species of gut bacteria are now known to degrade oxalate. This review focuses on the host-microbe and microbe-microbe interactions that regulate the degradation of oxalate by the gut microbiota. We discuss the pathways of oxalate throughout the body and the mammalian gut as a series of differentiated ecosystems that facilitate oxalate degradation. We also explore the mechanisms and functions of microbial oxalate degradation along with the implications for the ecological and evolutionary interactions within the microbiota and for mammalian hosts. Throughout, we consider questions that remain, as well as recent technological advances that can be employed to answer them.

  5. River basins as social-ecological systems: linking levels of societal and ecosystem water metabolism in a semiarid watershed

    Directory of Open Access Journals (Sweden)

    Violeta Cabello

    2015-09-01

    Full Text Available River basin modeling under complexity requires analytical frameworks capable of dealing with the multiple scales and dimensions of environmental problems as well as uncertainty in the evolution of social systems. Conceptual and methodological developments can now be framed using the wide socio-eco-hydrological approach. We add hierarchy theory into the mix to discuss the conceptualization of river basins as complex, holarchic social-ecological systems. We operationalize the social-ecological systems water metabolism framework in a semiarid watershed in Spain, and add the governance dimension that shapes human-environment reciprocity. To this purpose, we integrate an eco-hydrological model with the societal metabolism accounting scheme for land use, human activity, and water use. We explore four types of interactions: between societal organization and water uses/demands, between ecosystem organization and their water requirements/supplies, between societal metabolism and aquatic ecosystem health, and between water demand and availability. Our results reveal a metabolic pattern of a high mountain rural system striving to face exodus and agricultural land abandonment with a multifunctional economy. Centuries of social-ecological evolution shaping waterscapes through traditional water management practices have influenced the eco-hydrological functioning of the basin, enabling adaptation to aridity. We found a marked spatial gradient on water supply, use pattern, and impact on water bodies from the head to the mouth of the basin. Management challenges posed by the European water regulatory framework as a new driver of social-ecological change are highlighted.

  6. Developing predictive systems models to address complexity and relevance for ecological risk assessment.

    Science.gov (United States)

    Forbes, Valery E; Calow, Peter

    2013-07-01

    Ecological risk assessments (ERAs) are not used as well as they could be in risk management. Part of the problem is that they often lack ecological relevance; that is, they fail to grasp necessary ecological complexities. Adding realism and complexity can be difficult and costly. We argue that predictive systems models (PSMs) can provide a way of capturing complexity and ecological relevance cost-effectively. However, addressing complexity and ecological relevance is only part of the problem. Ecological risk assessments often fail to meet the needs of risk managers by not providing assessments that relate to protection goals and by expressing risk in ratios that cannot be weighed against the costs of interventions. Once more, PSMs can be designed to provide outputs in terms of value-relevant effects that are modulated against exposure and that can provide a better basis for decision making than arbitrary ratios or threshold values. Recent developments in the modeling and its potential for implementation by risk assessors and risk managers are beginning to demonstrate how PSMs can be practically applied in risk assessment and the advantages that doing so could have. Copyright © 2013 SETAC.

  7. A multimetric approach for predicting the ecological integrity of New Zealand streams

    Directory of Open Access Journals (Sweden)

    Clapcott J.E.

    2014-01-01

    Full Text Available Integrating multiple measures of stream health into a combined metric can provide a holistic assessment of the ecological integrity of a stream. The aim of this study was to develop a multimetric index (MMI of stream integrity based on predictive modelling of national data sets of water quality, macroinvertebrates, fish and ecosystem process metrics. We used a boosted regression tree approach to calculate an observed/expected score for each metric prior to combining metrics in a MMI based on data availability and the strength of predictive models. The resulting MMI provides a geographically meaningful prediction of the ecological integrity of rivers in New Zealand, but identifies limitations in data and approach, providing focus for ongoing research.

  8. Cross-validation of recent and longstanding resting metabolic rate prediction equations

    Science.gov (United States)

    Resting metabolic rate (RMR) measurement is time consuming and requires specialized equipment. Prediction equations provide an easy method to estimate RMR; however, their accuracy likely varies across individuals. Understanding the factors that influence predicted RMR accuracy at the individual lev...

  9. Predicting drug metabolism--an evaluation of the expert system METEOR.

    Science.gov (United States)

    Testa, Bernard; Balmat, Anne-Loyse; Long, Anthony; Judson, Philip

    2005-07-01

    The paper begins with a discussion of the goals of metabolic predictions in early drug research, and some difficulties toward this objective, mainly the various substrate and product selectivities characteristic of drug metabolism. The major in silico approaches to predict drug metabolism are then classified and summarized. A discrimination is, thus, made between 'local' and 'global' systems. In its second part, an evaluation of METEOR, a rule-based expert system used to predict the metabolism of drugs and other xenobiotics, is reported. The published metabolic data of ten substrates were used in this evaluation, the overall results being discussed in terms of correct vs. disputable (i.e., false-positive and false-negative) predictions. The predictions for four representative substrates are presented in detail (Figs. 1-4), illustrating the interest of such an evaluation in identifying where and how predictive rules can be improved.

  10. Prediction of lithium-ion battery capacity with metabolic grey model

    International Nuclear Information System (INIS)

    Chen, Lin; Lin, Weilong; Li, Junzi; Tian, Binbin; Pan, Haihong

    2016-01-01

    Given the popularity of Lithium-ion batteries in EVs (electric vehicles), predicting the capacity quickly and accurately throughout a battery's full life-time is still a challenging issue for ensuring the reliability of EVs. This paper proposes an approach in predicting the varied capacity with discharge cycles based on metabolic grey theory and consider issues from two perspectives: 1) three metabolic grey models will be presented, including MGM (metabolic grey model), MREGM (metabolic Residual-error grey model), and MMREGM (metabolic Markov-residual-error grey model); 2) the universality of these models will be explored under different conditions (such as various discharge rates and temperatures). Furthermore, the research findings in this paper demonstrate the excellent performance of the prediction depending on the three models; however, the precision of the MREGM model is inferior compared to the others. Therefore, we have obtained the conclusion in which the MGM model and the MMREGM model have excellent performances in predicting the capacity under a variety of load conditions, even using few data points for modeling. Also, the universality of the metabolic grey prediction theory is verified by predicting the capacity of batteries under different discharge rates and different temperatures. - Highlights: • The metabolic mechanism is introduced in a grey system for capacity prediction. • Three metabolic grey models are presented and studied. • The universality of these models under different conditions is assessed. • A few data points are required for predicting the capacity with these models.

  11. Adult Attachment Interview Discourse Patterns Predict Metabolic Syndrome in Midlife

    Science.gov (United States)

    Davis, Cynthia R.; Usher, Nicole; Dearing, Eric; Barkai, Ayelet R.; Crowell-Doom, Cindy; Mantzoros, Christos S.; Crowell, Judith A.

    2017-01-01

    Objective Adult attachment discourse patterns and current family relationship quality were examined as predictors of health behaviors and number of Metabolic Syndrome (MetS) criteria met. Methods A sample of 215 White/European American and Black/African American adults, aged 35 to 55, were examined cross-sectionally. Discourse was assessed with the Adult Attachment Interview (AAI), specifically: 1) coherence, a marker of attachment security, 2) unresolved trauma/loss, a marker of disorganized and distorted cognition related to trauma, and 3) idealization, the tendency to minimize the impact of stressful experiences. Health behaviors of diet, exercise, smoking and alcohol use were also assessed, as were adverse childhood experiences, current depressive symptoms and relationship functioning. MetS includes hypertension, hyperglycemia, high triglycerides, low HDL cholesterol, and obesity. Results Using path analysis and accounting for childhood adversity and depressive symptoms, AAI coherence and unresolved trauma or loss were directly linked to number of MetS criteria met (β = −.22 and .21 respectively). Idealization was indirectly linked to MetS through poor diet (β = −.26 and −.36 respectively), predicting 21% of the variance in number of MetS criteria met. Conclusions Attachment representations related to stress appraisal and care-seeking behaviors appear to serve as cognitive mechanisms increasing risk of MetS. PMID:25264975

  12. Validation of resting metabolic rate prediction equations for teenagers

    Directory of Open Access Journals (Sweden)

    Paulo Henrique Santos da Fonseca

    2007-09-01

    Full Text Available The resting metabolic rate (RMR can be defi ned as the minimum rate of energy spent and represents the main component of the energetic outlay. The purpose of this study is to validate equations to predict the resting metabolic rate in teenagers (103 individuals, being 51 girls and 52 boys, with age between 10 and 17 years from Florianópolis – SC – Brazil. It was measured: the body weight, body height, skinfolds and obtained the lean and body fat mass through bioimpedance. The nonproteic RMR was measured by Weir’s equation (1949, utilizing AeroSport TEEM-100 gas analyzer. The studied equations were: Harry and Benedict (1919, Schofi eld (1985, WHO/FAO/UNU (1985, Henry and Rees (1991, Molnár et al. (1998, Tverskaya et al. (1998 and Müller et al. (2004. In order to study the cross-validation of the RMR prediction equations and its standard measure (Weir 1949, the following statistics procedure were calculated: Pearson’s correlation (r ≥ 0.70, the “t” test with the signifi cance level of p0.05 in relation to the standard measure, with exception of the equations suggested for Tverskaya et al. (1998, and the two models of Müller et al (2004. Even though there was not a signifi cant difference, only the models considered for Henry and Rees (1991, and Molnár et al. (1995 had gotten constant error variation under 5%. All the equations analyzed in the study in girls had not reached criterion of correlation values of 0.70 with the indirect calorimetry. Analyzing the prediction equations of RMR in boys, all of them had moderate correlation coeffi cients with the indirect calorimetry, however below 0.70. Only the equation developed for Tverskaya et al. (1998 presented differences (p ABSTRACT0,05 em relação à medida padrão (Weir 1949, com exceção das equações sugeridas por Tverskaya et al. (1998 e os dois modelos de Müller et al (2004. Mesmo não havendo diferença signifi cativa, somente os modelos propostos por Henry e Rees (1991

  13. Xenobiotic metabolism markers in marine fish with different trophic strategies and their relationship to ecological variables.

    Science.gov (United States)

    Solé, M; Rodríguez, S; Papiol, V; Maynou, F; Cartes, J E

    2009-01-01

    Nine fish species of commercial interest from six teleost families and two species of elasmobranchs were selected for characterisation of hepatic biomarkers used in early-warning assessment of pollutant exposure. The sampling was carried out in front of the Barcelona coast (NW Mediterranean) during December 2006 at shelf (53 m) and slope (660 m) depths. The enzymes considered included the antioxidant defence catalase (CAT) and glutathione reductase (GR), phase I ethoxyresorufin O-deethylase (EROD) and phase II glutathione S-transferase (GST). Protein yield (PY) was used as a general marker of hepatic protein synthesis. Significant interspecies differences were evidenced, although each marker varied independently. Enzymatic activities in teleosts were higher than in elasmobranchs; they were very low in Scyliorhinus canicula (mainly a benthic feeder), but not so low in Galeus melastomus (pelagic feeder). In relation to depth, shallow water, shelf-living species had higher metabolic activities. Trophic variables were significantly related to PY and EROD activity, and were especially high in benthic/suprabenthic feeders. Trophic level (deduced from stable isotopy) and stomach fullness were associated with all hepatic markers, except GR. Swimming capacity was related to all hepatic enzymes. Our findings can be applied, not only from the perspective of conservation ecology regarding pollution, but also in fisheries, due to the economic interest of the species involved.

  14. Ecological pressures and milk metabolic hormones of ethnic Tibetans living at different altitudes.

    Science.gov (United States)

    Quinn, Elizabeth A; Childs, Geoff

    2017-02-01

    Very little is known about how milk hormones, shown to influence growth during infancy, may contribute to patterns of altered growth in high altitude living infants. This study investigated the association between maternal BMI, the metabolic hormones adiponectin and leptin in human milk and infant weight for age z-scores (WAZ) in Tibetans. A sample of 116 mothers and infants (aged 0-36 months) were recruited from two locations: the Nubri Valley, Nepal (rural; altitude = 2400-3900 m) and Kathmandu, Nepal (urban, 1400 m). Milk samples, anthropometrics, biological data and environmental information were collected on mothers and infants. Milk was analysed for leptin and adiponectin. Maternal BMI was significantly associated with milk leptin content, but not adiponectin in either group. In the rural high altitude sample, child WAZ declined with age, but no such decline was seen in the urban sample. Milk leptin and adiponectin were not associated with infant growth in the rural Nubri sample, but were both inversely associated with infant WAZ in the Kathmandu sample. It appears that, in ecologically stressful environments, associations between milk hormones and growth during infancy may not be detectable in cross-sectional studies.

  15. Assessing Confidence in Predictions Using Veracity and Utility - A Case Study on the Prediction of Mammalian Metabolism by Meteor Nexus.

    Science.gov (United States)

    Judson, Philip N; Long, Anthony; Murray, Ernest; Patel, Mukesh

    2015-05-01

    A previous paper1 described new metrics, veracity and utility, for assessing the performance of toxicity prediction systems that report confidence in their predictions. Assessing the performance of systems that predict mammalian metabolism is complicated by the absence of comprehensive sets of negative observations and predictions. This paper presents an approach to assessing the performance of such systems using veracity and utility. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Molecular evolutionary rates are not correlated with temperature and latitude in Squamata: an exception to the metabolic theory of ecology?

    Science.gov (United States)

    Rolland, Jonathan; Loiseau, Oriane; Romiguier, Jonathan; Salamin, Nicolas

    2016-05-20

    The metabolic theory of ecology stipulates that molecular evolutionary rates should correlate with temperature and latitude in ectothermic organisms. Previous studies have shown that most groups of vertebrates, such as amphibians, turtles and even endothermic mammals, have higher molecular evolutionary rates in regions where temperature is high. However, the association between molecular evolutionary rates and temperature or latitude has never been tested in Squamata. We used a large dataset including the spatial distributions and environmental variables for 1,651 species of Squamata and compared the contrast of the rates of molecular evolution with the contrast of temperature and latitude between sister species. Using major axis regressions and a new algorithm to choose independent sister species pairs, we found that temperature and absolute latitude were not associated with molecular evolutionary rates. This absence of association in such a diverse ectothermic group questions the mechanisms explaining current pattern of species diversity in Squamata and challenges the presupposed universality of the metabolic theory of ecology.

  17. Challenges in microbial ecology: Building predictive understanding of community function and dynamics

    DEFF Research Database (Denmark)

    Widder, Stefanie; Allen, Rosalind J.; Pfeiffer, Thomas

    2016-01-01

    The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly...... complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development...

  18. Comparative Functional Responses Predict the Invasiveness and Ecological Impacts of Alien Herbivorous Snails.

    Directory of Open Access Journals (Sweden)

    Meng Xu

    Full Text Available Understanding determinants of the invasiveness and ecological impacts of alien species is amongst the most sought-after and urgent research questions in ecology. Several studies have shown the value of comparing the functional responses (FRs of alien and native predators towards native prey, however, the technique is under-explored with herbivorous alien species and as a predictor of invasiveness as distinct from ecological impact. Here, in China, we conducted a mesocosm experiment to compare the FRs among three herbivorous snail species: the golden apple snail, Pomacea canaliculata, a highly invasive and high impact alien listed in "100 of the World's Worst Invasive Alien Species"; Planorbarius corneus, a non-invasive, low impact alien; and the Chinese native snail, Bellamya aeruginosa, when feeding on four locally occurring plant species. Further, by using a numerical response equation, we modelled the population dynamics of the snail consumers. For standard FR parameters, we found that the invasive and damaging alien snail had the highest "attack rates" a, shortest "handling times" h and also the highest estimated maximum feeding rates, 1/hT, whereas the native species had the lowest attack rates, longest handling times and lowest maximum feeding rates. The non-invasive, low impact alien species had consistently intermediate FR parameters. The invasive alien species had higher population growth potential than the native snail species, whilst that of the non-invasive alien species was intermediate. Thus, while the comparative FR approach has been proposed as a reliable method for predicting the ecological impacts of invasive predators, our results further suggest that comparative FRs could extend to predict the invasiveness and ecological impacts of alien herbivores and should be explored in other taxa and trophic groups to determine the general utility of the approach.

  19. Comparative Functional Responses Predict the Invasiveness and Ecological Impacts of Alien Herbivorous Snails

    Science.gov (United States)

    Xu, Meng; Mu, Xidong; Dick, Jaimie T. A.; Fang, Miao; Gu, Dangen; Luo, Du; Zhang, Jiaen; Luo, Jianren; Hu, Yinchang

    2016-01-01

    Understanding determinants of the invasiveness and ecological impacts of alien species is amongst the most sought-after and urgent research questions in ecology. Several studies have shown the value of comparing the functional responses (FRs) of alien and native predators towards native prey, however, the technique is under-explored with herbivorous alien species and as a predictor of invasiveness as distinct from ecological impact. Here, in China, we conducted a mesocosm experiment to compare the FRs among three herbivorous snail species: the golden apple snail, Pomacea canaliculata, a highly invasive and high impact alien listed in “100 of the World's Worst Invasive Alien Species”; Planorbarius corneus, a non-invasive, low impact alien; and the Chinese native snail, Bellamya aeruginosa, when feeding on four locally occurring plant species. Further, by using a numerical response equation, we modelled the population dynamics of the snail consumers. For standard FR parameters, we found that the invasive and damaging alien snail had the highest “attack rates” a, shortest “handling times” h and also the highest estimated maximum feeding rates, 1/hT, whereas the native species had the lowest attack rates, longest handling times and lowest maximum feeding rates. The non-invasive, low impact alien species had consistently intermediate FR parameters. The invasive alien species had higher population growth potential than the native snail species, whilst that of the non-invasive alien species was intermediate. Thus, while the comparative FR approach has been proposed as a reliable method for predicting the ecological impacts of invasive predators, our results further suggest that comparative FRs could extend to predict the invasiveness and ecological impacts of alien herbivores and should be explored in other taxa and trophic groups to determine the general utility of the approach. PMID:26771658

  20. Diagnosing and Predicting the Earth’s Health via Ecological Network Analysis

    Directory of Open Access Journals (Sweden)

    Zi-Ke Zhang

    2013-01-01

    Full Text Available Ecological balance is one of the most attractive topics in biological, environmental, earth sciences, and so on. However, due to the complexity of ecosystems, it is not easy to find a perfect way to conclusively explain all the potential impacts. In this paper, by considering several important elements, we seek to build a dynamic network model to predict the Earth’s health, trying to identify and explain how the human behavior and policies affect the model results. We firstly empirically analyze both the topological properties and time-dependent features of nodes and propose an Earth’s health index based on Shannon Entropy. Secondly, we identify the importance of each element by a machine learning approach. Thirdly, we use a spreading model to predict the Earth’s health. Finally, we integrate the topological property and the proposed health index to identify the influential nodes in the observed ecological network. Experimental results show that the oceans are the key nodes in affecting the Earth’s health, and Big countries are also important nodes in influencing the Earth’s health. In addition, the results suggest a possible solution that returning more living lands might be an effective way to solve the dilemma of ecological balance.

  1. Temperature dependences of growth rates and carrying capacities of marine bacteria depart from metabolic theoretical predictions

    KAUST Repository

    Huete-Stauffer, Tamara Megan

    2015-09-11

    Using the metabolic theory of ecology (MTE) framework, we evaluated over a whole annual cycle the monthly responses to temperature of the growth rates (μ) and carrying capacities (K) of heterotrophic bacterioplankton at a temperate coastal site. We used experimental incubations spanning 6oC with bacterial physiological groups identified by flow cytometry according to membrane integrity (live), nucleic acid content (HNA and LNA) and respiratory activity (CTC+). The temperature dependence of μat the exponential phase of growth was summarized by the activation energy (E), which was variable (-0.52 to 0.72 eV) but followed a seasonal pattern, only reaching the hypothesized value for aerobic heterotrophs of 0.65 eV during the spring bloom for the most active bacterial groups (live, HNA, CTC+). K (i.e. maximum experimental abundance) peaked at 4 × 106 cells mL-1 and generally covaried with μbut, contrary to MTE predictions, it did not decrease consistently with temperature. In the case of live cells, the responses of μand K to temperature were positively correlated and related to seasonal changes in substrate availability, indicating that the responses of bacteria to warming are far from homogeneous and poorly explained by MTE at our site. © FEMS 2015.

  2. Copepod community growth rates in relation to body size, temperature, and food availability in the East China Sea: a test of metabolic theory of ecology

    Directory of Open Access Journals (Sweden)

    K. Y. Lin

    2013-03-01

    Full Text Available Zooplankton play an essential role in marine food webs, and understanding how community-level growth rates of zooplankton vary in the field is critical for predicting how marine ecosystem function may vary in the face of environmental changes. Here, we used the artificial cohort method to examine the effects of temperature, body size, and chlorophyll concentration (a proxy for food on weight-specific growth rates for copepod communities in the East China Sea. Specifically, we tested the hypothesis that copepod community growth rates can be described by the metabolic theory of ecology (MTE, linking spatio-temporal variation of copepod growth rate with temperature and their body size. Our results generally agree with predictions made by the MTE and demonstrate that weight-specific growth rates of copepod communities in our study area are positively related with temperature and negatively related to body size. However, the regression coefficients of body size do not approach the theoretical predictions. Furthermore, we find that the deviation from the MTE predictions may be partly attributed to the effect of food availability (which is not explicitly accounted for by the MTE. In addition, significant difference in the coefficients of temperature and body size exists among taxonomic groups. Our results suggest that considering the effects of food limitation and taxonomy is necessary to better understand copepod growth rates under in situ conditions, and such effects on the MTE-based predictions need further investigation.

  3. Community ecology theory predicts the effects of agrochemical mixtures on aquatic biodiversity and ecosystem properties.

    Science.gov (United States)

    Halstead, Neal T; McMahon, Taegan A; Johnson, Steve A; Raffel, Thomas R; Romansic, John M; Crumrine, Patrick W; Rohr, Jason R

    2014-08-01

    Ecosystems are often exposed to mixtures of chemical contaminants, but the scientific community lacks a theoretical framework to predict the effects of mixtures on biodiversity and ecosystem properties. We conducted a freshwater mesocosm experiment to examine the effects of pairwise agrochemical mixtures [fertiliser, herbicide (atrazine), insecticide (malathion) and fungicide (chlorothalonil)] on 24 species- and seven ecosystem-level responses. As postulated, the responses of biodiversity and ecosystem properties to agrochemicals alone and in mixtures was predictable by integrating information on each functional group's (1) sensitivity to the chemicals (direct effects), (2) reproductive rates (recovery rates), (3) interaction strength with other functional groups (indirect effects) and (4) links to ecosystem properties. These results show that community ecology theory holds promise for predicting the effects of contaminant mixtures on biodiversity and ecosystem services and yields recommendations on which types of agrochemicals to apply together and separately to reduce their impacts on aquatic ecosystems. © 2014 John Wiley & Sons Ltd/CNRS.

  4. Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases.

    Science.gov (United States)

    Peterson, A Townsend; Martínez-Campos, Carmen; Nakazawa, Yoshinori; Martínez-Meyer, Enrique

    2005-09-01

    Numerous human diseases-malaria, dengue, yellow fever and leishmaniasis, to name a few-are transmitted by insect vectors with brief life cycles and biting activity that varies in both space and time. Although the general geographic distributions of these epidemiologically important species are known, the spatiotemporal variation in their emergence and activity remains poorly understood. We used ecological niche modeling via a genetic algorithm to produce time-specific predictive models of monthly distributions of Aedes aegypti in Mexico in 1995. Significant predictions of monthly mosquito activity and distributions indicate that predicting spatiotemporal dynamics of disease vector species is feasible; significant coincidence with human cases of dengue indicate that these dynamics probably translate directly into transmission of dengue virus to humans. This approach provides new potential for optimizing use of resources for disease prevention and remediation via automated forecasting of disease transmission risk.

  5. Application of alternative anthropometric measurements to predict metabolic syndrome

    Directory of Open Access Journals (Sweden)

    Gul Sagun

    2014-01-01

    Full Text Available OBJECTIVE: The association between rarely used anthropometric measurements (e.g., mid-upper arm, forearm, and calf circumference and metabolic syndrome has not been proven. The aim of this study was to assess whether mid-upper arm, forearm, calf, and waist circumferences, as well as waist/height ratio and waist-to-hip ratio, were associated with metabolic syndrome. METHODS: We enrolled 387 subjects (340 women, 47 men who were admitted to the obesity outpatient department of Istanbul Medeniyet University Goztepe Training and Research Hospital between September 2010 and December 2010. The following measurements were recorded: waist circumference, hip circumference, waist/height ratio, waist-to-hip ratio, mid-upper arm circumference, forearm circumference, calf circumference, and body composition. Fasting blood samples were collected to measure plasma glucose, lipids, uric acid, insulin, and HbA1c. RESULTS: The odds ratios for visceral fat (measured via bioelectric impedance, hip circumference, forearm circumference, and waist circumference/hip circumference were 2.19 (95% CI, 1.30-3.71, 1.89 (95% CI, 1.07-3.35, 2.47 (95% CI, 1.24-4.95, and 2.11(95% CI, 1.26-3.53, respectively. The bioelectric impedance-measured body fat percentage correlated with waist circumference only in subjects without metabolic syndrome; the body fat percentage was negatively correlated with waist circumference/hip circumference in the metabolic syndrome group. All measurements except for forearm circumference were equally well correlated with the bioelectric impedance-measured body fat percentages in both groups. Hip circumference was moderately correlated with bioelectric impedance-measured visceral fat in subjects without metabolic syndrome. Muscle mass (measured via bioelectric impedance was weakly correlated with waist and forearm circumference in subjects with metabolic syndrome and with calf circumference in subjects without metabolic syndrome. CONCLUSION: Waist

  6. Assessing validity of serum cystatin C for predicting metabolic syndrome.

    Science.gov (United States)

    Asefy, Zahra; Mirinejad, MirMoosa; Amirrasooli, Hooshang; Tagikhani, Mohammad

    2014-04-01

    Serum concentration of cystatin C a marker of glomerular filtration has been associated with Cardiovascular Disease (CVD). The aim of this study was to evaluate cystatin C as a marker of diabetic kidney disease in normoalbuminuric diabetic patients without Chronic Kidney Disease (CKD). The study population consisted of 65 subjects with metabolic syndrome and 32 subjects free of metabolic syndrome (control group). HDL-C, LDL-C, blood urea, triglycerides, glucose, HbA1c, serum cystatin C and serum creatinine were measured in both groups. GFR was calculated in both groups using Cockrofta Gault equation. Metabolic syndrome presented higher cystatin C levels than normal samples (0.98 8 0.26 1.24 8 0.24 p metabolic syndrome was significantly associated with elevated cystatin C levels. Diabetic patients also presented a slightly greater creatinine (1.11 8 0.09 1.04 0.15 p metabolic syndrome and may identify a certain degree of renal dysfunction even when serum creatinine does not exceed normal level.

  7. Measured and predicted resting metabolic rate in Italian males and females, aged 18-59y

    NARCIS (Netherlands)

    Lorenzo, de A.; Tagliabue, A.; Andreoli, A.; Testolin, G.; Comelli, M.; Deurenberg, P.

    2001-01-01

    To determine the resting metabolic rate in a sample of the Italian population, and to evaluate the validity of predictive equations for resting metabolic rate (RMR) from the literature in normal and obese subjects. Design: Cross-sectional observational study. Settings: Department of Human Physiology

  8. Ecological Niche Modeling for the Prediction of the Geographic Distribution of Cutaneous Leishmaniasis in Tunisia.

    Science.gov (United States)

    Chalghaf, Bilel; Chlif, Sadok; Mayala, Benjamin; Ghawar, Wissem; Bettaieb, Jihène; Harrabi, Myriam; Benie, Goze Bertin; Michael, Edwin; Salah, Afif Ben

    2016-04-01

    Cutaneous leishmaniasis is a very complex disease involving multiple factors that limit its emergence and spatial distribution. Prediction of cutaneous leishmaniasis epidemics in Tunisia remains difficult because most of the epidemiological tools used so far are descriptive in nature and mainly focus on a time dimension. The purpose of this work is to predict the potential geographic distribution of Phlebotomus papatasi and zoonotic cutaneous leishmaniasis caused by Leishmania major in Tunisia using Grinnellian ecological niche modeling. We attempted to assess the importance of environmental factors influencing the potential distribution of P. papatasi and cutaneous leishmaniasis caused by L. major. Vectors were trapped in central Tunisia during the transmission season using CDC light traps (John W. Hock Co., Gainesville, FL). A global positioning system was used to record the geographical coordinates of vector occurrence points and households tested positive for cutaneous leishmaniasis caused by L. major. Nine environmental layers were used as predictor variables to model the P. papatasi geographical distribution and five variables were used to model the L. major potential distribution. Ecological niche modeling was used to relate known species' occurrence points to values of environmental factors for these same points to predict the presence of the species in unsampled regions based on the value of the predictor variables. Rainfall and temperature contributed the most as predictors for sand flies and human case distributions. Ecological niche modeling anticipated the current distribution of P. papatasi with the highest suitability for species occurrence in the central and southeastern part of Tunisian. Furthermore, our study demonstrated that governorates of Gafsa, Sidi Bouzid, and Kairouan are at highest epidemic risk. © The American Society of Tropical Medicine and Hygiene.

  9. Predicting community structure in snakes on Eastern Nearctic islands using ecological neutral theory and phylogenetic methods.

    Science.gov (United States)

    Burbrink, Frank T; McKelvy, Alexander D; Pyron, R Alexander; Myers, Edward A

    2015-11-22

    Predicting species presence and richness on islands is important for understanding the origins of communities and how likely it is that species will disperse and resist extinction. The equilibrium theory of island biogeography (ETIB) and, as a simple model of sampling abundances, the unified neutral theory of biodiversity (UNTB), predict that in situations where mainland to island migration is high, species-abundance relationships explain the presence of taxa on islands. Thus, more abundant mainland species should have a higher probability of occurring on adjacent islands. In contrast to UNTB, if certain groups have traits that permit them to disperse to islands better than other taxa, then phylogeny may be more predictive of which taxa will occur on islands. Taking surveys of 54 island snake communities in the Eastern Nearctic along with mainland communities that have abundance data for each species, we use phylogenetic assembly methods and UNTB estimates to predict island communities. Species richness is predicted by island area, whereas turnover from the mainland to island communities is random with respect to phylogeny. Community structure appears to be ecologically neutral and abundance on the mainland is the best predictor of presence on islands. With regard to young and proximate islands, where allopatric or cladogenetic speciation is not a factor, we find that simple neutral models following UNTB and ETIB predict the structure of island communities. © 2015 The Author(s).

  10. In silico prediction of xenobiotic metabolism in humans

    Energy Technology Data Exchange (ETDEWEB)

    Mu, Fangping [Los Alamos National Laboratory

    2009-01-01

    Xenobiotic metabolism in humans is catalyzed by a few enzymes with broad substrate specificities, which provide the overall broad chemical specificity for nearly all xenobiotics that humans encounter. Xenobiotic metabolism are classified into functional group biotransformations. Based on bona fide reactions and negative examples for each reaction class, support vector machine (SVM) classifiers are built. The input to SVM is a set of atomic and molecular features to define the electrostatic, steric, energetic, geometrical and topological environment of the atoms in the reaction center under the molecule. Results show that the overall sensitivity and specificity of classifiers is around 87%.

  11. Testing the Metabolic Theory of Ecology with marine bacteria: Different temperature sensitivity of major phylogenetic groups during the spring phytoplankton bloom

    KAUST Repository

    Arandia-Gorostidi, Nestor

    2017-08-24

    Although temperature is a key driver of bacterioplankton metabolism, the effect of ocean warming on different bacterial phylogenetic groups remains unclear. Here, we conducted monthly short-term incubations with natural coastal bacterial communities over an annual cycle to test the effect of experimental temperature on the growth rates and carrying capacities of four phylogenetic groups: SAR11, Rhodobacteraceae, Gammaproteobacteria and Bacteroidetes. SAR11 was the most abundant group year-round as analysed by CARD-FISH, with maximum abundances in summer, while the other taxa peaked in spring. All groups, including SAR11, showed high temperature-sensitivity of growth rates and/or carrying capacities in spring, under phytoplankton bloom or post-bloom conditions. In that season, Rhodobacteraceae showed the strongest temperature response in growth rates, estimated here as activation energy (E, 1.43 eV), suggesting an advantage to outcompete other groups under warmer conditions. In summer E values were in general lower than 0.65 eV, the value predicted by the Metabolic Theory of Ecology (MTE). Contrary to MTE predictions, carrying capacity tended to increase with warming for all bacterial groups. Our analysis confirms that resource availability is key when addressing the temperature response of heterotrophic bacterioplankton. We further show that even under nutrient-sufficient conditions, warming differentially affected distinct bacterioplankton taxa. This article is protected by copyright. All rights reserved.

  12. Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

    Science.gov (United States)

    Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

    2017-01-01

    Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348

  13. Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

    Science.gov (United States)

    Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

    2017-06-15

    Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

  14. Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA Approach—A Case Study for the City of Wuhan in China

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2017-06-01

    Full Text Available Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level using an improved Cellular Automata (CA approach. First we used the pressure-state-response (PSR method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

  15. Predicting growth of the healthy infant using a genome scale metabolic model

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

    2017-01-01

    An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model...... to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body...

  16. Serum uric acid and appropriate cutoff value for prediction of metabolic syndrome among Chinese adults.

    Science.gov (United States)

    Zhang, Mei-Lin; Gao, Yu-Xia; Wang, Xuan; Chang, Hong; Huang, Guo-Wei

    2013-01-01

    The relation between serum uric acid and metabolic syndrome is observed not only with frank hyperuricemia but also with serum uric acid levels within the normal range. The current "normal" range set for hyperuricemia often fails to identify patients with potential metabolic disorders. We investigate the association between serum uric acid within the normal range and incident metabolic syndrome risk, and further to determine the optimal cut-off value of serum uric acid for the diagnosis or prediction of metabolic syndrome. A total of 7399 Chinese adults (2957 men and 4442 women; ≥20 years) free of metabolic syndrome were followed for 3 years. During the 3-year follow-up, 1190 normouricemic individuals developed metabolic syndrome (16.1%). After adjusting the associated variables, the top quartile of serum uric acid levels was associated with higher metabolic syndrome development compared with the bottom quartile in men (hazard ratio (HR), 1.29; puric acid to identify metabolic syndrome were 6.3 mg/dl in men and 4.9 mg/dl in women. Our results suggested that high baseline serum uric acid levels within the normal range predict future development of metabolic syndrome after 3 y of follow-up.

  17. Effect of Lineage-Specific Metabolic Traits of Lactobacillus reuteri on Sourdough Microbial Ecology

    OpenAIRE

    Lin, Xiaoxi B.; Gänzle, Michael G.

    2014-01-01

    This study determined the effects of specific metabolic traits of Lactobacillus reuteri on its competitiveness in sourdoughs. The competitiveness of lactobacilli in sourdough generally depends on their growth rate; acid resistance additionally contributes to competitiveness in sourdoughs with long fermentation times. Glycerol metabolism via glycerol dehydratase (gupCDE) accelerates growth by the regeneration of reduced cofactors; glutamate metabolism via glutamate decarboxylase (gadB) increas...

  18. Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.

    Science.gov (United States)

    Staniczenko, Phillip P A; Sivasubramaniam, Prabu; Suttle, K Blake; Pearson, Richard G

    2017-06-01

    Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

  19. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project.

    Science.gov (United States)

    Hudson, Lawrence N; Newbold, Tim; Contu, Sara; Hill, Samantha L L; Lysenko, Igor; De Palma, Adriana; Phillips, Helen R P; Alhusseini, Tamera I; Bedford, Felicity E; Bennett, Dominic J; Booth, Hollie; Burton, Victoria J; Chng, Charlotte W T; Choimes, Argyrios; Correia, David L P; Day, Julie; Echeverría-Londoño, Susy; Emerson, Susan R; Gao, Di; Garon, Morgan; Harrison, Michelle L K; Ingram, Daniel J; Jung, Martin; Kemp, Victoria; Kirkpatrick, Lucinda; Martin, Callum D; Pan, Yuan; Pask-Hale, Gwilym D; Pynegar, Edwin L; Robinson, Alexandra N; Sanchez-Ortiz, Katia; Senior, Rebecca A; Simmons, Benno I; White, Hannah J; Zhang, Hanbin; Aben, Job; Abrahamczyk, Stefan; Adum, Gilbert B; Aguilar-Barquero, Virginia; Aizen, Marcelo A; Albertos, Belén; Alcala, E L; Del Mar Alguacil, Maria; Alignier, Audrey; Ancrenaz, Marc; Andersen, Alan N; Arbeláez-Cortés, Enrique; Armbrecht, Inge; Arroyo-Rodríguez, Víctor; Aumann, Tom; Axmacher, Jan C; Azhar, Badrul; Azpiroz, Adrián B; Baeten, Lander; Bakayoko, Adama; Báldi, András; Banks, John E; Baral, Sharad K; Barlow, Jos; Barratt, Barbara I P; Barrico, Lurdes; Bartolommei, Paola; Barton, Diane M; Basset, Yves; Batáry, Péter; Bates, Adam J; Baur, Bruno; Bayne, Erin M; Beja, Pedro; Benedick, Suzan; Berg, Åke; Bernard, Henry; Berry, Nicholas J; Bhatt, Dinesh; Bicknell, Jake E; Bihn, Jochen H; Blake, Robin J; Bobo, Kadiri S; Bóçon, Roberto; Boekhout, Teun; Böhning-Gaese, Katrin; Bonham, Kevin J; Borges, Paulo A V; Borges, Sérgio H; Boutin, Céline; Bouyer, Jérémy; Bragagnolo, Cibele; Brandt, Jodi S; Brearley, Francis Q; Brito, Isabel; Bros, Vicenç; Brunet, Jörg; Buczkowski, Grzegorz; Buddle, Christopher M; Bugter, Rob; Buscardo, Erika; Buse, Jörn; Cabra-García, Jimmy; Cáceres, Nilton C; Cagle, Nicolette L; Calviño-Cancela, María; Cameron, Sydney A; Cancello, Eliana M; Caparrós, Rut; Cardoso, Pedro; Carpenter, Dan; Carrijo, Tiago F; Carvalho, Anelena L; Cassano, Camila R; Castro, Helena; Castro-Luna, Alejandro A; Rolando, Cerda B; Cerezo, Alexis; Chapman, Kim Alan; Chauvat, Matthieu; Christensen, Morten; Clarke, Francis M; Cleary, Daniel F R; Colombo, Giorgio; Connop, Stuart P; Craig, Michael D; Cruz-López, Leopoldo; Cunningham, Saul A; D'Aniello, Biagio; D'Cruze, Neil; da Silva, Pedro Giovâni; Dallimer, Martin; Danquah, Emmanuel; Darvill, Ben; Dauber, Jens; Davis, Adrian L V; Dawson, Jeff; de Sassi, Claudio; de Thoisy, Benoit; Deheuvels, Olivier; Dejean, Alain; Devineau, Jean-Louis; Diekötter, Tim; Dolia, Jignasu V; Domínguez, Erwin; Dominguez-Haydar, Yamileth; Dorn, Silvia; Draper, Isabel; Dreber, Niels; Dumont, Bertrand; Dures, Simon G; Dynesius, Mats; Edenius, Lars; Eggleton, Paul; Eigenbrod, Felix; Elek, Zoltán; Entling, Martin H; Esler, Karen J; de Lima, Ricardo F; Faruk, Aisyah; Farwig, Nina; Fayle, Tom M; Felicioli, Antonio; Felton, Annika M; Fensham, Roderick J; Fernandez, Ignacio C; Ferreira, Catarina C; Ficetola, Gentile F; Fiera, Cristina; Filgueiras, Bruno K C; Fırıncıoğlu, Hüseyin K; Flaspohler, David; Floren, Andreas; Fonte, Steven J; Fournier, Anne; Fowler, Robert E; Franzén, Markus; Fraser, Lauchlan H; Fredriksson, Gabriella M; Freire, Geraldo B; Frizzo, Tiago L M; Fukuda, Daisuke; Furlani, Dario; Gaigher, René; Ganzhorn, Jörg U; García, Karla P; Garcia-R, Juan C; Garden, Jenni G; Garilleti, Ricardo; Ge, Bao-Ming; Gendreau-Berthiaume, Benoit; Gerard, Philippa J; Gheler-Costa, Carla; Gilbert, Benjamin; Giordani, Paolo; Giordano, Simonetta; Golodets, Carly; Gomes, Laurens G L; Gould, Rachelle K; Goulson, Dave; Gove, Aaron D; Granjon, Laurent; Grass, Ingo; Gray, Claudia L; Grogan, James; Gu, Weibin; Guardiola, Moisès; Gunawardene, Nihara R; Gutierrez, Alvaro G; Gutiérrez-Lamus, Doris L; Haarmeyer, Daniela H; Hanley, Mick E; Hanson, Thor; Hashim, Nor R; Hassan, Shombe N; Hatfield, Richard G; Hawes, Joseph E; Hayward, Matt W; Hébert, Christian; Helden, Alvin J; Henden, John-André; Henschel, Philipp; Hernández, Lionel; Herrera, James P; Herrmann, Farina; Herzog, Felix; Higuera-Diaz, Diego; Hilje, Branko; Höfer, Hubert; Hoffmann, Anke; Horgan, Finbarr G; Hornung, Elisabeth; Horváth, Roland; Hylander, Kristoffer; Isaacs-Cubides, Paola; Ishida, Hiroaki; Ishitani, Masahiro; Jacobs, Carmen T; Jaramillo, Víctor J; Jauker, Birgit; Hernández, F Jiménez; Johnson, McKenzie F; Jolli, Virat; Jonsell, Mats; Juliani, S Nur; Jung, Thomas S; Kapoor, Vena; Kappes, Heike; Kati, Vassiliki; Katovai, Eric; Kellner, Klaus; Kessler, Michael; Kirby, Kathryn R; Kittle, Andrew M; Knight, Mairi E; Knop, Eva; Kohler, Florian; Koivula, Matti; Kolb, Annette; Kone, Mouhamadou; Kőrösi, Ádám; Krauss, Jochen; Kumar, Ajith; Kumar, Raman; Kurz, David J; Kutt, Alex S; Lachat, Thibault; Lantschner, Victoria; Lara, Francisco; Lasky, Jesse R; Latta, Steven C; Laurance, William F; Lavelle, Patrick; Le Féon, Violette; LeBuhn, Gretchen; Légaré, Jean-Philippe; Lehouck, Valérie; Lencinas, María V; Lentini, Pia E; Letcher, Susan G; Li, Qi; Litchwark, Simon A; Littlewood, Nick A; Liu, Yunhui; Lo-Man-Hung, Nancy; López-Quintero, Carlos A; Louhaichi, Mounir; Lövei, Gabor L; Lucas-Borja, Manuel Esteban; Luja, Victor H; Luskin, Matthew S; MacSwiney G, M Cristina; Maeto, Kaoru; Magura, Tibor; Mallari, Neil Aldrin; Malone, Louise A; Malonza, Patrick K; Malumbres-Olarte, Jagoba; Mandujano, Salvador; Måren, Inger E; Marin-Spiotta, Erika; Marsh, Charles J; Marshall, E J P; Martínez, Eliana; Martínez Pastur, Guillermo; Moreno Mateos, David; Mayfield, Margaret M; Mazimpaka, Vicente; McCarthy, Jennifer L; McCarthy, Kyle P; McFrederick, Quinn S; McNamara, Sean; Medina, Nagore G; Medina, Rafael; Mena, Jose L; Mico, Estefania; Mikusinski, Grzegorz; Milder, Jeffrey C; Miller, James R; Miranda-Esquivel, Daniel R; Moir, Melinda L; Morales, Carolina L; Muchane, Mary N; Muchane, Muchai; Mudri-Stojnic, Sonja; Munira, A Nur; Muoñz-Alonso, Antonio; Munyekenye, B F; Naidoo, Robin; Naithani, A; Nakagawa, Michiko; Nakamura, Akihiro; Nakashima, Yoshihiro; Naoe, Shoji; Nates-Parra, Guiomar; Navarrete Gutierrez, Dario A; Navarro-Iriarte, Luis; Ndang'ang'a, Paul K; Neuschulz, Eike L; Ngai, Jacqueline T; Nicolas, Violaine; Nilsson, Sven G; Noreika, Norbertas; Norfolk, Olivia; Noriega, Jorge Ari; Norton, David A; Nöske, Nicole M; Nowakowski, A Justin; Numa, Catherine; O'Dea, Niall; O'Farrell, Patrick J; Oduro, William; Oertli, Sabine; Ofori-Boateng, Caleb; Oke, Christopher Omamoke; Oostra, Vicencio; Osgathorpe, Lynne M; Otavo, Samuel Eduardo; Page, Navendu V; Paritsis, Juan; Parra-H, Alejandro; Parry, Luke; Pe'er, Guy; Pearman, Peter B; Pelegrin, Nicolás; Pélissier, Raphaël; Peres, Carlos A; Peri, Pablo L; Persson, Anna S; Petanidou, Theodora; Peters, Marcell K; Pethiyagoda, Rohan S; Phalan, Ben; Philips, T Keith; Pillsbury, Finn C; Pincheira-Ulbrich, Jimmy; Pineda, Eduardo; Pino, Joan; Pizarro-Araya, Jaime; Plumptre, A J; Poggio, Santiago L; Politi, Natalia; Pons, Pere; Poveda, Katja; Power, Eileen F; Presley, Steven J; Proença, Vânia; Quaranta, Marino; Quintero, Carolina; Rader, Romina; Ramesh, B R; Ramirez-Pinilla, Martha P; Ranganathan, Jai; Rasmussen, Claus; Redpath-Downing, Nicola A; Reid, J Leighton; Reis, Yana T; Rey Benayas, José M; Rey-Velasco, Juan Carlos; Reynolds, Chevonne; Ribeiro, Danilo Bandini; Richards, Miriam H; Richardson, Barbara A; Richardson, Michael J; Ríos, Rodrigo Macip; Robinson, Richard; Robles, Carolina A; Römbke, Jörg; Romero-Duque, Luz Piedad; Rös, Matthias; Rosselli, Loreta; Rossiter, Stephen J; Roth, Dana S; Roulston, T'ai H; Rousseau, Laurent; Rubio, André V; Ruel, Jean-Claude; Sadler, Jonathan P; Sáfián, Szabolcs; Saldaña-Vázquez, Romeo A; Sam, Katerina; Samnegård, Ulrika; Santana, Joana; Santos, Xavier; Savage, Jade; Schellhorn, Nancy A; Schilthuizen, Menno; Schmiedel, Ute; Schmitt, Christine B; Schon, Nicole L; Schüepp, Christof; Schumann, Katharina; Schweiger, Oliver; Scott, Dawn M; Scott, Kenneth A; Sedlock, Jodi L; Seefeldt, Steven S; Shahabuddin, Ghazala; Shannon, Graeme; Sheil, Douglas; Sheldon, Frederick H; Shochat, Eyal; Siebert, Stefan J; Silva, Fernando A B; Simonetti, Javier A; Slade, Eleanor M; Smith, Jo; Smith-Pardo, Allan H; Sodhi, Navjot S; Somarriba, Eduardo J; Sosa, Ramón A; Soto Quiroga, Grimaldo; St-Laurent, Martin-Hugues; Starzomski, Brian M; Stefanescu, Constanti; Steffan-Dewenter, Ingolf; Stouffer, Philip C; Stout, Jane C; Strauch, Ayron M; Struebig, Matthew J; Su, Zhimin; Suarez-Rubio, Marcela; Sugiura, Shinji; Summerville, Keith S; Sung, Yik-Hei; Sutrisno, Hari; Svenning, Jens-Christian; Teder, Tiit; Threlfall, Caragh G; Tiitsaar, Anu; Todd, Jacqui H; Tonietto, Rebecca K; Torre, Ignasi; Tóthmérész, Béla; Tscharntke, Teja; Turner, Edgar C; Tylianakis, Jason M; Uehara-Prado, Marcio; Urbina-Cardona, Nicolas; Vallan, Denis; Vanbergen, Adam J; Vasconcelos, Heraldo L; Vassilev, Kiril; Verboven, Hans A F; Verdasca, Maria João; Verdú, José R; Vergara, Carlos H; Vergara, Pablo M; Verhulst, Jort; Virgilio, Massimiliano; Vu, Lien Van; Waite, Edward M; Walker, Tony R; Wang, Hua-Feng; Wang, Yanping; Watling, James I; Weller, Britta; Wells, Konstans; Westphal, Catrin; Wiafe, Edward D; Williams, Christopher D; Willig, Michael R; Woinarski, John C Z; Wolf, Jan H D; Wolters, Volkmar; Woodcock, Ben A; Wu, Jihua; Wunderle, Joseph M; Yamaura, Yuichi; Yoshikura, Satoko; Yu, Douglas W; Zaitsev, Andrey S; Zeidler, Juliane; Zou, Fasheng; Collen, Ben; Ewers, Rob M; Mace, Georgina M; Purves, Drew W; Scharlemann, Jörn P W; Purvis, Andy

    2017-01-01

    The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.

  20. Trophic position and metabolic rate predict the long-term decay process of radioactive cesium in fish: a meta-analysis.

    Directory of Open Access Journals (Sweden)

    Hideyuki Doi

    Full Text Available Understanding the long-term behavior of radionuclides in organisms is important for estimating possible associated risks to human beings and ecosystems. As radioactive cesium (¹³⁷Cs can be accumulated in organisms and has a long physical half-life, it is very important to understand its long-term decay in organisms; however, the underlying mechanisms determining the decay process are little known. We performed a meta-analysis to collect published data on the long-term ¹³⁷Cs decay process in fish species to estimate biological (metabolic rate and ecological (trophic position, habitat, and diet type influences on this process. From the linear mixed models, we found that 1 trophic position could predict the day of maximum ¹³⁷Cs activity concentration in fish; and 2 the metabolic rate of the fish species and environmental water temperature could predict ecological half-lives and decay rates for fish species. These findings revealed that ecological and biological traits are important to predict the long-term decay process of ¹³⁷Cs activity concentration in fish.

  1. ABDOMINAL OBESITY, AN ANTHROPOMETRIC PARAMETER PREDICTING METABOLIC DISORDERS

    Directory of Open Access Journals (Sweden)

    Maricel Castellanos González

    2011-08-01

    Full Text Available Background: Waist circumference perimeter, as an indirect indicator of abdominal obesity, is commonly presented as an essential element in the clinical assessment of obesity. The link between abdominal obesity and insulin resistance is proposed as the core of metabolic syndrome’s pathophysiology and complications. Objective: To determine whether individuals with abdominal obesity present characteristics related to metabolic syndrome’s factors that differ from those observed in individuals with no abdominal obesity. Methods: A comparative analytical study was performed including cases control and design in two different groups. The sample was composed of 98 individuals of both sexes randomly selected out of a universe of 510 workers population at the Medical University of Cienfuegos from September to December 2005. They were all tested as to blood pressure, cholesterol, HDL cholesterol, fasting glucose and triglycerides. Results: Abdominal obesity was found in 30.6% of individuals. It was predominant in females (83.3% older than 40 years. The number of cases of obesity linked to hypertension was similar to the number of cases with low HDL cholesterol (53.3%. Impaired glucose was found in 16.7% of cases. Conclusions: Abdominal obesity is a health problem in the population included in this study and it increases as age does. Individuals with abdominal obesity are exposed to a higher risk of metabolic disorders, such as low levels of HDL cholesterol, high levels of triglycerides and total cholesterol, glucose alterations and hypertension.

  2. When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world

    Science.gov (United States)

    Eric J. Gustafson

    2013-01-01

    Researchers and natural resource managers need predictions of how multiple global changes (e.g., climate change, rising levels of air pollutants, exotic invasions) will affect landscape composition and ecosystem function. Ecological predictive models used for this purpose are constructed using either a mechanistic (process-based) or a phenomenological (empirical)...

  3. Toward a community ecology of landscapes: predicting multiple predator-prey interactions across geographic space.

    Science.gov (United States)

    Schmitz, Oswald J; Miller, Jennifer R B; Trainor, Anne M; Abrahms, Briana

    2017-09-01

    Community ecology was traditionally an integrative science devoted to studying interactions between species and their abiotic environments in order to predict species' geographic distributions and abundances. Yet for philosophical and methodological reasons, it has become divided into two enterprises: one devoted to local experimentation on species interactions to predict community dynamics; the other devoted to statistical analyses of abiotic and biotic information to describe geographic distribution. Our goal here is to instigate thinking about ways to reconnect the two enterprises and thereby return to a tradition to do integrative science. We focus specifically on the community ecology of predators and prey, which is ripe for integration. This is because there is active, simultaneous interest in experimentally resolving the nature and strength of predator-prey interactions as well as explaining patterns across landscapes and seascapes. We begin by describing a conceptual theory rooted in classical analyses of non-spatial food web modules used to predict species interactions. We show how such modules can be extended to consideration of spatial context using the concept of habitat domain. Habitat domain describes the spatial extent of habitat space that predators and prey use while foraging, which differs from home range, the spatial extent used by an animal to meet all of its daily needs. This conceptual theory can be used to predict how different spatial relations of predators and prey could lead to different emergent multiple predator-prey interactions such as whether predator consumptive or non-consumptive effects should dominate, and whether intraguild predation, predator interference or predator complementarity are expected. We then review the literature on studies of large predator-prey interactions that make conclusions about the nature of multiple predator-prey interactions. This analysis reveals that while many studies provide sufficient information

  4. Predicting performance for ecological restoration: A case study using Spartina altemiflora

    Science.gov (United States)

    Travis, S.E.; Grace, J.B.

    2010-01-01

    The success of population-based ecological restoration relies on the growth and reproductive performance of selected donor materials, whether consisting of whole plants or seed. Accurately predicting performance requires an understanding of a variety of underlying processes, particularly gene flow and selection, which can be measured, at least in part, using surrogates such as neutral marker genetic distances and simple latitudinal effects. Here we apply a structural equation modeling approach to understanding and predicting performance in a widespread salt marsh grass, Spartina alterniflora, commonly used for ecological restoration throughout its native range in North America. We collected source materials from throughout this range, consisting of eight clones each from 23 populations, for transplantation to a common garden site in coastal Louisiana and monitored their performance. We modeled performance as a latent process described by multiple indicator variables (e.g., clone diameter, stem number) and estimated direct and indirect influences of geographic and genetic distances on performance. Genetic distances were determined by comparison of neutral molecular markers with those from a local population at the common garden site. Geographic distance metrics included dispersal distance (the minimum distance over water between donor and experimental sites) and latitude. Model results indicate direct effects of genetic distance and latitude on performance variation among the donor sites. Standardized effect strengths indicate that performance was roughly twice as sensitive to variation in genetic distance as to latitudinal variation. Dispersal distance had an indirect influence on performance through effects on genetic distance, indicating a typical pattern of genetic isolation by distance. Latitude also had an indirect effect on genetic distance through its linear relationship with dispersal distance. Three performance indicators had significant loadings on

  5. A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Hojung Nam

    2014-09-01

    Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

  6. Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates

    DEFF Research Database (Denmark)

    Glazier, Douglas S.; Hirst, Andrew G.; Atkinson, D.

    2016-01-01

    Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts...... in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR ..., are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces...

  7. Predicting growth conditions from internal metabolic fluxes in an in-silico model of E. coli.

    Directory of Open Access Journals (Sweden)

    Viswanadham Sridhara

    Full Text Available A widely studied problem in systems biology is to predict bacterial phenotype from growth conditions, using mechanistic models such as flux balance analysis (FBA. However, the inverse prediction of growth conditions from phenotype is rarely considered. Here we develop a computational framework to carry out this inverse prediction on a computational model of bacterial metabolism. We use FBA to calculate bacterial phenotypes from growth conditions in E. coli, and then we assess how accurately we can predict the original growth conditions from the phenotypes. Prediction is carried out via regularized multinomial regression. Our analysis provides several important physiological and statistical insights. First, we show that by analyzing metabolic end products we can consistently predict growth conditions. Second, prediction is reliable even in the presence of small amounts of impurities. Third, flux through a relatively small number of reactions per growth source (∼10 is sufficient for accurate prediction. Fourth, combining the predictions from two separate models, one trained only on carbon sources and one only on nitrogen sources, performs better than models trained to perform joint prediction. Finally, that separate predictions perform better than a more sophisticated joint prediction scheme suggests that carbon and nitrogen utilization pathways, despite jointly affecting cellular growth, may be fairly decoupled in terms of their dependence on specific assortments of molecular precursors.

  8. Predicting the potential geographical distribution of Rhodnius neglectus (Hemiptera, Reduviidae) based on ecological niche modeling.

    Science.gov (United States)

    Gurgel-Goncalves, Rodrigo; Cuba, César Augusto Cuba

    2009-07-01

    Rhodnius neglectus is frequently found in palm trees and bird nests in sylvatic environments. However, adult specimens infected by Trypanosoma cruzi have been invading houses in central Brazil. Analyzing and predicting the geographical distribution of this species may improve vector surveillance strategies for Chagas disease. Ecological niche modeling using the genetic algorithm for rule-set production (GARP) was applied to predict the geographical distribution of R. neglectus from occurrence records and a set of 23 predictor variables (e.g., temperature, precipitation, altitude, and vegetation). Additionally, the geographical distribution of R. neglectus was compared with the geographical distribution of four species of palm trees and two species of birds from the study region. The models were able to predict, with high probability, the occurrence of R. neglectus as a regular (although nonendemic) species of the Cerrado biome in central Brazil. Caatinga, Amazonian savanna, Pantanal, and the Bolivian Chaco appear as areas with lower probabilities of potential occurrence for the species. A great overlap was observed between the distribution of R. neglectus, palm trees (Acrocomia aculeata and Syagrus oleracea), and birds (Phacellodomus ruber and Pseudoseisura cristata). By including new records for R. neglectus (from both sylvatic and domestic environments), our study showed a distribution increase toward the west and northeast areas of Brazil in the "diagonal of open/dry ecoregions of South America". These results should aid Chagas disease vector surveillance programs, given that household invasion by Rhodnius species maintains the risk of disease transmission and limits control strategies.

  9. The Metabolic Inhibition Model Which Predicts the Intestinal Absorbability and Metabolizability of Drug: Theory and Experiment

    Directory of Open Access Journals (Sweden)

    Mizuma Takashi

    1998-01-01

    Full Text Available The intestinal absorption of analgesic peptides (leucine enkephalin and kyotorphin and modified peptides in rat were studied. Although these peptides were not absorbed, the absorbability (absorption clearance of these peptides were increased in the presence of peptidase inhibitors. In order to kinetically analyze these phenomena, we proposed the metabolic inhibition model, which incorporated the metabolic clearance (metabolizability with the absorption clearance. Metabolic activity was determined with intestinal homogenates. The higher the metabolic clearance was, the lower was the absorption clearance. The relationships between the absorption clearance and the metabolic clearance of the experimental data as well as of the theoretical values were hyperbolic. This model predicted the maximum absorption clearances of cellobiose-coupled leucine enkephalin (0.654 &mgr;l/min/cm and kyotorphin (0.247 &mgr;l/min/cm. Details of the experimental methods are described.

  10. Poor breakfast habits in adolescence predict the metabolic syndrome in adulthood.

    Science.gov (United States)

    Wennberg, Maria; Gustafsson, Per E; Wennberg, Patrik; Hammarström, Anne

    2015-01-01

    To analyse whether poor breakfast habits in adolescence predict the metabolic syndrome and its components in adulthood. Previous studies suggest that regular breakfast consumption improves metabolic parameters. Prospective. Breakfast habits and other lifestyle variables at age 16 years were assessed from questionnaires. Poor breakfast habits were defined as skipping breakfast or only drinking or eating something sweet. At age 43 years, the effective sample consisted of 889 participants defined as having the metabolic syndrome or not, using the International Diabetes Federation criteria. Logistic regression was used to calculate odds ratios and confidence intervals. The Northern Swedish Cohort, a longitudinal population-based cohort with 27-year follow-up. Adolescents (age 16 years). Prevalence of the metabolic syndrome at age 43 years was 27·0 %. Of the participants, 9·9 % were classified with poor breakfast habits at age 16 years. Adjusted odds for the metabolic syndrome at age 43 years was OR = 1·68 (95 % CI 1·01, 2·78) for those with poor breakfast habits at age 16 years compared with breakfast eaters. Looking at the metabolic syndrome components, poor breakfast habits at age 16 years were associated with central obesity (OR = 1·71; 95 % CI 1·00, 2·92) and high fasting glucose (OR = 1·75; 95 % CI 1·01, 3·02) at age 43 years, even after multivariate adjustments. Poor breakfast habits in adolescence predicted the metabolic syndrome in adulthood. Of the metabolic syndrome components, poor breakfast habits in adolescence predicted central obesity and high fasting glucose in adulthood. Further research is needed to fully understand the relationship between early breakfast habits and adult metabolic syndrome.

  11. Uric Acid Levels Can Predict Metabolic Syndrome and Hypertension in Adolescents: A 10-Year Longitudinal Study

    OpenAIRE

    Sun, Hai-Lun; Pei, Dee; Lue, Ko-Huang; Chen, Yen-Lin

    2015-01-01

    The relationships between uric acid and chronic disease risk factors such as metabolic syndrome, type 2 diabetes mellitus, and hypertension have been studied in adults. However, whether these relationships exist in adolescents is unknown. We randomly selected 8,005 subjects who were between 10 to 15 years old at baseline. Measurements of uric acid were used to predict the future occurrence of metabolic syndrome, hypertension, and type 2 diabetes. In total, 5,748 adolescents were enrolled and ...

  12. Toward ecologically realistic predictions of species distributions: A cross-time example from tropical montane cloud forests.

    Science.gov (United States)

    Guevara, Lázaro; Gerstner, Beth E; Kass, Jamie M; Anderson, Robert P

    2018-04-01

    There is an urgent need for more ecologically realistic models for better predicting the effects of climate change on species' potential geographic distributions. Here we build ecological niche models using MAXENT and test whether selecting predictor variables based on biological knowledge and selecting ecologically realistic response curves can improve cross-time distributional predictions. We also evaluate how the method chosen for extrapolation into nonanalog conditions affects the prediction. We do so by estimating the potential distribution of a montane shrew (Mammalia, Soricidae, Cryptotis mexicanus) at present and the Last Glacial Maximum (LGM). Because it is tightly associated with cloud forests (with climatically determined upper and lower limits) whose distributional shifts are well characterized, this species provides clear expectations of plausible vs. implausible results. Response curves for the MAXENT model made using variables selected via biological justification were ecologically more realistic compared with those of the model made using many potential predictors. This strategy also led to much more plausible geographic predictions for upper and lower elevational limits of the species both for the present and during the LGM. By inspecting the modeled response curves, we also determined the most appropriate way to extrapolate into nonanalog environments, a previously overlooked factor in studies involving model transfer. This study provides intuitive context for recommendations that should promote more realistic ecological niche models for transfer across space and time. © 2017 John Wiley & Sons Ltd.

  13. Ecologically diverse and distinct neighbourhoods trigger persistent phenotypic consequences, and amine metabolic profiling detects them

    Czech Academy of Sciences Publication Activity Database

    Hennion, F.; Litrico, I.; Bartish, Igor V.; Weigelt, A.; Bouchereau, A.; Prinzing, A.

    2016-01-01

    Roč. 104, č. 1 (2016), s. 125-137 ISSN 0022-0477 Grant - others:AV ČR(CZ) Fellowship J. E. Purkyně Institutional support: RVO:67985939 Keywords : community phylogenetics * microevolution * metabolome Subject RIV: EH - Ecology, Behaviour Impact factor: 5.813, year: 2016

  14. A Cutoff for Age at Menarche Predicting Metabolic Syndrome in Egyptian Overweight/Obese Premenopausal Women.

    Science.gov (United States)

    Elsehely, Ibrahim; Abdel Hafez, Hala; Ghonem, Mohammed; Fathi, Ali; Elzehery, Rasha

    2017-04-01

    Previous studies showed that early age at menarche is associated with increased risk of metabolic syndrome. However, the definition of early menarche at these studies was based on background data in the communities at which these studies was carried on. The aim of this work is to determine a cutoff for age at menarche discriminating presence or absence of metabolic syndrome in overweight/obese premenopausal women. This study included 204 overweight/obese women. Metabolic syndrome was defined according to NCEP-ATP III (National Cholesterol Education Program Adult Treatment Panel III) criteria. Of a total 204 participants, 82 (40.2%) had metabolic syndrome. By using receiver operating characteristic analysis, age at menarche ≤12.25 year discriminated individuals with from those without metabolic syndrome. The area under the curve was 0.76 (95% confidence interval, 0.70 to 0.83). Sensitivity, specificity, negative predictive value, and positive predictive value were 82%, 70%, 85%, and 64%, respectively. Age at menarche ≤12.25 years predicts the presence of metabolic syndrome in overweight/obese women. Copyright © 2017 Korean Diabetes Association.

  15. Recent Advances of Computational Modeling for Predicting Drug Metabolism: A Perspective.

    Science.gov (United States)

    Kar, Supratik; Leszczynski, Jerzy

    2017-01-01

    Absorption, Distribution, Metabolism, Excretion (ADME) properties along with drug induced adverse effects are the major reasons for the late stage failure of drug candidates as well as the cause for the expensive withdrawal of many approved drugs from the market. Considering the adverse effects of drugs, metabolism factor has great importance in medicinal chemistry and clinical pharmacology because it influences the deactivation, activation, detoxification and toxification of drugs. Computational methods are effective approaches to reduce the number of safety issues by analyzing possible links between chemical structures and metabolism followed by adverse effects, as they serve the integration of information on several levels to enhance the reliability of outcomes. In silico profiling of drug metabolism can help progress only those molecules along the discovery chain that is less likely to fail later in the drug discovery process. This positively impacts the very high costs of drug discovery and development. Understanding the science behind computational tools, their opportunities, and limitations is essential to make a true influence on drug discovery at different levels. If applied in a scientifically consequential way, computational tools may improve the capability to identify and evaluate potential drug molecules considering pharmacokinetic properties of drugs. Herein, current trends in computational modeling for predicting drug metabolism are reviewed highlighting new computational tools for drug metabolism prediction followed by reporting large and integrated databases of approved drugs associated with diverse metabolism issues. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  16. Bacterial community composition and predicted functional ecology of sponges, sediment and seawater from the thousand islands reef complex, West Java, Indonesia.

    Science.gov (United States)

    de Voogd, Nicole J; Cleary, Daniel F R; Polónia, Ana R M; Gomes, Newton C M

    2015-04-01

    In the present study, we assessed the composition of Bacteria in four biotopes namely sediment, seawater and two sponge species (Stylissa massa and Xestospongia testudinaria) at four different reef sites in a coral reef ecosystem in West Java, Indonesia. In addition to this, we used a predictive metagenomic approach to estimate to what extent nitrogen metabolic pathways differed among bacterial communities from different biotopes. We observed marked differences in bacterial composition of the most abundant bacterial phyla, classes and orders among sponge species, water and sediment. Proteobacteria were by far the most abundant phylum in terms of both sequences and Operational Taxonomic Units (OTUs). Predicted counts for genes associated with the nitrogen metabolism suggested that several genes involved in the nitrogen cycle were enriched in sponge samples, including nosZ, nifD, nirK, norB and nrfA genes. Our data show that a combined barcoded pyrosequencing and predictive metagenomic approach can provide novel insights into the potential ecological functions of the microbial communities. Not only is this approach useful for our understanding of the vast microbial diversity found in sponges but also to understand the potential response of microbial communities to environmental change. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. Predicting geographic and ecological distributions of triatomine species in the southern Mexican state of Puebla using ecological niche modeling.

    Science.gov (United States)

    Sandoval-Ruiz, C A; Zumaquero-Rios, J L; Rojas-Soto, O R

    2008-05-01

    We analyzed the geographic distribution using ecological niche modeling of three species of triatomines distributed in the Mexican state of Puebla. Punctual records were gathered for a period of 5 yr of fieldwork sampling. We used the genetic algorithm for rule-set production (GARP) to achieve the potential distribution of the ecological niche of triatomines. The models showed that Triatoma barberi and Meccus pallidipennis are sympatric and widely distributed in the central-southern part of the state, whereas T. dimidata is restricted to the northern mountains of the state with no overlapping among other species, M. bassolsae was not modeled because of the scarce number of locality records. We highlighted the warm and dry conditions in southern Puebla as important potential areas for triatomine presence. Finally, we correlated the species potential presence with the human population at risk of acquiring Chagas disease by vector-borne transmission; it is showed that M. pallidipennis presents the highest values of both ecological and poverty risk scenarios representing the main potential vector in the state.

  18. The genome of the diatom Thalassiosira pseudonana: Ecology,evolution, and metabolism

    Energy Technology Data Exchange (ETDEWEB)

    Ambrust, E.V.; Berges, J.; Bowler, C.; Green, B.; Martinez, D.; Putnam, N.; Zhou, S.; Allen, A.; Apt, K.; Bechner, M.; Brzezinski, M.; Chaal, B.; Chiovitti, A.; Davis, A.; Goodstein, D.; Hadi, M.; Hellsten,U.; Hildebrand, M.; Jenkins, B.; Jurka, J.; Kapitonov, V.; Kroger, N.; Lau, W.; Lane, T.; Larimer, F.; Lippmeier, J.; Lucas, S.; Medina, M.; Montsant, A.; Obornik, M.; Parker, M. Schnitzler; Palenik, B.; Pazour,G.; Richardson, P.; Rynearson, T.; Saito, M.; Schwartz, D.; Thamatrakoln,K.; Valentin, K.; Vardi, A.; Wilkerson, F.; Rokhsar, D.; Vardi, A.; Wilkerson, F.P.; Rokhsar, D.S.

    2004-09-01

    Diatoms are unicellular algae with plastids acquired by secondary endosymbiosis. They are responsible for {approx}20% of global carbon fixation. We report the 34 Mbp draft nuclear genome of the marine diatom, Thalassiosira pseudonana and its 129 Kbp plastid and 44 Kbp mitochondrial genomes. Sequence and optical restriction mapping revealed 24 diploid nuclear chromosomes. We identified novel genes for silicic acid transport and formation of silica-based cell walls, high-affinity iron uptake, biosynthetic enzymes for several types of polyunsaturated fatty acids, utilization of a range of nitrogenous compounds and a complete urea cycle, all attributes that allow diatoms to prosper in the marine environment. Diatoms are unicellular, photosynthetic, eukaryotic algae found throughout the world's oceans and freshwater systems. They form the base of short, energetically-efficient food webs that support large-scale coastal fisheries. Photosynthesis by marine diatoms generates as much as 40% of the 45-50 billion tonnes of organic carbon produced each year in the sea (1), and their role in global carbon cycling is predicted to be comparable to that of all terrestrial rainforests combined (2, 3). Over geological time, diatoms may have influenced global climate by changing the flux of atmospheric carbon dioxide into the oceans (4). A defining feature of diatoms is their ornately patterned silicified cell wall or frustule, which displays species-specific nano-structures of such fine detail that diatoms have long been used to test the resolution of optical microscopes. Recent attention has focused on biosynthesis of these nano-structures as a paradigm for future silica nanotechnology (5). The long history (over 180 million years) and dominance of diatoms in the oceans is reflected by their contributions to vast deposits of diatomite, most cherts and a significant fraction of current petroleum reserves (6). As photosynthetic heterokonts, diatoms reflect a fundamentally

  19. Integrating understanding of hydrology, geomorphology and ecology to better predict periphyton abundance in New Zealand rivers

    Science.gov (United States)

    Hoyle, Jo; Kilroy, Cathy; Hicks, Murray

    2015-04-01

    Periphyton (the algae dominated community that grows on the bed of rivers) provide a rich food source for the upper trophic levels of stream ecosystems and can also provide an important ecological service by removing dissolved nutrients and contaminants from the flow. However, in excess, periphyton can have negative effects on habitat quality, water chemistry and biodiversity, and can reduce recreation and aesthetic values. The abundance of periphyton in rivers is influenced by a number of factors, but the two key factors that can be directly influenced by human activities are flow regime and nutrient concentrations. River managers in New Zealand are required to set objectives for periphyton abundance that meet or exceed national bottom lines, and they then need to set limits on freshwater quality and quantity in their region to ensure these objectives are met. Consequently, the ability to predict periphyton abundance under different conditions is crucial for management of rivers to protect ecological and other values. Establishing quantitative relationships between periphyton abundance, hydrologic regimes and nutrient concentrations has proven to be difficult but remains an urgent priority in New Zealand. A common index for predicting periphyton abundance has been the frequency of floods greater than 3 times the median flow (FRE3), and this has been successful on a regional average but can be quite unreliable on a site-specific basis. This stems largely from our limited ability to transform flow data into ecologically meaningful physical processes that directly affect periphyton removal (e.g., drag, abrasion, bed movement). The research we will present examines whether geomorphic variables, such as frequency of bed movement, are useful co-predictors in periphyton abundance-flow-nutrient relationships. We collected data on channel topography and bed material size for 20 reaches in the Manawatu-Wanganui Region which have at least 5 years of flow, nutrient

  20. Sex differences in the prediction of metabolic burden from physiological responses to stress.

    Science.gov (United States)

    Gentile, Christina; Dragomir, Anda Ioana; Solomon, Crina; Nigam, Anil; D'Antono, Bianca

    2015-02-01

    Heightened or prolonged physiological responses to stress may contribute to the development or progression of metabolic abnormalities. This study aims to examine the prospective relationships between stress responses and metabolic burden, and to determine whether age and/or sex moderate these relationships. One hundred ninety-nine healthy men and women (M(age) = 41 ± 11.5) were exposed to four stressors while blood pressure, heart rate, and heart rate variability were obtained. Residual change scores for reactivity (stress - baseline) and recovery (post-stress - baseline) scores were computed. Metabolic burden refers to the number of metabolic parameters for which participants were in the highest quartile (lowest for high-density lipoprotein cholesterol) for their sex. Metabolic burden was reassessed in 136 participants 3 years later. Greater parasympathetic withdrawal in response to stress was associated with increased metabolic burden, though this was evident mostly in men. In women, dampened autonomic responses to stress were associated with higher metabolic burden. Cardiac autonomic responses to stress predict future metabolic abnormalities, though the direction of effect differs according to sex.

  1. Does basal metabolic rate predict weight gain?12

    Science.gov (United States)

    Anthanont, Pimjai; Jensen, Michael D

    2016-01-01

    Background: Some previous studies have indicated that a low basal metabolic rate (BMR) is an independent predictor of future weight gain, but low rates of follow-up and highly select populations may limit the ability to generalize the results. Objective: We assessed whether adults with a low BMR gain more weight than do adults with a high BMR who are living in a typical Western environment. Design: We extracted BMR, body-composition, demographic, and laboratory data from electronic databases of 757 volunteers who were participating in our research protocols at the Mayo Clinic between 1995 and 2012. Research study volunteers were always weight stable, had no acute illnesses and no confounding medication use, and were nonsmokers. The top and bottom 15th percentiles of BMR, adjusted for fat-free mass (FFM), fat mass, age, and sex, were identified. Follow-up electronic medical record system data were available for 163 subjects, which allowed us to determine their subsequent weight changes for ≥3 y (mean: ∼9.7 y). Results: By definition, the BMR was different in the high-BMR group (2001 ± 317 kcal/d; n = 86) than in the low-BMR group (1510 ± 222 kcal/d; n = 77), but they were comparable with respect to age, body mass index, FFM, and fat mass. Rates of weight gain were not greater in the bottom BMR group (0.3 ± 1.0 kg/y) than in the top BMR group (0.5 ± 1.5 kg/y) (P = 0.17). Conclusion: Adults with low BMRs did not gain more weight than did adults with high BMRs, implying that habitual differences in food intake or activity counterbalance variations in BMR as a risk factor for weight gain in a typical Western population. PMID:27581474

  2. Predicting Sexual Revictimization in Childhood and Adolescence: A Longitudinal Examination Using Ecological Systems Theory.

    Science.gov (United States)

    Pittenger, Samantha L; Pogue, Jessica K; Hansen, David J

    2018-05-01

    A substantial proportion of sexual abuse victims report repeat sexual victimization within childhood or adolescence; however, there is limited understanding of factors contributing to revictimization for youth. Thus, the present study examined predictors of sexual revictimization prior to adulthood using ecological systems theory. Records of 1,915 youth presenting to a Child Advocacy Center (CAC) were reviewed to identify individual, familial, and community factors as well as initial abuse characteristics associated with risk for revictimization. Results showed that 11.1% of youth re-presented to the CAC for sexual revictimization. At the individual level, younger children, girls, ethnoracial minority youth, and those with an identified mental health problem were most likely to experience revictimization. Interpersonal factors that increased vulnerability included the presence of a noncaregiving adult in the home, being in mental health treatment, and domestic violence in the family. Community-level factors did not predict revictimization. When factors at all levels were examined in conjunction, however, only individual-level factors significantly predicted the risk for revictimization. Findings from this study provide valuable information for CACs when assessing risk for re-report of sexual abuse and add to the field's understanding of revictimization within childhood.

  3. Ecological niche modeling for predicting the potential risk areas of severe fever with thrombocytopenia syndrome.

    Science.gov (United States)

    Du, Zhaohui; Wang, Zhiqiang; Liu, Yunxia; Wang, Hao; Xue, Fuzhong; Liu, Yanxun

    2014-09-01

    Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by a novel bunyavirus. The spatial distribution has continued to expand, while the areas at potential high risk of SFTS have, to date, remained unclear. Using ecological factors as predictors, the MaxEnt model was first trained based on the locations of human SFTS occurrence in Shandong Province. The risk prediction map of China was then created by projecting the training model onto the whole country. The performance of the model was assessed using the known locations of disease occurrence in China. The key environmental factors affecting SFTS occurrence were temperature, precipitation, land cover, normalized difference vegetation index (NDVI), and duration of sunshine. The risk prediction maps suggested that central, southwestern, northeastern, and the eastern coast of China are potential areas at high risk of SFTS. The potential high risk SFTS areas are distributed widely in China. The epidemiological surveillance system should be enhanced in these high risk regions. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. Quantitative structure-activity relationships and ecological risk assessment: an overview of predictive aquatic toxicology research.

    Science.gov (United States)

    Bradbury, S P

    1995-09-01

    In the field of aquatic toxicology, quantitative structure-activity relationships (QSARs) have developed as scientifically credible tools for predicting the toxicity of chemicals when little or no empirical data are available. A fundamental understanding of toxicological principles has been considered an important component to the acceptance and application of QSAR approaches as biologically relevant in ecological risk assessments. As a consequence, there has been an evolution of QSAR development and application from that of a chemical-class perspective to one that is more consistent with assumptions regarding modes of toxic action. In this review, techniques to assess modes of toxic action from chemical structure are discussed, with consideration that toxicodynamic knowledge bases must be clearly defined with regard to exposure regimes, biological models/endpoints and compounds that adequately span the diversity of chemicals anticipated for future applications. With such knowledge bases, classification systems, including rule-based expert systems, have been established for use in predictive aquatic toxicology applications. The establishment of QSAR techniques that are based on an understanding of toxic mechanisms is needed to provide a link to physiologically based toxicokinetic and toxicodynamic models, which can provide the means to extrapolate adverse effects across species and exposure regimes.

  5. Biochemical trade-offs: evidence for ecologically linked secondary metabolism of the sponge Oscarella balibaloi.

    Directory of Open Access Journals (Sweden)

    Julijana Ivanisevic

    Full Text Available Secondary metabolite production is assumed to be costly and therefore the resource allocation to their production should be optimized with respect to primary biological functions such as growth or reproduction. Sponges are known to produce a great diversity of secondary metabolites with powerful biological activities that may explain their domination in some hard substrate communities both in terms of diversity and biomass. Oscarella balibaloi (Homoscleromorpha is a recently described, highly dynamic species, which often overgrows other sessile marine invertebrates. Bioactivity measurements (standardized Microtox assay and metabolic fingerprints were used as indicators of the baseline variations of the O. balibaloi secondary metabolism, and related to the sponge reproductive effort over two years. The bioactivity showed a significant seasonal variation with the lowest values at the end of spring and in early summer followed by the highest bioactivity in the late summer and autumn. An effect of the seawater temperature was detected, with a significantly higher bioactivity in warm conditions. There was also a tendency of a higher bioactivity when O. balibaloi was found overgrowing other sponge species. Metabolic fingerprints revealed the existence of three principal metabolic phenotypes: phenotype 1 exhibited by a majority of low bioactive, female individuals, whereas phenotypes 2 and 3 correspond to a majority of highly bioactive, non-reproductive individuals. The bioactivity was negatively correlated to the reproductive effort, minimal bioactivities coinciding with the period of embryogenesis and larval development. Our results fit the Optimal Defense Theory with an investment in the reproduction mainly shaping the secondary metabolism variability, and a less pronounced influence of other biotic (species interaction and abiotic (temperature factors.

  6. Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast.

    Science.gov (United States)

    Wang, Zhuo; Danziger, Samuel A; Heavner, Benjamin D; Ma, Shuyi; Smith, Jennifer J; Li, Song; Herricks, Thurston; Simeonidis, Evangelos; Baliga, Nitin S; Aitchison, John D; Price, Nathan D

    2017-05-01

    Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.

  7. Role of androgen ratios in the prediction of the metabolic phenotype in polycystic ovary syndrome.

    Science.gov (United States)

    Minooee, Sonia; Ramezani Tehrani, Fahimeh; Tohidi, Maryam; Azizi, Fereidoun

    2017-05-01

    To identify the androgen ratio that best predicts insulin resistance and metabolic syndrome among women with polycystic ovary syndrome (PCOS). Data for 180 women with PCOS and 180 healthy controls were extracted from two previous studies in Iran (conducted during 2008-2010 and 2011-2013). The diagnosis of PCOS was based on the Rotterdam criteria. The serum concentration of different androgens was measured. Receiver operating characteristic curve analysis was used to assess the ability of various androgen ratios to predict insulin resistance and metabolic syndrome. Among women with PCOS, the testosterone-to-androstenedione ratio was the best predictor of insulin resistance (sensitivity 0.83, specificity 0.42) and metabolic syndrome (sensitivity 0.85, specificity 0.70). Among healthy controls, the ratio of free androgen index to testosterone was the best predictor of insulin resistance (sensitivity 0.84, specificity 0.33) and metabolic syndrome (sensitivity 0.91, specificity 0.17). The prediction of insulin resistance and metabolic syndrome among women with PCOS was best accomplished with the testosterone-to-androstenedione ratio. © 2017 International Federation of Gynecology and Obstetrics.

  8. Metabolic response at repeat PET/CT predicts pathological response to neoadjuvant chemotherapy in oesophageal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Gillies, R.S. [Oxford Cancer and Haematology Centre, Department of Oncology, Oxford (United Kingdom); Oxford Cancer and Haematology Centre, Department of Oesophagogastric Surgery, Oxford (United Kingdom); NIHR Biomedical Research Centre, Oxford (United Kingdom); Middleton, M.R. [Oxford Cancer and Haematology Centre, Department of Oncology, Oxford (United Kingdom); NIHR Biomedical Research Centre, Oxford (United Kingdom); Blesing, C.; Patel, K.; Warner, N. [Oxford Cancer and Haematology Centre, Department of Oncology, Oxford (United Kingdom); Marshall, R.E.K.; Maynard, N.D. [Oxford Cancer and Haematology Centre, Department of Oesophagogastric Surgery, Oxford (United Kingdom); Bradley, K.M. [Oxford Cancer and Haematology Centre, Department of Radiology, Oxford (United Kingdom); Gleeson, F.V. [Oxford Cancer and Haematology Centre, Department of Radiology, Oxford (United Kingdom); NIHR Biomedical Research Centre, Oxford (United Kingdom)

    2012-09-15

    Reports have suggested that a reduction in tumour 18F-fluorodeoxyglucose (FDG) uptake on positron emission tomography (PET) examination during or after neoadjuvant chemotherapy may predict pathological response in oesophageal cancer. Our aim was to determine whether metabolic response predicts pathological response to a standardised neoadjuvant chemotherapy regimen within a prospective clinical trial. Consecutive patients staged with potentially curable oesophageal cancer who underwent treatment within a non-randomised clinical trial were included. A standardised chemotherapy regimen (two cycles of oxaliplatin and 5-fluorouracil) was used. PET/CT was performed before chemotherapy and repeated 24-28 days after the start of cycle 2. Forty-eight subjects were included: mean age 65 years; 37 male. Using the median percentage reduction in SUV{sub max} (42%) to define metabolic response, pathological response was seen in 71% of metabolic responders (17/24) compared with 33% of non-responders (8/24; P = 0.009, sensitivity 68%, specificity 70%). Pathological response was seen in 81% of subjects with a complete metabolic response (13/16) compared with 38% of those with a less than complete response (12/32; P = 0.0042, sensitivity 52%, specificity 87%). There was no significant histology-based effect. There was a significant association between metabolic response and pathological response; however, accuracy in predicting pathological response was relatively low. (orig.)

  9. Metabolism of oxycodone in human hepatocytes from different age groups and prediction of hepatic plasma clearance

    Directory of Open Access Journals (Sweden)

    Timo eKorjamo

    2012-01-01

    Full Text Available Oxycodone is commonly used to treat severe pain in adults and children. It is extensively metabolized in the liver in adults, but the maturation of metabolism is not well understood. Our aim was to study the metabolism of oxycodone in cryopreserved human hepatocytes from different age groups (3 days, 2 and 5 months, 4 years, adult pool and predict hepatic plasma clearance of oxycodone using these data. Oxycodone (0.1, 1 and 10 µM was incubated with hepatocytes for 4 hours, and 1 µM oxycodone also with CYP3A inhibitor ketoconazole (1 µM. Oxycodone and noroxycodone concentrations were determined at several time points with liquid chromatography-mass spectrometry. In vitro clearance of oxycodone was used to predict hepatic plasma clearance, using the well-stirred model and published physiological parameters. Noroxycodone was the major metabolite in all batches and ketoconazole inhibited the metabolism markedly in most cases. A clear correlation between in vitro oxycodone clearance and CYP3A4 activity was observed. The predicted hepatic plasma clearances were typically much lower than the published median total plasma clearance from pharmacokinetic studies. In general, this in vitro to in vivo extrapolation method provides valuable information on the maturation of oxycodone metabolism that can be utilized in the design of clinical pharmacokinetic studies in infants and young children.

  10. Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

    Science.gov (United States)

    Biggs, Matthew B; Papin, Jason A

    2017-03-01

    Genome-scale metabolic network reconstructions (GENREs) are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA). We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

  11. Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

    Directory of Open Access Journals (Sweden)

    Matthew B Biggs

    2017-03-01

    Full Text Available Genome-scale metabolic network reconstructions (GENREs are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA. We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

  12. Basal metabolic rate in free-living tropical birds: the influence of phylogenetic, behavioral, and ecological factors.

    Science.gov (United States)

    Bushuev, Andrey; Tolstenkov, Oleg; Zubkova, Ekaterina; Solovyeva, Eugenia; Kerimov, Anvar

    2018-02-01

    The majority of our knowledge of avian energetics is based on studies of birds from temperate and high latitudes. Using the largest existing sample of wild-caught Old World tropical species, we showed that birds from Southern Vietnam had lower basal metabolic rate (BMR) than temperate species. The strongest dissimilarity between tropical and temperate species was the low scaling exponent in the allometric relation between BMR and body mass in tropical birds (the regression slope was 0.573). The passerine migrants to temperate and high latitudes had higher BMR than tropical sedentary passerines. Body mass alone accounted for 93% of the variation in BMR (body mass ranged from 5 to 252 g). Contrary to some other studies, we did not find evidence besides the above mentioned that phylogeny, taxonomy, behavior, or ecology have a significant influence on BMR variation among tropical birds.

  13. Basal metabolic rate in free-living tropical birds: the influence of phylogenetic, behavioral, and ecological factors

    Science.gov (United States)

    Tolstenkov, Oleg; Zubkova, Ekaterina; Solovyeva, Eugenia; Kerimov, Anvar

    2018-01-01

    Abstract The majority of our knowledge of avian energetics is based on studies of birds from temperate and high latitudes. Using the largest existing sample of wild-caught Old World tropical species, we showed that birds from Southern Vietnam had lower basal metabolic rate (BMR) than temperate species. The strongest dissimilarity between tropical and temperate species was the low scaling exponent in the allometric relation between BMR and body mass in tropical birds (the regression slope was 0.573). The passerine migrants to temperate and high latitudes had higher BMR than tropical sedentary passerines. Body mass alone accounted for 93% of the variation in BMR (body mass ranged from 5 to 252 g). Contrary to some other studies, we did not find evidence besides the above mentioned that phylogeny, taxonomy, behavior, or ecology have a significant influence on BMR variation among tropical birds. PMID:29492036

  14. Ecological Models to Predict and Test the Effects of Chemical Stressors: Integration across 2 EPA STAR cooperative agreements

    Science.gov (United States)

    Accessible tools to quantify adverse outcomes pathways (AOPs) that can predict the ecological effects of chemicals and other stressors are a major goal of Chemical Safety and Sustainability research within US EPA’s Office of Research and Development. To address this goal, w...

  15. Diastereomer- and enantiomer-specific accumulation, depuration, bioisomerization, and metabolism of hexabromocyclododecanes (HBCDs) in two ecologically different species of earthworms.

    Science.gov (United States)

    Li, Bing; Yao, Tianqi; Sun, Hongwen; Zhang, Yanwei; Yang, Jirui

    2016-01-15

    In this study, two ecological types of earthworms were exposed to soil samples that were artificially contaminated with individual hexabromocyclododecane (HBCD) diastereomers (α-, β-, and γ-HBCDs) to investigate the bioaccumulation, depuration, enantiomer selectivity and isomerization of HBCDs in earthworms. The uptake rate constant (ku), bioaccumulation factor (BAF), biota soil accumulation factor (BSAF), and half-life (t1/2) for the α-HBCD were the highest among the three diastereomers. The bioaccumulation parameters of the three diastereoisomers differed between the two ecologically different species of earthworms. The BSAF values of α- and γ-HBCDs were substantially higher in Eisenia fetida than those in Metaphire guillelmi, with the higher lipid and protein contents in E. fetida as the primary reason for this difference. The other processes, such as uptake, depuration, metabolism and isomerization, also differed between the two species and led to a difference in the bioaccumulation of β-HBCD. The β- and γ-HBCDs were bioisomerized to α-HBCD in the earthworms, but to a greater extent in E. fetida. The highest BSAF, t1/2 of α-HBCD and the bioisomerization of β- and γ-HBCDs to α-HBCD might explain in part why α-HBCD was the dominant isomer in biota samples. Most of the enantiomer fractions (EFs) for the three HBCD diastereoisomers in the earthworms were different from those in standard samples (p<0.05), indicating that enantiomer selectivity occurred. Moreover, the trends and extent of the enantioselectivity were different between the two species. Additionally, the EFs of α-HBCD that was bioisomerized from β- or γ-isomers were also different from those in the standards (p<0.05), which likely reflect the integration of several processes, such as enantioselective isomerization and the subsequent selective metabolism of the produced α-HBCD or selective excretion of the enantiomers. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Computational modeling to predict nitrogen balance during acute metabolic decompensation in patients with urea cycle disorders.

    Science.gov (United States)

    MacLeod, Erin L; Hall, Kevin D; McGuire, Peter J

    2016-01-01

    Nutritional management of acute metabolic decompensation in amino acid inborn errors of metabolism (AA IEM) aims to restore nitrogen balance. While nutritional recommendations have been published, they have never been rigorously evaluated. Furthermore, despite these recommendations, there is a wide variation in the nutritional strategies employed amongst providers, particularly regarding the inclusion of parenteral lipids for protein-free caloric support. Since randomized clinical trials during acute metabolic decompensation are difficult and potentially dangerous, mathematical modeling of metabolism can serve as a surrogate for the preclinical evaluation of nutritional interventions aimed at restoring nitrogen balance during acute decompensation in AA IEM. A validated computational model of human macronutrient metabolism was adapted to predict nitrogen balance in response to various nutritional interventions in a simulated patient with a urea cycle disorder (UCD) during acute metabolic decompensation due to dietary non-adherence or infection. The nutritional interventions were constructed from published recommendations as well as clinical anecdotes. Overall, dextrose alone (DEX) was predicted to be better at restoring nitrogen balance and limiting nitrogen excretion during dietary non-adherence and infection scenarios, suggesting that the published recommended nutritional strategy involving dextrose and parenteral lipids (ISO) may be suboptimal. The implications for patients with AA IEM are that the medical course during acute metabolic decompensation may be influenced by the choice of protein-free caloric support. These results are also applicable to intensive care patients undergoing catabolism (postoperative phase or sepsis), where parenteral nutritional support aimed at restoring nitrogen balance may be more tailored regarding metabolic fuel selection.

  17. The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization.

    Directory of Open Access Journals (Sweden)

    Elad Noor

    2016-11-01

    Full Text Available Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell's capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering. It depends on enzyme parameters (such as kcat and KM constants, but also on metabolite concentrations. Moreover, similar amounts of different enzymes might incur different costs for the cell, depending on enzyme-specific properties such as protein size and half-life. Here, we developed enzyme cost minimization (ECM, a scalable method for computing enzyme amounts that support a given metabolic flux at a minimal protein cost. The complex interplay of enzyme and metabolite concentrations, e.g. through thermodynamic driving forces and enzyme saturation, would make it hard to solve this optimization problem directly. By treating enzyme cost as a function of metabolite levels, we formulated ECM as a numerically tractable, convex optimization problem. Its tiered approach allows for building models at different levels of detail, depending on the amount of available data. Validating our method with measured metabolite and protein levels in E. coli central metabolism, we found typical prediction fold errors of 4.1 and 2.6, respectively, for the two kinds of data. This result from the cost-optimized metabolic state is significantly better than randomly sampled metabolite profiles, supporting the hypothesis that enzyme cost is important for the fitness of E. coli. ECM can be used to predict enzyme levels and protein cost in natural and engineered pathways, and could be a valuable computational tool to assist metabolic engineering projects. Furthermore, it establishes a direct connection between protein cost and thermodynamics, and provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or

  18. Effect of lineage-specific metabolic traits of Lactobacillus reuteri on sourdough microbial ecology.

    Science.gov (United States)

    Lin, Xiaoxi B; Gänzle, Michael G

    2014-09-01

    This study determined the effects of specific metabolic traits of Lactobacillus reuteri on its competitiveness in sourdoughs. The competitiveness of lactobacilli in sourdough generally depends on their growth rate; acid resistance additionally contributes to competitiveness in sourdoughs with long fermentation times. Glycerol metabolism via glycerol dehydratase (gupCDE) accelerates growth by the regeneration of reduced cofactors; glutamate metabolism via glutamate decarboxylase (gadB) increases acid resistance by generating a proton motive force. Glycerol and glutamate metabolisms are lineage-specific traits in L. reuteri; therefore, this study employed glycerol dehydratase-positive sourdough isolates of human-adapted L. reuteri lineage I, glutamate decarboxylase-positive strains of rodent-adapted L. reuteri lineage II, as well as mutants with deletions in gadB or gupCDE. The competitivenesses of the strains were quantified by inoculation of wheat and sorghum sourdoughs with defined strains, followed by propagation of doughs with a 10% inoculum and 12-h or 72-h fermentation cycles. Lineage I L. reuteri strains dominated sourdoughs propagated with 12-h fermentation cycles; lineage II L. reuteri strains dominated sourdoughs propagated with 72-h fermentation cycles. L. reuteri 100-23ΔgadB was outcompeted by its wild-type strain in sourdoughs fermented with 72-h fermentation cycles; L. reuteri FUA3400ΔgupCDE was outcompeted by its wild-type strain in sourdoughs fermented with both 12-h and 72-h fermentation cycles. Competition experiments with isogenic pairs of strains resulted in a constant rate of strain displacement of the less competitive mutant strain. In conclusion, lineage-specific traits of L. reuteri determine the competitiveness of this species in sourdough fermentations. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

  19. Predicting metabolic syndrome using decision tree and support vector machine methods.

    Science.gov (United States)

    Karimi-Alavijeh, Farzaneh; Jalili, Saeed; Sadeghi, Masoumeh

    2016-05-01

    Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome. This study aims to employ decision tree and support vector machine (SVM) to predict the 7-year incidence of metabolic syndrome. This research is a practical one in which data from 2107 participants of Isfahan Cohort Study has been utilized. The subjects without metabolic syndrome according to the ATPIII criteria were selected. The features that have been used in this data set include: gender, age, weight, body mass index, waist circumference, waist-to-hip ratio, hip circumference, physical activity, smoking, hypertension, antihypertensive medication use, systolic blood pressure (BP), diastolic BP, fasting blood sugar, 2-hour blood glucose, triglycerides (TGs), total cholesterol, low-density lipoprotein, high density lipoprotein-cholesterol, mean corpuscular volume, and mean corpuscular hemoglobin. Metabolic syndrome was diagnosed based on ATPIII criteria and two methods of decision tree and SVM were selected to predict the metabolic syndrome. The criteria of sensitivity, specificity and accuracy were used for validation. SVM and decision tree methods were examined according to the criteria of sensitivity, specificity and accuracy. Sensitivity, specificity and accuracy were 0.774 (0.758), 0.74 (0.72) and 0.757 (0.739) in SVM (decision tree) method. The results show that SVM method sensitivity, specificity and accuracy is more efficient than decision tree. The results of decision tree method show that the TG is the most important feature in predicting metabolic syndrome. According

  20. A Western diet ecological module identified from the 'humanized' mouse microbiota predicts diet in adults and formula feeding in children.

    Science.gov (United States)

    Siddharth, Jay; Holway, Nicholas; Parkinson, Scott J

    2013-01-01

    The interplay between diet and the microbiota has been implicated in the growing frequency of chronic diseases associated with the Western lifestyle. However, the complexity and variability of microbial ecology in humans and preclinical models has hampered identification of the molecular mechanisms underlying the association of the microbiota in this context. We sought to address two key questions. Can the microbial ecology of preclinical models predict human populations? And can we identify underlying principles that surpass the plasticity of microbial ecology in humans? To do this, we focused our study on diet; perhaps the most influential factor determining the composition of the gut microbiota. Beginning with a study in 'humanized' mice we identified an interactive module of 9 genera allied with Western diet intake. This module was applied to a controlled dietary study in humans. The abundance of the Western ecological module correctly predicted the dietary intake of 19/21 top and 21/21 of the bottom quartile samples inclusive of all 5 Western and 'low-fat' diet subjects, respectively. In 98 volunteers the abundance of the Western module correlated appropriately with dietary intake of saturated fatty acids, fat-soluble vitamins and fiber. Furthermore, it correlated with the geographical location and dietary habits of healthy adults from the Western, developing and third world. The module was also coupled to dietary intake in children (and piglets) correlating with formula (vs breast) feeding and associated with a precipitous development of the ecological module in young children. Our study provides a conceptual platform to translate microbial ecology from preclinical models to humans and identifies an ecological network module underlying the association of the gut microbiota with Western dietary habits.

  1. Metabolic Noise, Vestigial Metabolites or the Raw Material of Ecological Adaptation? Opportunitistic Enzymes, Catalytic Promiscuity and the Evolution of chemodiversity in Nature (2010 JGI User Meeting)

    Energy Technology Data Exchange (ETDEWEB)

    Noel, Joseph

    2010-03-26

    Joseph Noel from the Salk Institute on "Metabolic Noise, Vestigial Metabolites or the Raw Material of Ecological Adaptation? Enzymes, Catalytic Promiscuity and the Evolution of Chemodiversity in Nature" on March 26, 2010 at the 5th Annual DOE JGI User Meeting

  2. Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates.

    Science.gov (United States)

    Glazier, Douglas S; Hirst, Andrew G; Atkinson, David

    2015-03-07

    Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR < 1), or the reverse, are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces, but contradict theory that emphasizes resource transport through internal networks. Geometric estimates of the scaling of surface area (SA) with body mass (bA) further show that ontogenetic shifts in bR and bA are positively correlated. These results support new metabolic scaling theory based on SA influences that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  3. Uric Acid Levels Can Predict Metabolic Syndrome and Hypertension in Adolescents: A 10-Year Longitudinal Study.

    Directory of Open Access Journals (Sweden)

    Hai-Lun Sun

    Full Text Available The relationships between uric acid and chronic disease risk factors such as metabolic syndrome, type 2 diabetes mellitus, and hypertension have been studied in adults. However, whether these relationships exist in adolescents is unknown. We randomly selected 8,005 subjects who were between 10 to 15 years old at baseline. Measurements of uric acid were used to predict the future occurrence of metabolic syndrome, hypertension, and type 2 diabetes. In total, 5,748 adolescents were enrolled and followed for a median of 7.2 years. Using cutoff points of uric acid for males and females (7.3 and 6.2 mg/dl, respectively, a high level of uric acid was either the second or third best predictor for hypertension in both genders (hazard ratio: 2.920 for males, 5.222 for females; p<0.05. However, uric acid levels failed to predict type 2 diabetes mellitus, and only predicted metabolic syndrome in males (hazard ratio: 1.658; p<0.05. The same results were found in multivariate adjusted analysis. In conclusion, a high level of uric acid indicated a higher likelihood of developing hypertension in both genders and metabolic syndrome in males after 10 years of follow-up. However, uric acid levels did not affect the occurrence of type 2 diabetes in both genders.

  4. Uric Acid Levels Can Predict Metabolic Syndrome and Hypertension in Adolescents: A 10-Year Longitudinal Study.

    Science.gov (United States)

    Sun, Hai-Lun; Pei, Dee; Lue, Ko-Huang; Chen, Yen-Lin

    2015-01-01

    The relationships between uric acid and chronic disease risk factors such as metabolic syndrome, type 2 diabetes mellitus, and hypertension have been studied in adults. However, whether these relationships exist in adolescents is unknown. We randomly selected 8,005 subjects who were between 10 to 15 years old at baseline. Measurements of uric acid were used to predict the future occurrence of metabolic syndrome, hypertension, and type 2 diabetes. In total, 5,748 adolescents were enrolled and followed for a median of 7.2 years. Using cutoff points of uric acid for males and females (7.3 and 6.2 mg/dl, respectively), a high level of uric acid was either the second or third best predictor for hypertension in both genders (hazard ratio: 2.920 for males, 5.222 for females; puric acid levels failed to predict type 2 diabetes mellitus, and only predicted metabolic syndrome in males (hazard ratio: 1.658; puric acid indicated a higher likelihood of developing hypertension in both genders and metabolic syndrome in males after 10 years of follow-up. However, uric acid levels did not affect the occurrence of type 2 diabetes in both genders.

  5. Predicting future thermal habitat suitability of competing native and invasive fish species: from metabolic scope to oceanographic modelling.

    Science.gov (United States)

    Marras, Stefano; Cucco, Andrea; Antognarelli, Fabio; Azzurro, Ernesto; Milazzo, Marco; Bariche, Michel; Butenschön, Momme; Kay, Susan; Di Bitetto, Massimiliano; Quattrocchi, Giovanni; Sinerchia, Matteo; Domenici, Paolo

    2015-01-01

    Global increase in sea temperatures has been suggested to facilitate the incoming and spread of tropical invaders. The increasing success of these species may be related to their higher physiological performance compared with indigenous ones. Here, we determined the effect of temperature on the aerobic metabolic scope (MS) of two herbivorous fish species that occupy a similar ecological niche in the Mediterranean Sea: the native salema (Sarpa salpa) and the invasive marbled spinefoot (Siganus rivulatus). Our results demonstrate a large difference in the optimal temperature for aerobic scope between the salema (21.8°C) and the marbled spinefoot (29.1°C), highlighting the importance of temperature in determining the energy availability and, potentially, the distribution patterns of the two species. A modelling approach based on a present-day projection and a future scenario for oceanographic conditions was used to make predictions about the thermal habitat suitability (THS, an index based on the relationship between MS and temperature) of the two species, both at the basin level (the whole Mediterranean Sea) and at the regional level (the Sicilian Channel, a key area for the inflow of invasive species from the Eastern to the Western Mediterranean Sea). For the present-day projection, our basin-scale model shows higher THS of the marbled spinefoot than the salema in the Eastern compared with the Western Mediterranean Sea. However, by 2050, the THS of the marbled spinefoot is predicted to increase throughout the whole Mediterranean Sea, causing its westward expansion. Nevertheless, the regional-scale model suggests that the future thermal conditions of Western Sicily will remain relatively unsuitable for the invasive species and could act as a barrier for its spread westward. We suggest that metabolic scope can be used as a tool to evaluate the potential invasiveness of alien species and the resilience to global warming of native species.

  6. Predicting future thermal habitat suitability of competing native and invasive fish species: from metabolic scope to oceanographic modelling

    Science.gov (United States)

    Marras, Stefano; Cucco, Andrea; Antognarelli, Fabio; Azzurro, Ernesto; Milazzo, Marco; Bariche, Michel; Butenschön, Momme; Kay, Susan; Di Bitetto, Massimiliano; Quattrocchi, Giovanni; Sinerchia, Matteo; Domenici, Paolo

    2015-01-01

    Global increase in sea temperatures has been suggested to facilitate the incoming and spread of tropical invaders. The increasing success of these species may be related to their higher physiological performance compared with indigenous ones. Here, we determined the effect of temperature on the aerobic metabolic scope (MS) of two herbivorous fish species that occupy a similar ecological niche in the Mediterranean Sea: the native salema (Sarpa salpa) and the invasive marbled spinefoot (Siganus rivulatus). Our results demonstrate a large difference in the optimal temperature for aerobic scope between the salema (21.8°C) and the marbled spinefoot (29.1°C), highlighting the importance of temperature in determining the energy availability and, potentially, the distribution patterns of the two species. A modelling approach based on a present-day projection and a future scenario for oceanographic conditions was used to make predictions about the thermal habitat suitability (THS, an index based on the relationship between MS and temperature) of the two species, both at the basin level (the whole Mediterranean Sea) and at the regional level (the Sicilian Channel, a key area for the inflow of invasive species from the Eastern to the Western Mediterranean Sea). For the present-day projection, our basin-scale model shows higher THS of the marbled spinefoot than the salema in the Eastern compared with the Western Mediterranean Sea. However, by 2050, the THS of the marbled spinefoot is predicted to increase throughout the whole Mediterranean Sea, causing its westward expansion. Nevertheless, the regional-scale model suggests that the future thermal conditions of Western Sicily will remain relatively unsuitable for the invasive species and could act as a barrier for its spread westward. We suggest that metabolic scope can be used as a tool to evaluate the potential invasiveness of alien species and the resilience to global warming of native species. PMID:27293680

  7. Prediction of the metabolic cost of walking with and without loads.

    Science.gov (United States)

    Duggan, A; Haisman, M F

    1992-04-01

    Measurement of the metabolic cost of walking inconveniences subjects, and requires skilled technical support and expensive equipment. These factors have stimulated interest in predictive equations. The present study assessed existing equations. Under each of 17 combinations of gradient (0-6%) and carried load (4.1-37.4 kg), 7-12 men undertook treadmill walking at 1.67 m/s. Measured oxygen consumption and respiratory exchange ratio were used to calculate metabolic rate (MRobserved). Metabolic rate was also predicted from the equation of Pandolf et al. (1977) (MRpandolf) and, where appropriate, from another five equations relating to walking without loads. MRobserved and MRpandolf did not differ significantly (p greater than 0.05) under any combination of gradient and load. The overall mean MRobserved and MRpandolf of 609 W and 602 W, respectively, also did not differ significantly (p greater than 0.05). These variables were highly correlated (r = 0.94) with a standard deviation about the prediction error of 47 W. For level walking without loads, the mean predictions from the equations of Pandolf et al. (1977) and Cotes and Meade (1960) did not differ significantly (p greater than 0.05) from the mean MRobserved of 428 Watts, but four other equations overestimated by 17-74 W. In conclusion, the Pandolf et al. (1977) equation has given good results across the range of combinations of load and gradient tested, and the errors are considered acceptable for most practical purposes.

  8. The database of the PREDICTS (Projecting Responses of Ecological Diversity in Changing Terrestrial Systems) project

    Czech Academy of Sciences Publication Activity Database

    Fayle, Tom Maurice; Sam, Kateřina

    2017-01-01

    Roč. 7, č. 1 (2017), s. 145-188 ISSN 2045-7758 Institutional support: RVO:60077344 Keywords : data sharing * global biodiversity modeling * global change Subject RIV: EH - Ecology, Behaviour OBOR OECD: Ecology Impact factor: 2.440, year: 2016 http://onlinelibrary.wiley.com/doi/10.1002/ece3.2579/abstract

  9. Blood analyses of wolf pups and their ecological and metabolic interpretation

    Science.gov (United States)

    Seal, U.S.; Mech, L.D.; Van Ballenberghe, V.

    1975-01-01

    Blood samples were obtained from 32 wolf (Canis lupus) pups live-trapped over a three-year period in northern Minnesota. The results of 21 laboratory analyses of hematology and blood chemistry are tabulated and analyzed in terms of study area, age, sex, and year of co11ection. Mean values are compared to those reported for dogs in the same age group. The numerous differences between dog and wolf pups are interpreted in terms of nutritional levels and dietary composition with the suggestion that the wolves are not achieving their full growth potential. Individual abnormal test results are tabulated and possible interpretations are suggested. Abnormal results were observed in 13 animals including 10 of 11 animals sampled in 1972. The results in the 1972 animals indicated a poorer nutrition. This preponderance of abnormal test results in pups from 1972 is correlated with ecological studies on this wolf population indicating decreased survival. The potential value of such long-term integrated field and laboratory studies for providing a more complete understanding of changes in the dynamics of natural populations in terms of the responses of individual animals is demonstrated.

  10. Redefining the Australian Anthrax Belt: Modeling the Ecological Niche and Predicting the Geographic Distribution of Bacillus anthracis.

    Science.gov (United States)

    Barro, Alassane S; Fegan, Mark; Moloney, Barbara; Porter, Kelly; Muller, Janine; Warner, Simone; Blackburn, Jason K

    2016-06-01

    The ecology and distribution of B. anthracis in Australia is not well understood, despite the continued occurrence of anthrax outbreaks in the eastern states of the country. Efforts to estimate the spatial extent of the risk of disease have been limited to a qualitative definition of an anthrax belt extending from southeast Queensland through the centre of New South Wales and into northern Victoria. This definition of the anthrax belt does not consider the role of environmental conditions in the distribution of B. anthracis. Here, we used the genetic algorithm for rule-set prediction model system (GARP), historical anthrax outbreaks and environmental data to model the ecological niche of B. anthracis and predict its potential geographic distribution in Australia. Our models reveal the niche of B. anthracis in Australia is characterized by a narrow range of ecological conditions concentrated in two disjunct corridors. The most dominant corridor, used to redefine a new anthrax belt, parallels the Eastern Highlands and runs from north Victoria to central east Queensland through the centre of New South Wales. This study has redefined the anthrax belt in eastern Australia and provides insights about the ecological factors that limit the distribution of B. anthracis at the continental scale for Australia. The geographic distributions identified can help inform anthrax surveillance strategies by public and veterinary health agencies.

  11. Validity of the Inbody 520™ to predict metabolic rate in apparently healthy adults.

    Science.gov (United States)

    Salacinski, Amanda J; Howell, Steven M; Hill, Danielle L

    2017-05-30

    The present study seeks to assess the validity of the InBody 520™ device to predict RMR in apparently healthy adults relative to a metabolic cart (the standard, yet time intensive, method for determining resting metabolic rate). Twenty-six apparently healthy adults participated in the study. Predicted RMR (pRMR) was calculated by the InBody 520™ and measured RMR (mRMR) was determined by 30-minute gas analysis and ventilated hood system. Of the 78 measurement trials conducted, 64 yielded acceptable measurement trials. A Pearson product-moment correlation was used to determine the relationship between pRMR and mRMR (r = .87, P InBody520™ provides valid measurements of RMR in apparently healthy adults and can be an effective and efficient method for collecting data in a clinical setting.

  12. Community metabolism of aquatic Closed Ecological Systems: Effects of nitrogen sources

    Science.gov (United States)

    Taub, Frieda B.

    2009-10-01

    To investigate the effect of nitrogen sources on Closed Ecological Systems (CESs), three nitrogen sources (NaNO 3, sodium nitrate; NH 4Cl, ammonium chloride; and NH 4NO 3, ammonium nitrate) were each tested in freshwater CESs consisting of a chemically defined medium, three species of green algae ( Ankistrodesmus, S cenedesmus, and Selenastrum), the grazer Daphnia magna, and associated microbes, under 12 h light/12 h dark cycles. It had been hypothesized that the development of high pH in earlier CESs was the result of nitrate utilization, and that ammonium might result in acid conditions, while ammonium nitrate might result in more moderate pH. The three nitrogen sources supported similar densities of algae (estimated by in vivo fluorescence) and similar Daphnia populations. The experiments showed that pH levels rapidly increased when grazers were absent or at low abundances irrespective of the nitrogen source. Consequently, it is hypothesized that carbon cycles, rather than nitrogen sources, are responsible for the pH dynamics. Oxygen diurnal (light:dark) cycles tended to come into balance more quickly than pH. It may be more feasible to convert O 2 data to energy units (using "oxycalorific" values) than CO 2 data since CO 2 dynamics may include other chemical reactions than just photosynthesis and respiration. The feasibility of sustaining grazer populations for at least several weeks in small, simple CESs was demonstrated, along with the ability to monitor algae-grazer dynamics, and the recording of O 2 and pH measurements.

  13. Chemical reaction vector embeddings: towards predicting drug metabolism in the human gut microbiome.

    Science.gov (United States)

    Mallory, Emily K; Acharya, Ambika; Rensi, Stefano E; Turnbaugh, Peter J; Bright, Roselie A; Altman, Russ B

    2018-01-01

    Bacteria in the human gut have the ability to activate, inactivate, and reactivate drugs with both intended and unintended effects. For example, the drug digoxin is reduced to the inactive metabolite dihydrodigoxin by the gut Actinobacterium E. lenta, and patients colonized with high levels of drug metabolizing strains may have limited response to the drug. Understanding the complete space of drugs that are metabolized by the human gut microbiome is critical for predicting bacteria-drug relationships and their effects on individual patient response. Discovery and validation of drug metabolism via bacterial enzymes has yielded >50 drugs after nearly a century of experimental research. However, there are limited computational tools for screening drugs for potential metabolism by the gut microbiome. We developed a pipeline for comparing and characterizing chemical transformations using continuous vector representations of molecular structure learned using unsupervised representation learning. We applied this pipeline to chemical reaction data from MetaCyc to characterize the utility of vector representations for chemical reaction transformations. After clustering molecular and reaction vectors, we performed enrichment analyses and queries to characterize the space. We detected enriched enzyme names, Gene Ontology terms, and Enzyme Consortium (EC) classes within reaction clusters. In addition, we queried reactions against drug-metabolite transformations known to be metabolized by the human gut microbiome. The top results for these known drug transformations contained similar substructure modifications to the original drug pair. This work enables high throughput screening of drugs and their resulting metabolites against chemical reactions common to gut bacteria.

  14. Metabolic diversity and ecological niches of Achromatium populations revealed with single-cell genomic sequencing

    Directory of Open Access Journals (Sweden)

    Muammar eMansor

    2015-08-01

    Full Text Available Large, sulfur-cycling, calcite-precipitating bacteria in the genus Achromatium represent a significant proportion of bacterial communities near sediment-water interfaces throughout the world. Our understanding of their potentially crucial roles in calcium, carbon, sulfur, nitrogen, and iron cycling is limited because they have not been cultured or sequenced using environmental genomics approaches to date. We utilized single-cell genomic sequencing to obtain one incomplete and two nearly complete draft genomes for Achromatium collected at Warm Mineral Springs, FL. Based on 16S rRNA gene sequences, the three cells represent distinct and relatively distant Achromatium populations (91-92% identity. The draft genomes encode key genes involved in sulfur and hydrogen oxidation; oxygen, nitrogen and polysulfide respiration; carbon and nitrogen fixation; organic carbon assimilation and storage; chemotaxis; twitching motility; antibiotic resistance; and membrane transport. Known genes for iron and manganese energy metabolism were not detected. The presence of pyrophosphatase and vacuolar (V-type ATPases, which are generally rare in bacterial genomes, suggests a role for these enzymes in calcium transport, proton pumping, and/or energy generation in the membranes of calcite-containing inclusions.

  15. Flor yeasts of Saccharomyces cerevisiae--their ecology, genetics and metabolism.

    Science.gov (United States)

    Alexandre, Hervé

    2013-10-15

    The aging of certain white wines is dependent on the presence of yeast strains that develop a biofilm on the wine surface after the alcoholic fermentation. These strains belong to the genus Saccharomyces and are called flor yeasts. These strains possess distinctive characteristics compared with Saccharomyces cerevisiae fermenting strain. The most important one is their capacity to form a biofilm on the air-liquid interface of the wine. The major gene involved in this phenotype is FLO11, however other genes are also involved in velum formation by these yeast and will be detailed. Other striking features presented in this review are their aneuploidy, and their mitochondrial DNA polymorphism which seems to reflect adaptive evolution of the yeast to a stressful environment where acetaldehyde and ethanol are present at elevated concentration. The biofilm assures access to oxygen and therefore permits continued growth on non-fermentable ethanol. This specific metabolism explains the peculiar organoleptic profile of these wines, especially their content in acetaldehyde and sotolon. This review deals with these different specificities of flor yeasts and will also underline the existing gaps regarding these astonishing yeasts. © 2013.

  16. Prediction of suitable habitats in Zostera noltii meadows by Ecological Niche Factor Analysis A tool for environmental management of coastal

    Directory of Open Access Journals (Sweden)

    Cynthia Silvina Fernandez Diaz

    2014-06-01

    Full Text Available Seagrasses are present in the entire coastal habitats around the world. These coastal habitats provide many goods and services which maintain the integrity of coastal ecosystems and consequently the quality of human life of the communities involved. In recent years, interest in these environments has resulted in its incorporation into European legislation to protect the natural heritage. However, seagrasses show a global reduction as a result of the development process and pollution, eutrophication and habitat degradation. The Ecological Niche Factor Analysis (ENFA was used to predict habitat suitability of Zostera noltii, a dominant species of intertidal meadows of Galicia. Within the ecological variables used in analysis Phi and redox potential mainly explain the presence of Zostera noltii in the study area with an adjustment of 90%. The predictive ability of ENFA analysis is presented as a useful tool for environmental public managers to manage the coastal spaces and for those who must design strategies for future adaptation.

  17. Early coagulopathy and metabolic acidosis predict transfusion of packed red blood cells in pediatric trauma patients.

    Science.gov (United States)

    Smith, Shane A; Livingston, Michael H; Merritt, Neil H

    2016-05-01

    Severely injured pediatric trauma patients often present to hospital with early coagulopathy and metabolic acidosis. These derangements are associated with poor outcomes, but it is unclear to what degree they predict transfusion of packed red blood cells (pRBC). We retrospectively identified pediatric trauma patients from a level 1 trauma center from 2006 to 2013. Inclusion criteria were age less than 18years, Injury Severity Score greater than 12, and pRBC transfusion within 24h of admission. We identified 96 pediatric trauma patients who underwent pRBC transfusion within 24h of presentation to hospital. On admission, 43% of these patients had one or more signs of coagulopathy, and 81% had metabolic acidosis. Size of pRBC transfusion in the first 24h ranged from 3 to 177mL/kg (mean 29mL/kg), and nineteen patients (20%) underwent massive transfusion (>40ml/kg in 24h). Univariate analysis indicated that size of pRBC transfusion was associated with initial base excess (r=0.46), international normalized ratio (r=0.35), partial thromboplastin time (r=0.41), fibrinogen (r=0.46), and BIG score (Base deficit, INR, Glasgow Coma Scale (GCS), r=0.36). Platelet count, age, GCS, and direct versus referred presentation were not predictive. Multivariable linear regression confirmed that coagulopathy and metabolic acidosis remained predictive after adjusting for direct versus referred presentation (R(2)=0.30). Early coagulopathy and metabolic acidosis predict size of pRBC transfusion among pediatric trauma patients. Further research is needed to develop massive transfusion protocols and guidelines for activation. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Novel predictive models for metabolic syndrome risk: a "big data" analytic approach.

    Science.gov (United States)

    Steinberg, Gregory B; Church, Bruce W; McCall, Carol J; Scott, Adam B; Kalis, Brian P

    2014-06-01

    We applied a proprietary "big data" analytic platform--Reverse Engineering and Forward Simulation (REFS)--to dimensions of metabolic syndrome extracted from a large data set compiled from Aetna's databases for 1 large national customer. Our goals were to accurately predict subsequent risk of metabolic syndrome and its various factors on both a population and individual level. The study data set included demographic, medical claim, pharmacy claim, laboratory test, and biometric screening results for 36,944 individuals. The platform reverse-engineered functional models of systems from diverse and large data sources and provided a simulation framework for insight generation. The platform interrogated data sets from the results of 2 Comprehensive Metabolic Syndrome Screenings (CMSSs) as well as complete coverage records; complete data from medical claims, pharmacy claims, and lab results for 2010 and 2011; and responses to health risk assessment questions. The platform predicted subsequent risk of metabolic syndrome, both overall and by risk factor, on population and individual levels, with ROC/AUC varying from 0.80 to 0.88. We demonstrated that improving waist circumference and blood glucose yielded the largest benefits on subsequent risk and medical costs. We also showed that adherence to prescribed medications and, particularly, adherence to routine scheduled outpatient doctor visits, reduced subsequent risk. The platform generated individualized insights using available heterogeneous data within 3 months. The accuracy and short speed to insight with this type of analytic platform allowed Aetna to develop targeted cost-effective care management programs for individuals with or at risk for metabolic syndrome.

  19. Incremental Predictive Value of Serum AST-to-ALT Ratio for Incident Metabolic Syndrome: The ARIRANG Study.

    Directory of Open Access Journals (Sweden)

    Dhananjay Yadav

    Full Text Available The ratio of aspartate aminotransferase (AST to alanine aminotransferase (ALT is of great interest as a possible novel marker of metabolic syndrome. However, longitudinal studies emphasizing the incremental predictive value of the AST-to-ALT ratio in diagnosing individuals at higher risk of developing metabolic syndrome are very scarce. Therefore, our study aimed to evaluate the AST-to-ALT ratio as an incremental predictor of new onset metabolic syndrome in a population-based cohort study.The population-based cohort study included 2276 adults (903 men and 1373 women aged 40-70 years, who participated from 2005-2008 (baseline without metabolic syndrome and were followed up from 2008-2011. Metabolic syndrome was defined according to the harmonized definition of metabolic syndrome. Serum concentrations of AST and ALT were determined by enzymatic methods.During an average follow-up period of 2.6-years, 395 individuals (17.4% developed metabolic syndrome. In a multivariable adjusted model, the odds ratio (95% confidence interval for new onset of metabolic syndrome, comparing the fourth quartile to the first quartile of the AST-to-ALT ratio, was 0.598 (0.422-0.853. The AST-to-ALT ratio also improved the area under the receiver operating characteristic curve (AUC for predicting new cases of metabolic syndrome (0.715 vs. 0.732, P = 0.004. The net reclassification improvement of prediction models including the AST-to-ALT ratio was 0.23 (95% CI: 0.124-0.337, P<0.001, and the integrated discrimination improvement was 0.0094 (95% CI: 0.0046-0.0143, P<0.001.The AST-to-ALT ratio independently predicted the future development of metabolic syndrome and had incremental predictive value for incident metabolic syndrome.

  20. Predicting Metabolic Syndrome in Obese Children and Adolescents: Look, Measure and Ask

    Directory of Open Access Journals (Sweden)

    Nicola Santoro

    2013-02-01

    Full Text Available Objective: To verify in obese children whether or not the presence of i high waist-to-height ratio (WHtR, ii family history for type 2 diabetes (T2D and iii acanthosis nigricans (AN, singularly or together, might predict the occurrence of metabolic syndrome or prediabetes. Methods. 1,080 Italian obese children (567 females were enrolled. Blood pressure, fasting plasma glucose, insulin, and lipids were measured, and oral glucose tolerance test (OGTT was performed. The WHtR was calculated, family history for T2D was assessed, and the presence of AN was noticed. The odds ratios for showing metabolic syndrome and/or prediabetes according to the presence of these features were calculated. Results: The prevalence of metabolic syndrome was 29.2%. AN (OR1.81; p = 0.002 and WHtR higher than 0.60 (OR 2.24; p Conclusions: Three simple actions, i.e., looking at the patient, asking about T2D family history, and measuring WHtR, may represent a powerful tool in the hands of pediatricians to identify obese children with high cardiovascular and metabolic risk.

  1. Delivery Mode and the Transition of Pioneering Gut-Microbiota Structure, Composition and Predicted Metabolic Function.

    Science.gov (United States)

    Mueller, Noel T; Shin, Hakdong; Pizoni, Aline; Werlang, Isabel C; Matte, Ursula; Goldani, Marcelo Z; Goldani, Helena A S; Dominguez-Bello, Maria G

    2017-12-04

    Cesarean (C-section) delivery, recently shown to cause excess weight gain in mice, perturbs human neonatal gut microbiota development due to the lack of natural mother-to-newborn transfer of microbes. Neonates excrete first the in-utero intestinal content (referred to as meconium) hours after birth, followed by intestinal contents reflective of extra-uterine exposure (referred to as transition stool) 2 to 3 days after birth. It is not clear when the effect of C-section on the neonatal gut microbiota emerges. We examined bacterial DNA in carefully-collected meconium, and the subsequent transitional stool, from 59 neonates [13 born by scheduled C-section and 46 born by vaginal delivery] in a private hospital in Brazil. Bacterial DNA was extracted, and the V4 region of the 16S rRNA gene was sequenced using the Illumina MiSeq (San Diego, CA, USA) platform. We found evidence of bacterial DNA in the majority of meconium samples in our study. The bacterial DNA structure (i.e., beta diversity) of meconium differed significantly from that of the transitional stool microbiota. There was a significant reduction in bacterial alpha diversity (e.g., number of observed bacterial species) and change in bacterial composition (e.g., reduced Proteobacteria) in the transition from meconium to stool. However, changes in predicted microbiota metabolic function from meconium to transitional stool were only observed in vaginally-delivered neonates. Within sample comparisons showed that delivery mode was significantly associated with bacterial structure, composition and predicted microbiota metabolic function in transitional-stool samples, but not in meconium samples. Specifically, compared to vaginally delivered neonates, the transitional stool of C-section delivered neonates had lower proportions of the genera Bacteroides , Parabacteroides and Clostridium . These differences led to C-section neonates having lower predicted abundance of microbial genes related to metabolism of amino and

  2. Delivery Mode and the Transition of Pioneering Gut-Microbiota Structure, Composition and Predicted Metabolic Function

    Directory of Open Access Journals (Sweden)

    Noel T. Mueller

    2017-12-01

    Full Text Available Cesarean (C-section delivery, recently shown to cause excess weight gain in mice, perturbs human neonatal gut microbiota development due to the lack of natural mother-to-newborn transfer of microbes. Neonates excrete first the in-utero intestinal content (referred to as meconium hours after birth, followed by intestinal contents reflective of extra-uterine exposure (referred to as transition stool 2 to 3 days after birth. It is not clear when the effect of C-section on the neonatal gut microbiota emerges. We examined bacterial DNA in carefully-collected meconium, and the subsequent transitional stool, from 59 neonates [13 born by scheduled C-section and 46 born by vaginal delivery] in a private hospital in Brazil. Bacterial DNA was extracted, and the V4 region of the 16S rRNA gene was sequenced using the Illumina MiSeq (San Diego, CA, USA platform. We found evidence of bacterial DNA in the majority of meconium samples in our study. The bacterial DNA structure (i.e., beta diversity of meconium differed significantly from that of the transitional stool microbiota. There was a significant reduction in bacterial alpha diversity (e.g., number of observed bacterial species and change in bacterial composition (e.g., reduced Proteobacteria in the transition from meconium to stool. However, changes in predicted microbiota metabolic function from meconium to transitional stool were only observed in vaginally-delivered neonates. Within sample comparisons showed that delivery mode was significantly associated with bacterial structure, composition and predicted microbiota metabolic function in transitional-stool samples, but not in meconium samples. Specifically, compared to vaginally delivered neonates, the transitional stool of C-section delivered neonates had lower proportions of the genera Bacteroides, Parabacteroides and Clostridium. These differences led to C-section neonates having lower predicted abundance of microbial genes related to metabolism of

  3. Predicting future biomass yield inMiscanthususing the carbohydrate metabolic profile as a biomarker.

    Science.gov (United States)

    Maddison, Anne L; Camargo-Rodriguez, Anyela; Scott, Ian M; Jones, Charlotte M; Elias, Dafydd M O; Hawkins, Sarah; Massey, Alice; Clifton-Brown, John; McNamara, Niall P; Donnison, Iain S; Purdy, Sarah J

    2017-07-01

    In perennial energy crop breeding programmes, it can take several years before a mature yield is reached when potential new varieties can be scored. Modern plant breeding technologies have focussed on molecular markers, but for many crop species, this technology is unavailable. Therefore, prematurity predictors of harvestable yield would accelerate the release of new varieties. Metabolic biomarkers are routinely used in medicine, but they have been largely overlooked as predictive tools in plant science. We aimed to identify biomarkers of productivity in the bioenergy crop, Miscanthus, that could be used prognostically to predict future yields. This study identified a metabolic profile reflecting productivity in Miscanthus by correlating the summer carbohydrate composition of multiple genotypes with final yield 6 months later. Consistent and strong, significant correlations were observed between carbohydrate metrics and biomass traits at two separate field sites over 2 years. Machine-learning feature selection was used to optimize carbohydrate metrics for support vector regression models, which were able to predict interyear biomass traits with a correlation ( R ) of >0.67 between predicted and actual values. To identify a causal basis for the relationships between the glycome profile and biomass, a 13 C-labelling experiment compared carbohydrate partitioning between high- and low-yielding genotypes. A lower yielding and slower growing genotype partitioned a greater percentage of the 13 C pulse into starch compared to a faster growing genotype where a greater percentage was located in the structural biomass. These results supported a link between plant performance and carbon flow through two rival pathways (starch vs. sucrose), with higher yielding plants exhibiting greater partitioning into structural biomass, via sucrose metabolism, rather than starch. Our results demonstrate that the plant metabolome can be used prognostically to anticipate future yields and

  4. Weight loss predictability by plasma metabolic signatures in adults with obesity and morbid obesity of the DiOGenes study

    NARCIS (Netherlands)

    Stroeve, Johanna H. M.; Saccenti, Edoardo; Bouwman, Jildau; Dane, Adrie; Strassburg, Katrin; Vervoort, Jacques; Hankemeier, Thomas; Astrup, Arne; Smilde, Age K.; van Ommen, Ben; Saris, Wim H. M.

    2016-01-01

    Aim is to predict successful weight loss by metabolic signatures at baseline and to identify which differences in metabolic status may underlie variations in weight loss success. In DiOGenes, a randomized, controlled trial, weight loss was induced using a low-calorie diet (800 kcal) for 8 weeks. Men

  5. Weight loss predictability by plasma metabolic signatures in adults with obesity and morbid obesity of the DiOGenes study

    NARCIS (Netherlands)

    Stroeve, J.H.M.; Saccenti, E.; Bouwman, J.; Dane, A.; Strassburg, K.; Vervoort, J.; Hankemeier, T.; Astrup, A.; Smilde, A.K.; van Ommen, B.; Saris, W.H.M.

    2016-01-01

    OBJECTIVE: Aim is to predict successful weight loss by metabolic signatures at baseline and to identify which differences in metabolic status may underlie variations in weight loss success. METHODS: In DiOGenes, a randomized, controlled trial, weight loss was induced using a low-calorie diet (800

  6. Prediction of metabolic drug clearance in humans: in vitro-in vivo extrapolation vs allometric scaling.

    Science.gov (United States)

    Shiran, M R; Proctor, N J; Howgate, E M; Rowland-Yeo, K; Tucker, G T; Rostami-Hodjegan, A

    2006-07-01

    Previously in vitro-in vivo extrapolation (IVIVE) with the Simcyp Clearance and Interaction Simulator has been used to predict the clearance of 15 clinically used drugs in humans. The criteria for the selection of the drugs were that they are used as probes for the activity of specific cytochromes P450 (CYPs) or have a single CYP isoform as the major or sole contributor to their metabolism and that they do not exhibit non-linear kinetics in vivo. Where data were available for the clearance of the drugs in at least three animal species, the predictions from IVIVE have now been compared with those based on allometric scaling (AS). Adequate data were available for estimating oral clearance (CLp.o.) in 9 cases (alprazolam, sildenafil, caffeine, clozapine, cyclosporine, dextromethorphan, midazolam, omeprazole and tolbutamide) and intravenous clearance in 6 cases (CLi.v.) (cyclosporine, diclofenac, midazolam, omeprazole, theophylline and tolterodine). AS predictions were based on five different methods: (1) simple allometry (clearance versus body weight); (2) correction for maximum life-span potential (CL x MLP); (3) correction for brain weight (CL x BrW); (4) the use of body surface area; and (5) the rule of exponents. A prediction accuracy was indicated by mean-fold error and the Pearson product moment correlation coefficient. Predictions were considered successful if the mean-fold error was error range: 1.02-4.00). All five AS methods were accurate in 13, 11, 10, 10 and 14 cases, respectively. However, in some cases the error of AS exceeded fivefold. On the basis of the current results, IVIVE is more reliable than AS in predicting human clearance values for drugs mainly metabolized by CYP450 enzymes. This suggests that the place of AS methods in pre-clinical drug development warrants further scrutiny.

  7. Can we rely on predicted basal metabolic rate in chronic pancreatitis outpatients?

    Science.gov (United States)

    Olesen, Søren Schou; Holst, Mette; Køhler, Marianne; Drewes, Asbjørn Mohr; Rasmussen, Henrik Højgaard

    2015-04-01

    Malnutrition is a common complication to chronic pancreatitis (CP) and many patients need nutritional support. An accurate estimation of the basal metabolic rate (BMR) is essential when appropriate nutritional support is to be initiated, but in the clinical settings BMR is cumbersome to measure. We therefore investigated whether BMR can be reliable predicted from a standard formula (the Harris-Benedict equation) in CP outpatients. Twenty-eight patients with clinical stable CP and no current alcohol abuse were enrolled. Patients were stratified according to nutritional risk using the Nutrition Risk Screening 2002 system. Body composition was estimated using bioelectrical impedance. BMR was measured using indirect calorimetry and predicted using the Harris-Benedict equation based on anthropometric data. The average predicted BMR was 1371 ± 216 kcal/day compared to an average measured BMR of 1399 ± 231 kcal/day (P = 0.4). The corresponding limits of agreement were -347 to 290 kcal/day. Twenty-two patients (79%) had a measured BMR between 85 and 115% of the predicted BMR. When analysing patients stratified according to nutritional risk profiles, no differences between predicted and measured BMR were evident for any of the risk profile subgroups (all P > 0.2). The BMR was correlated to fat free mass determined by bioelectrical impedance (rho = 0.55; P = 0.003), while no effect modification was seen from nutritional risk stratification in a linear regression analysis (P = 0.4). The Harris-Benedict equation reliable predicts the measured BMR in four out of five clinical stable CP outpatients with no current alcohol abuse. Copyright © 2015 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.

  8. Metabolic activity measured by FDG PET predicts pathological response in locally advanced superior sulcus NSCLC.

    Science.gov (United States)

    Bahce, I; Vos, C G; Dickhoff, C; Hartemink, K J; Dahele, M; Smit, E F; Boellaard, R; Hoekstra, O S; Thunnissen, E

    2014-08-01

    Pathological complete response and tumor regression to less than 10% vital tumor cells after induction chemoradiotherapy have been shown to be prognostically important in non-small cell lung cancer (NSCLC). Predictive imaging biomarkers could help treatment decision-making. The purpose of this study was to assess whether postinduction changes in tumor FDG uptake could predict pathological response and to evaluate the correlation between residual vital tumor cells and post-induction FDG uptake. NSCLC patients with sulcus superior tumor (SST), planned for trimodality therapy, routinely undergo FDG PET/CT scans before and after induction chemoradiotherapy in our institute. Metabolic end-points based on standardized uptake values (SUV) were calculated, including SUV(max) (maximum SUV), SUV(TTL) (tumor-to-liver ratio), SUV(peak) (SUV within 1 cc sphere with highest activity), and SUV(PTL) (peak-to-liver ratio). Pathology specimens were assessed for residual vital tumor cell percentages and scored as no (grade 3), 10% vital tumor cells (grade 2a/1). 19 and 23 patients were evaluated for (1) metabolic change and (2) postinduction PET-pathology correlation, respectively. Changes in all parameters were predictive for grade 2b/3 response. ΔSUV(TTL) and ΔSUV(PTL) were also predictive for grade 3 response. Remaining vital tumor cells correlated with post-induction SUV(peak) (R=0.55; P=0.007) and postinduction SUV(PTL) (R=0.59; P=0.004). Postinduction SUV(PTL) could predict both grades 3 and 2b/3 response. In NSCLC patients treated with chemoradiotherapy, changes in SUV(max), SUV(TTL), SUV(peak), and SUV(PTL) were predictive for pathological response (grade 2b/3 and for SUV(TTL) and SUV(PTL) grade 3 as well). Postinduction SUV(PTL) correlated with residual tumor cells. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  9. Predicting Basal Metabolic Rate in Men with Motor Complete Spinal Cord Injury.

    Science.gov (United States)

    Nightingale, Tom E; Gorgey, Ashraf S

    2018-01-08

    To assess the accuracy of existing basal metabolic rate (BMR) prediction equations in men with chronic (>1 year) spinal cord injury (SCI). The primary aim is to develop new SCI population-specific BMR prediction models, based on anthropometric, body composition and/or demographic variables that are strongly associated with BMR. Thirty men with chronic SCI (Paraplegic; n = 21, Tetraplegic; n = 9), aged 35 ± 11 years (mean ± SD) participated in this cross-sectional study. Criterion BMR values were measured by indirect calorimetry. Body composition (dual energy X-ray absorptiometry; DXA) and anthropometric measurements (circumferences and diameters) were also taken. Multiple linear regression analysis was performed to develop new SCI-specific BMR prediction models. Criterion BMR values were compared to values estimated from six existing and four developed prediction equations RESULTS: Existing equations that use information on stature, weight and/or age, significantly (P BMR by a mean of 14-17% (187-234 kcal/day). Equations that utilised fat-free mass (FFM) accurately predicted BMR. The development of new SCI-specific prediction models demonstrated that the addition of anthropometric variables (weight, height and calf circumference) to FFM (Model 3; r = 0.77), explained 8% more of the variance in BMR than FFM alone (Model 1; r = 0.69). Using anthropometric variables, without FFM, explained less of the variance in BMR (Model 4; r = 0.57). However, all the developed prediction models demonstrated acceptable mean absolute error ≤ 6%. BMR can be more accurately estimated when DXA derived FFM is incorporated into prediction equations. Utilising anthropometric measurements provides a promising alternative to improve the prediction of BMR, beyond that achieved by existing equations in persons with SCI.

  10. Validity of predictive equations for basal metabolic rate in Japanese adults.

    Science.gov (United States)

    Miyake, Rieko; Tanaka, Shigeho; Ohkawara, Kazunori; Ishikawa-Takata, Kazuko; Hikihara, Yuki; Taguri, Emiko; Kayashita, Jun; Tabata, Izumi

    2011-01-01

    Many predictive equations for basal metabolic rate (BMR) based on anthropometric measurements, age, and sex have been developed, mainly for healthy Caucasians. However, it has been reported that many of these equations, used widely, overestimate BMR not only for Asians, but also for Caucasians. The present study examined the accuracy of several predictive equations for BMR in Japanese subjects. In 365 healthy Japanese male and female subjects, aged 18 to 79 y, BMR was measured in the post-absorptive state using a mask and Douglas bag. Six predictive equations were examined. Total error was used as an index of the accuracy of each equation's prediction. Predicted BMR values by Dietary Reference Intakes for Japanese (Japan-DRI), Adjusted Dietary Reference Intakes for Japanese (Adjusted-DRI), and Ganpule equations were not significantly different from the measured BMR in either sex. On the other hand, Harris-Benedict, Schofield, and Food and Agriculture Organization of the United Nations/World Health Organization/United Nations University equations were significantly higher than the measured BMR in both sexes. The prediction error by Japan-DRI, Adjusted-DRI, and Harris-Benedict equations was significantly correlated with body weight in both sexes. Total error using the Ganpule equation was low in both males and females (125 and 99 kcal/d, respectively). In addition, total error using the Adjusted-DRI equation was low in females (95 kcal/d). Thus, the Ganpule equation was the most accurate in predicting BMR in our healthy Japanese subjects, because the difference between the predicted and measured BMR was relatively small, and body weight had no effect on the prediction error.

  11. Skinfold reference curves and their use in predicting metabolic syndrome risk in children.

    Science.gov (United States)

    Andaki, Alynne C R; Quadros, Teresa M B de; Gordia, Alex P; Mota, Jorge; Tinôco, Adelson L A; Mendes, Edmar L

    To draw skinfold (SF) reference curves (subscapular, suprailiac, biceps, triceps) and to determine SF cutoff points for predicting the risk of metabolic syndrome (MetS) in children aged 6-10 years old. This was a cross-sectional study with a random sample of 1480 children aged 6-10 years old, 52.2% females, from public and private schools located in the urban and rural areas of the municipality of Uberaba (MG). Anthropometry, blood pressure, and fasting blood samples were taken at school, following specific protocols. The LMS method was used to draw the reference curves and ROC curve analysis to determine the accuracy and cutoff points for the evaluated skinfolds. The four SF evaluated (subscapular, suprailiac, biceps, and triceps) and their sum (∑4SF) were accurate in predicting MetS for both girls and boys. Additionally, cutoffs have been proposed and percentile curves (p5, p10, p25, p50, p75, p90, and p95) were outlined for the four SF and ∑4SF, for both genders. SF measurements were accurate in predicting metabolic syndrome in children aged 6-10 years old. Age- and gender-specific smoothed percentiles curves of SF provide a reference for the detection of risk for MetS in children. Copyright © 2017. Published by Elsevier Editora Ltda.

  12. Changes in metabolic hormones after bariatric surgery and their predictive impact on weight loss.

    Science.gov (United States)

    Kruljac, Ivan; Mirošević, Gorana; Kirigin, Lora S; Nikolić, Marko; Ljubičić, Neven; Budimir, Ivan; Bekavac Bešlin, Miroslav; Vrkljan, Milan

    2016-12-01

    Although various metabolic hormones have been implicated in bariatric-related weight loss, their use as predictors of weight loss is unknown. Our study evaluates changes in metabolic hormones after bariatric surgery, and their role as predictors of weight loss. This nonrandomized study included 51 patients, 21 underwent laporascopic adjustable gastric banding (LAGB), 15 laparoscopic sleeve gastrectomy (LSG) and 15 Roux-en Y gastric bypass (RYGB). Serum ghrelin, leptin, insulin, growth hormone, HOMA-IR and HOMA-β was recorded at baseline and 1, 3, 6 and 12 months, and correlated with weight loss. Successful weight loss was defined as excess weight loss >50% at 12 months for all groups. Weight loss pattern was similar in all groups. Ghrelin increased only in the LAGB group (P = 0·016). However, baseline ghrelin concentrations >664·6 pg/mL in the LSG group predicted successful weight loss with 81·8% sensitivity and 100·0% specificity, and ghrelin >969·8 pg/mL in the 1st postoperative month predicted success with 83·3% sensitivity and 83·3% specificity in the LAGB group. Insulin and HOMA-IR decreased significantly in the LSG and RYGB group, HOMA-β increased in the LAGB and LSG group. Serum leptin decreased and GH increased in all groups (P Validation studies are required to confirm the role of ghrelin in predicting weight loss after bariatric surgery, but also in selecting candidates for specific bariatric procedures. © 2016 John Wiley & Sons Ltd.

  13. [ABDOMINAL BIOELECTRICAL IMPEDANCE ANALYSIS AND ANTHROPOMETRY FOR PREDICTING METABOLIC SYNDROME IN MIDDLE AGED MEN].

    Science.gov (United States)

    Fernández-Vázquez, Rosalía; Millán Romero, Ángel; Barbancho, Miguel Ángel; Alvero-Cruz, José Ramón

    2015-09-01

    central obesity has a higher risk of metabolic syndrome. The present work aimed to study the relationship of trunk fat and the visceral fat index, and other anthropometric indices in relation to the metabolic syndrome in middle aged male Methods: design: transversal descriptive and correlational study. 75 male, volunteers who have access to a medical assessment, with an age range of 21 to 59 years, from different professions. Weight, height, body mass index, waist circumference, gluteal circumference, waist-to-hip ratio, waist-to-height ratio, trunk fat and visceral fat level by bioelectrical abdominal impedance analysis with Tanita AB-140 (ViScan) and biochemical markers: fasting glucose, total cholesterol, and triglycerides. Likewise, the systolic and diastolic blood pressure was measured. there are significant correlations of anthropometric measurements with trunk fat and visceral fat level and the same with biochemical variables. Receptor-operator curves (ROC curve) analysis shows that the cutoff points from which arises the metabolic syndrome are 32.7% of trunk fat and a level of visceral fat of 13 with a high sensitivity and specificity, attaining the same cut-off points for the metabolic syndrome and obesity status. trunk fat and visceral fat levels determined by bioelectrical abdominal impedance analysis, values are variables very sensitive and specific for the detection of metabolic syndrome and obesity, though not over the variables and anthropometric indices. In the condition of the overweight, trunk fat and visceral fat level are more predictive than anthropometric measures. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

  14. Predicting metabolic rate during level and uphill outdoor walking using a low-cost GPS receiver.

    Science.gov (United States)

    de Müllenheim, Pierre-Yves; Dumond, Rémy; Gernigon, Marie; Mahé, Guillaume; Lavenu, Audrey; Bickert, Sandrine; Prioux, Jacques; Noury-Desvaux, Bénédicte; Le Faucheur, Alexis

    2016-08-01

    The objective of this study was to assess the accuracy of using speed and grade data obtained from a low-cost global positioning system (GPS) receiver to estimate metabolic rate (MR) during level and uphill outdoor walking. Thirty young, healthy adults performed randomized outdoor walking for 6-min periods at 2.0, 3.5, and 5.0 km/h and on three different grades: 1) level walking, 2) uphill walking on a 3.7% mean grade, and 3) uphill walking on a 10.8% mean grade. The reference MR [metabolic equivalents (METs) and oxygen uptake (V̇o2)] values were obtained using a portable metabolic system. The speed and grade were obtained using a low-cost GPS receiver (1-Hz recording). The GPS grade (Δ altitude/distance walked) was calculated using both uncorrected GPS altitude data and GPS altitude data corrected with map projection software. The accuracy of predictions using reference speed and grade (actual[SPEED/GRADE]) data was high [R(2) = 0.85, root-mean-square error (RMSE) = 0.68 MET]. The accuracy decreased when GPS speed and uncorrected grade (GPS[UNCORRECTED]) data were used, although it remained substantial (R(2) = 0.66, RMSE = 1.00 MET). The accuracy was greatly improved when the GPS speed and corrected grade (GPS[CORRECTED]) data were used (R(2) = 0.82, RMSE = 0.79 MET). Published predictive equations for walking MR were also cross-validated using actual or GPS speed and grade data when appropriate. The prediction accuracy was very close when either actual[SPEED/GRADE] values or GPS[CORRECTED] values (for level and uphill combined) or GPS speed values (for level walking only) were used. These results offer promising research and clinical applications related to the assessment of energy expenditure during free-living walking. Copyright © 2016 the American Physiological Society.

  15. Predicting success of metabolic surgery: age, body mass index, C-peptide, and duration score.

    Science.gov (United States)

    Lee, Wei-Jei; Hur, Kyung Yul; Lakadawala, Muffazal; Kasama, Kazunori; Wong, Simon K H; Chen, Shu-Chun; Lee, Yi-Chih; Ser, Kong-Han

    2013-01-01

    Surgery is the most effective treatment of morbid obesity and leads to dramatic improvements in type 2 diabetes mellitus (T2DM). Gastrointestinal metabolic surgery has been proposed as a treatment option for T2DM. However, a grading system to categorize and predict the outcome of metabolic surgery is lacking. The study setting was a tertiary referral hospital (Taoyuan City, Taoyuan County, Taiwan). We first evaluated 63 patients and identified 4 factors that predicted the success of T2DM remission after bariatric surgery in this cohort: body mass index, C-peptide level, T2DM duration, and patient age. We used these variables to construct the Diabetes Surgery Score, a multidimensional 10-point scale along which greater scores indicate a better chance of T2DM remission. We then validated the index in a prospective collected cohort of 176 patients, using remission of T2DM at 1 year after surgery as the outcome variable. A total of 48 T2DM remissions occurred among the 63 patients and 115 remissions (65.3%) in the validation cohort. Patients with T2DM remission after surgery had a greater Diabetes Surgery Score than those without (8 ± 4 versus 4 ± 4, P Surgery Score also had a greater rate of success with T2DM remission (from 33% at score 0 to 100% at score 10); A 1-point increase in the Diabetes Surgery Score translated to an absolute 6.7% in the success rate. The Diabetes Surgery Score is a simple multidimensional grading system that can predict the success of T2DM treatment using bariatric surgery among patients with inadequately controlled T2DM. Copyright © 2013 American Society for Metabolic and Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

  16. Metabolic activity in the insular cortex and hypothalamus predicts hot flashes: an FDG-PET study.

    Science.gov (United States)

    Joffe, Hadine; Deckersbach, Thilo; Lin, Nancy U; Makris, Nikos; Skaar, Todd C; Rauch, Scott L; Dougherty, Darin D; Hall, Janet E

    2012-09-01

    Hot flashes are a common side effect of adjuvant endocrine therapies (AET; leuprolide, tamoxifen, aromatase inhibitors) that reduce quality of life and treatment adherence in breast cancer patients. Because hot flashes affect only some women, preexisting neurobiological traits might predispose to their development. Previous studies have implicated the insula during the perception of hot flashes and the hypothalamus in thermoregulatory dysfunction. The aim of the study was to understand whether neurobiological factors predict hot flashes. [18F]-Fluorodeoxyglucose (FDG) positron emission tomography (PET) brain scans coregistered with structural magnetic resonance imaging were used to determine whether metabolic activity in the insula and hypothalamic thermoregulatory and estrogen-feedback regions measured before and in response to AET predict hot flashes. Findings were correlated with CYP2D6 genotype because of CYP2D6 polymorphism associations with tamoxifen-induced hot flashes. We measured regional cerebral metabolic rate of glucose uptake (rCMRglu) in the insula and hypothalamus on FDG-PET. Of 18 women without hot flashes who began AET, new-onset hot flashes were reported by 10 (55.6%) and were detected objectively in nine (50%) participants. Prior to the use of all AET, rCMRglu in the insula (P ≤ 0.01) and hypothalamic thermoregulatory (P = 0.045) and estrogen-feedback (P = 0.007) regions was lower in women who reported developing hot flashes. In response to AET, rCMRglu was further reduced in the insula in women developing hot flashes (P ≤ 0.02). Insular and hypothalamic rCMRglu levels were lower in intermediate than extensive CYP2D6 metabolizers. Trait neurobiological characteristics predict hot flashes. Genetic variability in CYP2D6 may underlie the neurobiological predisposition to hot flashes induced by AET.

  17. Construction of Metabolism Prediction Models for CYP450 3A4, 2D6, and 2C9 Based on Microsomal Metabolic Reaction System

    Directory of Open Access Journals (Sweden)

    Shuai-Bing He

    2016-10-01

    Full Text Available During the past decades, there have been continuous attempts in the prediction of metabolism mediated by cytochrome P450s (CYP450s 3A4, 2D6, and 2C9. However, it has indeed remained a huge challenge to accurately predict the metabolism of xenobiotics mediated by these enzymes. To address this issue, microsomal metabolic reaction system (MMRS—a novel concept, which integrates information about site of metabolism (SOM and enzyme—was introduced. By incorporating the use of multiple feature selection (FS techniques (ChiSquared (CHI, InfoGain (IG, GainRatio (GR, Relief and hybrid classification procedures (Kstar, Bayes (BN, K-nearest neighbours (IBK, C4.5 decision tree (J48, RandomForest (RF, Support vector machines (SVM, AdaBoostM1, Bagging, metabolism prediction models were established based on metabolism data released by Sheridan et al. Four major biotransformations, including aliphatic C-hydroxylation, aromatic C-hydroxylation, N-dealkylation and O-dealkylation, were involved. For validation, the overall accuracies of all four biotransformations exceeded 0.95. For receiver operating characteristic (ROC analysis, each of these models gave a significant area under curve (AUC value >0.98. In addition, an external test was performed based on dataset published previously. As a result, 87.7% of the potential SOMs were correctly identified by our four models. In summary, four MMRS-based models were established, which can be used to predict the metabolism mediated by CYP3A4, 2D6, and 2C9 with high accuracy.

  18. Test accuracy of metabolic indicators in predicting decreased fertility in dairy cows

    DEFF Research Database (Denmark)

    Lomander, H; Gustafsson, H; Svensson, C

    2012-01-01

    results and fertility parameters were investigated using logistic regression. The NEFA and BHBA tests for ANEST and DFAI had the highest combined Se and Sp and were thus evaluated further. Cut-off values with Sp around 80% were used in this step to provide a reasonable number of test-positive cows...... was low when metabolic indicators measured as single values in early lactation were used to predict fertility in dairy cows, but accuracy was influenced by cow-level factors such as parity. The prevalence of the target condition (in this case, decreased fertility) also influences test usefulness...

  19. ANN Prediction of Metabolic Syndrome: a Complex Puzzle that will be Completed.

    Science.gov (United States)

    Ivanović, Darko; Kupusinac, Aleksandar; Stokić, Edita; Doroslovački, Rade; Ivetić, Dragan

    2016-12-01

    The diagnosis of metabolic syndrome (MetS) has a leading role in the early prevention of chronic disease, such as cardiovascular disease, type 2 diabetes, cancers and chronic kidney disease. It would be very greatful that MetS diagnosis can be predicted in everyday clinical practice. This paper presents artificial neural network (ANN) prediction of the diagnosis of MetS that includes solely non-invasive, low-cost and easily-obtained diagnostic methods. This solution can extract the risky persons and suggests complete tests only on them by saving money and time. ANN input vectors are very simple and contain solely non-invasive, low-cost and easily-obtained parameters: gender, age, body mass index, waist-to-height ratio, systolic and diastolic blood pressures. ANN output is M e t S-coefficient in true/false form, obtained from MetS definition of International Diabetes Federation (IDF). ANN training, validation and testing are conducted on the large dataset that includes 2928 persons. Feed-forward ANNs with 1-100 hidden neurons were considered and an optimal architecture were determinated. Comparison with other authors leads to the conclusion that our solution achieves the highest positive predictive value P P V = 0.8579. Further, obtained negative predictive value N P V = 0.8319 is also high and close to PPV, which means that our ANN solution is suitable both for positive and negative MetS prediction.

  20. Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.

    Directory of Open Access Journals (Sweden)

    Hannah Slater

    Full Text Available Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic disease, lymphatic filariasis (LF, in Africa, and to estimate how future changes in climate and population could affect its spread and burden across the continent. We used 508 community-specific infection presence data collated from the published literature in conjunction with five predictive environmental/climatic and demographic variables, and a maximum entropy niche modelling method to construct the first ecological niche maps describing potential distribution and burden of LF in Africa. We also ran the best-fit model against climate projections made by the HADCM3 and CCCMA models for 2050 under A2a and B2a scenarios to simulate the likely distribution of LF under future climate and population changes. We predict a broad geographic distribution of LF in Africa extending from the west to the east across the middle region of the continent, with high probabilities of occurrence in the Western Africa compared to large areas of medium probability interspersed with smaller areas of high probability in Central and Eastern Africa and in Madagascar. We uncovered complex relationships between predictor ecological niche variables and the probability of LF occurrence. We show for the first time that predicted climate change and population growth will expand both the range and risk of LF infection (and ultimately disease in an endemic region. We estimate that populations at risk to LF may range from 543 and 804 million currently, and that this could rise to between 1.65 to 1.86 billion in the future depending on the climate scenario used and thresholds applied to signify infection presence.

  1. Incremental Predictive Value of Serum AST-to-ALT Ratio for Incident Metabolic Syndrome: The ARIRANG Study

    Science.gov (United States)

    Ahn, Song Vogue; Baik, Soon Koo; Cho, Youn zoo; Koh, Sang Baek; Huh, Ji Hye; Chang, Yoosoo; Sung, Ki-Chul; Kim, Jang Young

    2016-01-01

    Aims The ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT) is of great interest as a possible novel marker of metabolic syndrome. However, longitudinal studies emphasizing the incremental predictive value of the AST-to-ALT ratio in diagnosing individuals at higher risk of developing metabolic syndrome are very scarce. Therefore, our study aimed to evaluate the AST-to-ALT ratio as an incremental predictor of new onset metabolic syndrome in a population-based cohort study. Material and Methods The population-based cohort study included 2276 adults (903 men and 1373 women) aged 40–70 years, who participated from 2005–2008 (baseline) without metabolic syndrome and were followed up from 2008–2011. Metabolic syndrome was defined according to the harmonized definition of metabolic syndrome. Serum concentrations of AST and ALT were determined by enzymatic methods. Results During an average follow-up period of 2.6-years, 395 individuals (17.4%) developed metabolic syndrome. In a multivariable adjusted model, the odds ratio (95% confidence interval) for new onset of metabolic syndrome, comparing the fourth quartile to the first quartile of the AST-to-ALT ratio, was 0.598 (0.422–0.853). The AST-to-ALT ratio also improved the area under the receiver operating characteristic curve (AUC) for predicting new cases of metabolic syndrome (0.715 vs. 0.732, P = 0.004). The net reclassification improvement of prediction models including the AST-to-ALT ratio was 0.23 (95% CI: 0.124–0.337, Pmetabolic syndrome and had incremental predictive value for incident metabolic syndrome. PMID:27560931

  2. Incremental Predictive Value of Serum AST-to-ALT Ratio for Incident Metabolic Syndrome: The ARIRANG Study.

    Science.gov (United States)

    Yadav, Dhananjay; Choi, Eunhee; Ahn, Song Vogue; Baik, Soon Koo; Cho, Youn Zoo; Koh, Sang Baek; Huh, Ji Hye; Chang, Yoosoo; Sung, Ki-Chul; Kim, Jang Young

    2016-01-01

    The ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT) is of great interest as a possible novel marker of metabolic syndrome. However, longitudinal studies emphasizing the incremental predictive value of the AST-to-ALT ratio in diagnosing individuals at higher risk of developing metabolic syndrome are very scarce. Therefore, our study aimed to evaluate the AST-to-ALT ratio as an incremental predictor of new onset metabolic syndrome in a population-based cohort study. The population-based cohort study included 2276 adults (903 men and 1373 women) aged 40-70 years, who participated from 2005-2008 (baseline) without metabolic syndrome and were followed up from 2008-2011. Metabolic syndrome was defined according to the harmonized definition of metabolic syndrome. Serum concentrations of AST and ALT were determined by enzymatic methods. During an average follow-up period of 2.6-years, 395 individuals (17.4%) developed metabolic syndrome. In a multivariable adjusted model, the odds ratio (95% confidence interval) for new onset of metabolic syndrome, comparing the fourth quartile to the first quartile of the AST-to-ALT ratio, was 0.598 (0.422-0.853). The AST-to-ALT ratio also improved the area under the receiver operating characteristic curve (AUC) for predicting new cases of metabolic syndrome (0.715 vs. 0.732, P = 0.004). The net reclassification improvement of prediction models including the AST-to-ALT ratio was 0.23 (95% CI: 0.124-0.337, Pmetabolic syndrome and had incremental predictive value for incident metabolic syndrome.

  3. Quality of relationships with parents and friends in adolescence predicts metabolic risk in young adulthood.

    Science.gov (United States)

    Ehrlich, Katherine B; Hoyt, Lindsay Till; Sumner, Jennifer A; McDade, Thomas W; Adam, Emma K

    2015-09-01

    This study was designed to examine whether family and peer relationships in adolescence predict the emergence of metabolic risk factors in young adulthood. Participants from a large, nationally representative cohort study (N = 11,617 for these analyses) reported on their relationship experiences with parents and close friends during adolescence. Fourteen years later, interviewers collected blood samples, as well as anthropometric and blood pressure measurements. Blood samples were analyzed for HbA1c. Ordered logistic regressions revealed that for females, supportive parent-child relationships and close male friendships in adolescence were associated with reduced odds of having elevated metabolic risk markers in young adulthood. These effects remained significant even after controlling for baseline measures of body mass index (BMI) and health and demographic covariates. The protective effects of close relationships were not significant for males, however. Exploratory analyses with 2-parent families revealed that supportive father-child relationships were especially protective for females. These findings suggest that, for females, close and supportive relationships with parents and male friends in adolescence may reduce the risk of metabolic dysregulation in adulthood. (c) 2015 APA, all rights reserved).

  4. The Severity of Fatty Liver Disease Relating to Metabolic Abnormalities Independently Predicts Coronary Calcification

    International Nuclear Information System (INIS)

    Lee, Ying-Hsiang; Wu, Yih-Jer; Liu, Chuan-Chuan; Hou, Charles Jia-Yin; Yeh, Hung-I.; Tsai, Cheng-Ho; Shih, Shou-Chuan; Hung, Chung-Lieh

    2011-01-01

    Background. Nonalcoholic fatty liver disease (NAFLD) is one of the metabolic disorders presented in liver. The relationship between severity of NAFLD and coronary atherosclerotic burden remains largely unknown. Methods and Materials. We analyzed subjects undergoing coronary calcium score evaluation by computed tomography (MDCT) and fatty liver assessment using abdominal ultrasonography. Framingham risk score (FRS) and metabolic risk score (MRS) were obtained in all subjects. A graded, semiquantitative score was established to quantify the severity of NAFLD. Multivariate logistic regression analysis was used to depict the association between NAFLD and calcium score. Results. Of all, 342 participants (female: 22.5%, mean age: 48.7 ± 7.0 years) met the sufficient information rendering detailed analysis. The severity of NAFLD was positively associated with MRS (X 2 = 6.12, trend P < 0.001) and FRS (X 2 = 5.88, trend P < 0.001). After multivariable adjustment for clinical variables and life styles, the existence of moderate to severe NAFLD was independently associated with abnormal calcium score (P < 0.05). Conclusion. The severity of NAFLD correlated well with metabolic abnormality and was independently predict coronary calcification beyond clinical factors. Our data suggests that NAFLD based on ultrasonogram could positively reflect the burden of coronary calcification

  5. Hierarchical Status Predicts Behavioral Vulnerability and Nucleus Accumbens Metabolic Profile Following Chronic Social Defeat Stress.

    Science.gov (United States)

    Larrieu, Thomas; Cherix, Antoine; Duque, Aranzazu; Rodrigues, João; Lei, Hongxia; Gruetter, Rolf; Sandi, Carmen

    2017-07-24

    Extensive data highlight the existence of major differences in individuals' susceptibility to stress [1-4]. While genetic factors [5, 6] and exposure to early life stress [7, 8] are key components for such neurobehavioral diversity, intriguing observations revealed individual differences in response to stress in inbred mice [9-12]. This raised the possibility that other factors might be critical in stress vulnerability. A key challenge in the field is to identify non-invasively risk factors for vulnerability to stress. Here, we investigated whether behavioral factors, emerging from preexisting dominance hierarchies, could predict vulnerability to chronic stress [9, 13-16]. We applied a chronic social defeat stress (CSDS) model of depression in C57BL/6J mice to investigate the predictive power of hierarchical status to pinpoint which individuals will exhibit susceptibility to CSDS. Given that the high social status of dominant mice would be the one particularly challenged by CSDS, we predicted and found that dominant individuals were the ones showing a strong susceptibility profile as indicated by strong social avoidance following CSDS, while subordinate mice were not affected. Data from 1 H-NMR spectroscopy revealed that the metabolic profile in the nucleus accumbens (NAc) relates to social status and vulnerability to stress. Under basal conditions, subordinates show lower levels of energy-related metabolites compared to dominants. In subordinates, but not dominants, levels of these metabolites were increased after exposure to CSDS. To the best of our knowledge, this is the first study that identifies non-invasively the origin of behavioral risk factors predictive of stress-induced depression-like behaviors associated with metabolic changes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Water quality of Danube Delta systems: ecological status and prediction using machine-learning algorithms.

    Science.gov (United States)

    Stoica, C; Camejo, J; Banciu, A; Nita-Lazar, M; Paun, I; Cristofor, S; Pacheco, O R; Guevara, M

    2016-01-01

    Environmental issues have a worldwide impact on water bodies, including the Danube Delta, the largest European wetland. The Water Framework Directive (2000/60/EC) implementation operates toward solving environmental issues from European and national level. As a consequence, the water quality and the biocenosis structure was altered, especially the composition of the macro invertebrate community which is closely related to habitat and substrate heterogeneity. This study aims to assess the ecological status of Southern Branch of the Danube Delta, Saint Gheorghe, using benthic fauna and a computational method as an alternative for monitoring the water quality in real time. The analysis of spatial and temporal variability of unicriterial and multicriterial indices were used to assess the current status of aquatic systems. In addition, chemical status was characterized. Coliform bacteria and several chemical parameters were used to feed machine-learning (ML) algorithms to simulate a real-time classification method. Overall, the assessment of the water bodies indicated a moderate ecological status based on the biological quality elements or a good ecological status based on chemical and ML algorithms criteria.

  7. On Extrapolating Past the Range of Observed Data When Making Statistical Predictions in Ecology.

    Directory of Open Access Journals (Sweden)

    Paul B Conn

    Full Text Available Ecologists are increasingly using statistical models to predict animal abundance and occurrence in unsampled locations. The reliability of such predictions depends on a number of factors, including sample size, how far prediction locations are from the observed data, and similarity of predictive covariates in locations where data are gathered to locations where predictions are desired. In this paper, we propose extending Cook's notion of an independent variable hull (IVH, developed originally for application with linear regression models, to generalized regression models as a way to help assess the potential reliability of predictions in unsampled areas. Predictions occurring inside the generalized independent variable hull (gIVH can be regarded as interpolations, while predictions occurring outside the gIVH can be regarded as extrapolations worthy of additional investigation or skepticism. We conduct a simulation study to demonstrate the usefulness of this metric for limiting the scope of spatial inference when conducting model-based abundance estimation from survey counts. In this case, limiting inference to the gIVH substantially reduces bias, especially when survey designs are spatially imbalanced. We also demonstrate the utility of the gIVH in diagnosing problematic extrapolations when estimating the relative abundance of ribbon seals in the Bering Sea as a function of predictive covariates. We suggest that ecologists routinely use diagnostics such as the gIVH to help gauge the reliability of predictions from statistical models (such as generalized linear, generalized additive, and spatio-temporal regression models.

  8. Metabolism

    Science.gov (United States)

    ... functions: Anabolism (uh-NAB-uh-liz-um), or constructive metabolism, is all about building and storing. It ... in infants and young children. Hypothyroidism slows body processes and causes fatigue (tiredness), slow heart rate, excessive ...

  9. Metabolism

    Science.gov (United States)

    ... a particular food provides to the body. A chocolate bar has more calories than an apple, so ... acid phenylalanine, needed for normal growth and protein production). Inborn errors of metabolism can sometimes lead to ...

  10. Using hematogram model to predict future metabolic syndrome in elderly: a 4-year longitudinal study.

    Science.gov (United States)

    Fu, Yu-Hsiang; Hsu, Chun-Hsien; Lin, Jiunn-Diann; Hsieh, Chang-Hsun; Wu, Chung-Ze; Chao, Ting-Ting; Pei, Dee; Liang, Yao-Jen; Wang, Kun; Chen, Yen-Lin

    2015-03-01

    The metabolic syndrome (MetS) is proposed to predict future occurrence of cardiovascular diseases and diabetes. There are some other "non-traditional" risk factors such as hematogram components that are also related to the same endpoints as MetS. In this four-year longitudinal study, we used hematogram components to build models for predicting future occurrence of MetS in older men and women separately. Subjects above 65 years without MetS and related diseases were enrolled. All subjects were followed up until they developed MetS or until up to four years from the day of entry, whichever was earlier. Among the 4539 study participants, 1327 developed MetS. Models were built for men and women separately and the areas under the receiver operation curves were significant. The Kaplan-Meier plot showed that the models could predict future MetS. Finally, Cox regression analysis showed that the hematogram model was correlated to future MetS with hazard ratios of 1.567 and 1.738 in men and women, respectively. Our hematogram models could significantly predict future MetS in elderly and might be more practical and convenient for daily clinical practice.

  11. Predicting suitable habitat of the Chinese monal (Lophophorus lhuysii) using ecological niche modeling in the Qionglai Mountains, China.

    Science.gov (United States)

    Wang, Bin; Xu, Yu; Ran, Jianghong

    2017-01-01

    Understanding the distribution and the extent of suitable habitats is crucial for wildlife conservation and management. Knowledge is limited regarding the natural habitats of the Chinese monal ( Lophophorus lhuysii ), which is a vulnerable Galliform species endemic to the high-montane areas of southwest China and a good candidate for being an umbrella species in the Qionglai Mountains. Using ecological niche modeling, we predicted current potential suitable habitats for the Chinese monal in the Qionglai Mountains with 64 presence points collected between 2005 and 2015. Suitable habitats of the Chinese monal were associated with about 31 mm precipitation of the driest quarter, about 15 °C of maximum temperature of the warmest month, and far from the nearest human residential locations (>5,000 m). The predicted suitable habitats of the Chinese monal covered an area of 2,490 km 2 , approximately 9.48% of the Qionglai Mountains, and was highly fragmented. 54.78% of the suitable habitats were under the protection of existing nature reserves and two conservation gaps were found. Based on these results, we provide four suggestions for the conservation management of the Chinese monal: (1) ad hoc surveys targeting potential suitable habitats to determine species occurrence, (2) more ecological studies regarding its dispersal capacity, (3) establishment of more corridors and green bridges across roads for facilitating species movement or dispersal, and (4) minimization of local disturbances.

  12. Temperature dependence of planktonic metabolism in the ocean

    Science.gov (United States)

    Regaudie-De-Gioux, A.; Duarte, C. M.

    2012-03-01

    Standard metabolic theory predicts that both respiration and photosynthesis should increase with increasing temperature, albeit at different rates. However, test of this prediction for ocean planktonic communities is limited, despite the broad consequences of this prediction in the present context of global ocean warming. We compiled a large data set on volumetric planktonic metabolism in the open ocean and tested the relationship between specific metabolic rates and water temperature. The relationships derived are consistent with predictions derived from metabolic theory of ecology, yielding activation energy for planktonic metabolism consistent with predictions from the metabolic theory. These relationships can be used to predict the effect of warming on ocean metabolism and, thus, the role of planktonic communities in the flow of carbon in the global ocean.

  13. Standard Metabolic Rate (SMR) is inversely related to erythrocyte and genome size in allopolyploid fish of the Cobitis taenia hybrid complex

    OpenAIRE

    Maciak, S.; Janko, K. (Karel); Kotusz, J.; Choleva, L. (Lukáš); Boron, A.; Juchno, D.; Kujawa, R.; Kozlowski, J.; Konarzewski, M.

    2011-01-01

    As a first approximation, whole-body metabolic rate can be considered as the sum of metabolic rates of constituent cells. Yet, among several current explanations of metabolic rate scaling, only two explicitly invoke cell architecture of organisms: (1) the Metabolic Theory of Ecology, which predicts size invariance of metabolically active cells, such as erythrocytes and (2) the cell metabolism hypothesis postulating partial dependence of metabolic scaling on the cell size (CS), which is mediat...

  14. The utilisation of structural descriptors to predict metabolic constants of xenobiotics in mammals.

    Science.gov (United States)

    Pirovano, Alessandra; Brandmaier, Stefan; Huijbregts, Mark A J; Ragas, Ad M J; Veltman, Karin; Hendriks, A Jan

    2015-01-01

    Quantitative structure-activity relationships (QSARs) were developed to predict the Michaelis-Menten constant (Km) and the maximum reaction rate (Vmax) of xenobiotics metabolised by four enzyme classes in mammalian livers: alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO), and cytochrome P450 (CYP). Metabolic constants were gathered from the literature and a genetic algorithm was employed to select at most six predictors from a pool of over 2000 potential molecular descriptors using two-thirds of the xenobiotics in each enzyme class. The resulting multiple linear models were cross-validated using the remaining one-third of the compounds. The explained variances (R(2)adj) of the QSARs were between 50% and 80% and the predictive abilities (R(2)ext) between 50% and 60%, except for the Vmax QSAR of FMO with both R(2)adj and R(2)ext less than 30%. The Vmax values of FMO were independent of substrate chemical structure because the rate-limiting step of its catalytic cycle occurs before compound oxidation. For the other enzymes, Vmax was predominantly determined by functional groups or fragments and electronic properties because of the strong and chemical-specific interactions involved in the metabolic reactions. The most relevant predictors for Km were functional groups or fragments for the enzymes metabolising specific compounds (ADH, ALDH and FMO) and size and shape properties for CYP, likely because of the broad substrate specificity of CYP enzymes. The present study can be helpful to predict the Km and Vmax of four important oxidising enzymes in mammals and better understand the underlying principles of chemical transformation by liver enzymes. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Predicting antisocial behavior among latino young adolescents: an ecological systems analysis.

    Science.gov (United States)

    Eamon, Mary Keegan; Mulder, Cray

    2005-01-01

    The authors used data from a national sample of 420 Latino young adolescents to examine multiple predictors of antisocial behavior within an ecological systems framework. They found that boys and youths who lived a higher proportion of their life in poverty exhibited higher levels of antisocial behavior, and mothers' acculturation was associated with lower levels. Neighborhood and school environments, exposure to deviant peer pressure, and 3 parenting practices--parent-youth attachment, physical punishment, and mothers' monitoring--were related to Latino youth antisocial behavior. Neighborhood quality and peer pressure explained the relation between poverty and an increased risk for antisocial behavior.

  16. PERPEST Version 1.0, manual and technical description; a model that predicts the ecological risks of pesticides in freshwater ecosystems

    NARCIS (Netherlands)

    Nes, van E.H.; Brink, van den P.J.

    2003-01-01

    This report is a technical description and a user-manual of the PERPEST model, able to Predicts the Ecological Risks of PESTicides in freshwater ecosystems. This system predicts the effects of a particular concentration of a pesticide on various (community) endpoints, based on empirical data

  17. Predicting the sensitivity of populations from individual exposure to chemicals: the role of ecological interactions.

    Science.gov (United States)

    Gabsi, Faten; Schäffer, Andreas; Preuss, Thomas G

    2014-07-01

    Population responses to chemical stress exposure are influenced by nonchemical, environmental processes such as species interactions. A realistic quantification of chemical toxicity to populations calls for the use of methodologies that integrate these multiple stress effects. The authors used an individual-based model for Daphnia magna as a virtual laboratory to determine the influence of ecological interactions on population sensitivity to chemicals with different modes of action on individuals. In the model, hypothetical chemical toxicity targeted different vital individual-level processes: reproduction, survival, feeding rate, or somatic growth rate. As for species interactions, predatory and competition effects on daphnid populations were implemented following a worst-case approach. The population abundance was simulated at different food levels and exposure scenarios, assuming exposure to chemical stress solely or in combination with either competition or predation. The chemical always targeted one vital endpoint. Equal toxicity-inhibition levels differently affected the population abundance with and without species interactions. In addition, population responses to chemicals were highly sensitive to the environmental stressor (predator or competitor) and to the food level. Results show that population resilience cannot be attributed to chemical stress only. Accounting for the relevant ecological interactions would reduce uncertainties when extrapolating effects of chemicals from individuals to the population level. Validated population models should be used for a more realistic risk assessment of chemicals. © 2014 SETAC.

  18. Predicting ecological responses of the Florida Everglades to possible future climate scenarios: Introduction

    Science.gov (United States)

    Aumen, Nicholas G.; Havens, Karl E; Best, G. Ronnie; Berry, Leonard

    2015-01-01

    Florida’s Everglades stretch from the headwaters of the Kissimmee River near Orlando to Florida Bay. Under natural conditions in this flat landscape, water flowed slowly downstream as broad, shallow sheet flow. The ecosystem is markedly different now, altered by nutrient pollution and construction of canals, levees, and water control structures designed for flood control and water supply. These alterations have resulted in a 50 % reduction of the ecosystem’s spatial extent and significant changes in ecological function in the remaining portion. One of the world’s largest restoration programs is underway to restore some of the historic hydrologic and ecological functions of the Everglades, via a multi-billion dollar Comprehensive Everglades Restoration Plan. This plan, finalized in 2000, did not explicitly consider climate change effects, yet today we realize that sea level rise and future changes in rainfall (RF), temperature, and evapotranspiration (ET) may have system-wide impacts. This series of papers describes results of a workshop where a regional hydrologic model was used to simulate the hydrology expected in 2060 with climate changes including increased temperature, ET, and sea level, and either an increase or decrease in RF. Ecologists with expertise in various areas of the ecosystem evaluated the hydrologic outputs, drew conclusions about potential ecosystem responses, and identified research needs where projections of response had high uncertainty. Resource managers participated in the workshop, and they present lessons learned regarding how the new information might be used to guide Everglades restoration in the context of climate change.

  19. Energy storage and fecundity explain deviations from ecological stoichiometry predictions under global warming and size-selective predation.

    Science.gov (United States)

    Zhang, Chao; Jansen, Mieke; De Meester, Luc; Stoks, Robby

    2016-11-01

    stoichiometry, largely by changing levels of energy storage molecules. Our results highlight that two widespread patterns, the trade-off between rapid development and energy storage and the increased investment in reproduction under size-selective predation, cause predictable deviations from current ecological stoichiometry theory. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

  20. Prediction of Metabolic Pathway Involvement in Prokaryotic UniProtKB Data by Association Rule Mining

    KAUST Repository

    Boudellioua, Imene

    2016-07-08

    The widening gap between known proteins and their functions has encouraged the development of methods to automatically infer annotations. Automatic functional annotation of proteins is expected to meet the conflicting requirements of maximizing annotation coverage, while minimizing erroneous functional assignments. This trade-off imposes a great challenge in designing intelligent systems to tackle the problem of automatic protein annotation. In this work, we present a system that utilizes rule mining techniques to predict metabolic pathways in prokaryotes. The resulting knowledge represents predictive models that assign pathway involvement to UniProtKB entries. We carried out an evaluation study of our system performance using cross-validation technique. We found that it achieved very promising results in pathway identification with an F1-measure of 0.982 and an AUC of 0.987. Our prediction models were then successfully applied to 6.2 million UniProtKB/TrEMBL reference proteome entries of prokaryotes. As a result, 663,724 entries were covered, where 436,510 of them lacked any previous pathway annotations.

  1. Visceral Fat Area and Serum Adiponectin Level Predict the Development of Metabolic Syndrome in a Community-Based Asymptomatic Population.

    Directory of Open Access Journals (Sweden)

    Sang-A Cho

    Full Text Available Although it has been demonstrated that visceral adipose tissue content and serum levels of adiponectin are associated with metabolic syndrome, their predictive potential for the development of metabolic syndrome remains to be elucidated.We studied 1,130 participants of the Seoul Metabolic Syndrome cohort. A total of 337 subjects without metabolic syndrome underwent the follow-up evaluation and finally analyzed. Visceral fat area (VFA was measured using dual bioelectrical impedance analysis. We compared the 1-year incidence rate of metabolic syndrome among four different groups: Group 1 (high adiponectin level and low VFA, Group 2 (low adiponectin level and low VFA, Group 3 (high adiponectin level and high VFA and Group 4 (low adiponectin level and high VFA.Median follow-up duration was 17 months. Cut-off points of adiponectin level and VFA for metabolic syndrome were 7.34 ng/ml and 84 cm2 for men, and 12.55 and 58 cm2 ng/ml for women, respectively. The incidence of metabolic syndrome was the highest in Group 4 (Group 1; 16.47%, Group 2; 22.08%, Group 3; 25%, and Group 4; 46.15%, p<0.001. Adjusted logistic regression analyses for metabolic syndrome prediction demonstrated that Group 4 exhibited the highest odds ratio compared with Group 1 (4.918 [2.05-11.795], which was predominantly affected by waist circumference and serum triglyceride levels. Notably, triglyceride/high-density lipoprotein cholesterol (TG/HDL ratio was significantly higher in Group 4 (p = 0.017.Incidence rate of metabolic syndrome was the highest in subjects with low serum adiponectin levels and high visceral fat area. Higher TG/HDL ratio in these subjects suggested insulin resistance may contribute to the development of metabolic syndrome.

  2. Fat oxidation at rest predicts peak fat oxidation during exercise and metabolic phenotype in overweight men

    DEFF Research Database (Denmark)

    Rosenkilde, M; Nordby, P; Nielsen, L B

    2010-01-01

    OBJECTIVE: To elucidate if fat oxidation at rest predicts peak fat oxidation during exercise and/or metabolic phenotype in moderately overweight, sedentary men. DESIGN: Cross-sectional study.Subjects:We measured respiratory exchange ratio (RER) at rest in 44 moderately overweight, normotensive...... and normoglycemic men and selected 8 subjects with a low RER (L-RER, body mass index (BMI): 27.9+/-0.9 kg m(-2), RER: 0.76+/-0.02) and 8 with a high RER (H-RER; BMI 28.1+/-1.1 kg m(-2), RER: 0.89+/-0.02). After an overnight fast, a venous blood sample was obtained and a graded exercise test was performed. Fat...... oxidation during exercise was quantified using indirect calorimetry. RESULTS: Peak fat oxidation during exercise was higher in L-RER than in H-RER (0.333+/-0.096 vs 0.169+/-0.028 g min(-1); P

  3. A validated disease specific prediction equation for resting metabolic rate in underweight patients with COPD

    Directory of Open Access Journals (Sweden)

    Anita Nordenson

    2010-09-01

    Full Text Available Anita Nordenson2, Anne Marie Grönberg1,2, Lena Hulthén1, Sven Larsson2, Frode Slinde11Department of Clinical Nutrition, Sahlgrenska Academy at University of Gothenburg, Göteborg, Sweden; 2Department of Internal Medicine/Respiratory Medicine and Allergology, Sahlgrenska Academy at University of Gothenburg, SwedenAbstract: Malnutrition is a serious condition in chronic obstructive pulmonary disease (COPD. Successful dietary intervention calls for calculations of resting metabolic rate (RMR. One disease-specific prediction equation for RMR exists based on mainly male patients. To construct a disease-specific equation for RMR based on measurements in underweight or weight-losing women and men with COPD, RMR was measured by indirect calorimetry in 30 women and 11 men with a diagnosis of COPD and body mass index <21 kg/m2. The following variables, possibly influencing RMR were measured: length, weight, middle upper arm circumference, triceps skinfold, body composition by dual energy x-ray absorptiometry and bioelectrical impedance, lung function, and markers of inflammation. Relations between RMR and measured variables were studied using univariate analysis according to Pearson. Gender and variables that were associated with RMR with a P value <0.15 were included in a forward multiple regression analysis. The best-fit multiple regression equation included only fat-free mass (FFM: RMR (kJ/day = 1856 + 76.0 FFM (kg. To conclude, FFM is the dominating factor influencing RMR. The developed equation can be used for prediction of RMR in underweight COPD patients.Keywords: pulmonary disease, chronic obstructive, basal metabolic rate, malnutrition, body composition

  4. Brain metabolic maps in Mild Cognitive Impairment predict heterogeneity of progression to dementia

    Directory of Open Access Journals (Sweden)

    Chiara Cerami

    2015-01-01

    Full Text Available [18F]FDG-PET imaging has been recognized as a crucial diagnostic marker in Mild Cognitive Impairment (MCI, supporting the presence or the exclusion of Alzheimer's Disease (AD pathology. A clinical heterogeneity, however, underlies MCI definition. In this study, we aimed to evaluate the predictive role of single-subject voxel-based maps of [18F]FDG distribution generated through statistical parametric mapping (SPM in the progression to different dementia subtypes in a sample of 45 MCI. Their scans were compared to a large normal reference dataset developed and validated for comparison at single-subject level. Additionally, Aβ42 and Tau CSF values were available in 34 MCI subjects. Clinical follow-up (mean 28.5 ± 7.8 months assessed subsequent progression to AD or non-AD dementias. The SPM analysis showed: 1 normal brain metabolism in 14 MCI cases, none of them progressing to dementia; 2 the typical temporo-parietal pattern suggestive for prodromal AD in 15 cases, 11 of them progressing to AD; 3 brain hypometabolism suggestive of frontotemporal lobar degeneration (FTLD subtypes in 7 and dementia with Lewy bodies (DLB in 2 subjects (all fulfilled FTLD or DLB clinical criteria at follow-up; and 4 7 MCI cases showed a selective unilateral or bilateral temporo-medial hypometabolism without the typical AD pattern, and they all remained stable. In our sample, objective voxel-based analysis of [18F]FDG-PET scans showed high predictive prognostic value, by identifying either normal brain metabolism or hypometabolic patterns suggestive of different underlying pathologies, as confirmed by progression at follow-up. These data support the potential usefulness of this SPM [18F]FDG PET analysis in the early dementia diagnosis and for improving subject selection in clinical trials based on MCI definition.

  5. Timing of stage II lactogenesis is predicted by antenatal metabolic health in a cohort of primiparas.

    Science.gov (United States)

    Nommsen-Rivers, Laurie A; Dolan, Lawrence M; Huang, Bin

    2012-02-01

    Time to onset of stage II lactogenesis varies widely, and delayed onset of lactogenesis (OL) is common among first-time mothers in the United States. Higher body mass index, older age, and larger infant birth weight are identified risk factors for delayed OL; all are known correlates with glucose metabolism. Our objective was to prenatally assess maternal biomarkers related to metabolic health and determine the extent to which these biomarkers predict timing of OL. We enrolled a population-based sample of expectant primiparas attending a single prenatal clinic. We obtained a blood sample 1-hour post-glucose load from an antenatal oral glucose challenge test and assayed for the following biomarkers: serum insulin, glucose, adiponectin, leptin, C-reactive protein, interleukin-6, resistin, and tumor necrosis factor-α. Our outcome measure was timing of OL, based on maternal report at 3-5 days postpartum. We used linear regression to model OL hour. Twenty-six of 29 (90%) agreed to screening, 18 delivered at term and initiated breastfeeding, and 16 have complete data. Median (minimum-maximum) postpartum body mass index was 27.4 (21.8-34.7) kg/m(2), and median time to OL was 64 (10-121) hours. The model, OL = 232 - 34.9(ln[ratio insulin/glucose]) - 1.4(adiponectin), explained 56% of the variation in OL hour (p = 0.005) and was not weakened by potential confounders. Higher serum insulin secretion relative to serum glucose after a glucose challenge and higher serum adiponectin are associated with earlier onset of OL. These findings suggest that factors associated with better glucose tolerance predict earlier OL.

  6. Predicted distribution of major malaria vectors belonging to the Anopheles dirus complex in Asia: ecological niche and environmental influences.

    Science.gov (United States)

    Obsomer, Valerie; Defourny, Pierre; Coosemans, Marc

    2012-01-01

    Methods derived from ecological niche modeling allow to define species distribution based on presence-only data. This is particularly useful to develop models from literature records such as available for the Anopheles dirus complex, a major group of malaria mosquito vectors in Asia. This research defines an innovative modeling design based on presence-only model and hierarchical framework to define the distribution of the complex and attempt to delineate sibling species distribution and environmental preferences. At coarse resolution, the potential distribution was defined using slow changing abiotic factors such as topography and climate representative for the timescale covered by literature records of the species. The distribution area was then refined in a second step using a mask of current suitable land cover. Distribution area and ecological niche were compared between species and environmental factors tested for relevance. Alternatively, extreme values at occurrence points were used to delimit environmental envelopes. The spatial distribution for the complex was broadly consistent with its known distribution and influencing factors included temperature and rainfall. If maps developed from environmental envelopes gave similar results to modeling when the number of sites was high, the results were less similar for species with low number of recorded presences. Using presence-only models and hierarchical framework this study not only predicts the distribution of a major malaria vector, but also improved ecological modeling analysis design and proposed final products better adapted to malaria control decision makers. The resulting maps can help prioritizing areas which need further investigation and help simulate distribution under changing conditions such as climate change or reforestation. The hierarchical framework results in two products one abiotic based model describes the potential maximal distribution and remains valid for decades and the other

  7. Predicted distribution of major malaria vectors belonging to the Anopheles dirus complex in Asia: ecological niche and environmental influences.

    Directory of Open Access Journals (Sweden)

    Valerie Obsomer

    Full Text Available Methods derived from ecological niche modeling allow to define species distribution based on presence-only data. This is particularly useful to develop models from literature records such as available for the Anopheles dirus complex, a major group of malaria mosquito vectors in Asia. This research defines an innovative modeling design based on presence-only model and hierarchical framework to define the distribution of the complex and attempt to delineate sibling species distribution and environmental preferences. At coarse resolution, the potential distribution was defined using slow changing abiotic factors such as topography and climate representative for the timescale covered by literature records of the species. The distribution area was then refined in a second step using a mask of current suitable land cover. Distribution area and ecological niche were compared between species and environmental factors tested for relevance. Alternatively, extreme values at occurrence points were used to delimit environmental envelopes. The spatial distribution for the complex was broadly consistent with its known distribution and influencing factors included temperature and rainfall. If maps developed from environmental envelopes gave similar results to modeling when the number of sites was high, the results were less similar for species with low number of recorded presences. Using presence-only models and hierarchical framework this study not only predicts the distribution of a major malaria vector, but also improved ecological modeling analysis design and proposed final products better adapted to malaria control decision makers. The resulting maps can help prioritizing areas which need further investigation and help simulate distribution under changing conditions such as climate change or reforestation. The hierarchical framework results in two products one abiotic based model describes the potential maximal distribution and remains valid for decades

  8. Validity of predictive equations for resting metabolic rate in healthy older adults.

    Science.gov (United States)

    Itoi, Aya; Yamada, Yosuke; Yokoyama, Keiichi; Adachi, Tetsuji; Kimura, Misaka

    2017-12-01

    Accurate estimation of energy expenditure in older people is important for nutritional support. The current literature contains controversial or inconsistent data regarding the resting metabolic rate (RMR, or basal metabolic rate) in older adults, including the relationship between the RMR and ethnicity. Little information about the RMR in healthy Asian older adults is available. This study was performed to examine the RMR in healthy Japanese older adults and compare it with previously established 16 equations. Thirty-two community-dwelling, healthy, and active elderly Japanese adults were enrolled (age, 64-87 years; 14 men, 18 women; mean height, 154.9 ± 8.9 cm; mean weight, 53.5 ± 9.1 kg; mean body mass index, 22.2 ± 2.5 kg/m 2 ). The RMR was measured by indirect calorimetry. The measured RMR was compared among 16 equations. Correlation analysis, a paired t test, and a Bland-Altman plot were used to assess the agreement among the equations. The average RMR was 1132 ± 178 kcal/day with 2233 ± 437 kcal/day average total energy expenditure (TEE) measured by doubly labeled water (DLW). The smallest bias was established by De Lorenzo et al.'s equation as bias ±1.96SD = 4 ± 121 kcal/day. De Lorenzo et al. and Ikeda et al.'s equations had no significant average bias both in men and women (P > 0.05). The 1.96SD of bias in six equations was within 160 kcal/day. In contrast, residuals between the measured and predicted RMR were largely correlated with the RMR in four equations. A sex-related difference in the mean bias was observed in many equations. Although the average Japanese healthy older adult has a shorter stature and lower weight than older adults in the Western population, the current data suggest that a similar predictive equation for the RMR can be applied to both Japanese and Western older adults. This study demonstrate that the De Lorenzo et al.'s or Ikeda's equation may be useful for estimating RMR in the community

  9. Ecological network analysis for carbon metabolism of eco-industrial parks: a case study of a typical eco-industrial park in Beijing.

    Science.gov (United States)

    Lu, Yi; Chen, Bin; Feng, Kuishuang; Hubacek, Klaus

    2015-06-16

    Energy production and industrial processes are crucial economic sectors accounting for about 62% of greenhouse gas (GHG) emissions globally in 2012. Eco-industrial parks are practical attempts to mitigate GHG emissions through cooperation among businesses and the local community in order to reduce waste and pollution, efficiently share resources, and help with the pursuit of sustainable development. This work developed a framework based on ecological network analysis to trace carbon metabolic processes in eco-industrial parks and applied it to a typical eco-industrial park in Beijing. Our findings show that the entire metabolic system is dominated by supply of primary goods from the external environment and final demand. The more carbon flows through a sector, the more influence it would exert upon the whole system. External environment and energy providers are the most active and dominating part of the carbon metabolic system, which should be the first target to mitigate emissions by increasing efficiencies. The carbon metabolism of the eco-industrial park can be seen as an evolutionary system with high levels of efficiency, but this may come at the expense of larger levels of resilience. This work may provide a useful modeling framework for low-carbon design and management of industrial parks.

  10. Challenges in microbial ecology: building predictive understanding of community function and dynamics

    NARCIS (Netherlands)

    Widder, S.; Allen, R.J.; Pfeiffer, T.; Curtis, T.P.; Wiuf, C.; Sloan, W.T.; Cordero, O.X.; Brown, S.P.; Momeni, B.; Shou, W.; Kettle, H.; Flint, H.J.; Haas, A.F.; Laroche, B.; Kreft, J.U.; Rainey, P.B.; Freilich, S.; Schuster, S.; Milferstedt, K.; van der Meer, J.R.; Groβkopf, T.; Huisman, J.; Free, A.; Picioreanu, C.; Quince, C.; Klapper, I.; Labarthe, S.; Smets, B.F.; Wang, H; Soyer, O.S.

    2016-01-01

    The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth’s soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly

  11. Using Digital Terrain Modeling to Predict Ecological Types in the Balsam Mountains of Western North Carolina

    Science.gov (United States)

    Richard H. Odom; W. Henry McNab

    2000-01-01

    Relationships between overstory composition and topographic conditions were studied in high-elevation (>1300 meters) forests in the Balsam Mountains of western North Carolina to determine whether models could be developed to predict the occurrence of number vegetative communities in relation to topographic variables (elevation, landscape position, surface geometry,...

  12. Composition and predicted functional ecology of mussel - associated bacteria in Indonesian marine lakes

    NARCIS (Netherlands)

    Cleary, D.F.R.; Becking, L.E.; Polonia, A.; Freitas, R.M.; Gomes, N.

    2015-01-01

    In the present study, we sampled bacterial communities associated with mussels inhabiting two distinct coastal marine ecosystems in Kalimantan, Indonesia, namely, marine lakes and coastal mangroves. We used 16S rRNA gene pyrosequencing and predicted metagenomic analysis to compare microbial

  13. Beyond the mean: the role of variability in predicting ecological effects of stream temperature on salmon

    Science.gov (United States)

    E. Ashley Steel; Abby Tillotson; Donald A. Larson; Aimee H. Fullerton; Keith P. Denton; Brian R. Beckman

    2012-01-01

    Alterations in variance of riverine thermal regimes have been observed and are predicted with climate change and human development. We tested whether changes in daily or seasonal thermal variability, aside from changes in mean temperature, could have biological consequences by exposing Chinook salmon (Oncorhynchus tshawytscha) eggs to eight...

  14. Sasang constitutional types for the risk prediction of metabolic syndrome: a 14-year longitudinal prospective cohort study.

    Science.gov (United States)

    Lee, Sunghee; Lee, Seung Ku; Kim, Jong Yeol; Cho, Namhan; Shin, Chol

    2017-09-02

    To examine whether the use of Sasang constitutional (SC) types, such as Tae-yang (TY), Tae-eum (TE), So-yang (SY), and So-eum (SE) types, increases the accuracy of risk prediction for metabolic syndrome. From 2001 to 2014, 3529 individuals aged 40 to 69 years participated in a longitudinal prospective cohort. The Cox proportional hazard model was utilized to predict the risk of developing metabolic syndrome. During the 14 year follow-up, 1591 incident events of metabolic syndrome were observed. Individuals with TE type had higher body mass indexes and waist circumferences than individuals with SY and SE types. The risk of developing metabolic syndrome was the highest among individuals with the TE type, followed by the SY type and the SE type. When the prediction risk models for incident metabolic syndrome were compared, the area under the curve for the model using SC types was significantly increased to 0.8173. Significant predictors for incident metabolic syndrome were different according to the SC types. For individuals with the TE type, the significant predictors were age, sex, body mass index (BMI), education, smoking, drinking, fasting glucose level, high-density lipoprotein (HDL) cholesterol level, systolic and diastolic blood pressure, and triglyceride level. For Individuals with the SE type, the predictors were sex, smoking, fasting glucose, HDL cholesterol level, systolic and diastolic blood pressure, and triglyceride level, while the predictors in individuals with the SY type were age, sex, BMI, smoking, drinking, total cholesterol level, fasting glucose level, HDL cholesterol level, systolic and diastolic blood pressure, and triglyceride level. In this prospective cohort study among 3529 individuals, we observed that utilizing the SC types significantly increased the accuracy of the risk prediction for the development of metabolic syndrome.

  15. Origin of the Eumetazoa: testing ecological predictions of molecular clocks against the Proterozoic fossil record

    Science.gov (United States)

    Peterson, Kevin J.; Butterfield, Nicholas J.

    2005-01-01

    Molecular clocks have the potential to shed light on the timing of early metazoan divergences, but differing algorithms and calibration points yield conspicuously discordant results. We argue here that competing molecular clock hypotheses should be testable in the fossil record, on the principle that fundamentally new grades of animal organization will have ecosystem-wide impacts. Using a set of seven nuclear-encoded protein sequences, we demonstrate the paraphyly of Porifera and calculate sponge/eumetazoan and cnidarian/bilaterian divergence times by using both distance [minimum evolution (ME)] and maximum likelihood (ML) molecular clocks; ME brackets the appearance of Eumetazoa between 634 and 604 Ma, whereas ML suggests it was between 867 and 748 Ma. Significantly, the ME, but not the ML, estimate is coincident with a major regime change in the Proterozoic acritarch record, including: (i) disappearance of low-diversity, evolutionarily static, pre-Ediacaran acanthomorphs; (ii) radiation of the high-diversity, short-lived Doushantuo-Pertatataka microbiota; and (iii) an order-of-magnitude increase in evolutionary turnover rate. We interpret this turnover as a consequence of the novel ecological challenges accompanying the evolution of the eumetazoan nervous system and gut. Thus, the more readily preserved microfossil record provides positive evidence for the absence of pre-Ediacaran eumetazoans and strongly supports the veracity, and therefore more general application, of the ME molecular clock.

  16. Predicting geographic distributions of Phacellodomus species (Aves: Furnariidae in South America based on ecological niche modeling

    Directory of Open Access Journals (Sweden)

    Maria da Salete Gurgel Costa

    2014-08-01

    Full Text Available Phacellodomus Reichenbach, 1853, comprises nine species of Furnariids that occur in South America in open and generally dry areas. This study estimated the geographic distributions of Phacellodomus species in South America by ecological niche modeling. Applying maximum entropy method, models were produced for eight species based on six climatic variables and 949 occurrence records. Since highest climatic suitability for Phacellodomus species has been estimated in open and dry areas, the Amazon rainforest areas are not very suitable for these species. Annual precipitation and minimum temperature of the coldest month are the variables that most influence the models. Phacellodomus species occurred in 35 ecoregions of South America. Chaco and Uruguayan savannas were the ecoregions with the highest number of species. Despite the overall connection of Phacellodomus species with dry areas, species such as P. ruber, P. rufifrons, P. ferrugineigula and P. erythrophthalmus occurred in wet forests and wetland ecoregions.

  17. Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

    Science.gov (United States)

    Kimes, Daniel S.; Nelson, Ross F.

    1998-01-01

    A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

  18. The Metabolic Syndrome Predicts Longitudinal Changes in Clock Drawing Test Performance in Older Nondemented Hypertensive Individuals.

    Science.gov (United States)

    Viscogliosi, Giovanni; Chiriac, Iulia Maria; Andreozzi, Paola; Ettorre, Evaristo

    2016-05-01

    The present study evaluated the metabolic syndrome (MetS) as independent predictor of 1-year longitudinal changes in cognitive function. 104 stroke- and dementia-free older hypertensive subjects were studied. MetS was defined by NCEP ATP-III criteria. Cognitive function was assessed by the Clock Drawing Test (CDT); 1-year changes in cognitive function were expressed as annual changes in CDT performance. Brain magnetic resonance imaging studies (1.5T) were performed. Participants with MetS exhibited greater cognitive decline than those without (-1.78 ± 1.47 versus -0.74 ± 1.44 CDT points, t = 3.348, df = 102, p < 0.001). MetS predicted cognitive decline (β = -0.327, t = -3.059, df = 96, p = 0.003) independently of its components, age, baseline cognition, neuroimaging findings, blood pressure levels, and duration of hypertension. With the exception of systolic blood pressure, none of the individual components of MetS explained 1-year changes in CDT performance. MetS as an entity predicted accelerated 1-year decline in cognitive function, assessed by CDT, in a sample of older hypertensive subjects. Copyright © 2016 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

  19. A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2004-06-01

    Full Text Available Abstract Background The PathoLogic program constructs Pathway/Genome databases by using a genome's annotation to predict the set of metabolic pathways present in an organism. PathoLogic determines the set of reactions composing those pathways from the enzymes annotated in the organism's genome. Most annotation efforts fail to assign function to 40–60% of sequences. In addition, large numbers of sequences may have non-specific annotations (e.g., thiolase family protein. Pathway holes occur when a genome appears to lack the enzymes needed to catalyze reactions in a pathway. If a protein has not been assigned a specific function during the annotation process, any reaction catalyzed by that protein will appear as a missing enzyme or pathway hole in a Pathway/Genome database. Results We have developed a method that efficiently combines homology and pathway-based evidence to identify candidates for filling pathway holes in Pathway/Genome databases. Our program not only identifies potential candidate sequences for pathway holes, but combines data from multiple, heterogeneous sources to assess the likelihood that a candidate has the required function. Our algorithm emulates the manual sequence annotation process, considering not only evidence from homology searches, but also considering evidence from genomic context (i.e., is the gene part of an operon? and functional context (e.g., are there functionally-related genes nearby in the genome? to determine the posterior belief that a candidate has the required function. The method can be applied across an entire metabolic pathway network and is generally applicable to any pathway database. The program uses a set of sequences encoding the required activity in other genomes to identify candidate proteins in the genome of interest, and then evaluates each candidate by using a simple Bayes classifier to determine the probability that the candidate has the desired function. We achieved 71% precision at a

  20. Predicting glucose intolerance with normal fasting plasma glucose by the components of the metabolic syndrome

    International Nuclear Information System (INIS)

    Pei, D.; Lin, J.; Kuo, S.; Wu, D.; Li, J.; Hsieh, C.; Wu, C.; Hung, Y.; Kuo, K.

    2007-01-01

    Surprisingly it is estimated that about half of type 2 diabetics remain undetected. The possible causes may be partly attributable to people with normal fasting plasma glucose (FPG) but abnormal postprandial hyperglycemia. We attempted to develop an effective predictive model by using the metabolic syndrome (MeS) components as parameters to identify such persons. All participants received a standard 75 gm oral glucose tolerance test which showed that 106 had normal glucose tolerance, 61 had impaired glucose tolerance and 6 had diabetes on isolated postchallenge hyperglycemia. We tested five models which included various MeS components. Model 0: FPG; Model 1 (Clinical history model): family history (FH), FPG, age and sex; Model 2 (MeS model): Model 1 plus triglycerides, high-density lipoprotein cholesterol, body mass index, systolic blood pressure and diastolic blood pressure; Model 3: Model 2 plus fasting plasma insulin (FPI); Model 4: Model 3 plus homeostasis model assessment of insulin resistance. A receiver-operating characteristic (ROC) curve was used to determine the predictive discrimination of these models. The area under the ROC curve of the Model 0 was significantly larger than the area under the diagonal reference line. All the other 4 models had a larger area under the ROC curve than Model 0. Considering the simplicity and lower cost of Model 2, it would be the best model to use. Nevertheless, Model 3 had the largest area under the ROC curve. We demonstrated that Model 2 and 3 have a significantly better predictive discrimination to identify persons with normal FPG at high risk for glucose intolerance. (author)

  1. Brain networks predict metabolism, diagnosis and prognosis at the bedside in disorders of consciousness.

    Science.gov (United States)

    Chennu, Srivas; Annen, Jitka; Wannez, Sarah; Thibaut, Aurore; Chatelle, Camille; Cassol, Helena; Martens, Géraldine; Schnakers, Caroline; Gosseries, Olivia; Menon, David; Laureys, Steven

    2017-08-01

    Recent advances in functional neuroimaging have demonstrated novel potential for informing diagnosis and prognosis in the unresponsive wakeful syndrome and minimally conscious states. However, these technologies come with considerable expense and difficulty, limiting the possibility of wider clinical application in patients. Here, we show that high density electroencephalography, collected from 104 patients measured at rest, can provide valuable information about brain connectivity that correlates with behaviour and functional neuroimaging. Using graph theory, we visualize and quantify spectral connectivity estimated from electroencephalography as a dense brain network. Our findings demonstrate that key quantitative metrics of these networks correlate with the continuum of behavioural recovery in patients, ranging from those diagnosed as unresponsive, through those who have emerged from minimally conscious, to the fully conscious locked-in syndrome. In particular, a network metric indexing the presence of densely interconnected central hubs of connectivity discriminated behavioural consciousness with accuracy comparable to that achieved by expert assessment with positron emission tomography. We also show that this metric correlates strongly with brain metabolism. Further, with classification analysis, we predict the behavioural diagnosis, brain metabolism and 1-year clinical outcome of individual patients. Finally, we demonstrate that assessments of brain networks show robust connectivity in patients diagnosed as unresponsive by clinical consensus, but later rediagnosed as minimally conscious with the Coma Recovery Scale-Revised. Classification analysis of their brain network identified each of these misdiagnosed patients as minimally conscious, corroborating their behavioural diagnoses. If deployed at the bedside in the clinical context, such network measurements could complement systematic behavioural assessment and help reduce the high misdiagnosis rate reported

  2. An exploratory analysis of criteria for the metabolic syndrome and its prediction of long-term cardiovascular outcomes

    NARCIS (Netherlands)

    Girman, C.J.; Dekker, J.M.; Rhodes, T.; Nijpels, M.G.A.A.M.; Stehouwer, C.D.A.; Bouter, L.M.; Heine, R.J.

    2005-01-01

    Studies have shown an increased risk of cardiovascular outcomes with the metabolic syndrome, but information on predictive properties of the National Cholesterol Education Program Adult Treatment Panel 3 (NCEP) criteria is sparse. The authors used data from the Hoorn population-based study in the

  3. Do albuminuria and hs-CRP add to the International Diabetes Federation definition of the metabolic syndrome in predicting outcome?

    NARCIS (Netherlands)

    van der Velde, Marije; Bello, Aminu K.; Brantsma, Auke H.; El Nahas, Meguid; Bakker, Stephan J. L.; de Jong, Paul E.; Gansevoort, Ronald T.

    Background. To investigate the added value of elevated urinary albumin excretion (UAE) and high high-sensitive C-reactive protein (hs-CRP) in predicting new-onset type 2 diabetes mellitus (T2DM), cardiovascular disease (CVD) and chronic kidney disease (CKD) in addition to the present metabolic

  4. High invasion potential ofHydrilla verticillatain the Americas predicted using ecological niche modeling combined with genetic data.

    Science.gov (United States)

    Zhu, Jinning; Xu, Xuan; Tao, Qing; Yi, Panpan; Yu, Dan; Xu, Xinwei

    2017-07-01

    Ecological niche modeling is an effective tool to characterize the spatial distribution of suitable areas for species, and it is especially useful for predicting the potential distribution of invasive species. The widespread submerged plant Hydrilla verticillata (hydrilla) has an obvious phylogeographical pattern: Four genetic lineages occupy distinct regions in native range, and only one lineage invades the Americas. Here, we aimed to evaluate climatic niche conservatism of hydrilla in North America at the intraspecific level and explore its invasion potential in the Americas by comparing climatic niches in a phylogenetic context. Niche shift was found in the invasion process of hydrilla in North America, which is probably mainly attributed to high levels of somatic mutation. Dramatic changes in range expansion in the Americas were predicted in the situation of all four genetic lineages invading the Americas or future climatic changes, especially in South America; this suggests that there is a high invasion potential of hydrilla in the Americas. Our findings provide useful information for the management of hydrilla in the Americas and give an example of exploring intraspecific climatic niche to better understand species invasion.

  5. Evaluating the real-world predictive validity of the Body Image Quality of Life Inventory using Ecological Momentary Assessment.

    Science.gov (United States)

    Heron, Kristin E; Mason, Tyler B; Sutton, Tiphanie G; Myers, Taryn A

    2015-09-01

    Perceptions of physical appearance, or body image, can affect psychosocial functioning and quality of life (QOL). The present study evaluated the real-world predictive validity of the Body Image Quality of Life Inventory (BIQLI) using Ecological Momentary Assessment (EMA). College women reporting subclinical disordered eating/body dissatisfaction (N=131) completed the BIQLI and related measures. For one week they then completed five daily EMA surveys of mood, social interactions, stress, and eating behaviors on palmtop computers. Results showed better body image QOL was associated with less negative affect, less overwhelming emotions, more positive affect, more pleasant social interactions, and higher self-efficacy for handling stress. Lower body image QOL was marginally related to less overeating and lower loss of control over eating in daily life. To our knowledge, this is the first study to support the real-world predictive validity of the BIQLI by identifying social, affective, and behavioral correlates in everyday life using EMA. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Predictable variation of range-sizes across an extreme environmental gradient in a lizard adaptive radiation: evolutionary and ecological inferences.

    Directory of Open Access Journals (Sweden)

    Daniel Pincheira-Donoso

    Full Text Available Large-scale patterns of current species geographic range-size variation reflect historical dynamics of dispersal and provide insights into future consequences under changing environments. Evidence suggests that climate warming exerts major damage on high latitude and elevation organisms, where changes are more severe and available space to disperse tracking historical niches is more limited. Species with longer generations (slower adaptive responses, such as vertebrates, and with restricted distributions (lower genetic diversity, higher inbreeding in these environments are expected to be particularly threatened by warming crises. However, a well-known macroecological generalization (Rapoport's rule predicts that species range-sizes increase with increasing latitude-elevation, thus counterbalancing the impact of climate change. Here, I investigate geographic range-size variation across an extreme environmental gradient and as a function of body size, in the prominent Liolaemus lizard adaptive radiation. Conventional and phylogenetic analyses revealed that latitudinal (but not elevational ranges significantly decrease with increasing latitude-elevation, while body size was unrelated to range-size. Evolutionarily, these results are insightful as they suggest a link between spatial environmental gradients and range-size evolution. However, ecologically, these results suggest that Liolaemus might be increasingly threatened if, as predicted by theory, ranges retract and contract continuously under persisting climate warming, potentially increasing extinction risks at high latitudes and elevations.

  7. Dysregulation of the Autonomic Nervous System Predicts the Development of the Metabolic Syndrome

    NARCIS (Netherlands)

    Licht, Carmilla M. M.; de Geus, Eco J. C.; Penninx, Brenda W. J. H.

    Context: Stress is suggested to lead to metabolic dysregulations as clustered in the metabolic syndrome. Although dysregulation of the autonomic nervous system is found to associate with the metabolic syndrome and its dysregulations, no longitudinal study has been performed to date to examine the

  8. Does basal metabolic rate contain a useful signal? Mammalian BMR allometry and correlations with a selection of physiological, ecological, and life-history variables.

    Science.gov (United States)

    White, Craig R; Seymour, Roger S

    2004-01-01

    Basal metabolic rate (BMR, mL O2 h(-1)) is a useful measurement only if standard conditions are realised. We present an analysis of the relationship between mammalian body mass (M, g) and BMR that accounts for variation associated with body temperature, digestive state, and phylogeny. In contrast to the established paradigm that BMR proportional to M3/4, data from 619 species, representing 19 mammalian orders and encompassing five orders of magnitude variation in M, show that BMR proportional to M2/3. If variation associated with body temperature and digestive state are removed, the BMRs of eutherians, marsupials, and birds do not differ, and no significant allometric exponent heterogeneity remains between orders. The usefulness of BMR as a general measurement is supported by the observation that after the removal of body mass effects, the residuals of BMR are significantly correlated with the residuals for a variety of physiological and ecological variables, including maximum metabolic rate, field metabolic rate, resting heart rate, life span, litter size, and population density.

  9. A Physiologically Based Pharmacokinetic Model for Pregnant Women to Predict the Pharmacokinetics of Drugs Metabolized Via Several Enzymatic Pathways.

    Science.gov (United States)

    Dallmann, André; Ince, Ibrahim; Coboeken, Katrin; Eissing, Thomas; Hempel, Georg

    2017-09-18

    Physiologically based pharmacokinetic modeling is considered a valuable tool for predicting pharmacokinetic changes in pregnancy to subsequently guide in-vivo pharmacokinetic trials in pregnant women. The objective of this study was to extend and verify a previously developed physiologically based pharmacokinetic model for pregnant women for the prediction of pharmacokinetics of drugs metabolized via several cytochrome P450 enzymes. Quantitative information on gestation-specific changes in enzyme activity available in the literature was incorporated in a pregnancy physiologically based pharmacokinetic model and the pharmacokinetics of eight drugs metabolized via one or multiple cytochrome P450 enzymes was predicted. The tested drugs were caffeine, midazolam, nifedipine, metoprolol, ondansetron, granisetron, diazepam, and metronidazole. Pharmacokinetic predictions were evaluated by comparison with in-vivo pharmacokinetic data obtained from the literature. The pregnancy physiologically based pharmacokinetic model successfully predicted the pharmacokinetics of all tested drugs. The observed pregnancy-induced pharmacokinetic changes were qualitatively and quantitatively reasonably well predicted for all drugs. Ninety-seven percent of the mean plasma concentrations predicted in pregnant women fell within a twofold error range and 63% within a 1.25-fold error range. For all drugs, the predicted area under the concentration-time curve was within a 1.25-fold error range. The presented pregnancy physiologically based pharmacokinetic model can quantitatively predict the pharmacokinetics of drugs that are metabolized via one or multiple cytochrome P450 enzymes by integrating prior knowledge of the pregnancy-related effect on these enzymes. This pregnancy physiologically based pharmacokinetic model may thus be used to identify potential exposure changes in pregnant women a priori and to eventually support informed decision making when clinical trials are designed in this

  10. Anthropometric cutoff values for predicting metabolic syndrome in a Saudi community: from the SAUDI-DM study.

    Science.gov (United States)

    Al-Rubean, Khalid; Youssef, Amira M; AlFarsi, Yousuf; Al-Sharqawi, Ahmad H; Bawazeer, Nahla; AlOtaibi, Mohammad T; AlRumaih, Fahd Issa; Zaidi, Muhammad Shoaib

    2017-01-01

    The prevalence of metabolic syndrome varies widely by ethnicity and by the criteria used in its definition. To identify the optimal cutoff values for waist circumference (WC), waist-to-hip ratio (WHR) and body mass index (BMI) for identifying metabolic syndrome among the Saudi population. Nationwide household cross-sectional population-based survey. Thirteen health sectors in Saudi Arabia. We used data for subjects in the Saudi Abnormal Glucose Metabolism and Diabetes Impact Study (SAUDI-DM), which was conducted from 2007 to 2009. Using International Diabetes Federation (IDF) criteria, metabolic syndrome and its different components were assessed using anthropometric measurements, blood pressure, fasting plasma glucose, triglycerides and HDL cholesterol. Receiver operating characteristic (ROC) curves were generated to assess sensitivity and specificity for different cutoff values of WC, WHR, and BMI. The Youden index was used to calculate the optimal cutoff value for each anthropometric measurement. Optimal cutoff value for WC, WHR, and BMI for identifying the risk of metabolic syndrome. The prevalence of two or more risk factors for metabolic syndrome was observed in 43.42% of the total cohort of 12126 study participants >=18 years of age. The presence of two or more risk factors were significantly higher among men (46.81%) than women (40.53%) (P metabolic syndrome. The prevalence of elevated triglycerides, blood pressure, and fasting plasma glucose significantly increased with age for both genders. The proposed WC cutoff values were better than WHR and BMI in predicting metabolic syndrome and could be used for screening people at high risk for metabolic syndrome in the Saudi population. No direct measure of body fatness and fat distribution, cross-sectional design.

  11. Serum uric acid predicts both current and future components of the metabolic syndrome.

    Science.gov (United States)

    Osgood, Kristy; Krakoff, Jonathan; Thearle, Marie

    2013-06-01

    Uric acid (UA) is known to be associated with excess adiposity and insulin resistance. Our aim was to investigate the relationship between UA and the factors associated with the metabolic syndrome and type 2 diabetes mellitus (T2DM), both initially and longitudinally. Serum UA was assessed as a potential determinant of concurrent blood pressure, serum lipids, glucose regulation measured via an oral glucose tolerance test (OGTT), acute insulin response (AIR), and insulin action (M) measured with hyperinsulinemic-euglycemic clamps in 245 participants (72% Native American, 56% male). UA was also assessed as a predictor of the above variables in 60 participants with follow-up data available (median follow-up time=11.2 years [interquartile range (IQR)=8.1, 13.6 years]. The impact of UA on the risk of T2DM was determined as 36 of the 245 participants developed T2DM after the baseline visit. UA was negatively associated with both concurrent and future M, such that for every 1 mg/dL increase in serum UA, M decreased 7.6% (P<0.001) and future M decreased 6.3% (P=0.02). However, UA was not associated with AIR (P=0.7). UA concentrations were a predictor of T2DM [hazard risk ratio (HRR)=1.5; P=0.02]. UA was positively associated with both concurrent blood pressure and lipids and also predicted future increases in blood pressure and total cholesterol. Not only did UA associate with concomitant insulin action, blood pressure, and lipids, it also predicted future declines in insulin action and T2DM. UA is a potential target for preventing decreases in insulin sensitivity and rises in blood pressure and cholesterol.

  12. Does the metabolic syndrome predict subclinical atherosclerotic damage in an asymptomatic population at intermediate cardiovascular risk?

    Science.gov (United States)

    Zocchi, L; Perego, F; Casella, F; Arquati, M; Renesto, E; Casazza, G; D'Ambrosio, A; Cortellaro, M

    2013-09-01

    It is not clear whether the metabolic syndrome (MetS) is a distinct entity or a combination of risk factors. Several studies showed the association between MetS and cardiovascular disease (CVD). Subclinical target organ damage (TOD) is a recognized marker of atherosclerosis and predictor of cardiovascular events. Increased burden of subclinical atherosclerosis was detected in individuals with MetS. We thus aimed to examine the association between MetS and cumulative or specific TOD and to assess whether MetS predicts TOD better than the risk factors included in current definitions. We recorded TOD in 979 patients at intermediate cardiovascular risk with and without MetS according to IDF and NCEP criteria. We measured common carotid intima-media thickness, left ventricular mass index (LVMI), urine albumin to creatinine ratio (UACR), and ankle-brachial index. We found no correlation between having at least one TOD and being positive for MetS. A high UACR was associated with MetS using both IDF and NCEP criteria, while only NCEP identified individuals with increased LVMI. Using a multivariate logistic regression model including MetS, age, sex, waist circumference, triglycerides, HDL cholesterol, blood pressure and blood glucose levels we found no correlations between the presence of MetS and at least one TOD. The associations with high UACR and LVMI disappeared when age, blood pressure and glycemia were counted in. Although MetS showed some relation with subclinical renal and cardiac damage, it does not predict TOD any better than the risk factors specified in the definitions. Copyright © 2012 Elsevier B.V. All rights reserved.

  13. A computational approach predicting CYP450 metabolism and estrogenic activity of an endocrine disrupting compound (PCB-30).

    Science.gov (United States)

    Harris, Jason B; Eldridge, Melanie L; Sayler, Gary; Menn, Fu-Min; Layton, Alice C; Baudry, Jerome

    2014-07-01

    Endocrine disrupting chemicals influence growth and development through interactions with the hormone system, often through binding to hormone receptors such as the estrogen receptor. Computational methods can predict endocrine disrupting chemical activity of unmodified compounds, but approaches predicting activity following metabolism are lacking. The present study uses a well-known environmental contaminant, PCB-30 (2,4,6-trichlorobiphenyl), as a prototype endocrine disrupting chemical and integrates predictive (computational) and experimental methods to determine its metabolic transformation by cytochrome P450 3A4 (CYP3A4) and cytochrome P450 2D6 (CYP2D6) into estrogenic byproducts. Computational predictions suggest that hydroxylation of PCB-30 occurs at the 3- or 4-phenol positions and leads to metabolites that bind more strongly than the parent molecule to the human estrogen receptor alpha (hER-α). Gas chromatography-mass spectrometry experiments confirmed that the primary metabolite for CYP3A4 and CYP2D6 is 4-hydroxy-PCB-30, and the secondary metabolite is 3-hydroxy-PCB-30. Cell-based bioassays (bioluminescent yeast expressing hER-α) confirmed that hydroxylated metabolites are more estrogenic than PCB-30. These experimental results support the applied model's ability to predict the metabolic and estrogenic fate of PCB-30, which could be used to identify other endocrine disrupting chemicals involved in similar pathways. © 2014 SETAC.

  14. The metabolic syndrome is not a sensible tool for predicting the risk of coronary heart disease.

    Science.gov (United States)

    Woodward, Mark; Tunstall-Pedoe, Hugh

    2009-04-01

    The metabolic syndrome (MS) is a popularly used risk marker for coronary heart disease (CHD), yet its utility is in doubt. Cohort study based in Glasgow, Scotland, of 1471 men and women free of cardiovascular disease, followed up for a median of 13.7 years. MS was defined according to current criteria, requiring at least three of five dichotomous risk factors to be positive. Cox models were used to obtain hazard ratios (HRs) and discrimination was quantified by areas under receiver operating characteristic curves (AUCs) using 500 bootstrap samples. The HR (95% confidence interval) for CHD, MS versus no MS was 2.23 (1.67-2.97). However, the HR rose monotonically when plotted against the number of positive components, with no suggestion of a threshold effect at three positive components. Furthermore, the HR also changed monotonically as each of the five continuous variables defining the different components increased, again with no obvious threshold effects. The AUC for MS was low, at 0.5764, this being significantly (P<0.0001) lower than the AUCs for other risk prediction models, including the Framingham score, 0.7517. Although MS is related to CHD, there is no epidemiological justification for using it, rather than other criteria, as a risk predictor for CHD.

  15. Best-fitting prediction equations for basal metabolic rate: informing obesity interventions in diverse populations.

    Science.gov (United States)

    Sabounchi, N S; Rahmandad, H; Ammerman, A

    2013-10-01

    Basal metabolic rate (BMR) represents the largest component of total energy expenditure and is a major contributor to energy balance. Therefore, accurately estimating BMR is critical for developing rigorous obesity prevention and control strategies. Over the past several decades, numerous BMR formulas have been developed targeted to different population groups. A comprehensive literature search revealed 248 BMR estimation equations developed using diverse ranges of age, gender, race, fat-free mass, fat mass, height, waist-to-hip ratio, body mass index and weight. A subset of 47 studies included enough detail to allow for development of meta-regression equations. Utilizing these studies, meta-equations were developed targeted to 20 specific population groups. This review provides a comprehensive summary of available BMR equations and an estimate of their accuracy. An accompanying online BMR prediction tool (available at http://www.sdl.ise.vt.edu/tutorials.html) was developed to automatically estimate BMR based on the most appropriate equation after user-entry of individual age, race, gender and weight.

  16. Sphingoid Base Metabolism in Yeast: Mapping Gene Expression Patterns Into Qualitative Metabolite Time Course Predictions

    Directory of Open Access Journals (Sweden)

    Tomas Radivoyevitch

    2006-04-01

    Full Text Available Can qualitative metabolite time course predictions be inferred from measured mRNA expression patterns? Speaking against this possibility is the large number of ‘decoupling’ control points that lie between these variables, i.e. translation, protein degradation, enzyme inhibition and enzyme activation. Speaking for it is the notion that these control points might be coordinately regulated such that action exerted on the mRNA level is informative of action exerted on the protein and metabolite levels. A simple kinetic model of sphingoid base metabolism in yeast is postulated. When the enzyme activities in this model are modulated proportional to mRNA expression levels measured in heat shocked yeast, the model yields a transient rise and fall in sphingoid bases followed by a permanent rise in ceramide. This finding is in qualitative agreement with experiments and is thus consistent with the aforementioned coordinated control system hypothesis.

  17. Bacterial community structure and predicted alginate metabolic pathway in an alginate-degrading bacterial consortium.

    Science.gov (United States)

    Kita, Akihisa; Miura, Toyokazu; Kawata, Satoshi; Yamaguchi, Takeshi; Okamura, Yoshiko; Aki, Tsunehiro; Matsumura, Yukihiko; Tajima, Takahisa; Kato, Junichi; Nishio, Naomichi; Nakashimada, Yutaka

    2016-03-01

    Methane fermentation is one of the effective approaches for utilization of brown algae; however, this process is limited by the microbial capability to degrade alginate, a main polysaccharide found in these algae. Despite its potential, little is known about anaerobic microbial degradation of alginate. Here we constructed a bacterial consortium able to anaerobically degrade alginate. Taxonomic classification of 16S rRNA gene, based on high-throughput sequencing data, revealed that this consortium included two dominant strains, designated HUA-1 and HUA-2; these strains were related to Clostridiaceae bacterium SK082 (99%) and Dysgonomonas capnocytophagoides (95%), respectively. Alginate lyase activity and metagenomic analyses, based on high-throughput sequencing data, revealed that this bacterial consortium possessed putative genes related to a predicted alginate metabolic pathway. However, HUA-1 and 2 did not grow on agar medium with alginate by using roll-tube method, suggesting the existence of bacterial interactions like symbiosis for anaerobic alginate degradation. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  18. Magnetic resonance metabolic profiling of breast cancer tissue obtained with core needle biopsy for predicting pathologic response to neoadjuvant chemotherapy.

    Directory of Open Access Journals (Sweden)

    Ji Soo Choi

    Full Text Available The purpose of this study was to determine whether metabolic profiling of core needle biopsy (CNB samples using high-resolution magic angle spinning (HR-MAS magnetic resonance spectroscopy (MRS could be used for predicting pathologic response to neoadjuvant chemotherapy (NAC in patients with locally advanced breast cancer. After institutional review board approval and informed consent were obtained, CNB tissue samples were collected from 37 malignant lesions in 37 patients before NAC treatment. The metabolic profiling of CNB samples were performed by HR-MAS MRS. Metabolic profiles were compared according to pathologic response to NAC using the Mann-Whitney test. Multivariate analysis was performed with orthogonal projections to latent structure-discriminant analysis (OPLS-DA. Various metabolites including choline-containing compounds were identified and quantified by HR-MAS MRS in all 37 breast cancer tissue samples obtained by CNB. In univariate analysis, the metabolite concentrations and metabolic ratios of CNB samples obtained with HR-MAS MRS were not significantly different between different pathologic response groups. However, there was a trend of lower levels of phosphocholine/creatine ratio and choline-containing metabolite concentrations in the pathologic complete response group compared to the non-pathologic complete response group. In multivariate analysis, the OPLS-DA models built with HR-MAS MR metabolic profiles showed visible discrimination between the pathologic response groups. This study showed OPLS-DA multivariate analysis using metabolic profiles of pretreatment CNB samples assessed by HR- MAS MRS may be used to predict pathologic response before NAC, although we did not identify the metabolite showing statistical significance in univariate analysis. Therefore, our preliminary results raise the necessity of further study on HR-MAS MR metabolic profiling of CNB samples for a large number of cancers.

  19. AN ANALYSIS OF HATCHLING RESTING METABOLISM - IN SEARCH OF ECOLOGICAL CORRELATES THAT EXPLAIN DEVIATIONS FROM ALLOMETRIC RELATIONS

    NARCIS (Netherlands)

    KLAASSEN, M; DRENT, R

    From data in the literature, an allometric equation is compiled for hatchling resting metabolic rate and an attempt is made to explain residual variation in terms of hatchling type, yolk and water content, embryonic and postnatal growth rate, and environmental circumstances (latitudinal

  20. A Western Diet Ecological Module Identified from the ‘Humanized’ Mouse Microbiota Predicts Diet in Adults and Formula Feeding in Children

    Science.gov (United States)

    Siddharth, Jay; Holway, Nicholas; Parkinson, Scott J.

    2013-01-01

    The interplay between diet and the microbiota has been implicated in the growing frequency of chronic diseases associated with the Western lifestyle. However, the complexity and variability of microbial ecology in humans and preclinical models has hampered identification of the molecular mechanisms underlying the association of the microbiota in this context. We sought to address two key questions. Can the microbial ecology of preclinical models predict human populations? And can we identify underlying principles that surpass the plasticity of microbial ecology in humans? To do this, we focused our study on diet; perhaps the most influential factor determining the composition of the gut microbiota. Beginning with a study in ‘humanized’ mice we identified an interactive module of 9 genera allied with Western diet intake. This module was applied to a controlled dietary study in humans. The abundance of the Western ecological module correctly predicted the dietary intake of 19/21 top and 21/21 of the bottom quartile samples inclusive of all 5 Western and ‘low-fat’ diet subjects, respectively. In 98 volunteers the abundance of the Western module correlated appropriately with dietary intake of saturated fatty acids, fat-soluble vitamins and fiber. Furthermore, it correlated with the geographical location and dietary habits of healthy adults from the Western, developing and third world. The module was also coupled to dietary intake in children (and piglets) correlating with formula (vs breast) feeding and associated with a precipitous development of the ecological module in young children. Our study provides a conceptual platform to translate microbial ecology from preclinical models to humans and identifies an ecological network module underlying the association of the gut microbiota with Western dietary habits. PMID:24391809

  1. Serum uric acid and appropriate cutoff value for prediction of metabolic syndrome among Chinese adults

    OpenAIRE

    Zhang, Mei-lin; Gao, Yu-xia; Wang, Xuan; Chang, Hong; Huang, Guo-wei

    2012-01-01

    The relation between serum uric acid and metabolic syndrome is observed not only with frank hyperuricemia but also with serum uric acid levels within the normal range. The current ?normal? range set for hyperuricemia often fails to identify patients with potential metabolic disorders. We investigate the association between serum uric acid within the normal range and incident metabolic syndrome risk, and further to determine the optimal cut-off value of serum uric acid for the diagnosis or pre...

  2. Impaired cross-talk between mesolimbic food reward processing and metabolic signaling predicts body mass index

    Directory of Open Access Journals (Sweden)

    Joe J Simon

    2014-10-01

    Full Text Available The anticipation of the pleasure derived from food intake drives the motivation to eat, and hence facilitate overconsumption of food which ultimately results in obesity. Brain imaging studies provide evidence that mesolimbic brain regions underlie both general as well as food related anticipatory reward processing. In light of this knowledge, the present study examined the neural responsiveness of the ventral striatum in participants with a broad BMI spectrum. The study differentiated between general (i.e. monetary and food related anticipatory reward processing. We recruited a sample of volunteers with greatly varying body weights, ranging from a low BMI (below 20 kg/m² over a normal (20 to 25 kg/m² and overweight (25 to 30 kg/m² BMI, to class I (30 to 35 kg/m² and class II (35 to 40 kg/m² obesity. A total of 24 participants underwent functional magnetic resonance imaging whilst performing both a food and monetary incentive delay task, which allows to measure neural activation during the anticipation of rewards. After the presentation of a cue indicating the amount of food or money to be won, participants had to react correctly in order to earn snack points or money coins which could then be exchanged for real food or money, respectively, at the end of the experiment. During the anticipation of both types of rewards, participants displayed activity in the ventral striatum, a region that plays a pivotal role in the anticipation of rewards. Additionally, we observed that specifically anticipatory food reward processing predicted the individual BMI (current and maximum lifetime. This relation was found to be mediated by impaired hormonal satiety signaling, i.e. increased leptin levels and insulin resistance. These findings suggest that heightened food reward motivation contributes to obesity through impaired metabolic signaling.

  3. Do ecological niche model predictions reflect the adaptive landscape of species?: a test using Myristica malabarica Lam., an endemic tree in the Western Ghats, India.

    Science.gov (United States)

    Nagaraju, Shivaprakash K; Gudasalamani, Ravikanth; Barve, Narayani; Ghazoul, Jaboury; Narayanagowda, Ganeshaiah Kotiganahalli; Ramanan, Uma Shaanker

    2013-01-01

    Ecological niche models (ENM) have become a popular tool to define and predict the "ecological niche" of a species. An implicit assumption of the ENMs is that the predicted ecological niche of a species actually reflects the adaptive landscape of the species. Thus in sites predicted to be highly suitable, species would have maximum fitness compared to in sites predicted to be poorly suitable. As yet there are very few attempts to address this assumption. Here we evaluate this assumption. We used Bioclim (DIVA GIS version 7.3) and Maxent (version 3.3.2) to predict the habitat suitability of Myristica malabarica Lam., an economically important tree occurring in the Western Ghats, India. We located populations of the trees naturally occurring in different habitat suitability regimes (from highly suitable to poorly suitable) and evaluated them for their regeneration ability and genetic diversity. We also evaluated them for two plant functional traits, fluctuating asymmetry--an index of genetic homeostasis, and specific leaf weight--an index of primary productivity, often assumed to be good surrogates of fitness. We show a significant positive correlation between the predicted habitat quality and plant functional traits, regeneration index and genetic diversity of populations. Populations at sites predicted to be highly suitable had a higher regeneration and gene diversity compared to populations in sites predicted to be poor or unsuitable. Further, individuals in the highly suitable sites exhibited significantly less fluctuating asymmetry and significantly higher specific leaf weight compared to individuals in the poorly suitable habitats. These results for the first time provide an explicit test of the ENM with respect to the plant functional traits, regeneration ability and genetic diversity of populations along a habitat suitability gradient. We discuss the implication of these results for designing viable species conservation and restoration programs.

  4. Do ecological niche model predictions reflect the adaptive landscape of species?: a test using Myristica malabarica Lam., an endemic tree in the Western Ghats, India.

    Directory of Open Access Journals (Sweden)

    Shivaprakash K Nagaraju

    Full Text Available Ecological niche models (ENM have become a popular tool to define and predict the "ecological niche" of a species. An implicit assumption of the ENMs is that the predicted ecological niche of a species actually reflects the adaptive landscape of the species. Thus in sites predicted to be highly suitable, species would have maximum fitness compared to in sites predicted to be poorly suitable. As yet there are very few attempts to address this assumption. Here we evaluate this assumption. We used Bioclim (DIVA GIS version 7.3 and Maxent (version 3.3.2 to predict the habitat suitability of Myristica malabarica Lam., an economically important tree occurring in the Western Ghats, India. We located populations of the trees naturally occurring in different habitat suitability regimes (from highly suitable to poorly suitable and evaluated them for their regeneration ability and genetic diversity. We also evaluated them for two plant functional traits, fluctuating asymmetry--an index of genetic homeostasis, and specific leaf weight--an index of primary productivity, often assumed to be good surrogates of fitness. We show a significant positive correlation between the predicted habitat quality and plant functional traits, regeneration index and genetic diversity of populations. Populations at sites predicted to be highly suitable had a higher regeneration and gene diversity compared to populations in sites predicted to be poor or unsuitable. Further, individuals in the highly suitable sites exhibited significantly less fluctuating asymmetry and significantly higher specific leaf weight compared to individuals in the poorly suitable habitats. These results for the first time provide an explicit test of the ENM with respect to the plant functional traits, regeneration ability and genetic diversity of populations along a habitat suitability gradient. We discuss the implication of these results for designing viable species conservation and restoration

  5. 3D gut-liver chip with a PK model for prediction of first-pass metabolism.

    Science.gov (United States)

    Lee, Dong Wook; Ha, Sang Keun; Choi, Inwook; Sung, Jong Hwan

    2017-11-07

    Accurate prediction of first-pass metabolism is essential for improving the time and cost efficiency of drug development process. Here, we have developed a microfluidic gut-liver co-culture chip that aims to reproduce the first-pass metabolism of oral drugs. This chip consists of two separate layers for gut (Caco-2) and liver (HepG2) cell lines, where cells can be co-cultured in both 2D and 3D forms. Both cell lines were maintained well in the chip, verified by confocal microscopy and measurement of hepatic enzyme activity. We investigated the PK profile of paracetamol in the chip, and corresponding PK model was constructed, which was used to predict PK profiles for different chip design parameters. Simulation results implied that a larger absorption surface area and a higher metabolic capacity are required to reproduce the in vivo PK profile of paracetamol more accurately. Our study suggests the possibility of reproducing the human PK profile on a chip, contributing to accurate prediction of pharmacological effect of drugs.

  6. Urban political ecology: Twenty years of criticism, self-criticism and expansion of frontiers in the study of urban metabolism

    OpenAIRE

    Villar Navascués, Rubén

    2017-01-01

    La ecología política urbana (EPU) es una disciplina que explora las interacciones entre factores sociales, políticos, económicos y naturales en la producción y en la reproducción de los entornos urbanos, que son entendidos como híbridos socionaturales. El objetivo de este artículo es, a partir de una revisión bibliográfica de la producción científica, identificar las principales temáticas y líneas de investigación para poner de relieve nuevos enfoques desde los que abordar críticamente las in...

  7. Body shape shifting during growth permits tests that distinguish between competing geometric theories of metabolic scaling

    DEFF Research Database (Denmark)

    Hirst, Andrew G.; Glazier, Douglas S.; Atkinson, David

    2014-01-01

    Metabolism fuels all of life’s activities, from biochemical reactions to ecological interactions. According to two intensely debated theories, body size affects metabolism via geometrical influences on the transport of resources and wastes. However, these theories differ crucially in whether...... theory, but contradicting the negative correlations predicted by resource-transport network models. This finding explains strong deviations from predictions of widely adopted theory, and underpins a new explanation for mass-invariant metabolic scaling during ontogeny in animals and plants...

  8. A Malaria Ecology Index Predicted Spatial and Temporal Variation of Malaria Burden and Efficacy of Antimalarial Interventions Based on African Serological Data.

    Science.gov (United States)

    McCord, Gordon C; Anttila-Hughes, Jesse K

    2017-03-01

    AbstractReducing the global health burden of malaria is complicated by weak reporting systems for infectious diseases and a paucity of vital statistics registration. This limits our ability to predict changes in malaria health burden intensity, target antimalarial resources where needed, and identify malaria impacts in retrospective data. We refined and deployed a temporally and spatially varying Malaria Ecology Index (MEI) incorporating climatological and ecological data to estimate malaria transmission strength and validate it against cross-sectional serology data from 39,875 children from seven sub-Saharan African countries. The MEI is strongly associated with malaria burden; a 1 standard deviation higher MEI is associated with a 50-117% increase in malaria risk and a 3-5 g/dL lower level of Hg. Results show that the relationship between malaria ecology and disease burden is attenuated with sufficient coverage of insecticide treated nets (ITNs) or indoor residual spraying (IRS). Having both ITNs and IRS reduce the added risk from adverse malaria ecology conditions by half. Readily available climate and ecology data can be used to estimate the spatial and temporal variation in malaria disease burden, providing a feasible alternative to direct surveillance. This will help target resources for malaria programs in the absence of national coverage of active case detection systems, and facilitate malaria research using retrospective health data.

  9. Aquatic predicted no-effect concentration for three polycyclic aromatic hydrocarbons and probabilistic ecological risk assessment in Liaodong Bay of the Bohai Sea, China.

    Science.gov (United States)

    Wang, Ying; Wang, Juying; Mu, Jingli; Wang, Zhen; Yao, Ziwei; Lin, Zhongsheng

    2014-01-01

    Predicted no-effect concentration (PNEC) is often used in ecological risk assessment to determine low-risk concentrations for chemicals. In the present study, native marine species were selected for toxicity testing. The PNECs for three polycyclic aromatic hydrocarbons (PAHs), specifically phenanthrene (Phe), pyrene (Pyr), and benzo[a]pyrene (BaP), were derived from chronic and acute toxicity data with log-normal statistical methods. The achieved PNECs for Phe, Pyr, and BaP were 2.33, 1.09, and 0.011 μg/L, respectively. In Jinzhou Bay and the Shuangtaizi River Estuary of Liaodong Bay in the Bohai Sea, China, the surface water concentrations of the three PAHs were analyzed by gas chromatography-mass spectrometry. Based on two probabilistic ecological risk assessment (PERA) methods, namely probabilistic risk quotient and joint probability curve, the potential risk of Phe, Pyr, and BaP in Jinzhou Bay and Shuangtaizi River Estuary was assessed. The same order of ecological risk (BaP > Phe > Pyr) was found by both models. Our study considered regional characteristics of marine biota during the calculation of PNECs, and the PERA methods provided probabilities of potential ecological risks of chemicals. Within the study area, further research on BaP is required due to its high potential ecological risk.

  10. NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

    Science.gov (United States)

    Padmanabhan, Kanchana; Shpanskaya, Yekaterina; Banfield, Jill; Scott, Kathleen; Mihelcic, James R.; Samatova, Nagiza F.

    2012-01-01

    Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to

  11. Reduced FDG-PET brain metabolism and executive function predict clinical progression in elderly healthy subjects

    Directory of Open Access Journals (Sweden)

    Michael Ewers

    2014-01-01

    Full Text Available Brain changes reminiscent of Alzheimer disease (AD have been previously reported in a substantial portion of elderly cognitive healthy (HC subjects. The major aim was to evaluate the accuracy of MRI assessed regional gray matter (GM volume, 18F-fluorodeoxyglucose positron emission tomography (FDG-PET, and neuropsychological test scores to identify those HC subjects who subsequently convert to mild cognitive impairment (MCI or AD dementia. We obtained in 54 healthy control (HC subjects a priori defined region of interest (ROI values of medial temporal and parietal FDG-PET and medial temporal GM volume. In logistic regression analyses, these ROI values were tested together with neuropsychological test scores (free recall, trail making test B (TMT-B as predictors of HC conversion during a clinical follow-up between 3 and 4 years. In voxel-based analyses, FDG-PET and MRI GM maps were compared between HC converters and HC non-converters. Out of the 54 HC subjects, 11 subjects converted to MCI or AD dementia. Lower FDG-PET ROI values were associated with higher likelihood of conversion (p = 0.004, with the area under the curve (AUC yielding 82.0% (95% CI = (95.5%, 68.5%. The GM volume ROI was not a significant predictor (p = 0.07. TMT-B but not the free recall tests were a significant predictor (AUC = 71% (95% CI = 50.4%, 91.7%. For the combination of FDG-PET and TMT-B, the AUC was 93.4% (sensitivity = 82%, specificity = 93%. Voxel-based group comparison showed reduced FDG-PET metabolism within the temporo-parietal and prefrontal cortex in HC converters. In conclusion, medial temporal and-parietal FDG-PET and executive function show a clinically acceptable accuracy for predicting clinical progression in elderly HC subjects.

  12. Ecology, distribution, and predictive occurrence modeling of Palmers chipmunk (Tamias palmeri): a high-elevation small mammal endemic to the Spring Mountains in southern Nevada, USA

    Science.gov (United States)

    Lowrey, Chris E.; Longshore, Kathleen M.; Riddle, Brett R.; Mantooth, Stacy

    2016-01-01

    Although montane sky islands surrounded by desert scrub and shrub steppe comprise a large part of the biological diversity of the Basin and Range Province of southwestern North America, comprehensive ecological and population demographic studies for high-elevation small mammals within these areas are rare. Here, we examine the ecology and population parameters of the Palmer’s chipmunk (Tamias palmeri) in the Spring Mountains of southern Nevada, and present a predictive GIS-based distribution and probability of occurrence model at both home range and geographic spatial scales. Logistic regression analyses and Akaike Information Criterion model selection found variables of forest type, slope, and distance to water sources as predictive of chipmunk occurrence at the geographic scale. At the home range scale, increasing population density, decreasing overstory canopy cover, and decreasing understory canopy cover contributed to increased survival rates.

  13. Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration.

    Science.gov (United States)

    Schliess, Freimut; Hoehme, Stefan; Henkel, Sebastian G; Ghallab, Ahmed; Driesch, Dominik; Böttger, Jan; Guthke, Reinhard; Pfaff, Michael; Hengstler, Jan G; Gebhardt, Rolf; Häussinger, Dieter; Drasdo, Dirk; Zellmer, Sebastian

    2014-12-01

    The impairment of hepatic metabolism due to liver injury has high systemic relevance. However, it is difficult to calculate the impairment of metabolic capacity from a specific pattern of liver damage with conventional techniques. We established an integrated metabolic spatial-temporal model (IM) using hepatic ammonia detoxification as a paradigm. First, a metabolic model (MM) based on mass balancing and mouse liver perfusion data was established to describe ammonia detoxification and its zonation. Next, the MM was combined with a spatial-temporal model simulating liver tissue damage and regeneration after CCl4 intoxication. The resulting IM simulated and visualized whether, where, and to what extent liver damage compromised ammonia detoxification. It allowed us to enter the extent and spatial patterns of liver damage and then calculate the outflow concentrations of ammonia, glutamine, and urea in the hepatic vein. The model was validated through comparisons with (1) published data for isolated, perfused livers with and without CCl4 intoxication and (2) a set of in vivo experiments. Using the experimentally determined portal concentrations of ammonia, the model adequately predicted metabolite concentrations over time in the hepatic vein during toxin-induced liver damage and regeneration in rodents. Further simulations, especially in combination with a simplified model of blood circulation with three ammonia-detoxifying compartments, indicated a yet unidentified process of ammonia consumption during liver regeneration and revealed unexpected concomitant changes in amino acid metabolism in the liver and at extrahepatic sites. The IM of hepatic ammonia detoxification considerably improves our understanding of the metabolic impact of liver disease and highlights the importance of integrated modeling approaches on the way toward virtual organisms. © 2014 The Authors. Hepatology published by Wiley on behalf of the American Association for the Study of Liver Diseases.

  14. Environment and feeding change the ability of heart rate to predict metabolism in resting Steller sea lions (Eumetopias jubatus).

    Science.gov (United States)

    Young, Beth L; Rosen, David A S; Haulena, Martin; Hindle, Allyson G; Trites, Andrew W

    2011-01-01

    The ability to use heart rate (fh) to predict oxygen consumption rates ([Formula: see text]) in Steller sea lions and other pinnipeds has been investigated in fasting animals. However, it is unknown whether established fh:[Formula: see text] relationships hold under more complex physiological situations, such as when animals are feeding or digesting. We assessed whether fh could accurately predict [Formula: see text] in trained Steller sea lions while fasting and after being fed. Using linear mixed-effects models, we derived unique equations to describe the fh:[Formula: see text] relationship for fasted sea lions resting on land and in water. Feeding did not significantly change the fh:[Formula: see text] relationship on land. However, Steller sea lions in water displayed a different fh:[Formula: see text] relationship after consuming a 4-kg meal compared with the fasting condition. Incorporating comparable published fh:[Formula: see text] data from Steller sea lions showed a distinct effect of feeding after a 6-kg meal. Ultimately, our study illustrated that both feeding and physical environment are statistically relevant when deriving [Formula: see text] from telemetered fh, but that only environment affects the practical ability to predict metabolism from fh. Updating current bioenergetic models with data gathered using these predictive fh:[Formula: see text] equations will yield more accurate estimates of metabolic rates of free-ranging Steller sea lions under a variety of physiological, behavioral, and environmental states.

  15. Prediction of liver injury using the BP-ANN model with metabolic parameters in overweight and obese Chinese subjects.

    Science.gov (United States)

    Hu, Lufeng; Wang, Fan; Xu, Jinzhong; Wang, Xiaofang; Lin, Hong; Zhang, Yi; Yu, Yang; Wang, Youpei; Pang, Lingxia; Zhang, Xi; Liu, Qi; Qiu, Guoshi; Jiang, Yongsheng; Xie, Longteng; Liu, Yanlong

    2015-01-01

    Nonalcoholic fatty liver disease (NAFLD) is often associated with dyslipidemia. Metabolic disequilibrium, resulting from being overweight and obesity, increases risk to cardiovascular system and chronic liver disease. Alanine aminotransferase (ALT), aspartate aminotransferase (AST) and gamma-glutamyl transferase (GGT) are standard clinical markers for liver injury. In this study, we examined association of body mass index (BMI) and metabolic markers with serum ALT, AST and GGT activity in an overweight and obese Chinese population. A total of 421 overweight and obese Chinese adults (211 males and 210 females) from The First Affiliated Hospital of Wenzhou Medical University were recruited in this study in 2014. All participants underwent anthropometric measures and phlebotomy after an overnight fast. Elevated ALT, AST and GGT levels were found in 17%, 5% and 24%, respectively. There were significant correlations between ALT and BMI, plasma triglycerides (TG), cholesterol, HDL and glucose, and between AST and plasma TG and cholesterol. GGT also correlated with plasma TG, cholesterol and glucose. The levels of ALT, AST and GGT could be predicted by BMI, plasma TG, cholesterol, HDL and glucose using the back propagation artificial neural network model (BP-ANN). These data suggest that abnormal metabolic markers could be used to monitor liver function to determine whether liver damage has occurred in overweight and obese individuals. This approach has clinical utility with respect to early scanning of liver injury or NAFLD based on routinely available metabolic data in overweight and obese population.

  16. Impact of the basal metabolic ratio in predicting early deaths after allogeneic stem cell transplantation.

    Science.gov (United States)

    Nishiwaki, Satoshi; Miyamura, Koichi; Seto, Aika; Watanabe, Keisuke; Yanagisawa, Mayumi; Imahashi, Nobuhiko; Shimba, Makoto; Yasuda, Takahiko; Kuwatsuka, Yachiyo; Oba, Taku; Terakura, Seitaro; Kodera, Yoshihisa

    2009-09-01

    Early deaths after allogeneic stem cell transplantation (allo-SCT) are of major concern. On the assumption that both decreased and increased basal metabolism might relate to early deaths, we analyzed the risk factors for overall survival to days 30 (OS30) and 60 (OS60). The Harris-Benedict equation was used to calculate basal metabolism. Comparing a patient's basal metabolism (PBM) calculated from pretransplant body weight with the standard basal metabolism (SBM) calculated from standard body weight (body mass index (BMI) = 22), we defined the basal metabolic ratio (BMR) as a parameter (BMR = PBM/SBM). We retrospectively analyzed 360 adult patients transplanted between 1997 and 2006 at a single center in Japan. A multivariate analysis of OS30 showed risk factors to be: BMR BMR; LBR) (P = 0.01), BMR > 1.05 (high BMR; HBR) (P = 0.005) and non-complete remission (non-CR) (P 5 0.001), whereas a multivariate analysis of OS60 showed those risk factors to be: LBR (P = 0.02), HBR (P = 0.04), non-CR (P = 0.002), and performance status BMR BMR; ABR) (96.8 and 90.3% for ABR, 87.1 and 76.2% for LBR, and 87.8 and 81.1% for HBR). In conclusion, BMR could prove to be a predictor of early death after allo-SCT.

  17. Extending the Derek-Meteor Workflow to Predict Chemical-Toxicity Space Impacted by Metabolism: Application to ToxCast and Tox21 Chemical Inventories

    Science.gov (United States)

    A central aim of EPA’s ToxCast project is to use in vitro high-throughput screening (HTS) profiles to build predictive models of in vivo toxicity. Where assays lack metabolic capability, such efforts may need to anticipate the role of metabolic activation (or deactivation). A wo...

  18. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes

    Science.gov (United States)

    De Martino, Daniele

    2017-12-01

    In this work maximum entropy distributions in the space of steady states of metabolic networks are considered upon constraining the first and second moments of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux distributions, emerges upon considering control on the average growth (optimization) and its fluctuations (heterogeneity). This is applied to the carbon catabolic core of Escherichia coli where it quantifies the metabolic activity of slow growing phenotypes and it provides a quantitative map with metabolic fluxes, opening the possibility to detect coexistence from flux data. A preliminary analysis on data for E. coli cultures in standard conditions shows degeneracy for the inferred parameters that extend in the coexistence region.

  19. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Zhang, Xi-Cheng; Nilsson, Avlant

    2017-01-01

    , which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance...... and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping...... with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between...

  20. A Human Hepatocyte-Bearing Mouse: An Animal Model to Predict Drug Metabolism and Effectiveness in Humans

    Directory of Open Access Journals (Sweden)

    Katsutoshi Yoshizato

    2009-01-01

    Full Text Available Preclinical studies to predict the efficacy and safety of drugs have conventionally been conducted almost exclusively in mice and rats as rodents, despite the differences in drug metabolism between humans and rodents. Furthermore, human (ℎ viruses such as hepatitis viruses do not infect the rodent liver. A mouse bearing a liver in which the hepatocytes have been largely repopulated with ℎ-hepatocytes would overcome some of these disadvantages. We have established a practical, efficient, and large-scale production system for such mice. Accumulated evidence has demonstrated that these hepatocyte-humanized mice are a useful and reliable animal model, exhibiting ℎ-type responses in a series of in vivo drug processing (adsorption, distribution, metabolism, excretion experiments and in the infection and propagation of hepatic viruses. In this review, we present the current status of studies on chimeric mice and describe their usefulness in the study of peroxisome proliferator-activated receptors.

  1. Development of a computational tool to rival experts in the prediction of sites of metabolism of xenobiotics by p450s.

    Science.gov (United States)

    Campagna-Slater, Valérie; Pottel, Joshua; Therrien, Eric; Cantin, Louis-David; Moitessier, Nicolas

    2012-09-24

    The metabolism of xenobiotics--and more specifically drugs--in the liver is a critical process controlling their half-life. Although there exist experimental methods, which measure the metabolic stability of xenobiotics and identify their metabolites, developing higher throughput predictive methods is an avenue of research. It is expected that predicting the chemical nature of the metabolites would be an asset for designing safer drugs and/or drugs with modulated half-lives. We have developed IMPACTS (In-silico Metabolism Prediction by Activated Cytochromes and Transition States), a computational tool combining docking to metabolic enzymes, transition state modeling, and rule-based substrate reactivity prediction to predict the site of metabolism (SoM) of xenobiotics. Its application to sets of CYP1A2, CYP2C9, CYP2D6, and CYP3A4 substrates and comparison to experts' predictions demonstrates its accuracy and significance. IMPACTS identified an experimentally observed SoM in the top 2 predicted sites for 77% of the substrates, while the accuracy of biotransformation experts' prediction was 65%. Application of IMPACTS to external sets and comparison of its accuracy to those of eleven other methods further validated the method implemented in IMPACTS.

  2. Ecological niche modeling for visceral leishmaniasis in the state of Bahia, Brazil, using genetic algorithm for rule-set prediction and growing degree day-water budget analysis

    Directory of Open Access Journals (Sweden)

    Prixia Nieto

    2006-11-01

    Full Text Available Two predictive models were developed within a geographic information system using Genetic Algorithm Rule-Set Prediction (GARP and the growing degree day (GDD-water budget (WB concept to predict the distribution and potential risk of visceral leishmaniasis (VL in the State of Bahia, Brazil. The objective was to define the environmental suitability of the disease as well as to obtain a deeper understanding of the eco-epidemiology of VL by associating environmental and climatic variables with disease prevalence. Both the GARP model and the GDDWB model, using different analysis approaches and with the same human prevalence database, predicted similar distribution and abundance patterns for the Lutzomyia longipalpis-Leishmania chagasi system in Bahia. High and moderate prevalence sites for VL were significantly related to areas of high and moderate risk prediction by: (i the area predicted by the GARP model, depending on the number of pixels that overlapped among eleven annual model years, and (ii the number of potential generations per year that could be completed by the Lu. longipalpis-L. chagasi system by GDD-WB analysis. When applied to the ecological zones of Bahia, both the GARP and the GDD-WB prediction models suggest that the highest VL risk is in the interior region of the state, characterized by a semi-arid and hot climate known as Caatinga, while the risk in the Bahia interior forest and the Cerrado ecological regions is lower. The Bahia coastal forest was predicted to be a low-risk area due to the unsuitable conditions for the vector and VL transmission.

  3. Hypertensive patients exhibit an altered metabolism. A specific metabolite signature in urine is able to predict albuminuria progression.

    Science.gov (United States)

    Gonzalez-Calero, Laura; Martin-Lorenzo, Marta; Martínez, Paula J; Baldan-Martin, Montserrat; Ruiz-Hurtado, Gema; Segura, Julian; de la Cuesta, Fernando; Barderas, Maria G; Ruilope, Luis M; Vivanco, Fernando; Alvarez-Llamas, Gloria

    2016-12-01

    Hypertension (HTN) is increasing in prevalence, and albuminuria is a strong indicator of cardiovascular risk and renal damage progression. Despite blood pressure control with chronic treatment, a relevant subgroup of patients develop albuminuria. However, the biological factors responsible for albuminuria development and progression are underexplored. We aimed to identify key metabolic targets and biological pathways involved in the negative progression of cardiovascular and renal damage in hypertensives undergoing chronic treatment. A series of 1533 patients were followed for 5 years to investigate the evolution of albuminuria. Patients were classified as: (1) patients with persistent normoalbuminuria; (2) patients developing de novo albuminuria; and (3) patients with maintained albuminuria. At the end of follow-up, urine from 30 nonhypertensive subjects (control group) and a representative cohort of 118 patients was collected for metabolomic analysis. Metabolic patterns of interest were identified in a first discovery phase by nuclear magnetic resonance and further confirmed by liquid chromatography-mass spectrometry. Metabolites corresponding to HTN or albuminuria were measured in a prospective study carried out in 35 individuals still in normoalbuminuria, to evaluate their potential as predictors of albuminuria development. Nine metabolites were significantly altered, linking β-alanine metabolism, arginine and proline metabolism, and tricarboxylic acid cycle. The prospective study revealed a panel composed of guanidinoacetate, glutamate, and pantothenate, which was able to predict development of albuminuria. These metabolic signatures open new possibilities in hypertensive therapy and cardiovascular risk control, providing prompt and more efficient intervention, particularly in patients with worse cardiovascular prognosis. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. A Data Repository and Visualization Toolbox for Metabolic Pathways and PBPK parameter prediction

    Science.gov (United States)

    NHANES is an extensive, well-structured collection of data about hundreds chemicals products of human metabolism and their concentration in human biomarkers, which includes parent to product mapping where known. Together, these data can be used to test the efficacy of application...

  5. Waist height ratio: A universal screening tool for prediction of metabolic syndrome in urban and rural population of Haryana

    Directory of Open Access Journals (Sweden)

    Rajesh Rajput

    2014-01-01

    Methods and Results: A total of 3,042 adults (1,693 in rural area and 1,349 in urban area were screened for the presence of MetS according to the IDF definition. Among 3,042 adults selected as subjects, 1,518 were male and 1,524 were female. The receiver operating curve (ROC analysis was done to determine the optimal cut-off value and the best discriminatory value of each of these anthropometric parameters to predict two or more non-obese components of metabolic syndrome. The area under ROC (AURC for WC was superior to that for other anthropometric variables. The optimal cut-off value of WC in urban and rural males was >89 cm, which is higher than that in urban and rural females at 83 cm and 79 cm, respectively; the optimal cut-off for WHtR was >0.51 in rural females, 0.52 in rural males, and 0.53 in both urban males and females. Both parameters were found to be better than BMI and WHR. ROC and AURC values for WC were better than those for WHtR in men and women in both urban and rural areas (P = 0.0054; however, when the entire study cohort was analyzed together, irrespective of gender and place of residence, then at a value of 0.52, WHtR scored over WC as a predictor of metabolic syndrome (P = 0.001. Conclusion: Although the predictive value of different gender-specific WC values is clearly superior to other anthropometric measures for predicting two or more non-adipose components of MetS, a single value of WHtR irrespective of gender and the area of residence can be used as a universal screening tool for the identification of individuals at high risk of development of metabolic complications.

  6. An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

    Science.gov (United States)

    Nandi, Sutanu; Subramanian, Abhishek; Sarkar, Ram Rup

    2017-07-25

    Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems, like imbalanced provision of training datasets, biased choice of the best model for a given balanced dataset, choice of a complex machine learning algorithm, and data-based automated selection of biologically relevant features for classification. Here, we propose a simple support vector machine-based learning strategy for the prediction of essential genes in Escherichia coli K-12 MG1655 metabolism that integrates a non-conventional combination of an appropriate sample balanced training set, a unique organism-specific genotype, phenotype attributes that characterize essential genes, and optimal parameters of the learning algorithm to generate the best machine learning model (the model with the highest accuracy among all the models trained for different sample training sets). For the first time, we also introduce flux-coupled metabolic subnetwork-based features for enhancing the classification performance. Our strategy proves to be superior as compared to previous SVM-based strategies in obtaining a biologically relevant classification of genes with high sensitivity and specificity. This methodology was also trained with datasets of other recent supervised classification techniques for essential gene classification and tested using reported test datasets. The testing accuracy was always high as compared to the known techniques, proving that our method outperforms known methods. Observations from our study indicate that essential genes are conserved among homologous bacterial species, demonstrate high codon usage bias, GC content and gene expression, and predominantly possess a tendency to form physiological flux modules in metabolism.

  7. A macro-ecological perspective on crassulacean acid metabolism (CAM) photosynthesis evolution in Afro-Madagascan drylands: Eulophiinae orchids as a case study.

    Science.gov (United States)

    Bone, Ruth E; Smith, J Andrew C; Arrigo, Nils; Buerki, Sven

    2015-10-01

    Crassulacean acid metabolism (CAM) photosynthesis is an adaptation to water and atmospheric CO2 deficits that has been linked to diversification in dry-adapted plants. We investigated whether CAM evolution can be associated with the availability of new or alternative niches, using Eulophiinae orchids as a case study. Carbon isotope ratios, geographical and climate data, fossil records and DNA sequences were used to: assess the prevalence of CAM in Eulophiinae orchids; characterize the ecological niche of extant taxa; infer divergence times; and estimate whether CAM is associated with niche shifts. CAM evolved in four terrestrial lineages during the late Miocene/Pliocene, which have uneven diversification patterns. These lineages originated in humid habitats and colonized dry/seasonally dry environments in Africa and Madagascar. Additional key features (variegation, heterophylly) evolved in the most species-rich CAM lineages. Dry habitats were also colonized by a lineage that includes putative mycoheterotrophic taxa. These findings indicate that the switch to CAM is associated with environmental change. With its suite of adaptive traits, this group of orchids represents a unique opportunity to study the adaptations to dry environments, especially in the face of projected global aridification. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

  8. Metabolic syndrome, circulating RBP4, testosterone, and SHBG predict weight regain at 6 months after weight loss in men

    DEFF Research Database (Denmark)

    Wang, Ping; Menheere, Paul P C A; Astrup, Arne

    2013-01-01

    OBJECTIVE: Weight loss helps reduce the symptoms of the metabolic syndrome (MetS) in the obese, but weight regain after active weight loss is common. We investigated the changes and predictive role of circulating adipokines and sex hormones for weight regain in men during dietary intervention......, adiponectin, retinol-binding protein 4 (RBP4), luteinizing hormone, prolactin, progesterone, total and free testosterone, and sex hormone-binding globulin (SHBG) were measured at baseline, after 8-week low-calorie diet-induced active weight loss, and after a subsequent 26-week ad libitum weight maintenance...

  9. Comparing the measured basal metabolic rates in patients with chronic disorders of consciousness to the estimated basal metabolic rate calculated from common predictive equations.

    Science.gov (United States)

    Xiao, Guizhen; Xie, Qiuyou; He, Yanbin; Wang, Ziwen; Chen, Yan; Jiang, Mengliu; Ni, Xiaoxiao; Wang, Qinxian; Murong, Min; Guo, Yequn; Qiu, Xiaowen; Yu, Ronghao

    2017-10-01

    Accurately predicting the basal metabolic rate (BMR) of patients in a vegetative state (VS) or minimally conscious state (MCS) is critical to proper nutritional therapy, but commonly used equations have not been shown to be accurate. Therefore, we compared the BMR measured by indirect calorimetry (IC) to BMR values estimated using common predictive equations in VS and MCS patients. Body composition variables were measured using the bioelectric impedance analysis (BIA) technique. BMR was measured by IC in 82 patients (64 men and 18 women) with VS or MCS. Patients were classified by body mass index as underweight (BMR was estimated for each group using the Harris-Benedict (H-B), Schofield, or Cunningham equations and compared to the measured BMR using Bland-Altman analyses. For the underweight group, there was a significant difference between the measured BMR values and the estimated BMR values calculated using the H-B, Schofield, and Cunningham equations (p BMR values estimated using the H-B and Cunningham equations were different significantly from the measured BMR (p BMR in the normal-weight group. The Schofield equation showed the best concordance (only 41.5%) with the BMR values measured by IC. None of the commonly used equations to estimate BMR were suitable for the VS or MCS populations. Indirect calorimetry is the preferred way to avoid either over or underestimate of BMR values. Copyright © 2016. Published by Elsevier Ltd.

  10. Computational tools and resources for metabolism-related property predictions. 1. Overview of publicly available (free and commercial) databases and software.

    Science.gov (United States)

    Peach, Megan L; Zakharov, Alexey V; Liu, Ruifeng; Pugliese, Angelo; Tawa, Gregory; Wallqvist, Anders; Nicklaus, Marc C

    2012-10-01

    Metabolism has been identified as a defining factor in drug development success or failure because of its impact on many aspects of drug pharmacology, including bioavailability, half-life and toxicity. In this article, we provide an outline and descriptions of the resources for metabolism-related property predictions that are currently either freely or commercially available to the public. These resources include databases with data on, and software for prediction of, several end points: metabolite formation, sites of metabolic transformation, binding to metabolizing enzymes and metabolic stability. We attempt to place each tool in historical context and describe, wherever possible, the data it was based on. For predictions of interactions with metabolizing enzymes, we show a typical set of results for a small test set of compounds. Our aim is to give a clear overview of the areas and aspects of metabolism prediction in which the currently available resources are useful and accurate, and the areas in which they are inadequate or missing entirely.

  11. FDG-PET Response Prediction in Pediatric Hodgkin’s Lymphoma: Impact of Metabolically Defined Tumor Volumes and Individualized SUV Measurements on the Positive Predictive Value

    Energy Technology Data Exchange (ETDEWEB)

    Hussien, Amr Elsayed M. [Department of Nuclear Medicine (KME), Forschungszentrum Jülich, Medical Faculty, Heinrich-Heine-University Düsseldorf, Jülich, 52426 (Germany); Department of Nuclear Medicine, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, 40225 (Germany); Furth, Christian [Department of Radiology and Nuclear Medicine, Medical School, Otto-von-Guericke University Magdeburg, Magdeburg, 39120 (Germany); Schönberger, Stefan [Department of Pediatric Oncology, Hematology and Clinical Immunology, University Children’s Hospital, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, 40225 (Germany); Hundsdoerfer, Patrick [Department of Pediatric Oncology and Hematology, Charité Campus Virchow, Humboldt-University Berlin, Berlin, 13353 (Germany); Steffen, Ingo G.; Amthauer, Holger [Department of Radiology and Nuclear Medicine, Medical School, Otto-von-Guericke University Magdeburg, Magdeburg, 39120 (Germany); Müller, Hans-Wilhelm; Hautzel, Hubertus, E-mail: h.hautzel@fz-juelich.de [Department of Nuclear Medicine (KME), Forschungszentrum Jülich, Medical Faculty, Heinrich-Heine-University Düsseldorf, Jülich, 52426 (Germany); Department of Nuclear Medicine, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, 40225 (Germany)

    2015-01-28

    Background: In pediatric Hodgkin’s lymphoma (pHL) early response-to-therapy prediction is metabolically assessed by (18)F-FDG PET carrying an excellent negative predictive value (NPV) but an impaired positive predictive value (PPV). Aim of this study was to improve the PPV while keeping the optimal NPV. A comparison of different PET data analyses was performed applying individualized standardized uptake values (SUV), PET-derived metabolic tumor volume (MTV) and the product of both parameters, termed total lesion glycolysis (TLG); Methods: One-hundred-eight PET datasets (PET1, n = 54; PET2, n = 54) of 54 children were analysed by visual and semi-quantitative means. SUVmax, SUVmean, MTV and TLG were obtained the results of both PETs and the relative change from PET1 to PET2 (Δ in %) were compared for their capability of identifying responders and non-responders using receiver operating characteristics (ROC)-curves. In consideration of individual variations in noise and contrasts levels all parameters were additionally obtained after threshold correction to lean body mass and background; Results: All semi-quantitative SUV estimates obtained at PET2 were significantly superior to the visual PET2 analysis. However, ΔSUVmax revealed the best results (area under the curve, 0.92; p < 0.001; sensitivity 100%; specificity 85.4%; PPV 46.2%; NPV 100%; accuracy, 87.0%) but was not significantly superior to SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean body mass and background individualization of the datasets did not impove the results of the ROC analyses; Conclusions: Sophisticated semi-quantitative PET measures in early response assessment of pHL patients do not perform significantly better than the previously proposed ΔSUVmax. All analytical strategies failed to improve the impaired PPV to a clinically acceptable level while preserving the excellent NPV.

  12. FDG-PET Response Prediction in Pediatric Hodgkin’s Lymphoma: Impact of Metabolically Defined Tumor Volumes and Individualized SUV Measurements on the Positive Predictive Value

    Directory of Open Access Journals (Sweden)

    Amr Elsayed M. Hussien

    2015-01-01

    Full Text Available Background: In pediatric Hodgkin’s lymphoma (pHL early response-to-therapy prediction is metabolically assessed by (18F-FDG PET carrying an excellent negative predictive value (NPV but an impaired positive predictive value (PPV. Aim of this study was to improve the PPV while keeping the optimal NPV. A comparison of different PET data analyses was performed applying individualized standardized uptake values (SUV, PET-derived metabolic tumor volume (MTV and the product of both parameters, termed total lesion glycolysis (TLG; Methods: One-hundred-eight PET datasets (PET1, n = 54; PET2, n = 54 of 54 children were analysed by visual and semi-quantitative means. SUVmax, SUVmean, MTV and TLG were obtained the results of both PETs and the relative change from PET1 to PET2 (Δ in % were compared for their capability of identifying responders and non-responders using receiver operating characteristics (ROC-curves. In consideration of individual variations in noise and contrasts levels all parameters were additionally obtained after threshold correction to lean body mass and background; Results: All semi-quantitative SUV estimates obtained at PET2 were significantly superior to the visual PET2 analysis. However, ΔSUVmax revealed the best results (area under the curve, 0.92; p < 0.001; sensitivity 100%; specificity 85.4%; PPV 46.2%; NPV 100%; accuracy, 87.0% but was not significantly superior to SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean body mass and background individualization of the datasets did not impove the results of the ROC analyses; Conclusions: Sophisticated semi-quantitative PET measures in early response assessment of pHL patients do not perform significantly better than the previously proposed ΔSUVmax. All analytical strategies failed to improve the impaired PPV to a clinically acceptable level while preserving the excellent NPV.

  13. FDG-PET Response Prediction in Pediatric Hodgkin’s Lymphoma: Impact of Metabolically Defined Tumor Volumes and Individualized SUV Measurements on the Positive Predictive Value

    International Nuclear Information System (INIS)

    Hussien, Amr Elsayed M.; Furth, Christian; Schönberger, Stefan; Hundsdoerfer, Patrick; Steffen, Ingo G.; Amthauer, Holger; Müller, Hans-Wilhelm; Hautzel, Hubertus

    2015-01-01

    Background: In pediatric Hodgkin’s lymphoma (pHL) early response-to-therapy prediction is metabolically assessed by (18)F-FDG PET carrying an excellent negative predictive value (NPV) but an impaired positive predictive value (PPV). Aim of this study was to improve the PPV while keeping the optimal NPV. A comparison of different PET data analyses was performed applying individualized standardized uptake values (SUV), PET-derived metabolic tumor volume (MTV) and the product of both parameters, termed total lesion glycolysis (TLG); Methods: One-hundred-eight PET datasets (PET1, n = 54; PET2, n = 54) of 54 children were analysed by visual and semi-quantitative means. SUVmax, SUVmean, MTV and TLG were obtained the results of both PETs and the relative change from PET1 to PET2 (Δ in %) were compared for their capability of identifying responders and non-responders using receiver operating characteristics (ROC)-curves. In consideration of individual variations in noise and contrasts levels all parameters were additionally obtained after threshold correction to lean body mass and background; Results: All semi-quantitative SUV estimates obtained at PET2 were significantly superior to the visual PET2 analysis. However, ΔSUVmax revealed the best results (area under the curve, 0.92; p < 0.001; sensitivity 100%; specificity 85.4%; PPV 46.2%; NPV 100%; accuracy, 87.0%) but was not significantly superior to SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean body mass and background individualization of the datasets did not impove the results of the ROC analyses; Conclusions: Sophisticated semi-quantitative PET measures in early response assessment of pHL patients do not perform significantly better than the previously proposed ΔSUVmax. All analytical strategies failed to improve the impaired PPV to a clinically acceptable level while preserving the excellent NPV

  14. Predicting chronic copper and nickel reproductive toxicity to Daphnia pulex-pulicaria from whole-animal metabolic profiles.

    Science.gov (United States)

    Taylor, Nadine S; Kirwan, Jennifer A; Johnson, Craig; Yan, Norman D; Viant, Mark R; Gunn, John M; McGeer, James C

    2016-05-01

    The emergence of omics approaches in environmental research has enhanced our understanding of the mechanisms underlying toxicity; however, extrapolation from molecular effects to whole-organism and population level outcomes remains a considerable challenge. Using environmentally relevant, sublethal, concentrations of two metals (Cu and Ni), both singly and in binary mixtures, we integrated data from traditional chronic, partial life-cycle toxicity testing and metabolomics to generate a statistical model that was predictive of reproductive impairment in a Daphnia pulex-pulicaria hybrid that was isolated from an historically metal-stressed lake. Furthermore, we determined that the metabolic profiles of organisms exposed in a separate acute assay were also predictive of impaired reproduction following metal exposure. Thus we were able to directly associate molecular profiles to a key population response - reproduction, a key step towards improving environmental risk assessment and management. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  15. [Ecology and ecologies].

    Science.gov (United States)

    Valera, Luca

    2011-01-01

    Ecology (from the Greek words οιχοσ, "house" and λογια "study of") is the science of the "house", since it studies the environments where we live. There are three main ways of thinking about Ecology: Ecology as the study of interactions (between humans and the environment, between humans and living beings, between all living beings, etc.), Ecology as the statistical study of interactions, Ecology as a faith, or rather as a science that requires a metaphysical view. The history of Ecology shows us how this view was released by the label of "folk sense" to gain the epistemological status of science, a science that strives to be interdisciplinary. So, the aim of Ecology is to study, through a scientific methodology, the whole natural world, answering to very different questions, that arise from several fields (Economics, Biology, Sociology, Philosophy, etc.). The plurality of issues that Ecology has to face led, during the Twentieth-century, to branch off in several different "ecologies". As a result, each one of these new approaches chose as its own field a more limited and specific portion of reality.

  16. Apo Lipoprotein A1 Gene Polymorphisms Predict Cardio-Metabolic Risk in South Asian Immigrants

    Directory of Open Access Journals (Sweden)

    Sunita Dodani

    2012-01-01

    Full Text Available Objectives: Coronary artery disease (CAD is a leading cause of death globally with increasing burden in South Asians in the US. Specific genetic variants that influence CAD have not been fully assessed in South Asian Immigrants. The goal is to identify Apo lipoprotein A1 (APOA1 gene polymorphisms and their association with CAD risk factors, metabolic syndrome and dysfunctional HDL (Dys-HDL.

  17. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

    Science.gov (United States)

    2016-03-15

    dynamics. For instance, the gene expression data from the GEO database were collected under different condi- tions related to time, temperature , medium...Microcolony formation by the opportunistic pathogen Pseudomonas aeruginosa requires pyruvate and pyruvate fermentation . Mol Microbiol. 2012 Nov; 86...reso- lution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regula- tor Gcn4p. Proc Natl Acad Sci U S A

  18. A hybrid mathematical modeling approach of the metabolic fate of a fluorescent sphingolipid analogue to predict cancer chemosensitivity.

    Science.gov (United States)

    Molina-Mora, J A; Kop-Montero, M; Quirós-Fernández, I; Quiros, S; Crespo-Mariño, J L; Mora-Rodríguez, R A

    2018-04-13

    Sphingolipid (SL) metabolism is a complex biological system that produces and transforms ceramides and other molecules able to modulate other cellular processes, including survival or death pathways key to cell fate decisions. This signaling pathway integrates several types of stress signals, including chemotherapy, into changes in the activity of its metabolic enzymes, altering thereby the cellular composition of bioactive SLs. Therefore, the SL pathway is a promising sensor of chemosensitivity in cancer and a target hub to overcome resistance. However, there is still a gap in our understanding of how chemotherapeutic drugs can disturb the SL pathway in order to control cellular fate. We propose to bridge this gap by a systems biology approach to integrate i) a dynamic model of SL analogue (BODIPY-FL fluorescent-sphingomyelin analogue, SM-BOD) metabolism, ii) a Gaussian mixture model (GMM) of the fluorescence features to identify how the SL pathway senses the effect of chemotherapy and iii) a fuzzy logic model (FLM) to associate SL composition with cell viability by semi-quantitative rules. Altogether, this hybrid model approach was able to predict the cell viability of double experimental perturbations with chemotherapy, indicating that the SL pathway is a promising sensor to design strategies to overcome drug resistance in cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

  19. Prediction of cytochrome P450 xenobiotic metabolism: tethered docking and reactivity derived from ligand molecular orbital analysis.

    Science.gov (United States)

    Tyzack, Jonathan D; Williamson, Mark J; Torella, Rubben; Glen, Robert C

    2013-06-24

    Metabolism of xenobiotic and endogenous compounds is frequently complex, not completely elucidated, and therefore often ambiguous. The prediction of sites of metabolism (SoM) can be particularly helpful as a first step toward the identification of metabolites, a process especially relevant to drug discovery. This paper describes a reactivity approach for predicting SoM whereby reactivity is derived directly from the ground state ligand molecular orbital analysis, calculated using Density Functional Theory, using a novel implementation of the average local ionization energy. Thus each potential SoM is sampled in the context of the whole ligand, in contrast to other popular approaches where activation energies are calculated for a predefined database of molecular fragments and assigned to matching moieties in a query ligand. In addition, one of the first descriptions of molecular dynamics of cytochrome P450 (CYP) isoforms 3A4, 2D6, and 2C9 in their Compound I state is reported, and, from the representative protein structures obtained, an analysis and evaluation of various docking approaches using GOLD is performed. In particular, a covalent docking approach is described coupled with the modeling of important electrostatic interactions between CYP and ligand using spherical constraints. Combining the docking and reactivity results, obtained using standard functionality from common docking and quantum chemical applications, enables a SoM to be identified in the top 2 predictions for 75%, 80%, and 78% of the data sets for 3A4, 2D6, and 2C9, respectively, results that are accessible and competitive with other recently published prediction tools.

  20. Can We Rely on Predicted Basal Metabolic Rate in Patients With Intestinal Failure on Home Parenteral Nutrition?

    Science.gov (United States)

    Skallerup, Anders; Nygaard, Louis; Olesen, Søren Schou; Vinter-Jensen, Lars; Køhler, Marianne; Rasmussen, Henrik Højgaard

    2017-09-01

    Intestinal failure (IF) is a serious and common complication of short bowel syndrome with patients depending on parenteral nutrition (PN) support. Effective nutrition management requires an accurate estimation of the patient's basal metabolic rate (BMR) to avoid underfeeding or overfeeding. However, indirect calorimetry, considered the gold standard for BMR assessment, is a time- and resource-consuming procedure. Consequently, several equations for prediction of BMR have been developed in different settings, but their accuracy in patients with IF are yet to be investigated. We evaluated the accuracy of predicted BMR in clinically stable patients with IF dependent on home parenteral nutrition (HPN). In total, 103 patients with IF were included. We used indirect calorimetry for assessment of BMR and calculated predicted BMR using different equations based on anthropometric and/or bioelectrical impedance parameters. The accuracy of predicted BMR was evaluated using Bland-Altman analysis with measured BMR as the gold standard. The average measured BMR was 1272 ± 245 kcal/d. The most accurate estimations of BMR were obtained using the Harris-Benedict equation (mean bias, 14 kcal/d [ P = .28]; limits of agreement [LoA], -238 to 266 kcal/d) and the Johnstone equation (mean bias, -16 kcal/d [ P = .24]; LoA, -285 to 253 kcal/d). For both equations, 67% of patients had a predicted BMR from 90%-110% All other equations demonstrated a statistically and clinically significant difference between measured and predicted BMR. The Harris-Benedict and Johnstone equations reliably predict BMR in two-thirds of clinically stable patients with IF on HPN.

  1. Scaling of Metabolic Scaling within Physical Limits

    Directory of Open Access Journals (Sweden)

    Douglas S. Glazier

    2014-10-01

    Full Text Available Both the slope and elevation of scaling relationships between log metabolic rate and log body size vary taxonomically and in relation to physiological or developmental state, ecological lifestyle and environmental conditions. Here I discuss how the recently proposed metabolic-level boundaries hypothesis (MLBH provides a useful conceptual framework for explaining and predicting much, but not all of this variation. This hypothesis is based on three major assumptions: (1 various processes related to body volume and surface area exert state-dependent effects on the scaling slope for metabolic rate in relation to body mass; (2 the elevation and slope of metabolic scaling relationships are linked; and (3 both intrinsic (anatomical, biochemical and physiological and extrinsic (ecological factors can affect metabolic scaling. According to the MLBH, the diversity of metabolic scaling relationships occurs within physical boundary limits related to body volume and surface area. Within these limits, specific metabolic scaling slopes can be predicted from the metabolic level (or scaling elevation of a species or group of species. In essence, metabolic scaling itself scales with metabolic level, which is in turn contingent on various intrinsic and extrinsic conditions operating in physiological or evolutionary time. The MLBH represents a “meta-mechanism” or collection of multiple, specific mechanisms that have contingent, state-dependent effects. As such, the MLBH is Darwinian in approach (the theory of natural selection is also meta-mechanistic, in contrast to currently influential metabolic scaling theory that is Newtonian in approach (i.e., based on unitary deterministic laws. Furthermore, the MLBH can be viewed as part of a more general theory that includes other mechanisms that may also affect metabolic scaling.

  2. Identification of behavioural and metabolic factors predicting adiposity sensitivity to both high fat and high carbohydrate diets in rats.

    Directory of Open Access Journals (Sweden)

    Patrick Christian Even

    2011-12-01

    Full Text Available Individuals exhibit a great variation in their body weight gain response to a high-fat diet. Identification of predictive factors would enable better directed intervention towards susceptible individuals to treat obesity, and uncover potential mechanisms for treatment targeting. We set out to identify predictive behavioural and metabolic factors in an outbred rat model. 12 rats were analysed in metabolic cages for a period of 5 days during both high carbohydrate diet (HCD, and transition to a high fat diet (HFD. After a recovery period, rats were given a HFD for 6 days to identify those resistant or sensitive to it according to body weight gain. Rats were dissected at the end of the study to analyse body composition. This showed that in rats fed a HCD during most of their life, small differences in final body weight hid large variations in adiposity, allowing separation of rats into a second classification of carbohydrate-sensitive or -resistant. Meal size and meal number were found to be good predictors of sensitivity to a HFD, intensity of motor activity and ingestion speed good predictors of sensitivity to a HCD. Rats that were sensitive to the HCD could be resistant to the HFD and vice versa. This contributes to the idea that to be obesity prone does not necessarily need a HFD, it can also happen under a HCD, and be a hidden adiposity change with stable body weight.

  3. Does youth adiposity, or change in adiposity from youth to adulthood, predict metabolically healthy obesity in adulthood?

    Science.gov (United States)

    Smith, K J; Bessell, E; Magnussen, C G; Dwyer, T; Venn, A J

    2016-10-01

    Individuals with metabolically healthy obesity (MHO) do not have the metabolic complications usually associated with obesity. To examine whether youth adiposity, or change in adiposity from youth to adulthood, predicts MHO 20 years later. A national sample of 2410 Australian participants had height, weight and waist circumference (WC) measured in 1985 (7-15 years old) and 2004-2006 (26-36 years old). A fasting blood sample was taken in 2004-2006. MHO was defined as body mass index (BMI) ≥30 kg m(-2) , normal fasting glucose (1.036 mmol L(-1) men, > 1.295 mmol L(-1) women), blood pressure (youth BMI (or WC) z-score or change in BMI (or WC) z-score from youth to adulthood, adjusted for sex and youth age. In total 323 individuals were obese at follow-up, 79 (24.5%) were MHO. Adult MHO was not associated with youth BMI (RR: 1.00, 95%CI: 0.85-1.19) or WC (RR: 0.93, 95%CI: 0.79-1.11). Individuals were less likely to be MHO if they had larger increases in BMI (BMI RR: 0.74, 95%CI: 0.57-0.97) or WC (RR: 0.70, 95%CI: 0.55-0.90) from youth to adulthood. Change in adiposity from youth to adulthood predicted adult MHO better than youth adiposity alone. © 2015 World Obesity.

  4. Quantitative prediction of intestinal metabolism in humans from a simplified intestinal availability model and empirical scaling factor.

    Science.gov (United States)

    Kadono, Keitaro; Akabane, Takafumi; Tabata, Kenji; Gato, Katsuhiko; Terashita, Shigeyuki; Teramura, Toshio

    2010-07-01

    This study aimed to establish a practical and convenient method of predicting intestinal availability (F(g)) in humans for highly permeable compounds at the drug discovery stage, with a focus on CYP3A4-mediated metabolism. We constructed a "simplified F(g) model," described using only metabolic parameters, assuming that passive diffusion is dominant when permeability is high and that the effect of transporters in epithelial cells is negligible. Five substrates for CYP3A4 (alprazolam, amlodipine, clonazepam, midazolam, and nifedipine) and four for both CYP3A4 and P-glycoprotein (P-gp) (nicardipine, quinidine, tacrolimus, and verapamil) were used as model compounds. Observed fraction of drug absorbed (F(a)F(g)) values for these compounds were calculated from in vivo pharmacokinetic (PK) parameters, whereas in vitro intestinal intrinsic clearance (CL(int,intestine)) was determined using human intestinal microsomes. The CL(int,intestine) for the model compounds corrected with that of midazolam was defined as CL(m,index) and incorporated into a simplified F(g) model with empirical scaling factor. Regardless of whether the compound was a P-gp substrate, the F(a)F(g) could be reasonably fitted by the simplified F(g) model, and the value of the empirical scaling factor was well estimated. These results suggest that the effects of P-gp on F(a) and F(g) are substantially minor, at least in the case of highly permeable compounds. Furthermore, liver intrinsic clearance (CL(int,liver)) can be used as a surrogate index of intestinal metabolism based on the relationship between CL(int,liver) and CL(m,index). F(g) can be easily predicted using a simplified F(g) model with the empirical scaling factor, enabling more confident selection of drug candidates with desirable PK profiles in humans.

  5. Energizing miRNA research: a review of the role of miRNAs in lipid metabolism, with a prediction that miR-103/107 regulates human metabolic pathways.

    Science.gov (United States)

    Wilfred, Bernard R; Wang, Wang-Xia; Nelson, Peter T

    2007-07-01

    MicroRNAs (miRNAs) are powerful regulators of gene expression. Although first discovered in worm larvae, miRNAs play fundamental biological roles-including in humans-well beyond development. MiRNAs participate in the regulation of metabolism (including lipid metabolism) for all animal species studied. A review of the fascinating and fast-growing literature on miRNA regulation of metabolism can be parsed into three main categories: (1) adipocyte biochemistry and cell fate determination; (2) regulation of metabolic biochemistry in invertebrates; and (3) regulation of metabolic biochemistry in mammals. Most research into the 'function' of a given miRNA in metabolic pathways has concentrated on a given miRNA acting upon a particular 'target' mRNA. Whereas in some biological contexts the effects of a given miRNA:mRNA pair may predominate, this might not be the case generally. In order to provide an example of how a single miRNA could regulate multiple 'target' mRNAs or even entire human metabolic pathways, we include a discussion of metabolic pathways that are predicted to be regulated by the miRNA paralogs, miR-103 and miR-107. These miRNAs, which exist in vertebrate genomes within introns of the pantothenate kinase (PANK) genes, are predicted by bioinformatics to affect multiple mRNA targets in pathways that involve cellular Acetyl-CoA and lipid levels. Significantly, PANK enzymes also affect these pathways, so the miRNA and 'host' gene may act synergistically. These predictions require experimental verification. In conclusion, a review of the literature on miRNA regulation of metabolism leads us believe that the future will provide researchers with many additional energizing revelations.

  6. Lipid accumulation product: a simple and accurate index for predicting metabolic syndrome in Taiwanese people aged 50 and over

    Directory of Open Access Journals (Sweden)

    Chiang Jui-Kun

    2012-09-01

    Full Text Available Abstract Background Lipid accumulation product (LAP has been advocated as a simple clinical indicator of metabolic syndrome (MS. However, no studies have evaluated the accuracy of LAP in predicting MS in Taiwanese adults. The aim of our investigation was to use LAP to predict MS in Taiwanese adults. Methods Taiwanese adults aged 50 years and over (n = 513 were recruited from a physical examination center at a regional hospital in southern Taiwan. MS was defined according to the MS criteria for Taiwanese people. LAP was calculated as (waist circumference [cm] − 65 × (triglyceride concentration [mM] for men, and (waist circumference [cm] − 58 × (triglyceride concentration [mM] for women. Simple logistic regression and receiver-operating characteristic (ROC analyses were conducted. Results The prevalence of MS was 19.5 and 21.5% for males and females, respectively. LAP showed the highest prediction accuracy among adiposity measures with an area under the ROC curve (AUC of 0.901. This was significantly higher than the adiposity measure of waist-to-height ratio (AUC = 0.813. Conclusions LAP was a simple and accurate predictor of MS in Taiwanese people aged 50 years and over. LAP had significantly higher predictability than other adiposity measures tested.

  7. Performance of abdominal bioelectrical impedance analysis and comparison with other known parameters in predicting the metabolic syndrome.

    Science.gov (United States)

    Mousa, U; Kut, A; Bozkus, Y; Cicek Demir, C; Anil, C; Bascil Tutuncu, N

    2013-07-01

    Although obesity is a powerful risk factor for metabolic syndrome (MetS) it is not present in all obese individuals. Increased visceral adipose tissue is the hallmark of this syndrome. In this cross sectional survey we aimed to use abdominal bioelectrical impedance analysis to measure the visceral adipose tissue (VAT) and trunk fat percentages (TF%) in the study population, correlate these findings with traditional anthropometric measures and biochemical parameters of metabolic syndrome and estimate a cut-off value of visceral fat for development of MetS. A total of 285 subjects were enrolled. VAT and TF% were measured by the AB-140 device via abdominal bioelectrical impedance analysis. Fat% was measured by a body composition analyzer (TBF-300). VAT was significantly positively correlated with body mass index, waist circumference, TF%, HOMA IR, fat percentage, fasting plasma glucose and triglycerides. Strongest correlations were between VAT and TF%, VAT and device measured waist circumference and between VAT and manual waist circumference (r=0.95, r=0.93, r=0.92 respectively). Correlations of VAT and TF% with metabolic parameters were significant but weak. The mean VAT and TF% in MetS (+) groups were significantly higher than patients in MetS (-) groups in both sexes. The areas under the ROC curves were 0.730 (95% CI: 0.661-0.791) for female VAT and 0.702 (95% CI: 0.654-0.749) for male VAT in predicting MetS which were similar to the areas under ROC curves calculated for device and manually measured waist circumference, HOMA IR and TF% in predicting MetS (p>0.05 for all comparisons). The accuracy of VAT and TF% for predicting MetS was not sufficient. From our results we can deduce that the performance of abdominal BIA in predicting MetS is weak but could be used in the follow-up of patients with obesity and/or MetS. This has to be confirmed in future studies. © Georg Thieme Verlag KG Stuttgart · New York.

  8. Migrant Asian Indians in New Zealand; prediction of metabolic syndrome using body weights and measures.

    Science.gov (United States)

    Jowitt, Ljiljana M; Lu, Louise Weiwei; Rush, Elaine C

    2014-01-01

    The aim of this study of Asian Indian migrants in New Zealand was to determine cut-off points for body mass index, waist circumference, waist-to-hip ratio, and waist-to-height ratio that best discriminate for increased risk of type 2 diabetes and cardiovascular disease. One hundred and seventy-five (90F, 85M) Asian Indian volunteers (aged >50 y) were recruited from urban Auckland, New Zealand. Body weight, height and waist and hip circumferences were measured using standard techniques. Waist-to-hip ratio, waist-to-height ratio and body mass index were derived. Total and percent body fat by dual energy X-ray absorptiometry, and fasting glucose, insulin and lipids were measured. Three measures of metabolic risk were determined: the homeostasis model assessment of insulin resistance, the McAuley score for insulin sensitivity and metabolic syndrome by International Diabetes Federation criteria. Body mass index, percent body fat and anthropometric measurements of central adiposity generally did not perform well as indicators of metabolic risk in this high risk population of Asian Indian migrants. Our data support the use of lower ethnic specific body mass index and waist circumference for Asian Indian women and men. The discriminatory power of waist-to-height ratio was similar to that of body mass index. Hence, waist-to-height ratio could be used as a simple screening tool. A recommendation, of a waist-to- height ratio of less than 0.5 that would underpin the simple public health message of "your waist circumference should be less than half your height".

  9. Reconciled Rat and Human Metabolic Networks for Comparative Toxicogenomics and Biomarker Predictions

    Science.gov (United States)

    2017-02-08

    reactions. ETC, electron transport chain; PPP, pentose phosphate pathway. NATURE COMMUNICATIONS | DOI: 10.1038/ncomms14250 ARTICLE NATURE COMMUNICATIONS...CDCA) Alpha-muricholic acid (αMCA) x Beta-muricholic acid (βMCA) x Secondary bile acids Deoxycholic acid (DCA) Lithocholic acid ( LCA ) Hyocholic acid...than rats Neu5Ac Lewisa ManNAc Microbial metabolism MDCA Cyp3a18 Cyp3a18 CDCA LCA CDCA LCA SharedRat-specific Human-specific Figure 3 | Functional

  10. Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

    Science.gov (United States)

    Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

    2014-01-27

    The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W

  11. Acute post cessation smoking. A strong predictive factor for metabolic syndrome among adult Saudis

    International Nuclear Information System (INIS)

    AlDaghri, Nasser M.

    2009-01-01

    To determine the influence of tobacco exposure in the development of metabolic syndrome (MS) in the adult Saudi population. Six hundred and sixty-four adults (305 males and 359 females) aged 25-70 years were included in this cross-sectional study conducted at the King Abdul Aziz University Hospital, between June 2006 and May 2007. We classified the participants into non-smokers, smokers, and ex-smokers (defined as complete cessation for 1-2 years). All subjects were screened for the presence of MS using the modified American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI), International Diabetes Federation (IDF) and World Health Organization (WHO) definitions. Metabolic syndrome was highest among ex-smokers regardless of definition used. Relative risk for ex-smokers (95% CI: 2.23, 1.06-4.73) was more than twice in harboring MS as compared to non-smokers (95% CI: 2.78, 1.57-4.92) (p=0.009). Acute post-cessation smoking is a strong predictor for MS among male and female Arabs. Smoking cessation programs should include a disciplined lifestyle and dietary intervention to counteract the MS-augmenting side-effect of smoking cessation. (author)

  12. Assessment and prediction of land ecological environment quality change based on remote sensing-a case study of the Dongting lake area in China

    Science.gov (United States)

    Hu, Wenmin; Wang, Zhongcheng; Li, Chunhua; Zhao, Jin; Li, Yi

    2018-02-01

    Multi-source remote sensing data is rarely used for the comprehensive assessment of land ecologic environment quality. In this study, a digital environmental model was proposed with the inversion algorithm of land and environmental factors based on the multi-source remote sensing data, and a comprehensive index (Ecoindex) was applied to reconstruct and predict the land environment quality of the Dongting Lake Area to assess the effect of human activities on the environment. The main finding was that with the decrease of Grade I and Grade II quality had a decreasing tendency in the lake area, mostly in suburbs and wetlands. Atmospheric water vapour, land use intensity, surface temperature, vegetation coverage, and soil water content were the main driving factors. The cause of degradation was the interference of multi-factor combinations, which led to positive and negative environmental agglomeration effects. Positive agglomeration, such as increased rainfall and vegetation coverage and reduced land use intensity, could increase environmental quality, while negative agglomeration resulted in the opposite. Therefore, reasonable ecological restoration measures should be beneficial to limit the negative effects and decreasing tendency, improve the land ecological environment quality and provide references for macroscopic planning by the government.

  13. The FGF21 response to fructose predicts metabolic health and persists after bariatric surgery in obese humans

    Directory of Open Access Journals (Sweden)

    Kasper W. ter Horst

    2017-11-01

    Conclusions: Fructose ingestion in obese humans stimulates FGF21 secretion, and this response is related to systemic metabolism. Further studies are needed to establish if FGF21 signaling is (pathophysiologically involved in fructose metabolism and metabolic health.

  14. The redoubtable ecological periodic table

    Science.gov (United States)

    Ecological periodic tables are repositories of reliable information on quantitative, predictably recurring (periodic) habitat–community patterns and their uncertainty, scaling and transferability. Their reliability derives from their grounding in sound ecological principle...

  15. "Predictability of body mass index for diabetes: Affected by the presence of metabolic syndrome?"

    Directory of Open Access Journals (Sweden)

    Khalili Davood

    2011-05-01

    Full Text Available Abstract Background Metabolic syndrome (MetS and body mass index (BMI, kg.m-2 are established independent risk factors in the development of diabetes; we prospectively examined their relative contributions and joint relationship with incident diabetes in a Middle Eastern cohort. Method participants of the ongoing Tehran lipid and glucose study are followed on a triennial basis. Among non-diabetic participants aged≥ 20 years at baseline (8,121 those with at least one follow-up examination (5,250 were included for the current study. Multivariate logistic regression models were used to estimate sex-specific adjusted odd ratios (ORs and 95% confidence intervals (CIs of baseline BMI-MetS categories (normal weight without MetS as reference group for incident diabetes among 2186 men and 3064 women, aged ≥ 20 years, free of diabetes at baseline. Result During follow up (median 6.5 years; there were 369 incident diabetes (147 in men. In women without MetS, the multivariate adjusted ORs (95% CIs for overweight (BMI 25-30 kg/m2 and obese (BMI≥30 participants were 2.3 (1.2-4.3 and 2.2 (1.0-4.7, respectively. The corresponding ORs for men without MetS were 1.6 (0.9-2.9 and 3.6 (1.5-8.4 respectively. As compared to the normal-weight/without MetS, normal-weight women and men with MetS, had a multivariate-adjusted ORs for incident diabetes of 8.8 (3.7-21.2 and 3.1 (1.3-7.0, respectively. The corresponding ORs for overweight and obese women with MetS reached to 7.7 (4.0-14.9 and 12.6 (6.9-23.2 and for men reached to 3.4(2.0-5.8 and 5.7(3.9-9.9, respectively. Conclusion This study highlights the importance of screening for MetS in normal weight individuals. Obesity increases diabetes risk in the absence of MetS, underscores the need for more stringent criteria to define healthy metabolic state among obese individuals. Weight reduction measures, thus, should be encouraged in conjunction with achieving metabolic targets not addressed by current definition of

  16. Uric acid best predicts metabolically unhealthy obesity with increased cardiovascular risk in youth and adults.

    Science.gov (United States)

    Mangge, Harald; Zelzer, Sieglinde; Puerstner, Peter; Schnedl, Wolfgang J; Reeves, Gloria; Postolache, Teodor T; Weghuber, Daniel

    2013-01-01

    The obesity prevalence is growing worldwide and largely responsible for cardiovascular disease, the most common cause of death in the western world. The rationale of this study was to distinguish metabolically healthy from unhealthy overweight/obese young and adult patients as compared to healthy normal weight age matched controls by an extensive anthropometric, laboratory, and sonographic vascular assessment. Three hundred fifty five young [8 to obese(ow/ob), 56 normal weight (nw)] and 354 adult [>18-60 years, 175 (ow/ob), 179 nw)] participants of the STYJOBS/EDECTA (STYrian Juvenile Obesity Study/Early DEteCTion of Atherosclerosis) cohort were analyzed. STYJOBS/EDECTA (NCT00482924) is a crossectional study to investigate metabolic/cardiovascular risk profiles in normal and ow/ob people free of disease except metabolic syndrome (MetS). From 299 young ow/ob subjects (8-adult ow/ob subjects (>18-60 years), 79 (45%) had positive criteria for MetS. In both age groups, prevalence of MetS was greater among males. Overweight/obese subjects were divided into "healthy" (no MetS criterion except anthropometry fulfilled) and "unhealthy" (MetS positive). Although percentage body fat did not differ between "healthy" and "unhealthy" ow/ob, nuchal and visceral fat were significantly greater in the "unhealthy" group which had also significantly higher values of carotid intima media thickness (IMT). With MetS as the dependent variable, two logistic regressions including juveniles adults >18 years were performed. The potential predictor variables selected with the exception of age and gender by t test comparisons included IMT, ultrasensitive c-reactive protein (US-CRP), IL-6, malondialdehyde (MDA), oxidized LDL, leptin, adiponectin, uric acid (UA), aldosterone, cortisol, transaminases, fibrinogen. In both groups, uric acid and in adults only, leptin and adiponectin, turned out as the best predictor. Serum levels of UA are a significant predictor of unhealthy obesity in juveniles

  17. Predicting cognitive decline with deep learning of brain metabolism and amyloid imaging.

    Science.gov (United States)

    Choi, Hongyoon; Jin, Kyong Hwan

    2018-05-15

    For effective treatment of Alzheimer's disease (AD), it is important to identify subjects who are most likely to exhibit rapid cognitive decline. We aimed to develop an automatic image interpretation system based on a deep convolutional neural network (CNN) which can accurately predict future cognitive decline in mild cognitive impairment (MCI) patients using flurodeoxyglucose and florbetapir positron emission tomography (PET). PET images of 139 patients with AD, 171 patients with MCI and 182 normal subjects obtained from Alzheimer's Disease Neuroimaging Initiative database were used. Deep CNN was trained using 3-dimensional PET volumes of AD and normal controls as inputs. Manually defined image feature extraction such as quantification using predefined region-of-interests was unnecessary for our approach. Furthermore, it used minimally processed images without spatial normalization which has been commonly used in conventional quantitative analyses. Cognitive outcome of MCI subjects was predicted using this network. The prediction accuracy of the conversion of mild cognitive impairment to AD was compared with the conventional feature-based quantification approach. Accuracy of prediction (84.2%) for conversion to AD in MCI patients outperformed conventional feature-based quantification approaches. ROC analyses revealed that performance of CNN-based approach was significantly higher than that of the conventional quantification methods (p < 0.05). Output scores of the network were strongly correlated with the longitudinal change in cognitive measurements (p < 0.05). These results show the feasibility of deep learning as a practical tool for developing predictive neuroimaging biomarker. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Use of ecological niche modeling as a tool for predicting the potential distribution of Microcystis sp (cyanobacteria in the Aguamilpa Dam, Nayarit, Mexico

    Directory of Open Access Journals (Sweden)

    Enrique Martinez-Meyer

    2012-04-01

    Full Text Available Ecological niche modeling is an important tool to evaluate the spatial distribution of terrestrial species, however, its applicability has been little explored in the aquatic environment. Microcystis sp., a species of cyanobacteria, is widely recognized for its ability to produce a group of toxins known as microcystins, which can cause death of animals as fish, birds and mammals depending on the amount of toxin absorbed. Like any taxonomic group, cyanobacteria has environmental thresholds, therefore, a suitable ecological niche will define their distribution. This study was conducted in Aguamilpa Hydroelectric Reservoir, an artificial ecosystem that started operations in 1994. In this system we evaluated the potential distribution of Microcystis sp., by generating a prediction model based on the concept of ecological niche MAXENT, using a Digital Elevation Model in cells of 100 m x 100 m (1 ha spatial resolution and monitoring eleven physicochemical and biological variables and nutrients in water. The distribution maps were developed using ArcMap 9.2®. The results indicated that Microcystis sp., is distributed mainly in the upper tributary basin (Huaynamota basin during the dry season. There was less chance to find cyanobacteria in the entire system during the cold dry season, while during the warm dry season cyanobacteria was recognized at the confluence of two rivers. During the rainfall season there were no reports of cyanobacteria presence. This species is often associated with arising trophic processes of anthropogenic origin; therefore, attention is required in specific areas that have been identified in this work to improve Aguamilpa’s watershed management and restoration. It was also recognized the importance of phosphorus and nitrogen interaction, which determines the distribution of Microcystis sp., in the Aguamilpa Reservoir. The results of this study demonstrated that ecological niche modeling was a suitable tool to assess the

  19. Intratumoral metabolic heterogeneity predicts invasive components in breast ductal carcinoma in situ

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Hai-Jeon [Ewha Womans University School of Medicine, Department of Nuclear Medicine, Yangchun-Ku, Seoul (Korea, Republic of); Kim, Yemi [Ewha Womans University, Clinical Research Institute, Seoul (Korea, Republic of); Kim, Bom Sahn [Ewha Womans University School of Medicine, Department of Nuclear Medicine, Yangchun-Ku, Seoul (Korea, Republic of); Ewha Womans University, Clinical Research Institute, Seoul (Korea, Republic of)

    2015-12-15

    This study investigated whether texture-based imaging parameters could identify invasive components of ductal carcinoma in situ (DCIS). We enrolled 65 biopsy-confirmed DCIS patients (62 unilateral, 3 bilateral) who underwent {sup 18}F-FDG PET, diffusion-weighted imaging (DWI), or breast-specific gamma imaging (BSGI). We measured SUV{sub max} and intratumoral metabolic heterogeneity by the area under the curve (AUC) of cumulative SUV histograms (CSH) on PET, tumour-to-normal ratio (TNR) and coefficient of variation (COV) as an index of heterogeneity on BSGI, minimum ADC (ADC{sub min}) and ADC difference (ADC{sub diff}) as an index of heterogeneity on DWI. After surgery, final pathology was categorized as pure-DCIS (DCIS-P), DCIS with microinvasion (DCIS-MI), or invasive ductal carcinoma (IDC). Clinicopathologic features of DCIS were correlated with final classification. Final pathology confirmed 44 DCIS-P, 14 DCIS-MI, and 10 IDC. The invasive component of DCIS was significantly correlated with higher SUV{sub max} (p = 0.017) and lower AUC-CSH (p < 0.001) on PET, higher TNR (p = 0.008) and COV (p = 0.035) on BSGI, lower ADC{sub min} (p = 0.016) and higher ADC{sub diff} (p = 0.009) on DWI, and larger pathologic size (p = 0.018). On multiple regression analysis, AUC-CSH was the only significant predictor of invasive components (p = 0.044). The intratumoral metabolic heterogeneity of {sup 18}F-FDG PET was the most important predictor of invasive components of DCIS. (orig.)

  20. Intratumoral metabolic heterogeneity predicts invasive components in breast ductal carcinoma in situ

    International Nuclear Information System (INIS)

    Yoon, Hai-Jeon; Kim, Yemi; Kim, Bom Sahn

    2015-01-01

    This study investigated whether texture-based imaging parameters could identify invasive components of ductal carcinoma in situ (DCIS). We enrolled 65 biopsy-confirmed DCIS patients (62 unilateral, 3 bilateral) who underwent 18 F-FDG PET, diffusion-weighted imaging (DWI), or breast-specific gamma imaging (BSGI). We measured SUV max and intratumoral metabolic heterogeneity by the area under the curve (AUC) of cumulative SUV histograms (CSH) on PET, tumour-to-normal ratio (TNR) and coefficient of variation (COV) as an index of heterogeneity on BSGI, minimum ADC (ADC min ) and ADC difference (ADC diff ) as an index of heterogeneity on DWI. After surgery, final pathology was categorized as pure-DCIS (DCIS-P), DCIS with microinvasion (DCIS-MI), or invasive ductal carcinoma (IDC). Clinicopathologic features of DCIS were correlated with final classification. Final pathology confirmed 44 DCIS-P, 14 DCIS-MI, and 10 IDC. The invasive component of DCIS was significantly correlated with higher SUV max (p = 0.017) and lower AUC-CSH (p < 0.001) on PET, higher TNR (p = 0.008) and COV (p = 0.035) on BSGI, lower ADC min (p = 0.016) and higher ADC diff (p = 0.009) on DWI, and larger pathologic size (p = 0.018). On multiple regression analysis, AUC-CSH was the only significant predictor of invasive components (p = 0.044). The intratumoral metabolic heterogeneity of 18 F-FDG PET was the most important predictor of invasive components of DCIS. (orig.)

  1. Dietary Intake Can Predict and Protect Against Changes in Bone Metabolism during Spaceflight and Recovery (Pro K)

    Science.gov (United States)

    Smith, Scott M.; Zwart, S. R.; Shackelford, L.; Heer, M.

    2009-01-01

    Bone loss is not only a well-documented effect of spaceflight on astronauts, but also a condition that affects millions of men and women on Earth each year. Many countermeasures aimed at preventing bone loss during spaceflight have been proposed, and many have been evaluated to some degree. To date, those showing potential have focused on either exercise or pharmacological interventions, but none have targeted dietary intake alone as a factor to predict or minimize bone loss during spaceflight. The "Dietary Intake Can Predict and Protect against Changes in Bone Metabolism during Spaceflight and Recovery" investigation ("Pro K") is one of the first inflight evaluations of a dietary countermeasure to lessen bone loss of astronauts. This protocol will test the hypothesis that the ratio of acid precursors to base precursors (specifically animal protein to potassium) in the diet can predict directional changes in bone mineral during spaceflight and recovery. The ratio of animal protein to potassium in the diet will be controlled for multiple short (4-day) periods before and during flight. Based on multiple sets of bed rest data, we hypothesize that a higher ratio of the intake of animal protein to the intake of potassium will yield higher concentrations of markers of bone resorption and urinary calcium excretion during flight and during recovery from bone mineral loss after long-duration spaceflight.

  2. Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival.

    Science.gov (United States)

    Megchelenbrink, Wout; Katzir, Rotem; Lu, Xiaowen; Ruppin, Eytan; Notebaart, Richard A

    2015-09-29

    Synthetic dosage lethality (SDL) denotes a genetic interaction between two genes whereby the underexpression of gene A combined with the overexpression of gene B is lethal. SDLs offer a promising way to kill cancer cells by inhibiting the activity of SDL partners of activated oncogenes in tumors, which are often difficult to target directly. As experimental genome-wide SDL screens are still scarce, here we introduce a network-level computational modeling framework that quantitatively predicts human SDLs in metabolism. For each enzyme pair (A, B) we systematically knock out the flux through A combined with a stepwise flux increase through B and search for pairs that reduce cellular growth more than when either enzyme is perturbed individually. The predictive signal of the emerging network of 12,000 SDLs is demonstrated in five different ways. (i) It can be successfully used to predict gene essentiality in shRNA cancer cell line screens. Moving to clinical tumors, we show that (ii) SDLs are significantly underrepresented in tumors. Furthermore, breast cancer tumors with SDLs active (iii) have smaller sizes and (iv) result in increased patient survival, indicating that activation of SDLs increases cancer vulnerability. Finally, (v) patient survival improves when multiple SDLs are present, pointing to a cumulative effect. This study lays the basis for quantitative identification of cancer SDLs in a model-based mechanistic manner. The approach presented can be used to identify SDLs in species and cell types in which "omics" data necessary for data-driven identification are missing.

  3. Species-specific ecological niche modelling predicts different range contractions for Lutzomyia intermedia and a related vector of Leishmania braziliensis following climate change in South America.

    Science.gov (United States)

    McIntyre, Shannon; Rangel, Elizabeth F; Ready, Paul D; Carvalho, Bruno M

    2017-03-24

    Before 1996 the phlebotomine sand fly Lutzomyia neivai was usually treated as a synonym of the morphologically similar Lutzomyia intermedia, which has long been considered a vector of Leishmania braziliensis, the causative agent of much cutaneous leishmaniasis in South America. This report investigates the likely range changes of both sand fly species in response to a stabilisation climate change scenario (RCP4.5) and a high greenhouse gas emissions one (RCP8.5). Ecological niche modelling was used to identify areas of South America with climates currently suitable for each species, and then the future distributions of these climates were predicted based on climate change scenarios. Compared with the previous ecological niche model of L. intermedia (sensu lato) produced using the GARP algorithm in 2003, the current investigation modelled the two species separately, making use of verified presence records and additional records after 2001. Also, the new ensemble approach employed ecological niche modelling algorithms (including Maximum Entropy, Random Forests and Support Vector Machines) that have been widely adopted since 2003 and perform better than GARP, as well as using a more recent climate change model (HadGEM2) considered to have better performance at higher resolution than the earlier one (HadCM2). Lutzomyia intermedia was shown to be the more tropical of the two species, with its climatic niche defined by higher annual mean temperatures and lower temperature seasonality, in contrast to the more subtropical L. neivai. These different latitudinal ranges explain the two species' predicted responses to climate change by 2050, with L. intermedia mostly contracting its range (except perhaps in northeast Brazil) and L. neivai mostly shifting its range southwards in Brazil and Argentina. This contradicts the findings of the 2003 report, which predicted more range expansion. The different findings can be explained by the improved data sets and modelling methods. Our

  4. Percentage of Body Fat and Fat Mass Index as a Screening Tool for Metabolic Syndrome Prediction in Colombian University Students

    Science.gov (United States)

    Sanders-Tordecilla, Alejandra; Ojeda-Pardo, Mónica Liliana; Cobo-Mejía, Elisa Andrea; Castellanos-Vega, Rocío del Pilar; Schmidt-RioValle, Jacqueline; González-Ruíz, Katherine

    2017-01-01

    High body fat is related to metabolic syndrome (MetS) in all ethnic groups. Based on the International Diabetes Federation (IDF) definition of MetS, the aim of this study was to explore thresholds of body fat percentage (BF%) and fat mass index (FMI) for the prediction of MetS among Colombian University students. A cross-sectional study was conducted on 1687 volunteers (63.4% women, mean age = 20.6 years). Weight, waist circumference, serum lipids indices, blood pressure, and fasting plasma glucose were measured. Body composition was measured by bioelectrical impedance analysis (BIA) and FMI was calculated. MetS was defined as including more than or equal to three of the metabolic abnormalities according to the IDF definition. Receiver operating curve (ROC) analysis was used to determine optimal cut-off points for BF% and FMI in relation to the area under the curve (AUC), sensitivity, and specificity in both sexes. The overall prevalence of MetS was found to be 7.7%, higher in men than women (11.1% vs. 5.3%; p < 0.001). BF% and FMI were positively correlated to MetS components (p < 0.05). ROC analysis indicated that BF% and FMI can be used with moderate accuracy to identify MetS in university-aged students. BF% and FMI thresholds of 25.55% and 6.97 kg/m2 in men, and 38.95% and 11.86 kg/m2 in women, were found to be indicative of high MetS risk. Based on the IDF criteria, both indexes’ thresholds seem to be good tools to identify university students with unfavorable metabolic profiles. PMID:28902162

  5. Percentage of Body Fat and Fat Mass Index as a Screening Tool for Metabolic Syndrome Prediction in Colombian University Students

    Directory of Open Access Journals (Sweden)

    Robinson Ramírez-Vélez

    2017-09-01

    Full Text Available High body fat is related to metabolic syndrome (MetS in all ethnic groups. Based on the International Diabetes Federation (IDF definition of MetS, the aim of this study was to explore thresholds of body fat percentage (BF% and fat mass index (FMI for the prediction of MetS among Colombian University students. A cross-sectional study was conducted on 1687 volunteers (63.4% women, mean age = 20.6 years. Weight, waist circumference, serum lipids indices, blood pressure, and fasting plasma glucose were measured. Body composition was measured by bioelectrical impedance analysis (BIA and FMI was calculated. MetS was defined as including more than or equal to three of the metabolic abnormalities according to the IDF definition. Receiver operating curve (ROC analysis was used to determine optimal cut-off points for BF% and FMI in relation to the area under the curve (AUC, sensitivity, and specificity in both sexes. The overall prevalence of MetS was found to be 7.7%, higher in men than women (11.1% vs. 5.3%; p < 0.001. BF% and FMI were positively correlated to MetS components (p < 0.05. ROC analysis indicated that BF% and FMI can be used with moderate accuracy to identify MetS in university-aged students. BF% and FMI thresholds of 25.55% and 6.97 kg/m2 in men, and 38.95% and 11.86 kg/m2 in women, were found to be indicative of high MetS risk. Based on the IDF criteria, both indexes’ thresholds seem to be good tools to identify university students with unfavorable metabolic profiles.

  6. High levels of cystatin C predict the metabolic syndrome: the prospective Malmö Diet and Cancer Study.

    Science.gov (United States)

    Magnusson, M; Hedblad, B; Engström, G; Persson, M; Nilsson, P; Melander, O

    2013-08-01

    Cystatin C is a novel marker of cardiovascular disease (CVD); however, the underlying mechanisms remain unclear. Here, we prospectively investigated whether plasma levels of cystatin C predict new-onset metabolic syndrome (MetS) as well as long-term progression and incidence of the different components of the MetS. Cystatin C was measured in 1502 individuals included in the Malmö Diet and Cancer cardiovascular cohort (mean age 56 years, 59% women) who were free from the MetS at baseline and subsequently underwent a follow-up examination after a median of 16 years. MetS was defined according to the NCEP-ATP-III guidelines. Logistic regression was used to adjust for covariates. Metabolic syndrome and long-term progression as well as incidence of the different components of the MetS. During follow-up, 428 subjects developed new-onset MetS. In age- and sex-adjusted analysis, compared with the lowest quartile of cystatin C, the odds ratios (95% confidence interval) for incident MetS in subjects with cystatin C levels in quartiles 2, 3 and 4 were 1.00 (0.71-1.40), 1.48 (1.06-2.07) and 1.91 (1.37-2.68), respectively (Ptrend  cystatin C levels (Ptrend  = 0.008). These findings suggest that cystatin C may adversely affect metabolic factors, particularly abdominal obesity, thus contributing to development of the MetS. Our results may help to explain the link between cystatin C and development of CVD. © 2013 The Association for the Publication of the Journal of Internal Medicine.

  7. Virtual Screening and Prediction of Site of Metabolism for Cytochrome P450 1A2 Ligands

    DEFF Research Database (Denmark)

    Vasanthanathan, P.; Hritz, Jozef; Taboureau, Olivier

    2009-01-01

    questions have been addressed: 1. Binding orientations and conformations were successfully predicted for various substrates. 2. A virtual screen was performed with satisfying enrichment rates. 3. A classification of individual compounds into active and inactive was performed. It was found that while docking...... and earlier classification data using machine learning methods. The possibilities and limitations of using structure-based drug design tools for cytochrome P450 1A2 come to light and are discussed....

  8. Prediction of Metabolic Flux Distribution from Gene Expression Data Based on the Flux Minimization Principle

    Science.gov (United States)

    2014-11-14

    Saccharomyces cerevisiae , and wild-type and mutant Escherichia coli strains, our method achieved high prediction accuracy, as gauged by correlation...the aerobic growth of S. cerevisiae . We used experimental data collected by Lee et al., which included RNA-seq transcriptomic data and exchange flux...measurements of S. cerevisiae aerobically growing in chemostat cultures. This study provides data under two different growth conditions, i.e., glucose

  9. Predictive value of metabolic syndrome definitions in patients with myocardial infarction with ST segment elevation - are they all the same?

    Science.gov (United States)

    Lovic, Milan Branko; Savic, Lidija; Matic, Dragan; Djordjevic, Dragan; Nedeljkovic, Ivana; Tasic, Ivan

    2018-01-15

    We sought to determine the predictive power of metabolic syndrome (MS) definitions on the prognosis in patients with myocardial infarction with ST-segment elevation (STEMI). We prospectively included 507 patients with STEMI who were admitted for primary percutaneous coronary intervention and could be identified for MS using the AHA-NHLBI, NCEP-ATP III and IDF definitions. After applying these criteria, we divided the group in patients with MS and without MS; we compared baseline characteristics, clinical findings and outcomes among these patients. The prevalence of MS was lowest with the NCEP-ATP III definition (37.87%), followed by the AHA-NHLBI definition (42.80%) and highest when using the IDF definition (44.38%). During follow-up, the occurrence of new myocardial infarction and new revascularization was significantly higher in patients with MS. Only in a group of patients with MS according to the NCEP-ATP III definition, a higher number of strokes were recorded. Multivariate analysis shows that MS according to the NCEP-ATP III definition was an independent predictor for MACE (OR 1.830, 95% CI 1.238-2.704, p = .002) but not for mortality. Metabolic syndrome according to the NCEP-ATP III definition was associated with increased risk of the development of new cardiovascular events among the patients with STEMI.

  10. GIS-BASED EVALUATION AND PREDICTION OF ECOLOGICAL SITUATION IN THE COAL MINING AREAS WITH A CRITICAL TECHNOGENIC IMPACT

    Directory of Open Access Journals (Sweden)

    S. V. Pyankov

    2017-01-01

    Full Text Available The paper highlights the features of the creation of the basin GIS, developed to support the environmental monitoring, assessment and forecasting of negative consequences in the areas of technogenic disaster (on the example of abandoned Kizel coal basin, located in Perm Region, Russia. The world experience of applying GIS-technologies for solving environmental problems of coal-mining regions is also being discussed. The information basis and structure of the cartographic and attributive database of the Kizel coal basin GIS are presented. The main tasks of creating the GIS, including inventory of man-made impact sources, identification of the spatio-temporal distribution patterns of pollutants, quantification and mapping of the territory ecological status, forecasting of the environmental situation and planning of environmental measures have been identified. A system of spatial criteria for the integrated assessment of the territory ecological status within coal basins is proposed, which will allow monitoring of environmental changes and identifying areas with the critical environmental situation. These criteria include the pH value and the sulfates concentration in the streams, the complex of heavy metals, the species composition of microorganisms in surface waters, the area of degraded land and dead forest stands. The degree of negative impact of the abandoned coal mines on streams and groundwater is described, and the priority pollutants are identified.The estimates of the extent of contaminated streams, as well as areas of potential contamination of floodplain lands have been obtained using LANDSAT satellite imagery data. The significance of the creation of the algorithms for the integration of heterogeneous spatial information (ground-based and remote sensing observations for compiling synthetic maps that objectively estimate the ecological situation has been noted. 

  11. Twenty-four hour metabolic rate measurements utilized as a reference to evaluate several prediction equations for calculating energy requirements in healthy infants

    Directory of Open Access Journals (Sweden)

    Rising Russell

    2011-02-01

    Full Text Available Abstract Background To date, only short-duration metabolic rate measurements of less than four hours have been used to evaluate prediction equations for calculating energy requirements in healthy infants. Therefore, the objective of this analysis was to utilize direct 24-hour metabolic rate measurements from a prior study to evaluate the accuracy of several currently used prediction equations for calculating energy expenditure (EE in healthy infants. Methods Data from 24-hour EE, resting (RMR and sleeping (SMR metabolic rates obtained from 10 healthy infants, served as a reference to evaluate 11 length-weight (LWT and weight (WT based prediction equations. Six prediction equations have been previously derived from 50 short-term EE measurements in the Enhanced Metabolic Testing Activity Chamber (EMTAC for assessing 24-hour EE, (EMTACEE-LWT and EMTACEE-WT, RMR (EMTACRMR-LWT and EMTACRMR-WT and SMR (EMTACSMR-LWT and EMTACSMR-WT. The last five additional prediction equations for calculating RMR consisted of the World Health Organization (WHO, the Schofield (SCH-LWT and SCH-WT and the Oxford (OXFORD-LWT and OXFORD-WT. Paired t-tests and the Bland & Altman limit analysis were both applied to evaluate the performance of each equation in comparison to the reference data. Results 24-hour EE, RMR and SMR calculated with the EMTACEE-WT, EMTACRMR-WT and both the EMTACSMR-LWT and EMTACSMR-WT prediction equations were similar, p = NS, to that obtained from the reference measurements. However, RMR calculated using the WHO, SCH-LWT, SCH-WT, OXFORD-LWT and OXFORD-WT prediction equations were not comparable to the direct 24-hour metabolic measurements (p Conclusions Weight based prediction equations, derived from short-duration EE measurements in the EMTAC, were accurate for calculating EE, RMR and SMR in healthy infants.

  12. Role of heterogeneity of lipids in predicting risk of atheroma formation in metabolic syndrome

    International Nuclear Information System (INIS)

    Asim, M.; Ahmad, M.; Hasan, S.

    2013-01-01

    Objective: Assessing impact of heterogeneous lipids in predisposing cardiovascular (CV) atheroma formation in adolescents with metabolic syndrome (MS). Study Design: Cross-sectional analytical. Place and Duration of Study: Educational Institutes of Lahore. Six months Material and Methods: A total of 193, 17-25 year old subjects, 106 males and 87 females were recruited. A record regarding each subject's personal, socioeconomic, educational, dietary and family histories was taken. They underwent the following anthropometric measurements: waist circumference/WC (cm), hip circumference/HC (cm), height (inches), weight (kg), waist hip ratio/WHR, body mass index/BMI and blood pressure. Laboratory investigations included fasting blood samples for glucose and lipids; including total cholesterol (TC), high density lipoprotein-cholesterol (HDL-c), low density lipoprotein-cholesterol (LDL-c) and triglycerides (TG). Calculations for TG/HDL ratio and TC/HDL ratio were made. Results: Metabolic syndrome (MS) was present in 26 (13.5%) individuals. Male to female ratio was 3:1. Values of waist circumference, blood pressure, fasting plasma glucose, triglyceride and HDL-c, were all high. On comparison of fasting lipid profile, TC/HDL ratio and TG/HDL ratio, it was observed that the average total cholesterol, HDL cholesterol, TCL/HDL ratio were insignificant. The average triglyceride level and TG/HDL ratio were all high. The ROC curve for total cholesterol, HDL-c, TG, TC/HDL and TG/HDL ratio yielded 0.555, 0.526, 0.912, 0.548 and 0.913 areas under the curve. Plasma TG, TG/HDL ratio produced significant p-values < 0.001. Abnormal triglycerides and TG/HDL ratio at a cutoff of 3.98 was diagnosed with high sensitivity and specificity. Conclusion: Fasting triglyceride and HDL-c play a major role in the pathogenesis of MS at an early age. Triglyceride level and TG/HDL ratio as opposed to HDL-c and TC/HDL-c clearly define the risk for development of atheroma formation in our adolescent

  13. Prediction of basal metabolic rate in obese children and adolescents considering pubertal stages and anthropometric characteristics or body composition.

    Science.gov (United States)

    Lazzer, S; Patrizi, A; De Col, A; Saezza, A; Sartorio, A

    2014-06-01

    To develop and crossvalidate new equations for predicting basal metabolic rate (BMR) in obese children and adolescents in relation to pubertal stages, anthropometric characteristics or body composition. A total of 1696 obese Caucasian children and adolescents (mean body mass index z-score: 3.5±0.8) participated in this study. BMR was determined by indirect calorimetry and fat-free mass (FFM) and fat mass (FM) by bioelectrical impedance analysis. Equations were derived by stepwise multiple regression analysis using a calibration cohort of 848 subjects, and the equations were crossvalidated with a Bland and Altman method in the remaining 848 subjects. Two new specific equations based on gender (1: males; 0: females), pubertal stages (from 1 to 5, assessed according Marshall & Tanner methods) and body weight (BW, kg), stature (m) or body composition (kg) were generated as follows: (1) BMR=(BW × 0.044)+(stature × 2.836)-(pubertal stage × 0.148)+(gender × 0.781)-0.551 (adjusted coefficient of determination (R(2)adj)= 0.69 and root mean squared error (RMSE)=0.954 MJ); (2) BMR=(FFM × 0.082)+(FM × 0.037)-(pubertal stage × 0.125)+(gender × 0.706)+2.528 (R(2)adj= 0.70 and RMSE=0.943 MJ). In the crossvalidation group, mean-predicted BMR was not significantly different from the mean-measured BMR (MBMR) for all children and adolescents, as well as for boys and girls (differenceBMR was predicted accurately (90-110% of MBMR) in 67% of subjects. The new prediction equations considering the pubertal stages allow an accurate and more appropriate (vs equations using chronological age) estimation of BMR in obese children and adolescents.

  14. A novel cutoff for the waist-to-height ratio predicting metabolic syndrome in young American adults

    Directory of Open Access Journals (Sweden)

    Adam D. Bohr

    2016-04-01

    Full Text Available Abstract Background Recent studies have shown the enhanced diagnostic capability of the waist-to-height ratio (WHtR over BMI. However, while a structured cutoff hierarchy has been established for BMI, a rigorous analysis to define individuals as obese using the WHtR has not been performed on a sample of American adults. This study attempts to establish a cutoff for the WHtR using metabolic syndrome as the outcome. Methods The study sample consisted of individuals that were part of the National Longitudinal Study of Adolescent Health (Add Health. The final sample for analysis consisted of 7 935 participants (3 469 males, 4 466 females that were complete respondents for the variables of interest at Wave IV. The participants ranged from 24.55-33.60 years. Weighted and unweighted receiver operator characteristics (ROC analyses were performed predicting metabolic syndrome from the WHtR. Cutoffs were chosen using the Youden index. The derived cutoffs were validated by logistic regression analysis on the Add Health participants and an external sample of 1 236 participants from the National Health and Nutrition Examination Survey (NHANES. Results The ROC analysis resulted in a WHtR cutoff of 0.578 (Youden Index = 0.50 for the full sample of complete respondents, 0.578 (Youden Index = 0.55 for males only, and 0.580 (Youden Index = 0.50 for females only. The area under the curve was 0.798 (95 % CI (0.788, 0.809 for the full sample of complete respondents, 0.833 (95 % CI (0.818, 0.848 for males only, and 0.804 (95 % CI (0.791, 0.818 for females only. Participants in the validation sample with a WHtR greater than the derived cutoff were more likely (Odds Ratio = 9.8, 95 % CI (6.2, 15.3 to have metabolic syndrome than those that were not. Conclusion A WHtR cutoff of 0.580 is optimal for discriminating individuals with metabolic syndrome in two nationally representative samples of young adults. This cutoff is an improvement over a

  15. A comparison of predictability of cardiovascular events between each metabolic component in patients with metabolic syndrome based on the revised National Cholesterol Education Program criteria.

    Science.gov (United States)

    Hwang, In-Cheol; Kim, Kyoung-Kon; Jee, Sun-Ha; Kang, Hee-Cheol

    2011-03-01

    The prevalence of metabolic syndrome (MetS) generally varies depending on its diagnostic definition, and many different definitions inevitably lead to substantial confusion and lack of comparability between studies. Despite extensive research, there is still no gold standard for the definition of MetS, which continues to be a matter of debate. In this study, we investigate whether and to what extent its individual components are related to the risk of cardiovascular disease (CVD) in Korean population. We used data from the 2005 Korea National Health and Nutrition Examination Survey, which is a nationally representative survey of the noninstitutionalized civilian population. The study sample consisted of 1,406 Korean adults (587 men, 819 women) who were diagnosed with MetS based on the revised National Cholesterol Education Program (NCEP) criteria. Central obesity is defined as a waist circumference cutoff point reported in Asia-Pacific criteria for obesity based on waist circumference by the World Health Organization. CVD was defined as presence of stroke, myocardial infarction, or angina pectoris on a medical history questionnaire. The CVD prevalence among the subjects was 6.8% for men and 8.6% for women. Besides age, the components of MetS showing a significant difference in the number of CVD events were high fasting glucose (FG) in men and high blood pressure (BP) and high FG in women. After adjusting for gender and age, high FG was shown to yield a significant difference (odds ratio: unadjusted 2.08, adjusted 1.81), alone among all MetS components. However, after adjusting for only age, no significant difference was found. Fasting glucose level is the highest predicting factor for CVD in Korean patients with MetS based on the revised NECP definition.

  16. NCEP-ATP III and IDF criteria for metabolic syndrome predict type 2 diabetes mellitus

    Directory of Open Access Journals (Sweden)

    Eva Sulistiowati

    2016-05-01

    Full Text Available Background Subjects with metabolic syndrome (MetS have a greater risk for acquiring type 2 diabetes mellitus (type 2 DM. The MetS criteria usually used are those of the National Cholesterol Education Program Expert Panel (NCEP and Adult Treatment Panel III (ATP III and of the International Diabetes Federation (IDF. This study aimed to evaluate the modified NCEP-ATP III and IDF criteria as predictor of type 2 DM among subjects with MetS.   Methods A cohort study was conducted among 4240 subjects with MetS. MetS was determined according to the modified NCEP-ATP III and IDF criteria. The study followed up 3324 non-diabetic subjects of the cohort study of non-communicable disease (NCD risk factors (NCD study during a 2-year period. Type 2 DM was determined from the diagnosis by health personnel or from fasting blood glucose of ≥126 mg/dL or blood glucose of ≥200 mg/dL, 2 hours after 75g glucose loading.   Results The MetS prevalence based on modified NCEP ATP III and IDF criteria in non-DM subjects was 17.1% and 15.6%, respectively. The risk for DM in subjects with MetS using modified NCEP ATP III and IDF criteria was 4.7 (CI 95%: 3.4-6.5 and 4.1 (CI 95%: 3.0-5.7, respectively.   Conclusions Both MetS criteria can be used as predictors of the occurrence of DM type 2, but the modified NCEP-ATP III is more properly applied than the IDF criteria in subjects with MetS. Screening programs and routine monitoring of MetS components are required for early detection of type 2 DM.

  17. Limited predictive value of the IDF definition of metabolic syndrome for the diagnosis of insulin resistance measured with the oral minimal model.

    Science.gov (United States)

    Ghanassia, E; Raynaud de Mauverger, E; Brun, J-F; Fedou, C; Mercier, J

    2009-01-01

    To assess the agreement of the NCEP ATP-III and the IDF definitions of metabolic syndrome and to determine their predictive values for the diagnosis of insulin resistance. For this purpose, we recruited 150 subjects (94 women and 56 men) and determined the presence of metabolic syndrome using the NCEP-ATP III and IDF definitions. We evaluated their insulin sensitivity S(I) using Caumo's oral minimal model after a standardized hyperglucidic breakfast test. Subjects whose S(I) was in the lowest quartile were considered as insulin resistant. We then calculated sensitivity, specificity, positive and negative predictive values of both definitions for the diagnosis of insulin resistance. The prevalence of metabolic syndrome was 37.4% (NCEP-ATP III) and 40% (IDF). Agreement between the two definitions was 96%. Using NCEP-ATP III and IDF criteria for the identification of insulin resistant subjects, sensitivity was 55.3% and 63%, specificity was 68.8% and 67.8%, positive predictive value was 37.5% and 40%, negative predictive value was 81.9% and 84.5%, respectively. Positive predictive value increased with the number of criteria for both definitions. Whatever the definition, the scoring of metabolic syndrome is not a reliable tool for the individual diagnosis of insulin resistance, and is more useful for excluding this diagnosis.

  18. Computational Flux Balance Analysis Predicts that Stimulation of Energy Metabolism in Astrocytes and their Metabolic Interactions with Neurons Depend on Uptake of K(+) Rather than Glutamate

    DEFF Research Database (Denmark)

    DiNuzzo, Mauro; Giove, Federico; Maraviglia, Bruno

    2017-01-01

    Brain activity involves essential functional and metabolic interactions between neurons and astrocytes. The importance of astrocytic functions to neuronal signaling is supported by many experiments reporting high rates of energy consumption and oxidative metabolism in these glial cells...... utilization. In order to examine the participation of astrocytic energy metabolism in brain ion homeostasis, here we attempted to devise a simple stoichiometric relation linking glutamatergic neurotransmission to Na(+) and K(+) ionic currents. To this end, we took into account ion pumps and voltage....../ligand-gated channels using the stoichiometry derived from available energy budget for neocortical signaling and incorporated this stoichiometric relation into a computational metabolic model of neuron-astrocyte interactions. We aimed at reproducing the experimental observations about rates of metabolic pathways...

  19. Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China.

    Science.gov (United States)

    Du, Zhicheng; Xu, Lin; Zhang, Wangjian; Zhang, Dingmei; Yu, Shicheng; Hao, Yuantao

    2017-10-06

    Hand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD. Ecological study. Information on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011-2014. Analyses were conducted at aggregate level and no confidential information was involved. A seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI. A high correlation between HFMD incidence and BDI ( r =0.794, pinformation criterion (AIC) value of -345.332, whereas the model including both BDI and temperature had the most accurate prediction in terms of the mean absolute percentage error (MAPE) of 101.745%. An ARIMAX model incorporating search engine query data significantly improved the prediction of HFMD. Further studies are warranted to examine whether including search engine query data also improves the prediction of other infectious diseases in other settings. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  20. Individualized risk assessment in neuroblastoma. Does the tumoral metabolic activity on {sup 123}I-MIBG SPECT predict the outcome?

    Energy Technology Data Exchange (ETDEWEB)

    Rogasch, Julian M.M.; Furth, Christian; Wedel, Florian; Brenner, Winfried; Amthauer, Holger; Schatka, Imke [Charite - Universitaetsmedizin Berlin, Department of Nuclear Medicine, Berlin (Germany); Hundsdoerfer, Patrick [Charite - Universitaetsmedizin Berlin, Department of Pediatric Oncology/Hematology, Berlin (Germany); Berlin Institute of Health (BIH), Berlin (Germany); Hofheinz, Frank [Helmholtz Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, PET Center, Dresden (Germany); Krueger, Paul-Christian [University Medicine Greifswald, Institute for Diagnostic Radiology and Neuroradiology, Greifswald (Germany); Lode, Holger [University Medicine Greifswald, Department of Pediatric Oncology and Hematology, Greifswald (Germany); Eggert, Angelika [Charite - Universitaetsmedizin Berlin, Department of Pediatric Oncology/Hematology, Berlin (Germany)

    2017-12-15

    Risk-adapted treatment in children with neuroblastoma (NB) is based on clinical and genetic factors. This study evaluated the metabolic tumour volume (MTV) and its asphericity (ASP) in pretherapeutic {sup 123}I-MIBG SPECT for individualized image-based prediction of outcome. This retrospective study included 23 children (11 girls, 12 boys; median age 1.8 years, range 0.3-6.8 years) with newly diagnosed NB consecutively examined with pretherapeutic {sup 123}I-MIBG SPECT. Primary tumour MTV and ASP were defined using semiautomatic thresholds. Cox regression analysis, receiver operating characteristic analysis (cut-off determination) and Kaplan-Meier analysis with the log-rank test for event-free survival (EFS) were performed for ASP, MTV, laboratory parameters (including urinary homovanillic acid-to-creatinine ratio, HVA/C), and clinical (age, stage) and genetic factors. Predictive accuracy of the optimal multifactorial model was determined in terms of Harrell's C and likelihood ratio χ {sup 2}. Median follow-up was 36 months (range 7-107 months; eight patients showed disease progression/relapse, four patients died). The only significant predictors of EFS in the univariate Cox regression analysis were ASP (p = 0.029; hazard ratio, HR, 1.032 for a one unit increase), MTV (p = 0.038; HR 1.012) and MYCN amplification status (p = 0.047; HR 4.67). The mean EFS in patients with high ASP (>32.0%) and low ASP were 21 and 88 months, respectively (p = 0.013), and in those with high MTV (>46.7 ml) and low MTV were 22 and 87 months, respectively (p = 0.023). A combined risk model of either high ASP and high HVA/C or high MTV and high HVA/C best predicted EFS. In this exploratory study, pretherapeutic image-derived and laboratory markers of tumoral metabolic activity in NB (ASP, MTV, urinary HVA/C) allowed the identification of children with a high and low risk of progression/relapse under current therapy. (orig.)

  1. Metabolic markers associated with insulin resistance predict type 2 diabetes in Koreans with normal blood pressure or prehypertension.

    Science.gov (United States)

    Sung, Ki-Chul; Park, Hyun-Young; Kim, Min-Ju; Reaven, Gerald

    2016-03-22

    Questions remain as to the association between essential hypertension and increased incidence of type 2 diabetes (T2DM). The premise of this analysis is that insulin resistance/compensatory hyperinsulinemia is a major predictor of T2DM, and the greater the prevalence of insulin resistance within any population, normotensive or hypertensive, the more likely T2DM will develop. The hypothesis to be tested is that surrogate estimates of insulin resistance will predict incident T2DM to a significant degree in persons with normal blood pressure or prehypertension. Analysis of data from a population-based survey of 10, 038 inhabitants of rural and urban areas of Korea, ≥40 years-old, initiated in 2001, with measures of demographic and metabolic characteristics at baseline and 8-years later. Participants were classified as having normal blood pressure or prehypertension, and three simple manifestations of insulin resistance related to the pathophysiology of T2DM used to predict incident T2DM: (1) glycemia (plasma glucose concentration 2-hour after 75 g oral glucose challenge = 2-hour PG); (2) hyperinsulinemia (plasma insulin concentration 2-hour after 75 g oral glucose challenge = 2-hour PI); and (3) dyslipidemia (ratio of fasting plasma triglyceride/high/density lipoprotein cholesterol concentration = TG/HDL-C ratio). Fully adjusted hazard ratios (HR, 95 % CI) for incident T2DM were highest (P insulin resistance was the 2-hour PI concentration. Subjects with normal blood pressure in the highest quartile of 2-hour PI concentrations were significantly associated with incident T2DM, with HRs of 1.5 (1.02-2.20, P = 0.25) and 2.02 (1.35-3.02, P insulin resistance (glycemia, insulinemia, and dyslipidemia) predict the development of T2DM in patients with either normal blood pressure or prehypertension.

  2. Ecological Schoolyards.

    Science.gov (United States)

    Danks, Sharon Gamson

    2000-01-01

    Presents design guidelines and organizational and site principles for creating schoolyards where students can learn about ecology. Principles for building schoolyard ecological systems are described. (GR)

  3. Urinary Acid Excretion Can Predict Changes in Bone Metabolism During Space Flight

    Science.gov (United States)

    Zwart, Sara R.; Smith, Scott M.

    2011-01-01

    Mitigating space flight-induced bone loss is critical for space exploration, and a dietary countermeasure would be ideal. We present here preliminary data from a study where we examined the role of dietary intake patterns as one factor that can influence bone mineral loss in astronauts during space flight. Crewmembers (n=5) were asked to consume a prescribed diet with either a low (0.3-0.6) or high (1.0-1.3) ratio of animal protein to potassium (APro:K) before and during space flight for 4-d periods. Diets were controlled for energy, total protein, calcium, and sodium. 24-h urine samples were collected on the last day of each of the 4-d controlled diet sessions. 24-h urinary acid excretion, which was predicted by dietary potential renal acid load, was correlated with urinary n-telopeptide (NTX, Pearson R = 0.99 and 0.80 for the high and low APro:K sessions, respectively, p<0.001). The amount of protein when expressed as the percentage of total energy (but not as total grams) was also correlated with urinary NTX (R = 0.66, p<0.01). These results, from healthy individuals in a unique environment, will be important to better understand diet and bone interrelationships during space flight as well as on Earth. The study was funded by the NASA Human Research Program.

  4. A Predictive Metabolic Signature for the Transition From Gestational Diabetes Mellitus to Type 2 Diabetes

    DEFF Research Database (Denmark)

    Allalou, Amina; Nalla, Amarnadh; Prentice, Kacey J

    2016-01-01

    Gestational diabetes mellitus (GDM) affects 3-14% of pregnancies, with 20-50% of these women progressing to type 2 diabetes (T2D) within 5 years. This study sought to develop a metabolomics signature to predict the transition from GDM to T2D. A prospective cohort of 1,035 women with GDM pregnancy...... with a discriminative power of 83.0% in the training set and 76.9% in an independent testing set, which is far superior to measuring fasting plasma glucose levels alone. The American Diabetes Association recommends T2D screening in the early postpartum period via oral glucose tolerance testing after GDM, which...... were enrolled at 6-9 weeks postpartum (baseline) and were screened for T2D annually for 2 years. Of 1,010 women without T2D at baseline, 113 progressed to T2D within 2 years. T2D developed in another 17 women between 2 and 4 years. A nested case-control design used 122 incident case patients matched...

  5. Violent relationships at the social-ecological level: A multi-mediation model to predict adolescent victimization by peers, bullying and depression in early and late adolescence

    Science.gov (United States)

    Oriol, Xavier; Miranda, Rafael; Acosta, Hedy C.; Mendoza, Michelle C.; Torres-Vallejos, Javier

    2017-01-01

    Background From the social-ecological perspective, exposure to violence at the different developmental levels is fundamental to explain the dynamics of violence and victimization in educational centers. The following study aims at analyzing how these relationships are produced in the Peruvian context, where structural violence situations exist. Methods A multi-mediation structural model with 21,416 Peruvian adolescents (M = 13.69; SD = 0.71) was conducted to determine the influence of violence in the school environment on violence perceived within school and violence exercised by teachers. In addition, it was also intended to determine whether these violent relationships predict depression through loneliness, and bullying through peer victimization. The existence of differences between early and late adolescence was also verified. Results Results confirm that violence in the school setting has high influence on violence exercised by adolescents and teachers within the school. Teacher violence is the most important predictor of depression through loneliness, and encourages peer victimization and the emergence of aggressive behavior. Exposure to violence exercised by support sources—teachers and classmates—explains more than 90% of the total variance explained in bullying behavior. Differences were found between early and late adolescence models. Conclusion The high prevalence of structural violence in school settings facilitates the bullying/victimization dynamics within school. From a social-ecological perspective, this result suggests the importance of network cooperation at a mesosystem level, with teachers from educational centers playing a crucial role in the prevention of bullying/victimization. PMID:28358905

  6. Violent relationships at the social-ecological level: A multi-mediation model to predict adolescent victimization by peers, bullying and depression in early and late adolescence.

    Directory of Open Access Journals (Sweden)

    Xavier Oriol

    Full Text Available From the social-ecological perspective, exposure to violence at the different developmental levels is fundamental to explain the dynamics of violence and victimization in educational centers. The following study aims at analyzing how these relationships are produced in the Peruvian context, where structural violence situations exist.A multi-mediation structural model with 21,416 Peruvian adolescents (M = 13.69; SD = 0.71 was conducted to determine the influence of violence in the school environment on violence perceived within school and violence exercised by teachers. In addition, it was also intended to determine whether these violent relationships predict depression through loneliness, and bullying through peer victimization. The existence of differences between early and late adolescence was also verified.Results confirm that violence in the school setting has high influence on violence exercised by adolescents and teachers within the school. Teacher violence is the most important predictor of depression through loneliness, and encourages peer victimization and the emergence of aggressive behavior. Exposure to violence exercised by support sources-teachers and classmates-explains more than 90% of the total variance explained in bullying behavior. Differences were found between early and late adolescence models.The high prevalence of structural violence in school settings facilitates the bullying/victimization dynamics within school. From a social-ecological perspective, this result suggests the importance of network cooperation at a mesosystem level, with teachers from educational centers playing a crucial role in the prevention of bullying/victimization.

  7. Violent relationships at the social-ecological level: A multi-mediation model to predict adolescent victimization by peers, bullying and depression in early and late adolescence.

    Science.gov (United States)

    Oriol, Xavier; Miranda, Rafael; Amutio, Alberto; Acosta, Hedy C; Mendoza, Michelle C; Torres-Vallejos, Javier

    2017-01-01

    From the social-ecological perspective, exposure to violence at the different developmental levels is fundamental to explain the dynamics of violence and victimization in educational centers. The following study aims at analyzing how these relationships are produced in the Peruvian context, where structural violence situations exist. A multi-mediation structural model with 21,416 Peruvian adolescents (M = 13.69; SD = 0.71) was conducted to determine the influence of violence in the school environment on violence perceived within school and violence exercised by teachers. In addition, it was also intended to determine whether these violent relationships predict depression through loneliness, and bullying through peer victimization. The existence of differences between early and late adolescence was also verified. Results confirm that violence in the school setting has high influence on violence exercised by adolescents and teachers within the school. Teacher violence is the most important predictor of depression through loneliness, and encourages peer victimization and the emergence of aggressive behavior. Exposure to violence exercised by support sources-teachers and classmates-explains more than 90% of the total variance explained in bullying behavior. Differences were found between early and late adolescence models. The high prevalence of structural violence in school settings facilitates the bullying/victimization dynamics within school. From a social-ecological perspective, this result suggests the importance of network cooperation at a mesosystem level, with teachers from educational centers playing a crucial role in the prevention of bullying/victimization.

  8. Short communication: Use of genomic and metabolic information as well as milk performance records for prediction of subclinical ketosis risk via artificial neural networks.

    Science.gov (United States)

    Ehret, A; Hochstuhl, D; Krattenmacher, N; Tetens, J; Klein, M S; Gronwald, W; Thaller, G

    2015-01-01

    Subclinical ketosis is one of the most prevalent metabolic disorders in high-producing dairy cows during early lactation. This renders its early detection and prevention important for both economical and animal-welfare reasons. Construction of reliable predictive models is challenging, because traits like ketosis are commonly affected by multiple factors. In this context, machine learning methods offer great advantages because of their universal learning ability and flexibility in integrating various sorts of data. Here, an artificial-neural-network approach was applied to investigate the utility of metabolic, genetic, and milk performance data for the prediction of milk levels of β-hydroxybutyrate within and across consecutive weeks postpartum. Data were collected from 218 dairy cows during their first 5wk in milk. All animals were genotyped with a 50,000 SNP panel, and weekly information on the concentrations of the milk metabolites glycerophosphocholine and phosphocholine as well as milk composition data (milk yield, fat and protein percentage) was available. The concentration of β-hydroxybutyric acid in milk was used as target variable in all prediction models. Average correlations between observed and predicted target values up to 0.643 could be obtained, if milk metabolite and routine milk recording data were combined for prediction at the same day within weeks. Predictive performance of metabolic as well as milk performance-based models was higher than that of models based on genetic information. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  9. Composition and Predicted Metabolic Capacity of Upper and Lower Airway Microbiota of Healthy Dogs in Relation to the Fecal Microbiota.

    Science.gov (United States)

    Ericsson, Aaron C; Personett, Alexa R; Grobman, Megan E; Rindt, Hansjorg; Reinero, Carol R

    2016-01-01

    The upper and lower airways of healthy humans are reported to harbor stable and consistent bacterial populations, and the composition of these communities is altered in individuals affected with several respiratory diseases. Data regarding the presence of airway microbiota in other animals are scant and a better understanding of the composition and metabolic function of such bacterial populations is essential for the development of novel therapeutic and diagnostic modalities for use in both veterinary and human medicine. Based on targeted next-generation sequencing of feces and samples collected at multiple levels of the airways from 16 healthy female dogs, we demonstrate that canine airways harbor a topographically continuous microbiota with increasing relative abundance of proteobacterial species from the upper to lower airways. The lung-associated microbiota, as assessed via bronchoalveolar lavage fluid (BALF), was the most consistent between dogs and was dominated by three distinct taxa, two of which were resolved to the species level and one to the level of family. The gene content of the nasal, oropharyngeal, and lung-associated microbiota, predicted using the Phylogenetic Investigations into Communities by Reconstruction of Unobserved States (PICRUSt) software, provided information regarding the glyoxylate and citrate cycle metabolic pathways utilized by these bacterial populations to colonize such nutrient-poor, low-throughput environments. These data generated in healthy subjects provide context for future analysis of diseased canine airways. Moreover, as dogs have similar respiratory anatomy, physiology, and immune systems as humans, are exposed to many of the same environmental stimuli, and spontaneously develop similar respiratory diseases, these data support the use of dogs as a model species for prospective studies of the airway microbiota, with findings translatable to the human condition.

  10. Genome-Enabled Modeling of Biogeochemical Processes Predicts Metabolic Dependencies that Connect the Relative Fitness of Microbial Functional Guilds

    Science.gov (United States)

    Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Steefel, C. I.; Banfield, J. F.; Beller, H. R.; Anantharaman, K.; Ligocki, T. J.; Trebotich, D.

    2015-12-01

    Pore-scale processes mediated by microorganisms underlie a range of critical ecosystem services, regulating carbon stability, nutrient flux, and the purification of water. Advances in cultivation-independent approaches now provide us with the ability to reconstruct thousands of genomes from microbial populations from which functional roles may be assigned. With this capability to reveal microbial metabolic potential, the next step is to put these microbes back where they belong to interact with their natural environment, i.e. the pore scale. At this scale, microorganisms communicate, cooperate and compete across their fitness landscapes with communities emerging that feedback on the physical and chemical properties of their environment, ultimately altering the fitness landscape and selecting for new microbial communities with new properties and so on. We have developed a trait-based model of microbial activity that simulates coupled functional guilds that are parameterized with unique combinations of traits that govern fitness under dynamic conditions. Using a reactive transport framework, we simulate the thermodynamics of coupled electron donor-acceptor reactions to predict energy available for cellular maintenance, respiration, biomass development, and enzyme production. From metagenomics, we directly estimate some trait values related to growth and identify the linkage of key traits associated with respiration and fermentation, macromolecule depolymerizing enzymes, and other key functions such as nitrogen fixation. Our simulations were carried out to explore abiotic controls on community emergence such as seasonally fluctuating water table regimes across floodplain organic matter hotspots. Simulations and metagenomic/metatranscriptomic observations highlighted the many dependencies connecting the relative fitness of functional guilds and the importance of chemolithoautotrophic lifestyles. Using an X-Ray microCT-derived soil microaggregate physical model combined

  11. Hyperhomocysteinemia, coronary heart disease, and diabetes mellitus as predicted by various definitions for metabolic syndrome in a hypertensive Saudi population

    International Nuclear Information System (INIS)

    Al-Daghri, Nasser M.

    2007-01-01

    From the emergence of different definitions of metabolic syndrome (MS) we aim to determine the prevalence of such a condition among hypertensive Saudi population and to identify which definition can best assess the risk of hyperhomocysteinemia, coronary heart disease (CHD), and diabetes mellitus. In this cross-sectional study, we studied 581 hypertensive Saudis, aged 21-70, at the King Abdul-Aziz University Hospital, from June 2005 to December 2005 Each participant completed the questionnaire and underwent a complete physical examination. Metabolic parameters were measured using routine laboratory procedures and homocysteine using HPLC by the electrochemical detection method. According to the International Diabetes Federation (IDF) definition we diagnosed 222 males and 256 females. There is an increased risk for hyperhomocystenemia using the Adult Treatment Panel III (ATPIII) guidelines (odds ratio [OR] 3.30, 95% confidence interval [CI] 0.87-12.56; p=0.08) compared to IDF (OR 0.59, CI 0.17-2.10; p=0.41) and WHO (OR 0.45, CI 0.16-1.25; p=0.12); increased risk for probable CHD in patients with MS by WHO (OR 2.17, CI 1.11-4.25; p=0.02) compared to ATPIII (OR 2.14, CI 1.05-4.35; p=0.035) and IDF (OR 0.81, CI 0.37-1.78; p=0.6); risk of DM is highest with IDF (OR 13.07, CI 1.66-102.94; p=0.015). There is a high prevalence of MS among hypertensive Saudis regardless of definition used; it is most prevalent using the IDF definition as well as the risk for diabetes Patients diagnosed with ATPIII guidelines have greater risk of hyperhomocysteinemia. We recommend the WHO definition for Arabs since it predicts increased risk for CHD. (author)

  12. The Role of Uric Acid for Predicting Future Metabolic Syndrome and Type 2 Diabetes in Older People.

    Science.gov (United States)

    Chang, J-B; Chen, Y-L; Hung, Y-J; Hsieh, C-H; Lee, C-H; Pei, D; Lin, J-D; Wu, C-Z; Liang, Y-J; Lin, C-M

    2017-01-01

    Although it is known that high uric acid (UA) level is associated with type 2 diabetes (T2DM) and metabolic syndrome (MetS), most of the previous studies were focused on adults. Since aging becomes a major problem for many societies, in this longitudinal study, we investigated the role of UA in future T2DM and MetS in a large cohort of people who were older than 65 years. A cross-sectional and longitudinal study. 18,907 elderly (9,732 men, 9,175 women) aged above 65 years, enrolled from health check-up centers, were classified into three subgroups by 10-year intervals (young old 65-74 years, YO; old old 75-84 years, OO; and oldest old 85-94 years, ODO), with the average follow-up period of 4.3 years. The optimal cut-off values (CoVs) of baseline UA to predict future MetS and T2DM were determined by receiving operating characteristic (ROC) curve analysis. Using these CoVs of UA, the participants were divided into normal- and high-level groups of UA. Cox proportional hazard analysis was used to calculate hazard ratios (HRs) for the subjects with a high level of UA for the risk of future MetS and T2DM. In addition, Kaplan-Meier plots and log rank test were used to evaluate the time effect on the incidence of developing MetS and T2DM between the two groups. In ROC curve analysis, the optimal CoVs of baseline UA were 6.0, 6.3 and 6.7 mg/dl in YO, OO, and ODO men, respectively; 5.5 and 4.9 mg/dl in YO and OO women, respectively (all p metabolic biomarkers may help clinicians to early detect and prevent MetS and diabetes.

  13. Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China

    Science.gov (United States)

    Du, Zhicheng; Xu, Lin; Zhang, Wangjian; Zhang, Dingmei; Yu, Shicheng; Hao, Yuantao

    2017-01-01

    Objectives Hand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD. Design Ecological study. Setting and participants Information on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011–2014. Analyses were conducted at aggregate level and no confidential information was involved. Outcome measures A seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI. Results A high correlation between HFMD incidence and BDI (r=0.794, pdiseases in other settings. PMID:28988169

  14. Benefit of transferred mutations is better predicted by the fitness of recipients than by their ecological or genetic relatedness

    Science.gov (United States)

    Wang, Yinhua; Diaz Arenas, Carolina; Stoebel, Daniel M.; Flynn, Kenneth; Knapp, Ethan; Dillon, Marcus M.; Wünsche, Andrea; Hatcher, Philip J.; Moore, Francisco B.-G.; Cooper, Vaughn S.; Cooper, Tim F.

    2016-01-01

    The effect of a mutation depends on its interaction with the genetic background in which it is assessed. Studies in experimental systems have demonstrated that such interactions are common among beneficial mutations and often follow a pattern consistent with declining evolvability of more fit genotypes. However, these studies generally examine the consequences of interactions between a small number of focal mutations. It is not clear, therefore, that findings can be extrapolated to natural populations, where new mutations may be transferred between genetically divergent backgrounds. We build on work that examined interactions between four beneficial mutations selected in a laboratory-evolved population of Escherichia coli to test how they interact with the genomes of diverse natural isolates of the same species. We find that the fitness effect of transferred mutations depends weakly on the genetic and ecological similarity of recipient strains relative to the donor strain in which the mutations were selected. By contrast, mutation effects were strongly inversely correlated to the initial fitness of the recipient strain. That is, there was a pattern of diminishing returns whereby fit strains benefited proportionally less from an added mutation. Our results strengthen the view that the fitness of a strain can be a major determinant of its ability to adapt. They also support a role for barriers of transmission, rather than differential selection of transferred DNA, as an explanation of observed phylogenetically determined patterns of restricted recombination among E. coli strains. PMID:27091964

  15. Quantitative structure-activity relationships for predicting potential ecological hazard of organic chemicals for use in regulatory risk assessments.

    Science.gov (United States)

    Comber, Mike H I; Walker, John D; Watts, Chris; Hermens, Joop

    2003-08-01

    The use of quantitative structure-activity relationships (QSARs) for deriving the predicted no-effect concentration of discrete organic chemicals for the purposes of conducting a regulatory risk assessment in Europe and the United States is described. In the United States, under the Toxic Substances Control Act (TSCA), the TSCA Interagency Testing Committee and the U.S. Environmental Protection Agency (U.S. EPA) use SARs to estimate the hazards of existing and new chemicals. Within the Existing Substances Regulation in Europe, QSARs may be used for data evaluation, test strategy indications, and the identification and filling of data gaps. To illustrate where and when QSARs may be useful and when their use is more problematic, an example, methyl tertiary-butyl ether (MTBE), is given and the predicted and experimental data are compared. Improvements needed for new QSARs and tools for developing and using QSARs are discussed.

  16. Predicting the Metabolic Sites by Flavin-Containing Monooxygenase on Drug Molecules Using SVM Classification on Computed Quantum Mechanics and Circular Fingerprints Molecular Descriptors.

    Directory of Open Access Journals (Sweden)

    Chien-Wei Fu

    Full Text Available As an important enzyme in Phase I drug metabolism, the flavin-containing monooxygenase (FMO also metabolizes some xenobiotics with soft nucleophiles. The site of metabolism (SOM on a molecule is the site where the metabolic reaction is exerted by an enzyme. Accurate prediction of SOMs on drug molecules will assist the search for drug leads during the optimization process. Here, some quantum mechanics features such as the condensed Fukui function and attributes from circular fingerprints (called Molprint2D are computed and classified using the support vector machine (SVM for predicting some potential SOMs on a series of drugs that can be metabolized by FMO enzymes. The condensed Fukui function fA- representing the nucleophilicity of central atom A and the attributes from circular fingerprints accounting the influence of neighbors on the central atom. The total number of FMO substrates and non-substrates collected in the study is 85 and they are equally divided into the training and test sets with each carrying roughly the same number of potential SOMs. However, only N-oxidation and S-oxidation features were considered in the prediction since the available C-oxidation data was scarce. In the training process, the LibSVM package of WEKA package and the option of 10-fold cross validation are employed. The prediction performance on the test set evaluated by accuracy, Matthews correlation coefficient and area under ROC curve computed are 0.829, 0.659, and 0.877 respectively. This work reveals that the SVM model built can accurately predict the potential SOMs for drug molecules that are metabolizable by the FMO enzymes.

  17. Microbial Communities and Their Predicted Metabolic Functions in Growth Laminae of a Unique Large Conical Mat from Lake Untersee, East Antarctica

    Directory of Open Access Journals (Sweden)

    Hyunmin Koo

    2017-08-01

    Full Text Available In this study, we report the distribution of microbial taxa and their predicted metabolic functions observed in the top (U1, middle (U2, and inner (U3 decadal growth laminae of a unique large conical microbial mat from perennially ice-covered Lake Untersee of East Antarctica, using NextGen sequencing of the 16S rRNA gene and bioinformatics tools. The results showed that the U1 lamina was dominated by cyanobacteria, specifically Phormidium sp., Leptolyngbya sp., and Pseudanabaena sp. The U2 and U3 laminae had high abundances of Actinobacteria, Verrucomicrobia, Proteobacteria, and Bacteroidetes. Closely related taxa within each abundant bacterial taxon found in each lamina were further differentiated at the highest taxonomic resolution using the oligotyping method. PICRUSt analysis, which determines predicted KEGG functional categories from the gene contents and abundances among microbial communities, revealed a high number of sequences belonging to carbon fixation, energy metabolism, cyanophycin, chlorophyll, and photosynthesis proteins in the U1 lamina. The functional predictions of the microbial communities in U2 and U3 represented signal transduction, membrane transport, zinc transport and amino acid-, carbohydrate-, and arsenic- metabolisms. The Nearest Sequenced Taxon Index (NSTI values processed through PICRUSt were 0.10, 0.13, and 0.11 for U1, U2, and U3 laminae, respectively. These values indicated a close correspondence with the reference microbial genome database, implying high confidence in the predicted metabolic functions of the microbial communities in each lamina. The distribution of microbial taxa observed in each lamina and their predicted metabolic functions provides additional insight into the complex microbial ecosystem at Lake Untersee, and lays the foundation for studies that will enhance our understanding of the mechanisms responsible for the formation of these unique mat structures and their evolutionary significance.

  18. Time is an affliction: Why ecology cannot be as predictive as physics and why it needs time series

    Science.gov (United States)

    Boero, F.; Kraberg, A. C.; Krause, G.; Wiltshire, K. H.

    2015-07-01

    Ecological systems depend on both constraints and historical contingencies, both of which shape their present observable system state. In contrast to ahistorical systems, which are governed solely by constraints (i.e. laws), historical systems and their dynamics can be understood only if properly described, in the course of time. Describing these dynamics and understanding long-term variability can be seen as the mission of long time series measuring not only simple abiotic features but also complex biological variables, such as species diversity and abundances, allowing deep insights in the functioning of food webs and ecosystems in general. Long time-series are irreplaceable for understanding change, and crucially inherent system variability and thus envisaging future scenarios. This notwithstanding current policies in funding and evaluating scientific research discourage the maintenance of long term series, despite a clear need for long-term strategies to cope with climate change. Time series are crucial for a pursuit of the much invoked Ecosystem Approach and to the passage from simple monitoring programs of large-scale and long-term Earth observatories - thus promoting a better understanding of the causes and effects of change in ecosystems. The few ongoing long time series in European waters must be integrated and networked so as to facilitate the formation of nodes of a series of observatories which, together, should allow the long-term management of the features and characteristics of European waters. Human capacity building in this region of expertise and a stronger societal involvement are also urgently needed, since the expertise in recognizing and describing species and therefore recording them reliably in the context of time series is rapidly vanishing from the European Scientific community.

  19. Prediction of cardiovascular and total mortality in Chinese type 2 diabetic patients by the WHO definition for the metabolic syndrome.

    Science.gov (United States)

    Ko, G T-C; So, W-Y; Chan, N N; Chan, W-B; Tong, P C-Y; Li, J; Yeung, V; Chow, C-C; Ozaki, R; Ma, R C-W; Cockram, C S; Chan, J C-N

    2006-01-01

    The aim of this study is to investigate the prevalence of metabolic syndrome (MES) in type 2 diabetic patients and the predictive values of the World Health Organization (WHO) and National Cholesterol Education Programme (NCEP) definitions and the individual components of the MES on total and cardiovascular mortality. A prospective analysis of a consecutive cohort of 5202 Chinese type 2 diabetic patients recruited between July 1994 and April 2001. The prevalence of the MES was 49.2-58.1% depending on the use of various criteria. There were 189 deaths (men: 100 and women: 89) in these 5205 patients during a median (interquartile range) follow-up period of 2.1 (0.3-3.6 years). Of these, 164 (87%) were classified as cardiovascular deaths. Using the NCEP criterion, patients with MES had a death rate similar to those without (3.51 vs. 3.85%). By contrast, based on the WHO criteria, patients with MES had a higher mortality rate than those without (4.3 vs. 2.4%, p = 0.002). Compared to patients with neither NCEP- nor WHO-defined MES, only the group with MES defined by the WHO, but not NCEP, criterion had significantly higher mortality rate (2.6 vs. 6.8%, p hypertension, low BMI and albuminuria were the key predictors for these adverse events. In Chinese type 2 diabetic patients, the WHO criterion has a better discriminative power over the NCEP criterion for predicting death. Among the various components of the MES defined either by WHO or NCEP, hypertension, albuminuria and low BMI were the main predictors of cardiovascular and total mortality.

  20. Reverse perfusion-metabolism mismatch predicts good prognosis in patients undergoing cardiac resynchronization therapy. A pilot study

    International Nuclear Information System (INIS)

    Inoue, Noriko; Takahashi, Nobukazu; Ishikawa, Toshiyuki

    2007-01-01

    Cardiac resynchronization therapy (CRT) improves glucose metabolism in the septum of patients with heart failure, so in the present study the predictive value of combined fluorodeoxyglucose (FDG)-positron emission tomography (PET) and metoxy-isobutyl isonitrile (MIBI)-single photon emission computed tomography (SPECT) for the prognosis of patients undergoing CRT was investigated. Fourteen patients (70.3±8.2 years) who underwent FDG-PET and MIBI-SPECT before implantation of a biventricular pacemaker were enrolled. The total number of matches, mismatches, reverse mismatches, summed difference score (SDS: sum total of FDG-MIBI scores) and SDS per segment (%SDS) in each of 5 areas of myocardium (septum, anterior, lateral, inferior area, apex) was calculated and compared between the survival groups (all survival: survival group; survival without ischemic heart disease (IHD): non-IHD survival group) and non-survival group. Both the number of reverse mismatch segments and the %SDS in the septum in the non-IHD survival group were significantly greater than in the non-survival group (3.2±1.6 vs 0.5±0.6, p<0.05; 0.62±0.61 vs -0.11±0.19, p<0.05). The receiver-operating characteristics curves for prognosis showed that the area under the curve for the number of reverse mismatch segments in the septum (0.93; confidence interval 0.61-0.98) was significantly greater. A reverse mismatch pattern in the septum can predict a good prognosis for patients treated with CRT. (author)

  1. Serum uric acid does not predict incident metabolic syndrome in a population with high prevalence of obesity.

    Science.gov (United States)

    Ferrara, L A; Wang, H; Umans, J G; Franceschini, N; Jolly, S; Lee, E T; Yeh, J; Devereux, R B; Howard, B V; de Simone, G

    2014-12-01

    To evaluate whether uric acid (UA) predicts 4-yr incidence of metabolic syndrome (MetS) in non-diabetic participants of the Strong Heart Study (SHS) cohort. In this population-based prospective study we analyzed 1499 American Indians (890 women), without diabetes or MetS, controlled during the 4th SHS exam and re-examined 4 years later during the 5th SHS exam. Participants were divided into sex-specific tertiles of UA and the first two tertiles (group N) were compared with the third tertile (group H). Body mass index (BMI = 28.3 ± 7 vs. 31.1 ± 7 kg/m(2)), fat-free mass (FFM = 52.0 ± 14 vs. 54.9 ± 11 kg), waist-to-hip ratio, HOMA-IR (3.66 vs. 4.26), BP and indices of inflammation were significantly higher in group H than in group N (all p < 0.001). Incident MetS at the time of the 5th exam was more frequent in group H than group N (35 vs. 28%, OR 1.44 (95% CI = 1.10-1.91; p < 0.01). This association was still significant (OR = 1.13, p = 0.04) independently of family relatedness, sex, history of hypertension, HOMA-IR, central adiposity and renal function, but disappeared when fat-free mass was included in the model. In the SHS, UA levels are associated to parameters of insulin resistance and to indices of inflammation. UA levels, however, do not predict incident MetS independently of the initial obesity-related increased FFM. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Predicting the current potential and future world wide distribution of the onion maggot, Delia antiqua using maximum entropy ecological niche modeling.

    Science.gov (United States)

    Ning, Shuoying; Wei, Jiufeng; Feng, Jinian

    2017-01-01

    Climate change will markedly impact biology, population ecology, and spatial distribution patterns of insect pests because of the influence of future greenhouse effects on insect development and population dynamics. Onion maggot, Delia antiqua, larvae are subterranean pests with limited mobility, that directly feed on bulbs of Allium sp. and render them completely unmarketable. Modeling the spatial distribution of such a widespread and damaging pest is crucial not only to identify current potentially suitable climactic areas but also to predict where the pest is likely to spread in the future so that appropriate monitoring and management programs can be developed. In this study, Maximum Entropy Niche Modeling was used to estimate the current potential distribution of D. antiqua and to predict the future distribution of this species in 2030, 2050, 2070 and 2080 by using emission scenario (A2) with 7 climate variables. The results of this study show that currently highly suitable habitats for D.antiqua occur throughout most of East Asia, some regions of North America, Western Europe, and Western Asian countries near the Caspian sea and Black Sea. In the future, we predict an even broader distribution of this pest spread more extensively throughout Asia, North America and Europe, particularly in most of European countries, Central regions of United States and much of East Asia. Our present day and future predictions can enhance strategic planning of agricultural organizations by identifying regions that will need to develop Integrated Pest Management programs to manage the onion maggot. The distribution forecasts will also help governments to optimize economic investments in management programs for this pest by identifying regions that are or will become less suitable for current and future infestations.

  3. On the energetics of quadrupedal running: predicting the metabolic cost of transport via a flexible-torso model.

    Science.gov (United States)

    Cao, Qu; Poulakakis, Ioannis

    2015-09-03

    In this paper, the effect of torso flexibility on the energetics of quadrupedal bounding is examined in a template setting. Two reductive sagittal-plane models, one with a rigid, non-deformable torso and one with a flexible, unactuated torso are proposed. Both models feature non-trivial leg mass and inertia to capture the energy associated with repositioning the legs after liftoff as well as the energy lost due to impacts. Bounding motions that minimize the cost of transport are generated for both models via a simple controller that coordinates leg recirculation. Comparisons reveal that torso compliance promotes locomotion efficiency by facilitating leg recirculation in anticipation of touchdown at speeds that are sufficiently high. Furthermore, by considering non-ideal torque generating and compliant elements with biologically reasonable efficiency values, it is shown that the flexible-torso model can predict the metabolic cost of transport for different animals, estimated using measurements of oxygen consumption. This way, the proposed model offers a means for approximating the energetic cost of transport of running quadrupeds in a simple and direct fashion.

  4. Anthropometric parameters’ cut-off points and predictive value for metabolic syndrome in women from Cartagena, Colombia

    Directory of Open Access Journals (Sweden)

    Gustavo José Mora-García

    2014-03-01

    Full Text Available Objective. To estimate anthropometric parameters’ (APs cut-off points and association for metabolic syndrome (MetS. Materials and methods. A cross-sectional study was carried out with a total of 434 adult women from Cartagena de Indias, Colombia, in 2012. APs measured were waist circumference (WC, body mass index (BMI, body adiposity index (BAI, waist-hip ratio (WHR and waist-height ratio (WHtR. Cut-off points were estimated by a receiver operating characteristic curve (ROC. Logistic regression was applied to estimate possible associations. Results. Cut-off points for WC, BMI, BAI, WHR and WHtR were 85 cm, 28 kg/m2, 39%, 0.80 and 56, respectively. Only WHtR was associated to MetS (OR=1.11, CI95% [1.07-1.15]. Conclusion. WC cut-off point was higher than those proposed for Latin-American women by the Joint Interim Statement (JIS. WHtR had a low predictive value for MetS.

  5. Angiographically demonstrated coronary collaterals predict residual viable myocardium in patients with chronic myocardial infarction. A regional metabolic study

    International Nuclear Information System (INIS)

    Fukai, Masumi; Ii, Masaaki; Nakakoji, Takahiro

    2000-01-01

    Angiographical demonstration of coronary collateral circulation may suggest the presence of residual viable myocardium. The development of coronary collaterals was judged according to Rentrop's classification in 37 patients with old anteroseptal myocardial infarction and 13 control patients with chest pain syndrome. The subjects with myocardial infarction were divided into 2 groups: 17 patients with the main branch of the left coronary artery clearly identified by collateral blood flow from the contralateral coronary artery [Coll (+) group, male/female 10/7, mean age 56.6 years] and 20 patients with obscure coronary trunk [Coll (-) group, male/female 16/4, mean age 54.9 years]. Thallium-201 myocardial scintigraphy and examination of local myocardial metabolism were carried out by measuring the flux of lactic acid under dipyridamole infusion load. Coronary stenosis of 99% or total occlusion was found in only 5 of 20 patients (25%) in the Coll (-) group but in 16 of 17 patients (94%) in the Coll (+) group (p<0.001). Redistribution of myocardial scintigraphy was found in 11 of 15 patients (73%) in the Coll (+) group, but only 3 of 18 patients (17%) in the Coll (-) group (p<0.01). The myocardial lactic acid extraction rate was -13.2±17.0% in the Coll (+) group, but 9.1±13.2% in the Coll (-) group (p<0.001). These results suggest that coronary collateral may contribute to minimizing the infarct area and to prediction of the presence of viable myocardium. (author)

  6. Early metabolic change in (18)F-FDG-PET by measuring the single largest lesion predicts chemotherapeutic effects and patients' survival: PEACH study.

    Science.gov (United States)

    Tanaka, Yusuke; Ueda, Yutaka; Egawa-Takata, Tomomi; Matsuzaki, Shinya; Kobayashi, Eiji; Yoshino, Kiyoshi; Enomoto, Takayuki; Tatsumi, Mitsuaki; Kimura, Tadashi

    2016-01-01

    The objective of this study was to investigate the predictive value of F-18-fluorodeoxyglucose positron emission tomography (FDG-PET) for early assessment of tumor response to chemotherapy and for patient survival in gynecologic malignancies. We performed CT and FDG-PET scans before initiation of chemotherapy to determine baseline conditions. PET scan was repeated after the first cycle of chemotherapy. The tumor response was later evaluated by CT scans after three cycles of chemotherapy, using RECIST. The PET response was analyzed in terms of the difference in SUVmax for FDG of the patient's largest lesion between the baseline scan and after the first cycle of chemotherapy. The metabolic response for the tumor was defined as a 30% reduction in its SUVmax. Eleven patients received platinum-based regimens, and 20 patients received non-platinum-based regimens. The mean progression-free survival (PFS) for the patients with a metabolic response was 13 months (range 5-29). In contrast, the mean PFS of the patients with no metabolic response was only 4.3 months (range 1-18). There was a statistically significant difference between the metabolic response and PFS (p = 0.002, Mann-Whitney U test). There was a strong correlation between the metabolic response and RECIST, regardless of the chemotherapy regimens used (platinum-based group, p = 0.006; non-platinum group, p = 0.046, Fisher's exact test). The metabolic change in SUVmax was clearly predictive of tumor response in 93.5% of patients. Early FDG-PET assessment by measuring the single largest lesion is a very promising tool for rapidly predicting tumor responses and patient survival, regardless of the chemotherapy regimen.

  7. Metabolic health assessment of zoo elephants: Management factors predicting leptin levels and the glucose-to-insulin ratio and their associations with health parameters.

    Directory of Open Access Journals (Sweden)

    Kari A Morfeld

    Full Text Available Screening for metabolic-related health problems can enhance animal welfare, so the purpose of this study was to conduct the first metabolic health assessment of zoo elephants and use epidemiological methods to determine how factors in the captive environment were associated with metabolic hormone concentrations. In addition, we examined relationships between metabolic status and several fitness parameters: foot health, musculoskeletal health, reproductive cyclicity, and body condition. Two blood samples were collected 2 weeks apart from 87 Asian (Elephas maximus and 105 African (Loxodonta africana elephants managed by zoos accredited by the Association of Zoos and Aquariums for analysis of serum leptin, insulin, glucose and the glucose-to-insulin ratio (G:I. In females, mean (± SD leptin concentrations and the G:I were lower (P0.05. As mean leptin concentration increased there was an increase in the odds of a female being non-cycling (P = 0.0083. The G:I was associated inversely with body condition (P = 0.0002; as the G:I increased there was a decreased risk of BCS = 4 or 5 as compared to the ideal, or BCS = 3. Neither leptin nor G:I were predictive of foot or musculoskeletal health scores. Factors related to walking and feeding practices were most influential in predicting metabolic status, whereas social and housing factors showed smaller, but significant effects. The metabolic health benefits of walking were detected if the time spent in staff-directed walking was 7 hours or more per week. The most protective feeding practices included implementing a random rather than predictable feeding schedule and limiting the number of methods presentation methods. Results indicate that leptin levels and G:I can be used as predictors of both ovarian cycle function and body condition, and are affected by zoo management in elephants.

  8. Serum vaspin level as a predictive indicator in the amelioration of fatty liver and metabolic disturbance in patients with severe obesity after laparoscopic vertical banded gastroplasty.

    Science.gov (United States)

    Wang, Yong; Yu, Zong-Fan; Cheng, Yun-Sheng; Jia, Ben-Li; Yu, Gang; Yin, Xiao-Qiang; Wang, Yang

    2017-07-01

    This study is all about predicting the value of serum vaspin level in the amelioration of fatty liver and metabolic disturbance in patients with severe obesity after laparoscopic vertical banded gastroplasty (LVBG). A total of 164 patients (from January 2012 to May 2015) with severe obesity were chosen and performed LVBG. Enzyme-linked immunosorbent assay was performed to detect the serum vaspin level. The patients were given a biochemical automatic analyzer to measure the biochemical indicators. Homeostasis model assessment (HOMA) helps in the calculation of fasting insulin level (FINS) and insulin resistance (IR). The changes in fatty liver were examined by computed tomography (CT). Receiver operating characteristic curve is used to increase the predictive value of serum vaspin level in the amelioration of liver function and disturbances in the metabolism. Weight, BMI, waist circumference, serum vaspin level, and triglyceride (TG) decreased, but CT value of liver increased at 4th, 7th, and 12th month after surgery. After the 7th and 12th month period of surgery, the alanine aminotransferase, aspartate aminotransferase, FINS, and HOMA-IR reduced in the patients (P fatty liver and metabolic disturbance. This study proves that the serum vaspin level serves as a predictive indicator in the amelioration of fatty liver and metabolic disturbance in patients with severe obesity after LVBG.

  9. Ecological policy, assessment and prediction of the fate of Chernobyl radionuclides in sediments of the Black Sea

    International Nuclear Information System (INIS)

    Kontar, A.E.

    2002-01-01

    The mathematical model has been designed to investigate the fate and distribution of the Chernobyl radionuclides in sediments of the Black Sea. One of the regions of intensive radioactive precipitation during the Chernobyl disaster was the nothwestern Black Sea region. There are some canyon systems in this region, where bottom sediments of the shelf zone are removed to the continental slope region and finally to the abyssal part of the sea. The lack of reliable information on the removal intensity of the shelf sediments, which contain different kinds of radioactive precipitation, does not allow changes in the radioactive situation to be predicted reliably enough in the given region. On the other hand, the surface sedimentary layers dated by characteristic Chernobyl precipitation made it possible to obtain information on sediment movement rates and directions, as well as other quantitative and qualitative parameters for the mechanisms of canyon processes. This region was selected for our study

  10. Multimodality imaging can predict the metabolic response of unresectable colorectal liver metastases to radioembolization therapy with Yttrium-90 labeled resin microspheres

    Energy Technology Data Exchange (ETDEWEB)

    Flamen, Patrick [Departmentof Nuclear Medicine, Bordet Institute, Bordet Institute, Universite Libre de Bruxelles, Rue Heger-Bordet 1, B-1000 Brussels (Belgium); Vanderlinden, Bruno [Department of Radiophysics, Bordet Institute, Bordet Institute, Universite Libre de Bruxelles, Rue Heger-Bordet 1, B-1000 Brussels (Belgium); Delatte, Philippe [Department of Radiology, Hopital St-Pierre, Bordet Institute, Universite Libre de Bruxelles, Rue Heger-Bordet 1, B-1000 Brussels (Belgium); Ghanem, Ghanem [Department of Radiopharmacy, Bordet Institute, Bordet Institute, Universite Libre de Bruxelles, Rue Heger-Bordet 1, B-1000 Brussels (Belgium); Ameye, Lieveke [Data Center, Bordet Institute, Bordet Institute, Universite Libre de Bruxelles, Rue Heger-Bordet 1, B-1000 Brussels (Belgium); Eynde, Marc van den; Hendlisz, Alain [Department of Digestive Oncology, Bordet Institute, Bordet Institute, Universite Libre de Bruxelles, Rue Heger-Bordet 1, B-1000 Brussels (Belgium)], E-mail: Patrick.Flamen@bordet.be

    2008-11-21

    Selective internal radiotherapy (SIRT) using Yttrium-90 labeled resin microspheres is increasingly used for the radioembolization of unresectable liver metastases of colorectal cancer (CRC). The treatment can be simulated by scintigraphy with Tc{sup 99m}-labeled macroaggregates of albumin (MAA). The aim of the study was to develop a predictive dosimetric model for SIRT and to validate it by correlating results with the metabolic treatment response. The simulation of the dosimetry was performed by mathematically converting all liver voxel MAA-SPECT uptake values to the absolute Y{sup 90} activity. The voxel values were then converted to a simulated absorbed dose (Gy) using simple MIRD formalism. The metabolic response was defined as the change in total lesion glycolysis (TLG) on FDG-PET. A total of 39 metastatic liver lesions were studied in eight evaluable patients. The mean administered Y{sup 90} activity was 1.69 GBq (range: 1.33-2.04 GBq). The median change in TLG of the lesions was 48%. The median (95% CI) simulated absorbed dose (Gy) was 20 Gy (1-68 Gy) and 46 Gy (22-110 Gy) in the poor (<50% TLG change) and the good responders (TLG change > 50%), respectively. Using a simple cut-off value of 1 for the MAA-tumor-to-normal uptake ratio, a significant metabolic response was predicted with a sensitivity of 89% (17/19), a specificity of 65% (13/20), a positive predictive value of 71% (17/24) and a negative predictive value of 87% (13/15). Integrated multimodality imaging allows prediction of metabolic response post radioembolization using Y{sup 90}-resin microspheres, and should be used for patient selection.

  11. Multimodality imaging can predict the metabolic response of unresectable colorectal liver metastases to radioembolization therapy with Yttrium-90 labeled resin microspheres

    Science.gov (United States)

    Flamen, Patrick; Vanderlinden, Bruno; Delatte, Philippe; Ghanem, Ghanem; Ameye, Lieveke; Van Den Eynde, Marc; Hendlisz, Alain

    2008-11-01

    Selective internal radiotherapy (SIRT) using Yttrium-90 labeled resin microspheres is increasingly used for the radioembolization of unresectable liver metastases of colorectal cancer (CRC). The treatment can be simulated by scintigraphy with Tc99m-labeled macroaggregates of albumin (MAA). The aim of the study was to develop a predictive dosimetric model for SIRT and to validate it by correlating results with the metabolic treatment response. The simulation of the dosimetry was performed by mathematically converting all liver voxel MAA-SPECT uptake values to the absolute Y90 activity. The voxel values were then converted to a simulated absorbed dose (Gy) using simple MIRD formalism. The metabolic response was defined as the change in total lesion glycolysis (TLG) on FDG-PET. A total of 39 metastatic liver lesions were studied in eight evaluable patients. The mean administered Y90 activity was 1.69 GBq (range: 1.33-2.04 GBq). The median change in TLG of the lesions was 48%. The median (95% CI) simulated absorbed dose (Gy) was 20 Gy (1-68 Gy) and 46 Gy (22-110 Gy) in the poor ( 50%), respectively. Using a simple cut-off value of 1 for the MAA-tumor-to-normal uptake ratio, a significant metabolic response was predicted with a sensitivity of 89% (17/19), a specificity of 65% (13/20), a positive predictive value of 71% (17/24) and a negative predictive value of 87% (13/15). Integrated multimodality imaging allows prediction of metabolic response post radioembolization using Y90-resin microspheres, and should be used for patient selection.

  12. Metabolic tumour burden assessed by 18F-FDG PET/CT associated with serum CA19-9 predicts pancreatic cancer outcome after resection

    International Nuclear Information System (INIS)

    Xu, Hua-Xiang; Chen, Tao; Wang, Wen-Quan; Wu, Chun-Tao; Liu, Chen; Long, Jiang; Xu, Jin; Liu, Liang; Yu, Xian-Jun; Zhang, Ying-Jian; Chen, Run-Hao

    2014-01-01

    Tumour burden is one of the most important prognosticators for pancreatic ductal adenocarcinoma (PDAC). The aim of this study was to investigate the predictive significance of metabolic tumour burden measured by 18 F-FDG PET/CT in patients with resectable PDAC. Included in the study were 122 PDAC patients who received preoperative 18 F-FDG PET/CT examination and radical pancreatectomy. Metabolic tumour burden in terms of metabolic tumour volume (MTV) and total lesion glycolysis (TLG), pathological tumour burden (tumour size), serum tumour burden (baseline serum CA19-9 level), and metabolic activity (maximum standard uptake value, SUVmax) were determined, and compared for their performance in predicting overall survival (OS) and recurrence-free survival (RFS). MTV and TLG were significantly associated with baseline serum CA19-9 level (P = 0.001 for MTV, P < 0.001 for TLG) and tumour size (P < 0.001 for MTV, P = 0.001 for TLG). Multivariate analysis showed that MTV, TLG and baseline serum CA19-9 level as either categorical or continuous variables, but not tumour size or SUVmax, were independent risk predictors for both OS and RFS. Time-dependent receiving operating characteristics analysis further indicated that better predictive performances for OS and RFS were achieved by MTV and TLG compared to baseline serum CA19-9 level, SUVmax and tumour size (P < 0.001 for all). MTV and TLG showed strong consistency with baseline serum CA19-9 level in better predicting OS and RFS, and might serve as surrogate markers for prediction of outcome in patients with resectable PDAC. (orig.)

  13. Metabolic tumour burden assessed by {sup 18}F-FDG PET/CT associated with serum CA19-9 predicts pancreatic cancer outcome after resection

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Hua-Xiang; Chen, Tao; Wang, Wen-Quan; Wu, Chun-Tao; Liu, Chen; Long, Jiang; Xu, Jin; Liu, Liang; Yu, Xian-Jun [Fudan University, Shanghai Cancer Center, Pancreatic Cancer Institute and Department of Pancreatic and Hepatobiliary Surgery, Shanghai (China); Fudan University, Department of Oncology, Shanghai Medical College, Shanghai (China); Zhang, Ying-Jian [Fudan University, Shanghai Cancer Center, Department of Nuclear Medicine, Shanghai (China); Fudan University, Department of Oncology, Shanghai Medical College, Shanghai (China); Chen, Run-Hao [Fudan University, Department of General Surgery, Jinshan Hospital, Shanghai (China)

    2014-06-15

    Tumour burden is one of the most important prognosticators for pancreatic ductal adenocarcinoma (PDAC). The aim of this study was to investigate the predictive significance of metabolic tumour burden measured by {sup 18}F-FDG PET/CT in patients with resectable PDAC. Included in the study were 122 PDAC patients who received preoperative {sup 18}F-FDG PET/CT examination and radical pancreatectomy. Metabolic tumour burden in terms of metabolic tumour volume (MTV) and total lesion glycolysis (TLG), pathological tumour burden (tumour size), serum tumour burden (baseline serum CA19-9 level), and metabolic activity (maximum standard uptake value, SUVmax) were determined, and compared for their performance in predicting overall survival (OS) and recurrence-free survival (RFS). MTV and TLG were significantly associated with baseline serum CA19-9 level (P = 0.001 for MTV, P < 0.001 for TLG) and tumour size (P < 0.001 for MTV, P = 0.001 for TLG). Multivariate analysis showed that MTV, TLG and baseline serum CA19-9 level as either categorical or continuous variables, but not tumour size or SUVmax, were independent risk predictors for both OS and RFS. Time-dependent receiving operating characteristics analysis further indicated that better predictive performances for OS and RFS were achieved by MTV and TLG compared to baseline serum CA19-9 level, SUVmax and tumour size (P < 0.001 for all). MTV and TLG showed strong consistency with baseline serum CA19-9 level in better predicting OS and RFS, and might serve as surrogate markers for prediction of outcome in patients with resectable PDAC. (orig.)

  14. Ecological Niche Modelling Predicts Southward Expansion of Lutzomyia (Nyssomyia flaviscutellata (Diptera: Psychodidae: Phlebotominae, Vector of Leishmania (Leishmania amazonensis in South America, under Climate Change.

    Directory of Open Access Journals (Sweden)

    Bruno M Carvalho

    Full Text Available Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia flaviscutellata and the parasite it transmits, Leishmania (Leishmania amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector's climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest. Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: "stabilization" and "high increase". Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador

  15. Ecological Niche Modelling Predicts Southward Expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), Vector of Leishmania (Leishmania) amazonensis in South America, under Climate Change.

    Science.gov (United States)

    Carvalho, Bruno M; Rangel, Elizabeth F; Ready, Paul D; Vale, Mariana M

    2015-01-01

    Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector's climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest). Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: "stabilization" and "high increase". Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador, Colombia and Venezuela

  16. Travelling on a budget: predictions and ecological evidence for bottlenecks in the annual cycle of long-distance migrants.

    Science.gov (United States)

    Buehler, Deborah M; Piersma, Theunis

    2008-01-27

    Long-distance migration, and the study of the migrants who undertake these journeys, has fascinated generations of biologists. However, many aspects of the annual cycles of these migrants remain a mystery as do many of the driving forces behind the evolution and maintenance of the migrations themselves. In this article we discuss nutritional, energetic, temporal and disease-risk bottlenecks in the annual cycle of long-distance migrants, taking a sandpiper, the red knot Calidris canutus, as a focal species. Red knots have six recognized subspecies each with different migratory routes, well-known patterns of connectivity and contrasting annual cycles. The diversity of red knot annual cycles allows us to discuss the existence and the effects of bottlenecks in a comparative framework. We examine the evidence for bottlenecks focusing on the quality of breeding plumage and the timing of moult as indicators in the six subspecies. In terms of breeding plumage coloration, quality and timing of prealternate body moult (from non-breeding into breeding plumage), the longest migrating knot subspecies, Calidris canutus rogersi and Calidris canutus rufa, show the greatest impact of bottlenecking. The same is true in terms of prebasic body moult (from breeding into non-breeding plumage) which in case of both C. c. rogersi and C. c. rufa overlaps with southward migration and may even commence in the breeding grounds. To close our discussion of bottlenecks in long-distance migrants, we make predictions about how migrants might be impacted via physiological 'trade-offs' throughout the annual cycle, using investment in immune function as an example. We also predict how bottlenecks may affect the distribution of mortality throughout the annual cycle. We hope that this framework will be applicable to other species and types of migrants, thus expanding the comparative database for the future evaluation of seasonal selection pressures and the evolution of annual cycles in long

  17. Predictive value of serum apolipoprotein B/apolipoprotein A-I ratio in metabolic syndrome risk: a Chinese cohort study.

    Science.gov (United States)

    Chou, Yu-Ching; Kuan, Jen-Chun; Bai, Chyi-Huey; Yang, Tsan; Chou, Wan-Yun; Hsieh, Po-Chien; You, San-Lin; Hwang, Lee-Ching; Chen, Chien-Hua; Wei, Cheng-Yu; Sun, Chien-An

    2015-06-01

    The purpose of this study was to evaluate whether the apolipoprotein B/apolipoprotein A-I (apoB/apoA-I) ratio is a promising risk predictor of metabolic syndrome (MetS) and to determine the optimal cut-off value of this ratio in detecting subjects with MetS in a Chinese population. A prospective study was conducted using a representative sample of non-institutionized people in Taiwan. A total of 3,343 participants with mean age (±SD) of 39.86 (±15.61) years old were followed up from 2002 to 2007. The primary outcome was the incidence of MetS. The MetS was defined according to a unified criterion established by several major organizations. There were 462 cases of incident MetS during a mean follow-up period of 5.26 years. A significantly stepwise increase in the incidence of MetS across quartiles of the apoB/apoA-I ratio was noted in both sexes after adjustment for potential confounders (p for trend risk of MetS in both men [adjusted hazard ratio (HR) = 6.29, 95 % confidence interval (CI) = 2.79-9.13] and women (adjusted HR = 3.82, 95 % CI = 1.06-6.63). Comparisons of receiver operating characteristics curves indicated that the predictive ability of apoB/apoA-I ratio to detect MetS was better than conventional lipid ratio measurements. Furthermore, the optimal cut-off value of apoB/apoA-I ratio for MetS diagnosis was 0.71 in men and 0.56 in women. These results suggest that an elevated apoB/apoA-I ratio might constitute a potentially crucial measure linked to the risk of developing MetS.

  18. Integrating metabolic performance, thermal tolerance, and plasticity enables for more accurate predictions on species vulnerability to acute and chronic effects of global warming.

    Science.gov (United States)

    Magozzi, Sarah; Calosi, Piero

    2015-01-01

    Predicting species vulnerability to global warming requires a comprehensive, mechanistic understanding of sublethal and lethal thermal tolerances. To date, however, most studies investigating species physiological responses to increasing temperature have focused on the underlying physiological traits of either acute or chronic tolerance in isolation. Here we propose an integrative, synthetic approach including the investigation of multiple physiological traits (metabolic performance and thermal tolerance), and their plasticity, to provide more accurate and balanced predictions on species and assemblage vulnerability to both acute and chronic effects of global warming. We applied this approach to more accurately elucidate relative species vulnerability to warming within an assemblage of six caridean prawns occurring in the same geographic, hence macroclimatic, region, but living in different thermal habitats. Prawns were exposed to four incubation temperatures (10, 15, 20 and 25 °C) for 7 days, their metabolic rates and upper thermal limits were measured, and plasticity was calculated according to the concept of Reaction Norms, as well as Q10 for metabolism. Compared to species occupying narrower/more stable thermal niches, species inhabiting broader/more variable thermal environments (including the invasive Palaemon macrodactylus) are likely to be less vulnerable to extreme acute thermal events as a result of their higher upper thermal limits. Nevertheless, they may be at greater risk from chronic exposure to warming due to the greater metabolic costs they incur. Indeed, a trade-off between acute and chronic tolerance was apparent in the assemblage investigated. However, the invasive species P. macrodactylus represents an exception to this pattern, showing elevated thermal limits and plasticity of these limits, as well as a high metabolic control. In general, integrating multiple proxies for species physiological acute and chronic responses to increasing

  19. Modeling the Differences in Biochemical Capabilities of Pseudomonas Species by Flux Balance Analysis: How Good Are Genome-Scale Metabolic Networks at Predicting the Differences?

    Directory of Open Access Journals (Sweden)

    Parizad Babaei

    2014-01-01

    Full Text Available To date, several genome-scale metabolic networks have been reconstructed. These models cover a wide range of organisms, from bacteria to human. Such models have provided us with a framework for systematic analysis of metabolism. However, little effort has been put towards comparing biochemical capabilities of closely related species using their metabolic models. The accuracy of a model is highly dependent on the reconstruction process, as some errors may be included in the model during reconstruction. In this study, we investigated the ability of three Pseudomonas metabolic models to predict the biochemical differences, namely, iMO1086, iJP962, and iSB1139, which are related to P. aeruginosa PAO1, P. putida KT2440, and P. fluorescens SBW25, respectively. We did a comprehensive literature search for previous works containing biochemically distinguishable traits over these species. Amongst more than 1700 articles, we chose a subset of them which included experimental results suitable for in silico simulation. By simulating the conditions provided in the actual biological experiment, we performed case-dependent tests to compare the in silico results to the biological ones. We found out that iMO1086 and iJP962 were able to predict the experimental data and were much more accurate than iSB1139.

  20. Modeling the differences in biochemical capabilities of pseudomonas species by flux balance analysis: how good are genome-scale metabolic networks at predicting the differences?

    Science.gov (United States)

    Babaei, Parizad; Ghasemi-Kahrizsangi, Tahereh; Marashi, Sayed-Amir

    2014-01-01

    To date, several genome-scale metabolic networks have been reconstructed. These models cover a wide range of organisms, from bacteria to human. Such models have provided us with a framework for systematic analysis of metabolism. However, little effort has been put towards comparing biochemical capabilities of closely related species using their metabolic models. The accuracy of a model is highly dependent on the reconstruction process, as some errors may be included in the model during reconstruction. In this study, we investigated the ability of three Pseudomonas metabolic models to predict the biochemical differences, namely, iMO1086, iJP962, and iSB1139, which are related to P. aeruginosa PAO1, P. putida KT2440, and P. fluorescens SBW25, respectively. We did a comprehensive literature search for previous works containing biochemically distinguishable traits over these species. Amongst more than 1700 articles, we chose a subset of them which included experimental results suitable for in silico simulation. By simulating the conditions provided in the actual biological experiment, we performed case-dependent tests to compare the in silico results to the biological ones. We found out that iMO1086 and iJP962 were able to predict the experimental data and were much more accurate than iSB1139.

  1. Ecological Misconceptions.

    Science.gov (United States)

    Munson, Bruce H.

    1994-01-01

    Presents a summary of the research literature on students' ecological conceptions and the implications of misconceptions. Topics include food webs, ecological adaptation, carrying capacity, ecosystem, and niche. (Contains 35 references.) (MKR)

  2. Quantitative plant ecology

    DEFF Research Database (Denmark)

    Damgaard, Christian

    2014-01-01

    This e-book is written in the Wolfram' CDF format (download free CDF player from Wolfram.com) The objective of this e-book is to introduce the population ecological concepts for measuring and predicting the ecological success of plant species. This will be done by focusing on the measurement...... and statistical modelling of plant species abundance and the relevant ecological processes that control species abundance. The focus on statistical modelling and likelihood function based methods also means that more algorithm based methods, e.g. ordination techniques and boosted regression tress...

  3. Leisure time physical activity in middle age predicts the metabolic syndrome in old age: results of a 28-year follow-up of men in the Oslo study

    Science.gov (United States)

    Holme, Ingar; Tonstad, Serena; Sogaard, Anne Johanne; Larsen, Per G Lund; Haheim, Lise Lund

    2007-01-01

    Background Data are scarce on the long term relationship between leisure time physical activity, smoking and development of metabolic syndrome and diabetes. We wanted to investigate the relationship between leisure time physical activity and smoking measured in middle age and the occurrence of the metabolic syndrome and diabetes in men that participated in two cardiovascular screenings of the Oslo Study 28 years apart. Methods Men residing in Oslo and born in 1923–32 (n = 16 209) were screened for cardiovascular diseases and risk factors in 1972/3. Of the original cohort, those who also lived in same area in 2000 were invited to a repeat screening examination, attended by 6 410 men. The metabolic syndrome was defined according to a modification of the National Cholesterol Education Program criteria. Leisure time physical activity, smoking, educational attendance and the presence of diabetes were self-reported. Results Leisure time physical activity decreased between the first and second screening and tracked only moderately between the two time points (Spearman's ρ = 0.25). Leisure time physical activity adjusted for age and educational attendance was a significant predictor of both the metabolic syndrome and diabetes in 2000 (odds ratio for moderately vigorous versus sedentary/light activity was 0.65 [95% CI, 0.54–0.80] for the metabolic syndrome and 0.68 [0.52–0.91] for diabetes) (test for trend P < 0.05). However, when adjusted for more factors measured in 1972/3 including glucose, triglycerides, body mass index, treated hypertension and systolic blood pressure these associations were markedly attenuated. Smoking was associated with the metabolic syndrome but not with diabetes in 2000. Conclusion Physical activity during leisure recorded in middle age prior to the current waves of obesity and diabetes had an independent predictive association with the presence of the metabolic syndrome but not significantly so with diabetes 28 years later in life, when

  4. Ecological networks--beyond food webs.

    Science.gov (United States)

    Ings, Thomas C; Montoya, José M; Bascompte, Jordi; Blüthgen, Nico; Brown, Lee; Dormann, Carsten F; Edwards, François; Figueroa, David; Jacob, Ute; Jones, J Iwan; Lauridsen, Rasmus B; Ledger, Mark E; Lewis, Hannah M; Olesen, Jens M; van Veen, F J Frank; Warren, Phil H; Woodward, Guy

    2009-01-01

    1. A fundamental goal of ecological network research is to understand how the complexity observed in nature can persist and how this affects ecosystem functioning. This is essential for us to be able to predict, and eventually mitigate, the consequences of increasing environmental perturbations such as habitat loss, climate change, and invasions of exotic species. 2. Ecological networks can be subdivided into three broad types: 'traditional' food webs, mutualistic networks and host-parasitoid networks. There is a recent trend towards cross-comparisons among network types and also to take a more mechanistic, as opposed to phenomenological, perspective. For example, analysis of network configurations, such as compartments, allows us to explore the role of co-evolution in structuring mutualistic networks and host-parasitoid networks, and of body size in food webs. 3. Research into ecological networks has recently undergone a renaissance, leading to the production of a new catalogue of evermore complete, taxonomically resolved, and quantitative data. Novel topological patterns have been unearthed and it is increasingly evident that it is the distribution of interaction strengths and the configuration of complexity, rather than just its magnitude, that governs network stability and structure. 4. Another significant advance is the growing recognition of the importance of individual traits and behaviour: interactions, after all, occur between individuals. The new generation of high-quality networks is now enabling us to move away from describing networks based on species-averaged data and to start exploring patterns based on individuals. Such refinements will enable us to address more general ecological questions relating to foraging theory and the recent metabolic theory of ecology. 5. We conclude by suggesting a number of 'dead ends' and 'fruitful avenues' for future research into ecological networks.

  5. Controlled experiments of hillslope co-evolution at the Biosphere 2 Landscape Evolution Observatory: toward prediction of coupled hydrological, biogeochemical, and ecological change

    Science.gov (United States)

    Volkmann, T. H. M.; Sengupta, A.; Pangle, L.; Abramson, N.; Barron-Gafford, G.; Breshears, D. D.; Bugaj, A.; Chorover, J.; Dontsova, K.; Durcik, M.; Ferre, T. P. A.; Harman, C. J.; Hunt, E.; Huxman, T. E.; Kim, M.; Maier, R. M.; Matos, K.; Alves Meira Neto, A.; Meredith, L. K.; Monson, R. K.; Niu, G. Y.; Pelletier, J. D.; Rasmussen, C.; Ruiz, J.; Saleska, S. R.; Schaap, M. G.; Sibayan, M.; Tuller, M.; Van Haren, J. L. M.; Wang, Y.; Zeng, X.; Troch, P. A.

    2017-12-01

    the evolutionary trajectory, integrating data with models, and fostering community-wide collaborations, we envision that emergent landscape structures and functions can be linked and significant progress can be made toward predicting the coupled hydro-biogeochemical and ecological responses to global change.

  6. The Use of Remote Sensing for Monitoring, Prediction, and Management of Hydrologic, Agricultural, and Ecological Processes in the Northern Great Plains

    Science.gov (United States)

    Farwell, Sherry O.; DeTroye, Diane (Technical Monitor)

    2002-01-01

    The NASA-EPSCoR program in South Dakota is focused on the enhancement of NASA-related research in earth system science and corresponding infrastructure development to support this theme. Hence, the program has adopted a strategy that keys on research projects that: a) establish quantitative links between geospatial information technologies and fundamental climatic and ecosystem processes in the Northern Great Plains (NGP) and b) develop and use coupled modeling tools, which can be initialized by data from combined satellite and surface measurements, to provide reliable predictions and management guidance for hydrologic, agricultural, and ecological systems of the NGP. Building a partnership network that includes both internal and external team members is recognized as an essential element of the SD NASA-EPSCoR program. Hence, promoting and tracking such linkages along with their relevant programmatic consequences are used as one metric to assess the program's progress and success. This annual report first summarizes general activities and accomplishments, and then provides progress narratives for the two separate, yet related research projects that are essential components of the SD NASA-EPSCoR program.

  7. Metabolic activity by {sup 18}F-FDG-PET/CT is predictive of early response after nivolumab in previously treated NSCLC

    Energy Technology Data Exchange (ETDEWEB)

    Kaira, Kyoichi; Altan, Bolag [Gunma University Graduate School of Medicine, Department of Oncology Clinical Development, Maebashi, Gunma (Japan); Higuchi, Tetsuya; Arisaka, Yukiko; Tokue, Azusa [Gunma University Graduate School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, Maebashi, Gunma (Japan); Naruse, Ichiro [Hidaka Hospital, Department of Respiratory Medicine, Hidaka (Japan); Suda, Satoshi [Hidaka Hospital, Department of Radiology, Hidaka (Japan); Mogi, Akira; Shimizu, Kimihiro [Gunma University Graduate School of Medicine, Department of General Surgical Science, Maebashi, Gunma (Japan); Sunaga, Noriaki [Gunma University Hospital, Oncology Center, Maebashi, Gunma (Japan); Hisada, Takeshi [Gunma University Hospital, Department of Respiratory Medicine, Maebashi, Gunma (Japan); Kitano, Shigehisa [National Cancer Center Hospital, Department of Experimental Therapeutics, Tokyo (Japan); Obinata, Hideru; Asao, Takayuki [Gunma University Initiative for Advanced Research, Big Data Center for Integrative Analysis, Maebashi, Gunma (Japan); Yokobori, Takehiko [Gunma University Initiative for Advanced Research, Division of Integrated Oncology Research, Research Program for Omics-based Medical Science, Maebashi, Gunma (Japan); Mori, Keita [Clinical Research Support Center, Shizuoka Cancer Center, Suntou-gun (Japan); Nishiyama, Masahiko [Gunma University Graduate School of Medicine, Department of Molecular Pharmacology and Oncology, Maebashi, Gunma (Japan); Tsushima, Yoshihito [Gunma University Graduate School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, Maebashi, Gunma (Japan); Gunma University Initiative for Advanced Research (GIAR), Research Program for Diagnostic and Molecular Imaging, Division of Integrated Oncology Research, Maebashi, Gunma (Japan)

    2018-01-15

    Nivolumab, an anti-programmed death-1 (PD-1) antibody, is administered in patients with previously treated non-small cell lung cancer. However, little is known about the established biomarker predicting the efficacy of nivolumab. Here, we conducted a preliminary study to investigate whether {sup 18}F-FDG-PET/CT could predict the therapeutic response of nivolumab at the early phase. Twenty-four patients were enrolled in this study. {sup 18}F-FDG-PET/CT was carried out before and 1 month after nivolumab therapy. SUV{sub max}, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were calculated. Immunohistochemical analysis of PD-L1 expression and tumour-infiltrating lymphocytes was conducted. Among all patients, a partial metabolic response to nivolumab was observed in 29% on SUV{sub max}, 25% on MTV, and 33% on TLG, whereas seven (29%) patients achieved a partial response (PR) based on RECIST v1.1. The predictive probability of PR (100% vs. 29%, p = 0.021) and progressive disease (100% vs. 22.2%, p = 0.002) at 1 month after nivolumab initiation was significantly higher in {sup 18}F-FDG on PET/CT than in CT scans. Multivariate analysis confirmed that {sup 18}F-FDG uptake after administration of nivolumab was an independent prognostic factor. PD-L1 expression and nivolumab plasma concentration could not precisely predict the early therapeutic efficacy of nivolumab. Metabolic response by {sup 18}F-FDG was effective in predicting efficacy and survival at 1 month after nivolumab treatment. (orig.)

  8. Baseline and changes in serum uric acid independently predict 11-year incidence of metabolic syndrome among community-dwelling women.

    Science.gov (United States)

    Kawamoto, R; Ninomiya, D; Kasai, Y; Senzaki, K; Kusunoki, T; Ohtsuka, N; Kumagi, T

    2018-02-19

    Metabolic syndrome (MetS) is associated with an increased risk of major cardiovascular events. In women, increased serum uric acid (SUA) levels are associated with MetS and its components. However, whether baseline and changes in SUA predict incidence of MetS and its components remains unclear. The subjects comprised 407 women aged 71 ± 8 years from a rural village. We have identified participants who underwent a similar examination 11 years ago, and examined the relationship between baseline and changes in SUA, and MetS based on the modified criteria of the National Cholesterol Education Program's Adult Treatment Panel (NCEP-ATP) III report. Of these subjects, 83 (20.4%) women at baseline and 190 (46.7%) women at follow-up had MetS. Multiple linear regression analysis was performed to evaluate the contribution of each confounding factor for MetS; both baseline and changes in SUA as well as history of cardiovascular disease, low-density lipoprotein cholesterol, and estimated glomerular filtration ratio (eGFR) were independently and significantly associated with the number of MetS components during an 11-year follow-up. The adjusted odds ratios (ORs) (95% confidence interval) for incident MetS across tertiles of baseline SUA and changes in SUA were 1.00, 1.47 (0.82-2.65), and 3.11 (1.66-5.83), and 1.00, 1.88 (1.03-3.40), and 2.49 (1.38-4.47), respectively. In addition, the combined effect between increased baseline and changes in SUA was also a significant and independent determinant for the accumulation of MetS components (F = 20.29, p < 0.001). The ORs for incident MetS were significant only in subjects with age ≥ 55 years, decline in eGFR, and no baseline MetS. These results suggested that combined assessment of baseline and changes in SUA levels provides increased information for incident MetS, independent of other confounding factors in community-dwelling women.

  9. Leisure time physical activity in middle age predicts the metabolic syndrome in old age: results of a 28-year follow-up of men in the Oslo study

    Directory of Open Access Journals (Sweden)

    Sogaard Anne

    2007-07-01

    Full Text Available Abstract Background Data are scarce on the long term relationship between leisure time physical activity, smoking and development of metabolic syndrome and diabetes. We wanted to investigate the relationship between leisure time physical activity and smoking measured in middle age and the occurrence of the metabolic syndrome and diabetes in men that participated in two cardiovascular screenings of the Oslo Study 28 years apart. Methods Men residing in Oslo and born in 1923–32 (n = 16 209 were screened for cardiovascular diseases and risk factors in 1972/3. Of the original cohort, those who also lived in same area in 2000 were invited to a repeat screening examination, attended by 6 410 men. The metabolic syndrome was defined according to a modification of the National Cholesterol Education Program criteria. Leisure time physical activity, smoking, educational attendance and the presence of diabetes were self-reported. Results Leisure time physical activity decreased between the first and second screening and tracked only moderately between the two time points (Spearman's ρ = 0.25. Leisure time physical activity adjusted for age and educational attendance was a significant predictor of both the metabolic syndrome and diabetes in 2000 (odds ratio for moderately vigorous versus sedentary/light activity was 0.65 [95% CI, 0.54–0.80] for the metabolic syndrome and 0.68 [0.52–0.91] for diabetes (test for trend P Conclusion Physical activity during leisure recorded in middle age prior to the current waves of obesity and diabetes had an independent predictive association with the presence of the metabolic syndrome but not significantly so with diabetes 28 years later in life, when the subjects were elderly.

  10. 5. Space and Ecology

    Science.gov (United States)

    Kondratiev, K. L.; Supmi, W.

    1989-08-01

    The Space and Ecology round table was attented by 73 persons and addressed by 27 speakers on topics bearing on major global ecological problems: biogeophysical exchanges of matter and energy: the key aspect of global ecology; current problems in exploring the World Ocean and the Earth's climate; dynamics of global systems and processes with the potential to control it in future; mutual influence of changes in natural resources and the environment as they occur in different regions on the globe; spaceborne observational systems: a means for revealing the dynamics of natural processes and a basis for making ecological predictions. Scientists and specialists in space ecology — Prof. I. Rasool (U.S.A.), R. Moore (U.S.A.), W. Suomi (U.S.A.), Academician K. Kondratiev (U.S.S.R.), Prof. Zavarzin, Corresponding Member of the Academy of Sciences (U.S.S.R.), Prof. W. Peters (Denmark), Prof. B. Nei, Corresponding Member of the Academy of Sciences (Poland), the Soviet cosmonauts G. Beregovoi, G. Grechko, B. Volynov, and other attendees of the round table on Space and Ecology stressed the immediate urgency of addressing vitally important ecological problems through widescale uses of space technologies. Wide-ranging international cooperative programme in space ecology have now been designed and started, bringing together space-related expertise from more than 70 countries. The round table participants made several suggestions for ways to enhanced cooperation and collaboration on ecological problems; one of these proposed setting up an International Organisation on Problems of Global Ecology. The discussion was held in an atmosphere of friendship, mutual understanding and further enhancement of cooperative effort in space for the sake of peace on Earth.

  11. Metabolic health assessment of zoo elephants: Management factors predicting leptin levels and the glucose-to-insulin ratio and their associations with health parameters.

    Science.gov (United States)

    Morfeld, Kari A; Brown, Janine L

    2017-01-01

    Screening for metabolic-related health problems can enhance animal welfare, so the purpose of this study was to conduct the first metabolic health assessment of zoo elephants and use epidemiological methods to determine how factors in the captive environment were associated with metabolic hormone concentrations. In addition, we examined relationships between metabolic status and several fitness parameters: foot health, musculoskeletal health, reproductive cyclicity, and body condition. Two blood samples were collected 2 weeks apart from 87 Asian (Elephas maximus) and 105 African (Loxodonta africana) elephants managed by zoos accredited by the Association of Zoos and Aquariums for analysis of serum leptin, insulin, glucose and the glucose-to-insulin ratio (G:I). In females, mean (± SD) leptin concentrations and the G:I were lower (Pelephants, respectively. For males, mean leptin and the G:I were 4.99 ± 3.61 ng/ml and 253 ± 181 units for Asian, and 3.72 ± 2.00 ng/ml and 326 ± 231 units for African elephants, respectively, with no differences between species (P>0.05). As mean leptin concentration increased there was an increase in the odds of a female being non-cycling (P = 0.0083). The G:I was associated inversely with body condition (P = 0.0002); as the G:I increased there was a decreased risk of BCS = 4 or 5 as compared to the ideal, or BCS = 3. Neither leptin nor G:I were predictive of foot or musculoskeletal health scores. Factors related to walking and feeding practices were most influential in predicting metabolic status, whereas social and housing factors showed smaller, but significant effects. The metabolic health benefits of walking were detected if the time spent in staff-directed walking was 7 hours or more per week. The most protective feeding practices included implementing a random rather than predictable feeding schedule and limiting the number of methods presentation methods. Results indicate that leptin levels and G:I can be used as predictors

  12. Landscape Ecology

    DEFF Research Database (Denmark)

    Christensen, Andreas Aagaard; Brandt, Jesper; Svenningsen, Stig Roar

    2017-01-01

    pattern analysis and ecological interaction of land units. The landscape is seen as a holon: an assemblage of interrelated phenomena, both cultural and biophysical, that together form a complex whole. Enduring challenges to landscape ecology include the need to develop a systematic approach able......Landscape ecology is an interdisciplinary field of research and practice that deals with the mutual association between the spatial configuration and ecological functioning of landscapes, exploring and describing processes involved in the differentiation of spaces within landscapes......, and the ecological significance of the patterns which are generated by such processes. In landscape ecology, perspectives drawn from existing academic disciplines are integrated based on a common, spatially explicit mode of analysis developed from classical holistic geography, emphasizing spatial and landscape...

  13. Landscape Ecology

    DEFF Research Database (Denmark)

    Christensen, Andreas Aagaard; Brandt, Jesper; Svenningsen, Stig Roar

    2017-01-01

    Landscape ecology is an interdisciplinary field of research and practice that deals with the mutual association between the spatial configuration and ecological functioning of landscapes, exploring and describing processes involved in the differentiation of spaces within landscapes......, and the ecological significance of the patterns which are generated by such processes. In landscape ecology, perspectives drawn from existing academic disciplines are integrated based on a common, spatially explicit mode of analysis developed from classical holistic geography, emphasizing spatial and landscape...... pattern analysis and ecological interaction of land units. The landscape is seen as a holon: an assemblage of interrelated phenomena, both cultural and biophysical, that together form a complex whole. Enduring challenges to landscape ecology include the need to develop a systematic approach able...

  14. High-sensitivity C-reactive protein predicts target organ damage in Chinese patients with metabolic syndrome

    DEFF Research Database (Denmark)

    Zhao, Zhigang; Nie, Hai; He, Hongbo

    2007-01-01

    with metabolic syndrome. A total of 1082 consecutive patients of Chinese origin were screened for the presence of metabolic syndrome according to the National Cholesterol Education Program's Adult Treatment Panel III. High-sensitivity C-reactive protein and target organ damage, including cardiac hypertrophy......, carotid intima-media thickness, and renal impairment, were investigated. The median (25th and 75th percentiles) of high-sensitivity C-reactive protein in 619 patients with metabolic syndrome was 2.42 mg/L (0.75 and 3.66 mg/L) compared with 1.13 mg/L (0.51 and 2.46 mg/L) among 463 control subjects (P ...). There was a progressive increase in high-sensitivity C-reactive protein level with the number of components of the metabolic syndrome. Stratification of patients with metabolic syndrome into 3 groups according to their high-sensitivity C-reactive protein concentrations (3.0 mg/L) showed that the subjects...

  15. Statistical ecology comes of age

    Science.gov (United States)

    Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

    2014-01-01

    The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data. PMID:25540151

  16. Statistical ecology comes of age.

    Science.gov (United States)

    Gimenez, Olivier; Buckland, Stephen T; Morgan, Byron J T; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

    2014-12-01

    The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

  17. A metabolic and body-size scaling framework for parasite within-host abundance, biomass, and energy flux.

    Science.gov (United States)

    Hechinger, Ryan F

    2013-08-01

    Energetics may provide a useful currency for studying the ecology of parasite assemblages within individual hosts. Parasite assemblages may also provide powerful models to study general principles of ecological energetics. Yet there has been little ecological research on parasite-host energetics, probably due to methodological difficulties. However, the scaling relationships of individual metabolic rate with body or cell size and temperature may permit us to tackle the energetics of parasite assemblages in hosts. This article offers the foundations and initial testing of a metabolic theory of ecology (MTE) framework for parasites in hosts. I first provide equations to estimate energetic flux through observed parasite assemblages. I then develop metabolic scaling theory for parasite abundance, energetics, and biomass in individual hosts. In contrast to previous efforts, the theory factors in both host and parasite metabolic scaling, how parasites use host space, and whether energy or space dictates carrying capacity. Empirical tests indicate that host energetic flux can set parasite carrying capacity, which decreases as predicted considering the scaling of host and parasite metabolic rates. The theory and results also highlight that the phenomenon of "energetic equivalence" is not an assumption of MTE but a possible outcome contingent on how species partition resources. Hence, applying MTE to parasites can lend mechanistic, quantitative, predictive insight into the nature of parasitism and can inform general ecological theory.

  18. Marx, Engels and Ecology

    Directory of Open Access Journals (Sweden)

    Michael Löwy

    2017-11-01

    Full Text Available This is a brief survey of Marx and Engels’ views on ecology, from the viewpoint of their relevance for 21th Century ecosocialism. While there are some serious limitations in the way both consider the “development of productive forces”, there are powerfull insights in their discussion of the destructive consequences of capitalist expansion for the environment - an expansion that generates a disastrous metabolic rift in the exchanges between human societies and nature. Some ecological Marxists distinguish between “first stage ecosocialists” - who believe that Marx analyses on ecological issues are too incomplete and dated to be of real relevance today - and “second stage ecosocialists” that emphasize the contemporary methodological significance of Marx’s ecological critique of capitalism. This paper tries to argue for a third position (which probably could be accepted by several people of the two groups above: Marx and Engels discussion on ecological issues is incomplete and dated, but inspite these shortcomings, it has real relevance and methodological significance today.

  19. Index of central obesity as a parameter to replace waist circumference for the definition of metabolic syndrome in predicting cardiovascular disease.

    Science.gov (United States)

    Luo, Wenshu; Guo, Zhirong; Wu, Ming; Hao, Chao; Zhou, Zhengyuan; Yao, Xingjuan

    2014-10-01

    To compare the suitability of metabolic syndrome definitions in predicting cardiovascular disease (CVD) risk. We analyzed data from a population-based prospective cohort of 3598 participants from Jiangsu, China. Waist circumference was replaced with central obesity [index of central obesity (ICO), a ratio of waist circumference and height] in Cholesterol Education Program Adult Treatment Panel III (ICO-replaced ATPIII) and International Diabetes Federation (ICO-replaced IDF), respectively. Cox proportional-hazards regression model and the receiver operating characteristic curve (ROC curve) was used to evaluate the suitability of ATPIII, IDF, ICO-replaced IDF and ICO-replaced ATPIII in predicting CVD risk. ICO was a better parameter in predicting CVD risk by ROC curve analysis. The ROC curve analysis also showed that although ICO-replaced IDF and IDF had the higher degree of specificity, lower sensitivity, longer ROC curve distance, less area under the curve to identify CVD than ATPIII and ICO-replaced ATPIII, therefore ICO-replaced IDF and IDF seemed to be undesirable. However, there was no significant difference in area under the curve between ATPIII and ICO-replaced ATPIII in predicting CVD risk. But it seems that odds ratios for abnormal triglyceride and high-density lipoprotein levels increase slightly when using ICO, but decrease for hyperglycemia and hypertension when using ICO. ICO was a better predictor of abnormal triglyceride and high-density lipoprotein levels than waist circumference, but waist circumference was a better predictor of hyperglycemia and hypertension than ICO. However, we failed to support ICO as a better parameter for metabolic syndrome definition in predicting CVD risk compared with waist circumference.

  20. Ecological stability in response to warming

    Science.gov (United States)

    Fussmann, Katarina E.; Schwarzmüller, Florian; Brose, Ulrich; Jousset, Alexandre; Rall, Björn C.

    2014-03-01

    That species’ biological rates including metabolism, growth and feeding scale with temperature is well established from warming experiments. The interactive influence of these changes on population dynamics, however, remains uncertain. As a result, uncertainty about ecological stability in response under warming remains correspondingly high. In previous studies, severe consumer extinction waves in warmed microcosms were explained in terms of warming-induced destabilization of population oscillations. Here, we show that warming stabilizes predator-prey dynamics at the risk of predator extinction. Our results are based on meta-analyses of a global database of temperature effects on metabolic and feeding rates and maximum population size that includes species of different phylogenetic groups and ecosystem types. To unravel population-level consequences we parameterized a bioenergetic predator-prey model and simulated warming effects within ecological, non-evolutionary timescales. In contrast to previous studies, we find that warming stabilized population oscillations up to a threshold temperature, which is true for most of the possible parameter combinations. Beyond the threshold level, warming caused predator extinction due to starvation. Predictions were tested in a microbial predator-prey system. Together, our results indicate a major change in how we expect climate change to alter natural ecosystems: warming should increase population stability while undermining species diversity.

  1. Landscape Ecology

    DEFF Research Database (Denmark)

    Christensen, Andreas Aagaard; Brandt, Jesper; Svenningsen, Stig Roar

    2017-01-01

    pattern analysis and ecological interaction of land units. The landscape is seen as a holon: an assemblage of interrelated phenomena, both cultural and biophysical, that together form a complex whole. Enduring challenges to landscape ecology include the need to develop a systematic approach able...

  2. The association and predictive value analysis of metabolic syndrome combined with resting heart rate on cardiovascular autonomic neuropathy in the general Chinese population

    OpenAIRE

    Lu, Yu; Tang, Zi-Hui; Zeng, Fangfang; Li, Yiming; Zhou, Linuo

    2013-01-01

    Background The purpose of this study was to explore the extent of associations of cardiovascular autonomic neuropathy (CAN) with metabolic syndrome (MetS) and resting heart reate (HR), and to evaluate the predictive value of MetS combined with HR on CAN in a large sample derived from a Chinese population. Materials and methods We conducted a large-scale, population-based, cross-sectional study to explore the relationships of CAN with MetS and resting HR. This study included 2092 participants ...

  3. Cutoff Values of the Body Fat Mass and Visceral Adiposity for the Prediction of Metabolic Syndrome in a sample of Colombian University Students

    OpenAIRE

    Romero Tovar, Lorena Isabel

    2017-01-01

    Background: Visceral obesity and high body fat percentages are related to metabolic syndrome (MetS) in all ethnic groups. Based on the International Diabetes Federation (IDF) definition of MetS, the aim of the study was to explore thresholds of body fat (BF%) and the visceral fat area (VFA) for the prediction of MetS among Colombian university students. Methods: A cross-sectional study was conducted on 886 volunteers (51.9% women, mean age= 21.4 years). Weight, height, serum lipids indices, b...

  4. The Multi-factor Predictive Seis &Gis Model of Ecological, Genetical, Population Health Risk and Bio-geodynamic Processes In Geopathogenic Zones

    Science.gov (United States)

    Bondarenko, Y.

    I. Goal and Scope. Human birth rate decrease, death-rate growth and increase of mu- tagenic deviations risk take place in geopathogenic and anthropogenic hazard zones. Such zones create unfavourable conditions for reproductive process of future genera- tions. These negative trends should be considered as a protective answer of the com- plex biosocial system to the appearance of natural and anthropogenic risk factors that are unfavourable for human health. The major goals of scientific evaluation and de- crease of risk of appearance of hazardous processes on the territory of Dnipropetrovsk, along with creation of the multi-factor predictive Spirit-Energy-Information Space "SEIS" & GIS Model of ecological, genetical and population health risk in connection with dangerous bio-geodynamic processes, were: multi-factor modeling and correla- tion of natural and anthropogenic environmental changes and those of human health; determination of indicators that show the risk of destruction structures appearance on different levels of organization and functioning of the city ecosystem (geophys- ical and geochemical fields, soil, hydrosphere, atmosphere, biosphere); analysis of regularities of natural, anthropogenic, and biological rhythms' interactions. II. Meth- ods. The long spatio-temporal researches (Y. Bondarenko, 1996, 2000) have proved that the ecological, genetic and epidemiological processes are in connection with de- velopment of dangerous bio-geophysical and bio-geodynamic processes. Mathemat- ical processing of space photos, lithogeochemical and geophysical maps with use of JEIS o and ERDAS o computer systems was executed at the first stage of forma- tion of multi-layer geoinformation model "Dnipropetrovsk ARC View GIS o. The multi-factor nonlinear correlation between solar activity and cosmic ray variations, geophysical, geodynamic, geochemical, atmospheric, technological, biological, socio- economical processes and oncologic case rate frequency, general and primary

  5. Human metabolism and ecological transfer of radioactive caesium. Comparative studies of Chernobyl debris and nuclear weapons fallout, in southern Sweden and in Bryansk, Russia

    International Nuclear Information System (INIS)

    Raeaef, C.L.

    2000-05-01

    The whole-body content of radiocaesium was measured in a South Swedish urban group of people residing in the city of Lund between 1960 and 1994. The results from the survey have been analysed in order to estimate the ecological half time, T eff,eco of fallout radiocaesium, and the aggregate transfer from ground deposition to man in the region. After 1987, the biological half times, T e of 137 Cs and 40 K in man were also determined in the reference group through whole-body content measurements in combination with 24-hour urine sampling. Relationships between 24-hour urinary excretion and body burden of 137 Cs in the group together with data from the literature were then applied to urine samples collected in 1994 and 1995 from adult subjects living in the highly contaminated region of Bryansk, Russia, in order to estimate their average body burden of 137 Cs. The equivalent biological half-time for 137 Cs in females of the Lund reference group was, on average 66±3 d, which agrees with other findings, whereas the value for the males, 81±4 d, was, on average, significantly lower than what is found in the literature. This is partly explained by the elevated mean age and relatively low mean body muscle mass of the males investigated. The 137 Cs from nuclear weapons tests in the 1950s and 1960s still gave a significant contribution to the total 137 Cs levels in man during the post-Chernobyl study period (1987-1994). About 10% of the peak post-Chernobyl concentration level of 137 Cs (3.5-4 Bq/kg) in 1987, was attributed to pre-Chernobyl 137 Cs. The effective ecological half-time for 137 Cs from Chernobyl was found to be 1.8±0.2 y. The time-integrated aggregate transfer of 137 Cs from ground deposition to mean activity concentration in man was estimated to be 0.4 Bq/kg/kBq/m 2 . These values may be compared with an effective ecological half-time of 1.3 years found in the Lund reference group in the 1960s, and in time-integrated aggregate transfer factor of 4.4 Bq

  6. Weight loss predictability by plasma metabolic signatures in adults with obesity and morbid obesity of the DiOGenes study

    DEFF Research Database (Denmark)

    Stroeve, Johanna H M; Saccenti, Edoardo; Bouwman, Jildau

    2016-01-01

    parameters, NMR-based plasma metabolites, and LC-MS-based plasma lipid species. RESULTS: Maximally, 57% of the variation in weight loss success can be predicted by baseline parameters. The most powerful predictive models were obtained in subjects with morbid obesity. In these models, the metabolites most...

  7. Role of the microbiome in energy regulation and metabolism

    NARCIS (Netherlands)

    Nieuwdorp, Max; Gilijamse, Pim W.; Pai, Nikhil; Kaplan, Lee M.

    2014-01-01

    Intestinal microbes regulate metabolic function and energy balance; an altered microbial ecology is believed to contribute to the development of several metabolic diseases. Relative species abundance and metabolic characteristics of the intestinal microbiota change substantially in those who are

  8. Ecological release in White Sands lizards.

    Science.gov (United States)

    Roches, S Des; Robertson, J M; Harmon, L J; Rosenblum, E B

    2011-12-01

    Ecological opportunity is any change that allows populations to escape selection from competition and predation. After encountering ecological opportunity, populations may experience ecological release: enlarged population size, broadened resource use, and/or increased morphological variation. We identified ecological opportunity and tested for ecological release in three lizard colonists of White Sands, New Mexico (Sceloporus undulatus, Holbrookia maculata, and Aspidoscelis inornata). First, we provide evidence for ecological opportunity by demonstrating reduced species richness and abundance of potential competitors and predators at White Sands relative to nearby dark soils habitats. Second, we characterize ecological release at White Sands by demonstrating density compensation in the three White Sands lizard species and expanded resource use in White Sands S. undulatus. Contrary to predictions from ecological release models, we observed directional trait change but not increased trait variation in S. undulatus. Our results suggest that ecological opportunity and ecological release can be identified in natural populations, especially those that have recently colonized isolated ecosystems.

  9. Ecological stability in response to warming

    NARCIS (Netherlands)

    Fussmann, Katarina E.; Schwarzmueller, Florian; Brose, Ulrich; Jousset, Alexandre|info:eu-repo/dai/nl/370632656; Rall, Bjoern C.

    That species' biological rates including metabolism, growth and feeding scale with temperature is well established from warming experiments(1). The interactive influence of these changes on population dynamics, however, remains uncertain. As a result, uncertainty about ecological stability in

  10. Continuous and Dichotomous Metabolic Syndrome Definitions in Youth Predict Adult Type 2 Diabetes and Carotid Artery Intima Media Thickness: The Cardiovascular Risk in Young Finns Study.

    Science.gov (United States)

    Magnussen, Costan G; Cheriyan, Sanith; Sabin, Matthew A; Juonala, Markus; Koskinen, Juha; Thomson, Russell; Skilton, Michael R; Kähönen, Mika; Laitinen, Tomi; Taittonen, Leena; Hutri-Kähönen, Nina; Viikari, Jorma S A; Raitakari, Olli T

    2016-04-01

    To examine the utility of continuous metabolic syndrome (cMetS) scores vs a dichotomous metabolic syndrome (MetS) definition in youth to predict adult type 2 diabetes mellitus (T2DM) and carotid intima-media thickness (IMT). Participants (n = 1453) from the population-based, prospective, observational Cardiovascular Risk in Young Finns Study who were examined in youth (when aged 9-18 years) and re-examined 15-25 years later. Four cMetS scores were constructed according to procedures most often used in the literature that comprised the youth risk factor inputs of body mass index, blood pressure, glucose, insulin, high-density lipoprotein-cholesterol, and triglycerides. Adult outcomes included T2DM and high carotid IMT (≥ 90 th percentile). For a 1 SD increase in cMetS scores in youth, participants had a 30%-78% increased risk of T2DM and 12%-61% increased risk of high carotid IMT. Prediction of adult T2DM and high carotid IMT using cMetS scores in youth was essentially no different to a dichotomous MetS definition with area under the receiver-operating characteristic curve ranging from 0.54-0.60 (continuous definitions) and 0.55-0.59 (dichotomous) with 95% CIs often including 0.5, and integrated discrimination improvement from -0.2% to -0.6%. cMetS scores in youth are predictive of cardiometabolic outcomes in adulthood. However, they do not have increased predictive utility over a dichotomous definition of MetS. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Interactions between temperature and nutrients across levels of ecological organization.

    Science.gov (United States)

    Cross, Wyatt F; Hood, James M; Benstead, Jonathan P; Huryn, Alexander D; Nelson, Daniel

    2015-03-01

    Temperature and nutrient availability play key roles in controlling the pathways and rates at which energy and materials move through ecosystems. These factors have also changed dramatically on Earth over the past century as human activities have intensified. Although significant effort has been devoted to understanding the role of temperature and nutrients in isolation, less is known about how these two factors interact to influence ecological processes. Recent advances in ecological stoichiometry and metabolic ecology provide a useful framework for making progress in this area, but conceptual synthesis and review are needed to help catalyze additional research. Here, we examine known and potential interactions between temperature and nutrients from a variety of physiological, community, and ecosystem perspectives. We first review patterns at the level of the individual, focusing on four traits--growth, respiration, body size, and elemental content--that should theoretically govern how temperature and nutrients interact to influence higher levels of biological organization. We next explore the interactive effects of temperature and nutrients on populations, communities, and food webs by synthesizing information related to community size spectra, biomass distributions, and elemental composition. We use metabolic theory to make predictions about how population-level secondary production should respond to interactions between temperature and resource supply, setting up qualitative predictions about the flows of energy and materials through metazoan food webs. Last, we examine how temperature-nutrient interactions influence processes at the whole-ecosystem level, focusing on apparent vs. intrinsic activation energies of ecosystem processes, how to represent temperature-nutrient interactions in ecosystem models, and patterns with respect to nutrient uptake and organic matter decomposition. We conclude that a better understanding of interactions between temperature and

  12. Integrating ecological theories and traits in process-based modeling of macroinvertebrate community dynamics in streams.

    Science.gov (United States)

    Mondy, Cédric P; Schuwirth, Nele

    2017-06-01

    Predicting the composition and dynamics of communities is a challenging but useful task to efficiently support ecosystem management. Community ecology has developed a number of promising theories, including food webs, metabolic theory, ecological stoichiometry, and environmental filtering. Their joint implementation in a mechanistic modeling framework should help us to bring community ecology to a new level by improving its predictive abilities. One of the challenges lies in the proper consideration of model uncertainty. In this paper, we contribute to this challenging task by modeling the temporal dynamics of macroinvertebrate communities in a stream subjected to hydropeaking in Switzerland. To this end, we extended the mechanistic model Streambugs regarding flood-induced drift processes and the use of trait information to define performance filters. Model predictions without any calibration were in the right order of magnitude but did not reflect the dynamics of most of the invertebrate taxa well. Bayesian inference drastically improved the model fit. It revealed that a large share of total model output uncertainty can be attributed to observation errors, which exceeded model parameter uncertainty. Observed and simulated community-aggregated traits helped to identify and understand model deficits. The combination of different ecological theories and trait information in a single mechanistic modeling framework combined with Bayesian inference can thus help to predict responses of communities to environmental changes, which can support ecosystem management. © 2017 by the Ecological Society of America.

  13. Predictive and prognostic potential of volume-based metabolic variables obtained by a baseline18F-FDG PET/CT in breast cancer with neoadjuvant chemotherapy indication.

    Science.gov (United States)

    Garcia-Vicente, A M; Pérez-Beteta, J; Amo-Salas, M; Molina, D; Jimenez-Londoño, G A; Soriano-Castrejón, A M; Pena Pardo, F J; Martínez-González, A

    To investigate the usefulness of metabolic variables using 18 F-FDG PET/CT in the prediction of neoadjuvant chemotherapy (NC) response and the prognosis in locally advanced breast cancer (LABC). Prospective study including 67 patients with LABC, NC indication and a baseline 18 F-FDG PET/CT. After breast tumor segmentation, SUV variables (SUVmax, SUVmean and SUVpeak) and volume-based variables, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), were obtained. Tumors were grouped into molecular phenotypes, and classified as responders or non-responders after completion of NC. Disease-free status (DFs), disease-free survival (DFS), and overall survival (OS) were assessed. A univariate and multivariate analysis was performed to study the potential of all variables to predict DFs, DFS, and OS. Fourteen patients were classified as responders. Median±SD of DFS and OS was 43±15 and 46±13 months, respectively. SUV and TLG showed a significant correlation (pmetabolic variables obtained with 18 F-FDG PET/CT, unlike SUV based variables, were good predictors of both neoadjuvant chemotherapy response and prognosis. Copyright © 2017 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

  14. Kinetic Modeling of Human Hepatic Glucose Metabolism in Type 2 Diabetes Mellitus Predicts Higher Risk of Hypoglycemic Events in Rigorous Insulin Therapy*

    Science.gov (United States)

    König, Matthias; Holzhütter, Hermann-Georg

    2012-01-01

    A major problem in the insulin therapy of patients with diabetes type 2 (T2DM) is the increased occurrence of hypoglycemic events which, if left untreated, may cause confusion or fainting and in severe cases seizures, coma, and even death. To elucidate the potential contribution of the liver to hypoglycemia in T2DM we applied a detailed kinetic model of human hepatic glucose metabolism to simulate changes in glycolysis, gluconeogenesis, and glycogen metabolism induced by deviations of the hormones insulin, glucagon, and epinephrine from their normal plasma profiles. Our simulations reveal in line with experimental and clinical data from a multitude of studies in T2DM, (i) significant changes in the relative contribution of glycolysis, gluconeogenesis, and glycogen metabolism to hepatic glucose production and hepatic glucose utilization; (ii) decreased postprandial glycogen storage as well as increased glycogen depletion in overnight fasting and short term fasting; and (iii) a shift of the set point defining the switch between hepatic glucose production and hepatic glucose utilization to elevated plasma glucose levels, respectively, in T2DM relative to normal, healthy subjects. Intriguingly, our model simulations predict a restricted gluconeogenic response of the liver under impaired hormonal signals observed in T2DM, resulting in an increased risk of hypoglycemia. The inability of hepatic glucose metabolism to effectively counterbalance a decline of the blood glucose level becomes even more pronounced in case of tightly controlled insulin treatment. Given this Janus face mode of action of insulin, our model simulations underline the great potential that normalization of the plasma glucagon profile may have for the treatment of T2DM. PMID:22977253

  15. Kinetic modeling of human hepatic glucose metabolism in type 2 diabetes mellitus predicts higher risk of hypoglycemic events in rigorous insulin therapy.

    Science.gov (United States)

    König, Matthias; Holzhütter, Hermann-Georg

    2012-10-26

    A major problem in the insulin therapy of patients with diabetes type 2 (T2DM) is the increased occurrence of hypoglycemic events which, if left untreated, may cause confusion or fainting and in severe cases seizures, coma, and even death. To elucidate the potential contribution of the liver to hypoglycemia in T2DM we applied a detailed kinetic model of human hepatic glucose metabolism to simulate changes in glycolysis, gluconeogenesis, and glycogen metabolism induced by deviations of the hormones insulin, glucagon, and epinephrine from their normal plasma profiles. Our simulations reveal in line with experimental and clinical data from a multitude of studies in T2DM, (i) significant changes in the relative contribution of glycolysis, gluconeogenesis, and glycogen metabolism to hepatic glucose production and hepatic glucose utilization; (ii) decreased postprandial glycogen storage as well as increased glycogen depletion in overnight fasting and short term fasting; and (iii) a shift of the set point defining the switch between hepatic glucose production and hepatic glucose utilization to elevated plasma glucose levels, respectively, in T2DM relative to normal, healthy subjects. Intriguingly, our model simulations predict a restricted gluconeogenic response of the liver under impaired hormonal signals observed in T2DM, resulting in an increased risk of hypoglycemia. The inability of hepatic glucose metabolism to effectively counterbalance a decline of the blood glucose level becomes even more pronounced in case of tightly controlled insulin treatment. Given this Janus face mode of action of insulin, our model simulations underline the great potential that normalization of the plasma glucagon profile may have for the treatment of T2DM.

  16. Comparing the predictive abilities of different metabolic syndrome definitions for acute coronary syndrome: a case-control study in Chinese adults.

    Science.gov (United States)

    Wang, Qun; Chair, Sek Ying; Wong, Eliza Mi Ling; Li, Xiaomei; Liu, Meili; Zhang, Yulian

    2014-09-01

    Different institutions have proposed various definitions for metabolic syndrome, which is a combination of risk factors for cardiovascular diseases (CVD). This study aimed to compare the feasibilities and abilities of different metabolic syndrome definitions in predicting acute coronary syndrome (ACS) in Chinese adults. A case-control study was designed. This study recruited 162 newly diagnosed ACS patients (the case group) and 162 non-ACS patients (the control group) according to the study criteria. Metabolic syndrome definitions proposed by the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), International Diabetes Federation (IDF), American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI), Chinese Diabetes Society (CDS), and Joint Committee for Developing Chinese Guidelines on Dyslipidemia in Adults (JCDCG) were studied. After collecting demographic and clinical data, sensitivity, specificity, positive and negative predictive values (PPV, NPV), the likelihood ratio of a positive test and a negative test (LR+, LR-), odds ratios (OR), diagnostic accuracy, and the Youden index (YI) were compared. Of the 324 participants, the mean age was 59.1 ± 10.5 years, and 56.8% were males. The AHA/NHLBI and IDF definitions had better sensitivity (53.09%, 48.77%). The CDS definition was more specific (76.54%), but less sensitive (25.93%). The IDF definition performed better in PPV (53.74%), NPV (53.11%), LR+ (1.15) and LR- (0.89), OR (1.32), and diagnostic accuracy (53.4%). The IDF definition also provided optimal cutoff points with the biggest YI. The IDF definition performed better in detecting the onsets of nonfatal ACS in the northwestern Chinese population. All studied definitions were feasible in Chinese clinical settings.

  17. Human metabolism and ecological transfer of radioactive caesium. Comparative studies of Chernobyl debris and nuclear weapons fallout, in southern Sweden and in Bryansk, Russia

    Energy Technology Data Exchange (ETDEWEB)

    Raeaef, C.L

    2000-05-01

    The whole-body content of radiocaesium was measured in a South Swedish urban group of people residing in the city of Lund between 1960 and 1994. The results from the survey have been analysed in order to estimate the ecological half time, T{sub eff,eco} of fallout radiocaesium, and the aggregate transfer from ground deposition to man in the region. After 1987, the biological half times, T{sub e} of {sup 137}Cs and {sup 40}K in man were also determined in the reference group through whole-body content measurements in combination with 24-hour urine sampling. Relationships between 24-hour urinary excretion and body burden of {sup 137}Cs in the group together with data from the literature were then applied to urine samples collected in 1994 and 1995 from adult subjects living in the highly contaminated region of Bryansk, Russia, in order to estimate their average body burden of {sup 137}Cs. The equivalent biological half-time for {sup 137}Cs in females of the Lund reference group was, on average 66{+-}3 d, which agrees with other findings, whereas the value for the males, 81{+-}4 d, was, on average, significantly lower than what is found in the literature. This is partly explained by the elevated mean age and relatively low mean body muscle mass of the males investigated. The {sup 137}Cs from nuclear weapons tests in the 1950s and 1960s still gave a significant contribution to the total {sup 137}Cs levels in man during the post-Chernobyl study period (1987-1994). About 10% of the peak post-Chernobyl concentration level of {sup 137}Cs (3.5-4 Bq/kg) in 1987, was attributed to pre-Chernobyl {sup 137}Cs. The effective ecological half-time for {sup 137}Cs from Chernobyl was found to be 1.8{+-}0.2 y. The time-integrated aggregate transfer of {sup 137}Cs from ground deposition to mean activity concentration in man was estimated to be 0.4 Bq/kg/kBq/m{sup 2}. These values may be compared with an effective ecological half-time of 1.3 years found in the Lund reference group in

  18. Community Ecology

    CERN Document Server

    1988-01-01

    This book presents the proceedings of a workshop on community ecology organized at Davis, in April, 1986, sponsored by the Sloan Foundation. There have been several recent symposia on community ecology (Strong et. al., 1984, Diamond and Case, 1987) which have covered a wide range of topics. The goal of the workshop at Davis was more narrow: to explore the role of scale in developing a theoretical approach to understanding communities. There are a number of aspects of scale that enter into attempts to understand ecological communities. One of the most basic is organizational scale. Should community ecology proceed by building up from population biology? This question and its ramifications are stressed throughout the book and explored in the first chapter by Simon Levin. Notions of scale have long been important in understanding physical systems. Thus, in understanding the interactions of organisms with their physical environment, questions of scale become paramount. These more physical questions illustrate the...

  19. Ecological Impacts of the Cerro Grande Fire: Predicting Elk Movement and Distribution Patterns in Response to Vegetative Recovery through Simulation Modeling October 2005

    Energy Technology Data Exchange (ETDEWEB)

    Rupp, Susan P. [Texas Tech Univ., Lubbock, TX (United States)

    2005-10-01

    In May 2000, the Cerro Grande Fire burned approximately 17,200 ha in north-central New Mexico as the result of an escaped prescribed burn initiated by Bandelier National Monument. The interaction of large-scale fires, vegetation, and elk is an important management issue, but few studies have addressed the ecological implications of vegetative succession and landscape heterogeneity on ungulate populations following large-scale disturbance events. Primary objectives of this research were to identify elk movement pathways on local and landscape scales, to determine environmental factors that influence elk movement, and to evaluate movement and distribution patterns in relation to spatial and temporal aspects of the Cerro Grande Fire. Data collection and assimilation reflect the collaborative efforts of National Park Service, U.S. Forest Service, and Department of Energy (Los Alamos National Laboratory) personnel. Geographic positioning system (GPS) collars were used to track 54 elk over a period of 3+ years and locational data were incorporated into a multi-layered geographic information system (GIS) for analysis. Preliminary tests of GPS collar accuracy indicated a strong effect of 2D fixes on position acquisition rates (PARs) depending on time of day and season of year. Slope, aspect, elevation, and land cover type affected dilution of precision (DOP) values for both 2D and 3D fixes, although significant relationships varied from positive to negative making it difficult to delineate the mechanism behind significant responses. Two-dimensional fixes accounted for 34% of all successfully acquired locations and may affect results in which those data were used. Overall position acquisition rate was 93.3% and mean DOP values were consistently in the range of 4.0 to 6.0 leading to the conclusion collar accuracy was acceptable for modeling purposes. SAVANNA, a spatially explicit, process-oriented ecosystem model, was used to simulate successional dynamics. Inputs to the

  20. Metabolic Response on Post-therapy FDG-PET Predicts Patterns of Failure After Radiotherapy for Cervical Cancer

    International Nuclear Information System (INIS)

    Schwarz, Julie K.; Siegel, Barry A.; Dehdashti, Farrokh; Grigsby, Perry W.

    2012-01-01

    Purpose: To determine the patterns of failure in patients with cervical cancer treated with definitive radiotherapy and evaluated for metabolic response with early posttherapy 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET). Methods and Materials: The records of 238 patients with cervical cancer were reviewed. All patients were treated with a combination of external radiotherapy and intracavitary brachytherapy. Two hundred and nineteen patients (92%) received concurrent chemotherapy. All patients underwent pretreatment FDG-PET, and posttherapy FDG-PET was performed within 8–16 weeks of the completion of radiotherapy. Posttherapy FDG-PET results were categorized as complete metabolic response (CMR), partial metabolic response (PMR), and progressive disease (PD). Failure patterns were categorized as none, isolated local failure (central pelvis ± pelvic lymph nodes), distant failure, or combined local plus distant failure. Results: Of the 91 patients (38%) who had a recurrence, 22 had isolated local failures, and 69 had distant failures (49 distant failures and 20 combined local plus distant failures). Of the 173 patients with a CMR, 40 (23%) experienced treatment failure. All 25 patients with PD experienced treatment failure, which was distant in 24 patients (96%). Among the 40 patients with PMR, no failure has been observed for 14 patients (35%). Of the 26 failures within the PMR group, 15 (58%) were limited to the pelvis. Differences in the patterns of failure between the three groups (CMR, PMR, PD) were statistically significant (chi-square test; p < 0.0001). Conclusions: The majority of failures after definitive radiotherapy for cervical cancer include distant failures, even in the setting of concurrent chemotherapy. PMR within the cervix or lymph nodes is more commonly associated with isolated local recurrence.

  1. Increased Plasma Citrulline in Mice Marks Diet-Induced Obesity and May Predict the Development of the Metabolic Syndrome

    Science.gov (United States)

    Sailer, Manuela; Dahlhoff, Christoph; Giesbertz, Pieter; Eidens, Mena K.; de Wit, Nicole; Rubio-Aliaga, Isabel; Boekschoten, Mark V.; Müller, Michael; Daniel, Hannelore

    2013-01-01

    In humans, plasma amino acid concentrations of branched-chain amino acids (BCAA) and aromatic amino acids (AAA) increase in states of obesity, insulin resistance and diabetes. We here assessed whether these putative biomarkers can also be identified in two different obesity and diabetic mouse models. C57BL/6 mice with diet-induced obesity (DIO) mimic the metabolic impairments of obesity in humans characterized by hyperglycemia, hyperinsulinemia and hepatic triglyceride accumulation. Mice treated with streptozotocin (STZ) to induce insulin deficiency were used as a type 1 diabetes model. Plasma amino acid profiling of two high fat (HF) feeding trials revealed that citrulline and ornithine concentrations are elevated in obese mice, while systemic arginine bioavailability (ratio of plasma arginine to ornithine + citrulline) is reduced. In skeletal muscle, HF feeding induced a reduction of arginine levels while citrulline levels were elevated. However, arginine or citrulline remained unchanged in their key metabolic organs, intestine and kidney. Moreover, the intestinal conversion of labeled arginine to ornithine and citrulline in vitro remained unaffected by HF feeding excluding the intestine as prime site of these alterations. In liver, citrulline is mainly derived from ornithine in the urea cycle and DIO mice displayed reduced hepatic ornithine levels. Since both amino acids share an antiport mechanism for mitochondrial import and export, elevated plasma citrulline may indicate impaired hepatic amino acid handling in DIO mice. In the insulin deficient mice, plasma citrulline and ornithine levels also increased and additionally these animals displayed elevated BCAA and AAA levels like insulin resistant and diabetic patients. Therefore, type 1 diabetic mice but not DIO mice show the “diabetic fingerprint” of plasma amino acid changes observed in humans. Additionally, citrulline may serve as an early indicator of the obesity-dependent metabolic impairments. PMID

  2. Metabolomics in chemical ecology.

    Science.gov (United States)

    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

    Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

  3. Numerical ecology with R

    CERN Document Server

    Borcard, Daniel; Legendre, Pierre

    2018-01-01

    This new edition of Numerical Ecology with R guides readers through an applied exploration of the major methods of multivariate data analysis, as seen through the eyes of three ecologists. It provides a bridge between a textbook of numerical ecology and the implementation of this discipline in the R language. The book begins by examining some exploratory approaches. It proceeds logically with the construction of the key building blocks of most methods, i.e. association measures and matrices, and then submits example data to three families of approaches: clustering, ordination and canonical ordination. The last two chapters make use of these methods to explore important and contemporary issues in ecology: the analysis of spatial structures and of community diversity. The aims of methods thus range from descriptive to explanatory and predictive and encompass a wide variety of approaches that should provide readers with an extensive toolbox that can address a wide palette of questions arising in contemporary mul...

  4. Numerical ecology with r

    CERN Document Server

    Borcard, Daniel; Legendre, Pierre

    2018-01-01

    This new edition of Numerical Ecology with R guides readers through an applied exploration of the major methods of multivariate data analysis, as seen through the eyes of three ecologists. It provides a bridge between a textbook of numerical ecology and the implementation of this discipline in the R language. The book begins by examining some exploratory approaches. It proceeds logically with the construction of the key building blocks of most methods, i.e. association measures and matrices, and then submits example data to three families of approaches: clustering, ordination and canonical ordination. The last two chapters make use of these methods to explore important and contemporary issues in ecology: the analysis of spatial structures and of community diversity. The aims of methods thus range from descriptive to explanatory and predictive and encompass a wide variety of approaches that should provide readers with an extensive toolbox that can address a wide palette of questions arising in contemporary mul...

  5. Transcriptional Signatures Related to Glucose and Lipid Metabolism Predict Treatment Response to the Tumor Necrosis Factor Antagonist Infliximab in Patients with Treatment-Resistant Depression

    Science.gov (United States)

    Mehta, Divya; Raison, Charles L.; Woolwine, Bobbi J.; Haroon, Ebrahim; Binder, Elisabeth B.; Miller, Andrew H.; Felger, Jennifer C.

    2013-01-01

    The tumor necrosis factor (TNF) antagonist infliximab was recently found to reduce depressive symptoms in patients with increased baseline inflammation as reflected by a plasma C-reactive protein concentration >5mg/L. To further explore predictors and targets of response to infliximab, differential gene expression was examined in peripheral blood mononuclear cells from infliximab responders (n=13) versus non-responders (n=14) compared to placebo at baseline and 6hr, 24hr, and 2 weeks after the first infliximab infusion. Treatment response was defined as 50% reduction in depressive symptoms at any point during the 12-week trial. One-hundred-forty-eight gene transcripts were significantly associated (1.2 fold, adjusted p≤0.01) with response to infliximab and were distinct from placebo responders. Transcripts predictive of infliximab response were associated with gluconeogenesis and cholesterol transport, and were enriched in a network regulated by hepatocyte nuclear factor (HNF)4-alpha, a transcription factor involved in gluconeogenesis and cholesterol and lipid homeostasis. Of the 148 transcripts differentially expressed at baseline, 48% were significantly regulated over time in infliximab responders, including genes related to gluconeogenesis and the HNF4-alpha network, indicating that these predictive genes were responsive to infliximab. Responders also demonstrated inhibition of genes related to apoptosis through TNF signaling at 6hr and 24hr after infusion. Transcripts down-regulated in responders 2 weeks after infliximab were related to innate immune signaling and nuclear factor-kappa B. Thus, baseline transcriptional signatures reflective of alterations in glucose and lipid metabolism predicted antidepressant response to infliximab, and infliximab response involved regulation of metabolic genes and inhibition of genes related to innate immune activation. PMID:23624296

  6. Evolving ecological networks and the emergence of biodiversity patterns across temperature gradients.

    Science.gov (United States)

    Stegen, James C; Ferriere, Regis; Enquist, Brian J

    2012-03-22

    In ectothermic organisms, it is hypothesized that metabolic rates mediate influences of temperature on the ecological and evolutionary processes governing biodiversity. However, it is unclear how and to what extent the influence of temperature on metabolism scales up to shape large-scale diversity patterns. In order to clarify the roles of temperature and metabolism, new theory is needed. Here, we establish such theory and model eco-evolutionary dynamics of trophic networks along a broad temperature gradient. In the model temperature can influence, via metabolism, resource supply, consumers' vital rates and mutation rate. Mutation causes heritable variation in consumer body size, which diversifies and governs consumer function in the ecological network. The model predicts diversity to increase with temperature if resource supply is temperature-dependent, whereas temperature-dependent consumer vital rates cause diversity to decrease with increasing temperature. When combining both thermal dependencies, a unimodal temperature-diversity pattern evolves, which is reinforced by temperature-dependent mutation rate. Studying coexistence criteria for two consumers showed that these outcomes are owing to temperature effects on mutual invasibility and facilitation. Our theory shows how and why metabolism can influence diversity, generates predictions useful for understanding biodiversity gradients and represents an extendable framework that could include factors such as colonization history and niche conservatism.

  7. Making ecological models adequate

    Science.gov (United States)

    Getz, Wayne M.; Marshall, Charles R.; Carlson, Colin J.; Giuggioli, Luca; Ryan, Sadie J.; Romañach, Stephanie; Boettiger, Carl; Chamberlain, Samuel D.; Larsen, Laurel; D'Odorico, Paolo; O'Sullivan, David

    2018-01-01

    Critical evaluation of the adequacy of ecological models is urgently needed to enhance their utility in developing theory and enabling environmental managers and policymakers to make informed decisions. Poorly supported management can have detrimental, costly or irreversible impacts on the environment and society. Here, we examine common issues in ecological modelling and suggest criteria for improving modelling frameworks. An appropriate level of process description is crucial to constructing the best possible model, given the available data and understanding of ecological structures. Model details unsupported by data typically lead to over parameterisation and poor model performance. Conversely, a lack of mechanistic details may limit a model's ability to predict ecological systems’ responses to management. Ecological studies that employ models should follow a set of model adequacy assessment protocols that include: asking a series of critical questions regarding state and control variable selection, the determinacy of data, and the sensitivity and validity of analyses. We also need to improve model elaboration, refinement and coarse graining procedures to better understand the relevancy and adequacy of our models and the role they play in advancing theory, improving hind and forecasting, and enabling problem solving and management.

  8. Impact of the metabolic syndrome on the predictive values of new risk markers in the general population

    DEFF Research Database (Denmark)

    Olsen, MH; Hansen, Tine Willum; Christensen, M K

    2008-01-01

    with cardiovascular events. Therefore, we wanted to determine the influence of MetS on the predictive values of UACR, hsCRP and Nt-proBNP. On the basis of the definition of MetS by the International Diabetes Federation, a Danish population sample of 1983 apparently healthy subjects was divided into three groups: 530...

  9. Negative Affectivity Predicts Lower Quality of Life and Metabolic Control in Type 2 Diabetes Patients: A Structural Equation Modeling Approach.

    Science.gov (United States)

    Conti, Chiara; Di Francesco, Giulia; Fontanella, Lara; Carrozzino, Danilo; Patierno, Chiara; Vitacolonna, Ester; Fulcheri, Mario

    2017-01-01

    Introduction: It is essential to consider the clinical assessment of psychological aspects in patients with Diabetes Mellitus (DM), in order to prevent potentially adverse self-management care behaviors leading to diabetes-related complications, including declining levels of Quality of Life (QoL) and negative metabolic control. Purpose : In the framework of Structural Equation Modeling (SEM), the specific aim of this study is to evaluate the influence of distressed personality factors as Negative Affectivity (NA) and Social Inhibition (SI) on diabetes-related clinical variables (i.e., QoL and glycemic control). Methods: The total sample consists of a clinical sample, including 159 outpatients with Type 2 Diabetes Mellitus (T2DM), and a control group composed of 102 healthy respondents. All participants completed the following self- rating scales: The Type D Scale (DS14) and the World Health Organization QoL Scale (WHOQOLBREF). Furthermore, the participants of the clinical group were assessed for HbA1c, disease duration, and BMI. The observed covariates were BMI, gender, and disease duration, while HbA1c was considered an observed variable. Results: SEM analysis revealed significant differences between groups in regards to the latent construct of NA and the Environmental dimension of QoL. For the clinical sample, SEM showed that NA had a negative impact on both QoL dimensions and metabolic control. Conclusions: Clinical interventions aiming to improve medication adherence in patients with T2DM should include the psychological evaluation of Type D Personality traits, by focusing especially on its component of NA as a significant risk factor leading to negative health outcomes.

  10. Negative Affectivity Predicts Lower Quality of Life and Metabolic Control in Type 2 Diabetes Patients: A Structural Equation Modeling Approach

    Directory of Open Access Journals (Sweden)

    Chiara Conti

    2017-05-01

    Full Text Available Introduction: It is essential to consider the clinical assessment of psychological aspects in patients with Diabetes Mellitus (DM, in order to prevent potentially adverse self-management care behaviors leading to diabetes-related complications, including declining levels of Quality of Life (QoL and negative metabolic control.Purpose: In the framework of Structural Equation Modeling (SEM, the specific aim of this study is to evaluate the influence of distressed personality factors as Negative Affectivity (NA and Social Inhibition (SI on diabetes-related clinical variables (i.e., QoL and glycemic control.Methods: The total sample consists of a clinical sample, including 159 outpatients with Type 2 Diabetes Mellitus (T2DM, and a control group composed of 102 healthy respondents. All participants completed the following self- rating scales: The Type D Scale (DS14 and the World Health Organization QoL Scale (WHOQOLBREF. Furthermore, the participants of the clinical group were assessed for HbA1c, disease duration, and BMI. The observed covariates were BMI, gender, and disease duration, while HbA1c was considered an observed variable.Results: SEM analysis revealed significant differences between groups in regards to the latent construct of NA and the Environmental dimension of QoL. For the clinical sample, SEM showed that NA had a negative impact on both QoL dimensions and metabolic control.Conclusions: Clinical interventions aiming to improve medication adherence in patients with T2DM should include the psychological evaluation of Type D Personality traits, by focusing especially on its component of NA as a significant risk factor leading to negative health outcomes.

  11. Improving Predictions of Tree Drought Mortality in the Community Land Model Using Hydraulic Physiology Theory and its Effects on Carbon Metabolism

    Science.gov (United States)

    McNellis, B.; Hudiburg, T. W.

    2017-12-01

    Tree mortality due to drought is predicted to have increasing impacts on ecosystem structure and function during the 21st century. Models can attempt to predict which forests are most at risk from drought, but novel environments may preclude analysis that relies on past observations. The inclusion of more mechanistic detail may reduce uncertainty in predictions, but can also compound model complexity, especially in global models. The Community Land Model version 5 (CLM5), itself a component of the Community Earth System Model (CESM), has recently integrated cohort-based demography into its dynamic vegetation component and is in the process of coupling this demography to a model of plant hydraulic physiology (FATES-Hydro). Previous treatment of drought stress and plant mortality within CLM has been relatively broad, but a detailed hydraulics module represents a key step towards accurate mortality prognosis. Here, we examine the structure of FATES-Hydro with respect to two key physiological attributes: tissue osmotic potentials and embolism refilling. Specifically, we ask how FATES-Hydro captures mechanistic realism within each attribute and how much support there is within the physiological literature for its further elaboration within the model structure. Additionally, connections to broader aspects of carbon metabolism within FATES are explored to better resolve emergent consequences of drought stress on ecosystem function and tree demographics. An on-going field experiment in managed stands of Pinus ponderosa and mixed conifers is assessed for model parameterization and performance across PNW forests, with important implications for future forest management strategy.

  12. Basal Metabolic Rate of Adolescent Modern Pentathlon Athletes: Agreement between Indirect Calorimetry and Predictive Equations and the Correlation with Body Parameters

    Science.gov (United States)

    Loureiro, Luiz Lannes; Fonseca, Sidnei; Castro, Natalia Gomes Casanova de Oliveira e; dos Passos, Renata Baratta; Porto, Cristiana Pedrosa Melo; Pierucci, Anna Paola Trindade Rocha

    2015-01-01

    Purpose The accurate estimative of energy needs is crucial for an optimal physical performance among athletes and the basal metabolic rate (BMR) equations often are not well adjusted for adolescent athletes requiring the use of specific methods, such as the golden standard indirect calorimetry (IC). Therefore, we had the aim to analyse the agreement between the BMR of adolescents pentathletes measured by IC and estimated by commonly used predictive equations. Methods Twenty-eight athletes (17 males and 11 females) were evaluated for BMR, using IC and the predictive equations Harris and Benedict (HB), Cunningham (CUN), Henry and Rees (HR) and FAO/WHO/UNU (FAO). Body composition was obtained using DXA and sexual maturity data were retrieved through validated questionnaires. The correlations among anthropometric variables an IC were analysed by T-student test and ICC, while the agreement between IC and the predictive equations was analysed according to Bland and Altman and by survival-agreement plotting. Results The whole sample average BMR measured by IC was significantly different from the estimated by FAO (pBMR when compared with IC (T Test). When compared to the golden standard IC, using Bland and Altman, ICC and Survival-Agreement, the equations underestimated the energy needs of adolescent pentathlon athletes up to 300kcal/day. Therefore, they should be used with caution when estimating individual energy requirements in such populations. PMID:26569101

  13. Prediction of basal metabolic rate in overweight/obese and non-obese subjects and its relation to pulmonary function tests.

    Science.gov (United States)

    Merghani, Tarig H; Alawad, Azza O; Ibrahim, Rihab M; Abdelmoniem, Asim M

    2015-08-15

    Few studies investigated the association between basal metabolic rate (BMR) and indicators of pulmonary function. This study was conducted to estimate BMR in overweight/obese and non-obese healthy subjects using four commonly used predictive equations and to investigate its relation to the indicators of lung function tests (LFT). A cross sectional study was conducted in Tabuk University, Tabuk, Saudi Arabia. A total of 201 students (98 males and 103 females) participated in the study. Four different values of BMR were calculated for each participant using four different predictive equations (Harris-Benedict, Mifflin, FAO/WHO/UNU and Henry-Rees). A portable All-flow spirometer (Clement Clarke International, Harlow, UK) was used for measurements of LFT. Significantly higher values of spirometric indicators (p BMR values predicted with the four equations were significantly higher in the males compared to the females and among the overweight/obese compared to the non-obese subjects (p BMR values and the indicators of LFT was statistically insignificant (p > 0.05). Mean values of LFT indicators are not related to the estimated values of BMR. A practical calculation of BMR based on direct measurement of oxygen consumption is recommended to confirm the absence of this association.

  14. Ecological macroeconomics

    DEFF Research Database (Denmark)

    Røpke, Inge

    2013-01-01

    by a more theoretical debate and increased interaction between the heterodox schools of ecological economics and post-Keynesian economics. In addition, both the degrowth community and the research community organized around sustainable transitions of socio-technical systems have contributed to discussions...... on how to reconcile environmental and social concerns. Based on this broad variety of pieces in a jigsaw puzzle, a new ecological macroeconomics is emerging, but the contours are still vague. This chapter seeks to outline some of this topography and to add a few pieces of its own by highlighting the need...... to shift resources from consumption to investment and describing the role of consumer-citizens in such a change. The chapter starts by identifying the problems and challenges for an ecological macroeconomics. The next section outlines some of the shortcomings of traditional macroeconomics...

  15. Information Ecology

    DEFF Research Database (Denmark)

    Christiansen, Ellen Tove

    2006-01-01

    The paper describes a pedagogical didactical paradigm for teaching student-designers how to deal with context issues. Form/context-relationships are conceptualized as information ecologies and described as behavioral settings using a key concept developed by social psychologist R.A. Baker...... in the 1960ties, and chosen here because it integrates cultural and psychological trajectories in a theory of living settings. The pedagogical-didactical paradigm comprises three distinct information ecologies, named after their intended outcome: the problem-setting, the exploration-setting, and the fit......-setting. It is specified how context issues can be treated within each of these information ecologies. The paper concludes by discussing the outcome of applying this paradigm with respect to the student-designers’ competence as reflective practitioners....

  16. The ecological impacts of leaf drought tolerance

    OpenAIRE

    Bartlett, Megan Kathleen

    2016-01-01

    Climate change is expected to exacerbate drought for many plants, making drought tolerance a key driver of species and ecosystem responses. However, predicting responses from traits requires greater understanding of how physiological processes impact ecology. I developed new theory and methods and applied meta-analyses to characterize the ecological impacts of leaf drought tolerance. I compared the predictive ability of several traits for ecological drought tolerance and showed that the leaf ...

  17. Biomimetic in vitro oxidation of lapachol: a model to predict and analyse the in vivo phase I metabolism of bioactive compounds.

    Science.gov (United States)

    Niehues, Michael; Barros, Valéria Priscila; Emery, Flávio da Silva; Dias-Baruffi, Marcelo; Assis, Marilda das Dores; Lopes, Norberto Peporine

    2012-08-01

    The bioactive naphtoquinone lapachol was studied in vitro by a biomimetic model with Jacobsen catalyst (manganese(III) salen) and iodosylbenzene as oxidizing agent. Eleven oxidation derivatives were thus identified and two competitive oxidation pathways postulated. Similar to Mn(III) porphyrins, Jacobsen catalyst mainly induced the formation of para-naphtoquinone derivatives of lapachol, but also of two ortho-derivatives. The oxidation products were used to develop a GC-MS (SIM mode) method for the identification of potential phase I metabolites in vivo. Plasma analysis of Wistar rats orally administered with lapachol revealed two metabolites, α-lapachone and dehydro-α-lapachone. Hence, the biomimetic model with a manganese salen complex has evidenced its use as a valuable tool to predict and elucidate the in vivo phase I metabolism of lapachol and possibly also of other bioactive natural compounds. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

  18. Physiological differences between a noncontinuous and a continuous endurance training protocol in recreational runners and metabolic demand prediction.

    Science.gov (United States)

    Ali, Muhammad J; Govindasamay, Balasekaran; Kay Hiang, Hoon; Seet Gim Lee, Gerald

    2017-12-01

    This study investigated the physiological difference in recreational runners between a noncontinuous and a continuous endurance training protocol. It also aimed to determine physiological surrogate that could monitor metabolic demand of prolonged running in real-time. For data collection, a total of 18 active male recreational runners were recruited. Physiological (HR, RR, RER, Ṽ O 2 , BLa), and overall perceptual (RPE O ) responses were recorded against three designed test sessions. Session 1 included Ṽ O 2submax test to determine critical speed (CS) at anaerobic threshold (AT). Session 2 was the noncontinuous CS test until exhaustion, having 4:1 min work-to-rest ratio at CS, whereas session 3 was the continuous CS test till exhaustion. As 1-min recovery during session 2 may change fatigue behavior, it was hypothesized that it will significantly change the physiological stress and hence endurance outcomes. Results reported average time to exhaustion (TTE) was 37.33(9.8) mins for session 2 and 23.28(9.87) mins for session 3. Participants experienced relatively higher metabolic demand (BLa) 6.78(1.43) mmol.l -1 in session 3 as compared to session 2 (5.52(0.93) mmol.l -1 ). RER was observed to increase in session 3 and decrease in session 2. Student's paired t -test only reported a significant difference in TTE, ṼO 2 , RER, RPE O , and BLa at "End" between session 2 and 3. Reported difference in RPE O and %HR max at "AT" were 5 (2.2) and 89.8 (2.60)% during session 2 and 6 (2.5) and 89.8 (2.59)% during session 3, respectively. Regression analysis reported strong correlation of %HR max (adj. R-square = 0.588) with BLa than RPE O (adj. R-square = 0.541). The summary of findings suggests that decreasing RER increased TTE and reduced BLa toward "End" during session 2 which might have helped to have better endurance. The %HR max was identified to be used as a better noninvasive surrogate of endurance intensity estimator. © 2017 The Authors. Physiological

  19. Influence of Software Tool and Methodological Aspects of Total Metabolic Tumor Volume Calculation on Baseline [18F]FDG PET to Predict Survival in Hodgkin Lymphoma.

    Science.gov (United States)

    Kanoun, Salim; Tal, Ilan; Berriolo-Riedinger, Alina; Rossi, Cédric; Riedinger, Jean-Marc; Vrigneaud, Jean-Marc; Legrand, Louis; Humbert, Olivier; Casasnovas, Olivier; Brunotte, François; Cochet, Alexandre

    2015-01-01

    To investigate the respective influence of software tool and total metabolic tumor volume (TMTV0) calculation method on prognostic stratification of baseline 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography ([18F]FDG-PET) in newly diagnosed Hodgkin lymphoma (HL). 59 patients with newly diagnosed HL were retrospectively included. [18F]FDG-PET was performed before any treatment. Four sets of TMTV0 were calculated with Beth Israel (BI) software: based on an absolute threshold selecting voxel with standardized uptake value (SUV) >2.5 (TMTV02.5), applying a per-lesion threshold of 41% of the SUV max (TMTV041) and using a per-patient adapted threshold based on SUV max of the liver (>125% and >140% of SUV max of the liver background; TMTV0125 and TMTV0140). TMTV041 was also determined with commercial software for comparison of software tools. ROC curves were used to determine the optimal threshold for each TMTV0 to predict treatment failure. Median follow-up was 39 months. There was an excellent correlation between TMTV041 determined with BI and with the commercial software (r = 0.96, pfree survival (PFS) were respectively: 313 ml and 0.70, 432 ml and 0.68, 450 ml and 0.68, 330 ml and 0.68. There was no significant difference between ROC curves. High TMTV0 value was predictive of poor PFS in all methodologies: 4-years PFS was 83% vs 42% (p = 0.006) for TMTV02.5, 83% vs 41% (p = 0.003) for TMTV041, 85% vs 40% (p<0.001) for TMTV0125 and 83% vs 42% (p = 0.004) for TMTV0140. In newly diagnosed HL, baseline metabolic tumor volume values were significantly influenced by the choice of the method used for determination of volume. However, no significant differences were found in term of prognosis.

  20. Combination of baseline metabolic tumour volume and early response on PET/CT improves progression-free survival prediction in DLBCL

    Energy Technology Data Exchange (ETDEWEB)

    Mikhaeel, N.G.; Smith, Daniel [Guy' s and St Thomas' NHS Foundation Trust, Department of Clinical Oncology, London (United Kingdom); Dunn, Joel T.; Phillips, Michael; Barrington, Sally F. [King' s College London, PET Imaging Centre at St Thomas' Hospital, Division of Imaging Sciences and Biomedical Engineering, London (United Kingdom); Moeller, Henrik [King' s College London, Department of Cancer Epidemiology and Population Health, London (United Kingdom); Fields, Paul A.; Wrench, David [Guy' s and St Thomas' NHS Foundation Trust, Department of Haematology, London (United Kingdom)

    2016-07-15

    The study objectives were to assess the prognostic value of quantitative PET and to test whether combining baseline metabolic tumour burden with early PET response could improve predictive power in DLBCL. A total of 147 patients with DLBCL underwent FDG-PET/CT scans before and after two cycles of RCHOP. Quantitative parameters including metabolic tumour volume (MTV) and total lesion glycolysis (TLG) were measured, as well as the percentage change in these parameters. Cox regression analysis was used to test the relationship between progression-free survival (PFS) and the study variables. Receiver operator characteristics (ROC) analysis determined the op