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Sample records for change predict functional

  1. Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism

    PubMed Central

    Plitt, Mark; Barnes, Kelly Anne; Wallace, Gregory L.; Kenworthy, Lauren; Martin, Alex

    2015-01-01

    Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome—adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement. PMID:26627261

  2. Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism.

    PubMed

    Plitt, Mark; Barnes, Kelly Anne; Wallace, Gregory L; Kenworthy, Lauren; Martin, Alex

    2015-12-01

    Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome--adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement.

  3. Predicting climate change effects on wetland ecosystem services using species distribution modeling and plant functional traits.

    PubMed

    Moor, Helen; Hylander, Kristoffer; Norberg, Jon

    2015-01-01

    Wetlands provide multiple ecosystem services, the sustainable use of which requires knowledge of the underlying ecological mechanisms. Functional traits, particularly the community-weighted mean trait (CWMT), provide a strong link between species communities and ecosystem functioning. We here combine species distribution modeling and plant functional traits to estimate the direction of change of ecosystem processes under climate change. We model changes in CWMT values for traits relevant to three key services, focusing on the regional species pool in the Norrström area (central Sweden) and three main wetland types. Our method predicts proportional shifts toward faster growing, more productive and taller species, which tend to increase CWMT values of specific leaf area and canopy height, whereas changes in root depth vary. The predicted changes in CWMT values suggest a potential increase in flood attenuation services, a potential increase in short (but not long)-term nutrient retention, and ambiguous outcomes for carbon sequestration.

  4. Predicting effects of climate change on the composition and function of soil microbial communities

    NASA Astrophysics Data System (ADS)

    Dubinsky, E.; Brodie, E.; Myint, C.; Ackerly, D.; van Nostrand, J.; Bird, J.; Zhou, J.; Andersen, G.; Firestone, M.

    2008-12-01

    Complex soil microbial communities regulate critical ecosystem processes that will be altered by climate change. A critical step towards predicting the impacts of climate change on terrestrial ecosystems is to determine the primary controllers of soil microbial community composition and function, and subsequently evaluate climate change scenarios that alter these controllers. We surveyed complex soil bacterial and archaeal communities across a range of climatic and edaphic conditions to identify critical controllers of soil microbial community composition in the field and then tested the resulting predictions using a 2-year manipulation of precipitation and temperature using mesocosms of California annual grasslands. Community DNA extracted from field soils sampled from six different ecosystems was assayed for bacterial and archaeal communities using high-density phylogenetic microarrays as well as functional gene arrays. Correlations among the relative abundances of thousands of microbial taxa and edaphic factors such as soil moisture and nutrient content provided a basis for predicting community responses to changing soil conditions. Communities of soil bacteria and archaea were strongly structured by single environmental predictors, particularly variables related to soil water. Bacteria in the Actinomycetales and Bacilli consistently demonstrated a strong negative response to increasing soil moisture, while taxa in a greater variety of lineages responded positively to increasing soil moisture. In the climate change experiment, overall bacterial community structure was impacted significantly by total precipitation but not by plant species. Changes in soil moisture due to decreased rainfall resulted in significant and predictable alterations in community structure. Over 70% of the bacterial taxa in common with the cross-ecosystem study responded as predicted to altered precipitation, with the most conserved response from Actinobacteria. The functional consequences

  5. A global remote sensing mission to detect and predict plant functional biodiversity change

    NASA Astrophysics Data System (ADS)

    Cavender-Bares, J.; Jetz, W.; Pavlick, R.; Schimel, D.; Gamon, J. A.; Hobbie, S. E.; Townsend, P. A.

    2015-12-01

    Global biodiversity is one of the most crucial and least-observed dimensions of the earth system and increasingly important for anticipating changes to both the climate system and ecosystem services. Parallel developments in biodiversity science and remote sensing show that new satellite observations could directly provide global monitoring of one key dimension of global biodiversity, plant functional trait diversity. Remote sensing has already proven a pivotal aid to address the biodiversity data gap. Data on plant productivity, phenology, land-cover and other environmental parameters from MODIS and Landsat satellites currently serve as highly effective covariates for spatiotemporal biodiversity models. The growing functional trait paradigm in ecology, supported by the development of a global plant trait database that includes information for more than one-third of the global flora, highlights the importance of detecting functional diversity globally. Functional traits such as nutrient concentrations, characteristic growth forms and wood density drive both, how organisms respond to environmental change and the effects of organisms on ecosystems. Additionally, the ever more complete tree of life for plants, which presents a link to the shared evolutionary history of plant traits within lineages, coupled with advances in macroevolutionary models and data gap filling techniques, allows predictions of traits that cannot be directly observed. Using experimental manipulations of plant functional and phylogenetic diversity, our team is testing the extent to which we can link above and belowground measurements of biodiversity to remotely sensed optical diversity using hyperspectral data. These efforts will provide the means to fruitfully harness functional diversity data from space from the envisioned Global Biodiversity Observatory (GBO) mission. In turn, remotely sensed hyperspectral data from GBO will allow fundamental breakthroughs and resolve one of the most

  6. Understanding the structure and functioning of polar pelagic ecosystems to predict the impacts of change

    PubMed Central

    Drinkwater, K. F.; Grant, S. M.; Heymans, J. J.; Hofmann, E. E.; Hunt, G. L.; Johnston, N. M.

    2016-01-01

    The determinants of the structure, functioning and resilience of pelagic ecosystems across most of the polar regions are not well known. Improved understanding is essential for assessing the value of biodiversity and predicting the effects of change (including in biodiversity) on these ecosystems and the services they maintain. Here we focus on the trophic interactions that underpin ecosystem structure, developing comparative analyses of how polar pelagic food webs vary in relation to the environment. We highlight that there is not a singular, generic Arctic or Antarctic pelagic food web, and, although there are characteristic pathways of energy flow dominated by a small number of species, alternative routes are important for maintaining energy transfer and resilience. These more complex routes cannot, however, provide the same rate of energy flow to highest trophic-level species. Food-web structure may be similar in different regions, but the individual species that dominate mid-trophic levels vary across polar regions. The characteristics (traits) of these species are also different and these differences influence a range of food-web processes. Low functional redundancy at key trophic levels makes these ecosystems particularly sensitive to change. To develop models for projecting responses of polar ecosystems to future environmental change, we propose a conceptual framework that links the life histories of pelagic species and the structure of polar food webs. PMID:27928038

  7. Using Prediction Markets to Generate Probability Density Functions for Climate Change Risk Assessment

    NASA Astrophysics Data System (ADS)

    Boslough, M.

    2011-12-01

    Climate-related uncertainty is traditionally presented as an error bar, but it is becoming increasingly common to express it in terms of a probability density function (PDF). PDFs are a necessary component of probabilistic risk assessments, for which simple "best estimate" values are insufficient. Many groups have generated PDFs for climate sensitivity using a variety of methods. These PDFs are broadly consistent, but vary significantly in their details. One axiom of the verification and validation community is, "codes don't make predictions, people make predictions." This is a statement of the fact that subject domain experts generate results using assumptions within a range of epistemic uncertainty and interpret them according to their expert opinion. Different experts with different methods will arrive at different PDFs. For effective decision support, a single consensus PDF would be useful. We suggest that market methods can be used to aggregate an ensemble of opinions into a single distribution that expresses the consensus. Prediction markets have been shown to be highly successful at forecasting the outcome of events ranging from elections to box office returns. In prediction markets, traders can take a position on whether some future event will or will not occur. These positions are expressed as contracts that are traded in a double-action market that aggregates price, which can be interpreted as a consensus probability that the event will take place. Since climate sensitivity cannot directly be measured, it cannot be predicted. However, the changes in global mean surface temperature are a direct consequence of climate sensitivity, changes in forcing, and internal variability. Viable prediction markets require an undisputed event outcome on a specific date. Climate-related markets exist on Intrade.com, an online trading exchange. One such contract is titled "Global Temperature Anomaly for Dec 2011 to be greater than 0.65 Degrees C." Settlement is based

  8. Compositional changes upon compression of sodium azide predicted using density functional theory

    NASA Astrophysics Data System (ADS)

    Steele, Brad; Landerville, Aaron; Oleynik, Ivan

    2014-03-01

    The pressure induced phase transitions in sodium azide, which include a potential polymeric nitrogen phase transition, are investigated using evolutionary crystal structure prediction methods coupled with density functional theory calculations. Two new phases are predicted to be stable above 53 GPa that have an inequivalent ratio of sodium to nitrogen atoms as compared to sodium azide. The Raman spectrum is calculated from 0-100 GPa using these newly predicted structures, as well as the newly discovered I4/mcm phase of sodium azide. The predicted Raman spectrum is shown to give good agreement to experimental data above 30 GPa and below 15 GPa.

  9. Functional trade-offs in succulent stems predict responses to climate change in columnar cacti.

    PubMed

    Williams, David G; Hultine, Kevin R; Dettman, David L

    2014-07-01

    Columnar cacti occur naturally in many habitats and environments in the Americas but are conspicuously dominant in very dry desert regions. These majestic plants are widely regarded for their cultural, economic, and ecological value and, in many ecosystems, support highly diverse communities of pollinators, seed dispersers, and frugivores. Massive amounts of water and other resources stored in the succulent photosynthetic stems of these species confer a remarkable ability to grow and reproduce during intensely hot and dry periods. Yet many columnar cacti are potentially under severe threat from environmental global changes, including climate change and loss of habitat. Stems in columnar cacti and other cylindrical-stemmed cacti are morphologically diverse; stem volume-to-surface area ratio (V:S) across these taxa varies by almost two orders of magnitude. Intrinsic functional trade-offs are examined here across a broad range of V:S in species of columnar cacti. It is proposed that variation in photosynthetic gas exchange, growth, and response to stress is highly constrained by stem V:S, establishing a mechanistic framework for understanding the sensitivity of columnar cacti to climate change and drought. Specifically, species that develop stems with low V:S, and thus have little storage capacity, are expected to express high mass specific photosynthesis and growth rates under favourable conditions compared with species with high V:S. But the trade-off of having little storage capacity is that low V:S species are likely to be less tolerant of intense or long-duration drought compared with high V:S species. The application of stable isotope measurements of cactus spines as recorders of growth, water relations, and metabolic responses to the environment across species of columnar cacti that vary in V:S is also reviewed. Taken together, our approach provides a coherent theory and required set of observations needed for predicting the responses of columnar cacti to

  10. Predictive Models for Pulmonary Function Changes After Radiotherapy for Breast Cancer and Lymphoma

    SciTech Connect

    Sanchez-Nieto, Beatriz; Goset, Karen C.; Caviedes, Ivan; Delgado, Iris O.; Cordova, Andres

    2012-02-01

    Purpose: To propose multivariate predictive models for changes in pulmonary function tests ({Delta}PFTs) with respect to preradiotherapy (pre-RT) values in patients undergoing RT for breast cancer and lymphoma. Methods and Materials: A prospective study was designed to measure {Delta}PFTs of patients undergoing RT. Sixty-six patients were included. Spirometry, lung capacity (measured by helium dilution), and diffusing capacity of carbon monoxide tests were used to measure lung function. Two lung definitions were considered: paired lung vs. irradiated lung (IL). Correlation analysis of dosimetric parameters (mean lung dose and the percentage of lung volume receiving more than a threshold dose) and {Delta}PFTs was carried out to find the best dosimetric predictor. Chemotherapy, age, smoking, and the selected dose-volume parameter were considered as single and interaction terms in a multivariate analysis. Stability of results was checked by bootstrapping. Results: Both lung definitions proved to be similar. Modeling was carried out for IL. Acute and late damage showed the highest correlations with volumes irradiated above {approx}20 Gy (maximum R{sup 2} = 0.28) and {approx}40 Gy (maximum R{sup 2} = 0.21), respectively. RT alone induced a minor and transitory restrictive defect (p = 0.013). Doxorubicin-cyclophosphamide-paclitaxel (Taxol), when administered pre-RT, induced a late, large restrictive effect, independent of RT (p = 0.031). Bootstrap values confirmed the results. Conclusions: None of the dose-volume parameters was a perfect predictor of outcome. Thus, different predictor models for {Delta}PFTs were derived for the IL, which incorporated other nondosimetric parameters mainly through interaction terms. Late {Delta}PFTs seem to behave more serially than early ones. Large restrictive defects were demonstrated in patients pretreated with doxorubicin-cyclophosphamide-paclitaxel.

  11. Final technical report. Can microbial functional traits predict the response and resilience of decomposition to global change?

    SciTech Connect

    Allison, Steven D.

    2015-09-24

    The role of specific micro-organisms in the carbon cycle, and their responses to environmental change, are unknown in most ecosystems. This knowledge gap limits scientists’ ability to predict how important ecosystem processes, like soil carbon storage and loss, will change with climate and other environmental factors. The investigators addressed this knowledge gap by transplanting microbial communities from different environments into new environments and measuring the response of community composition and carbon cycling over time. Using state-of-the-art sequencing techniques, computational tools, and nanotechnology, the investigators showed that microbial communities on decomposing plant material shift dramatically with natural and experimentally-imposed drought. Microbial communities also shifted in response to added nitrogen, but the effects were smaller. These changes had implications for carbon cycling, with lower rates of carbon loss under drought conditions, and changes in the efficiency of decomposition with nitrogen addition. Even when transplanted into the same conditions, microbial communities from different environments remained distinct in composition and functioning for up to one year. Changes in functioning were related to differences in enzyme gene content across different microbial groups. Computational approaches developed for this project allowed the conclusions to be tested more broadly in other ecosystems, and new computer models will facilitate the prediction of microbial traits and functioning across environments. The data and models resulting from this project benefit the public by improving the ability to predict how microbial communities and carbon cycling functions respond to climate change, nutrient enrichment, and other large-scale environmental changes.

  12. Structural habitat predicts functional dispersal habitat of a large carnivore: how leopards change spots.

    PubMed

    Fattebert, Julien; Robinson, Hugh S; Balme, Guy; Slotow, Rob; Hunter, Luke

    2015-10-01

    Natal dispersal promotes inter-population linkage, and is key to spatial distribution of populations. Degradation of suitable landscape structures beyond the specific threshold of an individual's ability to disperse can therefore lead to disruption of functional landscape connectivity and impact metapopulation function. Because it ignores behavioral responses of individuals, structural connectivity is easier to assess than functional connectivity and is often used as a surrogate for landscape connectivity modeling. However using structural resource selection models as surrogate for modeling functional connectivity through dispersal could be erroneous. We tested how well a second-order resource selection function (RSF) models (structural connectivity), based on GPS telemetry data from resident adult leopard (Panthera pardus L.), could predict subadult habitat use during dispersal (functional connectivity). We created eight non-exclusive subsets of the subadult data based on differing definitions of dispersal to assess the predictive ability of our adult-based RSF model extrapolated over a broader landscape. Dispersing leopards used habitats in accordance with adult selection patterns, regardless of the definition of dispersal considered. We demonstrate that, for a wide-ranging apex carnivore, functional connectivity through natal dispersal corresponds to structural connectivity as modeled by a second-order RSF. Mapping of the adult-based habitat classes provides direct visualization of the potential linkages between populations, without the need to model paths between a priori starting and destination points. The use of such landscape scale RSFs may provide insight into predicting suitable dispersal habitat peninsulas in human-dominated landscapes where mitigation of human-wildlife conflict should be focused. We recommend the use of second-order RSFs for landscape conservation planning and propose a similar approach to the conservation of other wide-ranging large

  13. Functional network changes in hippocampal CA1 after status epilepticus predict spatial memory deficits in rats.

    PubMed

    Tyler, Anna L; Mahoney, J Matthew; Richard, Gregory R; Holmes, Gregory L; Lenck-Santini, Pierre-Pascal; Scott, Rod C

    2012-08-15

    Status epilepticus (SE) is a common neurological emergency, which has been associated with subsequent cognitive impairments. Neuronal death in hippocampal CA1 is thought to be an important mechanism of these impairments. However, it is also possible that functional interactions between surviving neurons are important. In this study we recorded in vivo single-unit activity in the CA1 hippocampal region of rats while they performed a spatial memory task. From these data we constructed functional networks describing pyramidal cell interactions. To build the networks, we used maximum entropy algorithms previously applied only to in vitro data. We show that several months following SE pyramidal neurons display excessive neuronal synchrony and less neuronal reactivation during rest compared with those in healthy controls. Both effects predict rat performance in a spatial memory task. These results provide a physiological mechanism for SE-induced cognitive impairment and highlight the importance of the systems-level perspective in investigating spatial cognition.

  14. A trait-based framework for predicting when and where microbial adaptation to climate change will affect ecosystem functioning

    USGS Publications Warehouse

    Wallenstein, Matthew D.; Hall, Edward K.

    2012-01-01

    As the earth system changes in response to human activities, a critical objective is to predict how biogeochemical process rates (e.g. nitrification, decomposition) and ecosystem function (e.g. net ecosystem productivity) will change under future conditions. A particular challenge is that the microbial communities that drive many of these processes are capable of adapting to environmental change in ways that alter ecosystem functioning. Despite evidence that microbes can adapt to temperature, precipitation regimes, and redox fluctuations, microbial communities are typically not optimally adapted to their local environment. For example, temperature optima for growth and enzyme activity are often greater than in situ temperatures in their environment. Here we discuss fundamental constraints on microbial adaptation and suggest specific environments where microbial adaptation to climate change (or lack thereof) is most likely to alter ecosystem functioning. Our framework is based on two principal assumptions. First, there are fundamental ecological trade-offs in microbial community traits that occur across environmental gradients (in time and space). These trade-offs result in shifting of microbial function (e.g. ability to take up resources at low temperature) in response to adaptation of another trait (e.g. limiting maintenance respiration at high temperature). Second, the mechanism and level of microbial community adaptation to changing environmental parameters is a function of the potential rate of change in community composition relative to the rate of environmental change. Together, this framework provides a basis for developing testable predictions about how the rate and degree of microbial adaptation to climate change will alter biogeochemical processes in aquatic and terrestrial ecosystems across the planet.

  15. Highlights, predictions, and changes.

    PubMed

    Jeang, Kuan-Teh

    2012-11-15

    Recent literature highlights at Retrovirology are described. Predictions are made regarding "hot" retrovirology research trends for the coming year based on recent journal access statistics. Changes in Retrovirology editor and the frequency of the Retrovirology Prize are announced.

  16. Pupil diameter tracks changes in control state predicted by the adaptive gain theory of locus coeruleus function.

    PubMed

    Gilzenrat, Mark S; Nieuwenhuis, Sander; Jepma, Marieke; Cohen, Jonathan D

    2010-05-01

    An important dimension of cognitive control is the adaptive regulation of the balance between exploitation (pursuing known sources of reward) and exploration (seeking new ones) in response to changes in task utility. Recent studies have suggested that the locus coeruleus-norepinephrine system may play an important role in this function and that pupil diameter can be used to index locus coeruleus activity. On the basis of this, we reasoned that pupil diameter may correlate closely with control state and associated changes in behavior. Specifically, we predicted that increases in baseline pupil diameter would be associated with decreases in task utility and disengagement from the task (exploration), whereas reduced baseline diameter (but increases in task-evoked dilations) would be associated with task engagement (exploitation). Findings in three experiments were consistent with these predictions, suggesting that pupillometry may be useful as an index of both control state and, indirectly, locus coeruleus function.

  17. Research into the Predictive Effect of TEG in the Changes of Coagulation Functions of the Patients with Traumatic Brain Hemorrhage

    PubMed Central

    Liu, Huanqiu; Li, Ji; Yu, Jinlu; Yuan, Tong

    2015-01-01

    To analyze the predictive effect of thrombelastogram (TEG) in the changes of coagulation functions of patients with traumatic brain hemorrhage, as well as to provide a practice basis for clinical guidance. 54 cases were observed from Aug. 2013–Oct. 2014. All patients received a TEG test 1d, 3d and 7d after traumatic injury. According to the statistical analysis, the comparison among the aforementioned coagulation function parameters in each group of patients, K, α and Ma all had significant differences. In the comparison between different time points in the same group, there was still a significant difference. Compared to the patients, the changes of R and K reached the lowest at 1d and the highest at 3d, but there was no significant difference between two groups at 7d. The changes of α and Ma reached its highest at 1d and the lowest at 3d after traumatic injury, but there was no significant difference at 7d. There was some difference in changes of coagulation functions between all groups. The former was more serious and the changes of coagulation functions had certain regularity, i.e., after traumatic injury, 1d showed a hypercoagulable state; 3d showed a hypocoagulable state; the coagulation functions of 7d returned to normal.

  18. Contextual Factors Predict Patterns of Change in Functioning over 10 Years Among Adolescents and Adults with Autism Spectrum Disorders

    PubMed Central

    Smith, Leann E.; Greenberg, Jan S.; Mailick, Marsha R.

    2015-01-01

    In the present study, we jointly employ and integrate variable- and person-centered approaches to identify groups of individuals with autism spectrum disorders (ASD) who have similar profiles of change over a period of 10 years across three critical domains of functioning: maladaptive behaviors, autism symptoms, and daily living skills. Two distinct developmental profiles were identified. Above and beyond demographic and individual characteristics, aspects of both the educational context (level of inclusion) and the family context (maternal positivity) were found to predict the likelihood of following a positive pattern of change. Implementing evidence-based interventions that target the school and home environments during childhood and adolescence may have lasting impacts on functioning into adulthood for individuals with ASD. PMID:26319253

  19. Predicting climate change

    SciTech Connect

    Drake, J.B.

    1995-12-31

    Few scientific topics evoke such general interests and public discussion as climate change. It is a subject that has been highly politicized. New results enter the environmental debate as evidence supporting a position. Usually the qualifiers, the background, and perspective needed to understand the result have been stripped away to form an appropriate sound bite. The attention is understandable given the importance of climate to agriculture and energy use. Fear of global warming and the greenhouse effect has been justification for reducing the use of fossil fuels and increasing use of nuclear energy and alternative energy sources. It has been suggested to avoid climate change, a return to a preindustrial level of emissions is necessary. The subject of this article is not the policy implications of greenhouse warming, or even the validity of the premise that global warming caused by the greenhouse effect is occurring. The subject is the current array of concepts and tools available to understand and predict the earth`s climate based on mathematical models of physical processes. These tools for climate simulations include some of the world`s most powerful computers, including the Intel Paragon XP/S 150 at ORNL. With these tools, the authors are attempting to predict the climate changes that may occur 100 years from now for different temperatures of the earth`s surface that will likely result from rising levels of carbon dioxide in the atmosphere.

  20. Individual differences in decision making and reward processing predict changes in cannabis use: a prospective functional magnetic resonance imaging study.

    PubMed

    Cousijn, Janna; Wiers, Reinout W; Ridderinkhof, K Richard; van den Brink, Wim; Veltman, Dick J; Porrino, Linda J; Goudriaan, Anna E

    2013-11-01

    Decision-making deficits are thought to play an important role in the development and persistence of substance use disorders. Individual differences in decision-making abilities and their underlying neurocircuitry may, therefore, constitute an important predictor for the course of substance use and the development of substance use disorders. Here, we investigate the predictive value of decision making and neural mechanisms underlying decision making for future cannabis use and problem severity in a sample of heavy cannabis users. Brain activity during a monetary decision-making task (Iowa gambling task) was compared between 32 heavy cannabis users and 41 matched non-using controls using functional magnetic resonance imaging. In addition, within the group of heavy cannabis users, associations were examined between task-related brain activations, cannabis use and cannabis use-related problems at baseline, and change in cannabis use and problem severity after a 6-month follow-up. Despite normal task performance, heavy cannabis users compared with controls showed higher activation during wins in core areas associated with decision making. Moreover, within the group of heavy cannabis users, win-related activity and activity anticipating loss outcomes in areas generally involved in executive functions predicted change in cannabis use after 6 months. These findings are consistent with previous studies and point to abnormal processing of motivational information in heavy cannabis users. A new finding is that individuals who are biased toward immediate rewards have a higher probability of increasing drug use, highlighting the importance of the relative balance between motivational processes and regulatory executive processes in the development of substance use disorders.

  1. Pons to Posterior Cingulate Functional Projections Predict Affective Processing Changes in the Elderly Following Eight Weeks of Meditation Training.

    PubMed

    Shao, Robin; Keuper, Kati; Geng, Xiujuan; Lee, Tatia M C

    2016-08-01

    Evidence indicates meditation facilitates affective regulation and reduces negative affect. It also influences resting-state functional connectivity between affective networks and the posterior cingulate (PCC)/precuneus, regions critically implicated in self-referential processing. However, no longitudinal study employing active control group has examined the effect of meditation training on affective processing, PCC/precuneus connectivity, and their association. Here, we report that eight-week meditation, but not relaxation, training 'neutralized' affective processing of positive and negative stimuli in healthy elderly participants. Additionally, meditation versus relaxation training increased the positive connectivity between the PCC/precuneus and the pons, the direction of which was largely directed from the pons to the PCC/precuneus, as revealed by dynamic causal modeling. Further, changes in connectivity between the PCC/precuneus and pons predicted changes in affective processing after meditation training. These findings indicate meditation promotes self-referential affective regulation based on increased regulatory influence of the pons on PCC/precuneus, which new affective-processing strategy is employed across both resting state and when evaluating affective stimuli. Such insights have clinical implications on interventions on elderly individuals with affective disorders.

  2. Functional magnetic resonance imaging in aging and dementia: detection of age-related cognitive changes and prediction of cognitive decline.

    PubMed

    Woodard, John L; Sugarman, Michael A

    2012-01-01

    Functional magnetic resonance imaging (fMRI) allows for dynamic observation of the neural substrates of cognitive processing, which makes it a valuable tool for studying brain changes that may occur with both normal and pathological aging. fMRI studies have revealed that older adults frequently exhibit a greater magnitude and extent activation of the blood-oxygen-level-dependent signal compared to younger adults. This additional activation may reflect compensatory recruitment associated with functional and structural deterioration of neural resources. Increased activation has also been associated with several risk factors for Alzheimer's disease (AD), including the apolipoprotein ε4 allele. Longitudinal studies have also demonstrated that fMRI may have predictive utility in determining which individuals are at the greatest risk of developing cognitive decline. This chapter will review the results of a number of task-activated fMRI studies of older adults, focusing on both healthy aging and neuropathology associated with AD. We also discuss models that account for cognitive aging processes, including the hemispheric asymmetry reduction in older adults (HAROLD) and scaffolding theory of aging and cognition (STAC) models. Finally, we discuss methodological issues commonly associated with fMRI research in older adults.

  3. Is Climate Change Predictable? Really?

    SciTech Connect

    Dannevik, W P; Rotman, D A

    2005-11-14

    This project is the first application of a completely different approach to climate modeling, in which new prognostic equations are used to directly compute the evolution of two-point correlations. This project addresses three questions that are critical for the credibility of the science base for climate prediction: (1) What is the variability spectrum at equilibrium? (2) What is the rate of relaxation when subjected to external perturbations? (3) Can variations due to natural processes be distinguished from those due to transient external forces? The technical approach starts with the evolution equation for the probability distribution function and arrives at a prognostic equation for ensemble-mean two-point correlations, bypassing the detailed weather calculation. This work will expand our basic understanding of the theoretical limits of climate prediction and stimulate new experiments to perform with conventional climate models. It will furnish statistical estimates that are inaccessible with conventional climate simulations and likely will raise important new questions about the very nature of climate change and about how (and whether) climate change can be predicted. Solid progress on such issues is vital to the credibility of the science base for climate change research and will provide policymakers evaluating tradeoffs among energy technology options and their attendant environmental and economic consequences.

  4. Predicting Changes in Macrophyte Community Structure from Functional Traits in a Freshwater Lake: A Test of Maximum Entropy Model

    PubMed Central

    Fu, Hui; Zhong, Jiayou; Yuan, Guixiang; Guo, Chunjing; Lou, Qian; Zhang, Wei; Xu, Jun; Ni, Leyi; Xie, Ping; Cao, Te

    2015-01-01

    Trait-based approaches have been widely applied to investigate how community dynamics respond to environmental gradients. In this study, we applied a series of maximum entropy (maxent) models incorporating functional traits to unravel the processes governing macrophyte community structure along water depth gradient in a freshwater lake. We sampled 42 plots and 1513 individual plants, and measured 16 functional traits and abundance of 17 macrophyte species. Study results showed that maxent model can be highly robust (99.8%) in predicting the species relative abundance of macrophytes with observed community-weighted mean (CWM) traits as the constraints, while relative low (about 30%) with CWM traits fitted from water depth gradient as the constraints. The measured traits showed notably distinct importance in predicting species abundances, with lowest for perennial growth form and highest for leaf dry mass content. For tuber and leaf nitrogen content, there were significant shifts in their effects on species relative abundance from positive in shallow water to negative in deep water. This result suggests that macrophyte species with tuber organ and greater leaf nitrogen content would become more abundant in shallow water, but would become less abundant in deep water. Our study highlights how functional traits distributed across gradients provide a robust path towards predictive community ecology. PMID:26167856

  5. Plastic changes at corticostriatal synapses predict improved motor function in a partial lesion model of Parkinson's disease.

    PubMed

    Bentea, Eduard; Moore, Cynthia; Deneyer, Lauren; Verbruggen, Lise; Churchill, Madeline J; Hood, Rebecca L; Meshul, Charles K; Massie, Ann

    2017-02-19

    In Parkinson's disease, striatal dopamine depletion leads to plastic changes at excitatory corticostriatal and thalamostriatal synapses. The functional consequences of these responses on the expression of behavioral deficits are incompletely understood. In addition, most of the information on striatal synaptic plasticity has been obtained in models with severe striatal dopamine depletion, and less is known regarding changes during early stages of striatal denervation. Using a partial model of nigral cell loss based on intranigral injection of the proteasome inhibitor lactacystin, we demonstrate ultrastructural changes at corticostriatal synapses with a 15% increase in the length and 30% increase in the area of the postsynaptic densities at corticostriatal synapses 1 week following toxin administration. This increase was positively correlated with the performance of lactacystin-lesioned mice on the rotarod task, such that mice with a greater increase in the size of the postsynaptic density performed better on the rotarod task. We therefore propose that lengthening of the postsynaptic density at corticostriatal synapses acts as a compensatory mechanism to maintain motor function under conditions of partial dopamine depletion. The ultrastructure of thalamostriatal synapses remained unchanged following lactacystin administration. Our findings provide novel insights into the mechanisms of synaptic plasticity and behavioral compensation following partial loss of substantia nigra pars compacta neurons, such as those occurring during the early stages of Parkinson's disease.

  6. Changes in pain-related beliefs, coping, and catastrophizing predict changes in pain intensity, pain interference, and psychological functioning in individuals with Myotonic Muscular Dystrophy and Facioscapulohumeral Dystrophy

    PubMed Central

    Nieto, Rubén; Raichle, Katherine A.; Jensen, Mark P.; Miró, Jordi

    2011-01-01

    Objectives The primary aim of this study was to test hypothesized associations between changes in psychological variables (i.e., pain beliefs, catastrophizing and coping strategies) and changes in pain intensity and related adjustment (i.e., pain interference and psychological functioning) in individuals with Myotonic Muscular Dystrophy (MMD) and Facioscapulohumeral Muscular Dystrophy (FSHD). Methods A sample of 107 adults with a diagnosis of MMD or FSHD, reporting pain in the past three months, completed assessments at two time-points, separated by about 24 months. Results Results showed that changes in pain-related psychological variables were significantly associated with changes in psychological functioning, pain intensity and pain interference. Specifically, increases in the belief that emotion influences pain, and catastrophizing were associated with decreases in psychological functioning. Increases in the coping strategies of asking for assistance and resting, and the increases of catastrophizing were associated with increases in pain intensity. Finally, increases in pain intensity and asking for assistance were associated with increases in pain interference. Discussion The results support the utility of the biopsychosocial model of pain for understanding pain and its impact in individuals with MMD or FSHD. These findings may inform the design and implementation of psychosocial pain treatments for people with muscular dystrophy and chronic pain. PMID:21642844

  7. Functional load and the lexicon: Evidence that syntactic category and frequency relationships in minimal lemma pairs predict the loss of phoneme contrasts in language change.

    PubMed

    Wedel, Andrew; Jackson, Scott; Kaplan, Abby

    2013-09-01

    All languages use individually meaningless, contrastive categories in combination to create distinct words. Despite their central role in communication, these "phoneme" contrasts can be lost over the course of language change. The century-old functional load hypothesis proposes that loss of a phoneme contrast will be inhibited in relation to the work that it does in distinguishing words. In a previous work we showed for the first time that a simple measure of functional load does significantly predict patterns of contrast loss within a diverse set of languages: the more minimal word pairs that a phoneme contrast distinguishes, the less likely those phonemes are to have merged over the course of language change. Here, we examine several lexical properties that are predicted to influence the uncertainty between word pairs in usage. We present evidence that (a) the lemma rather than surface-form count of minimal pairs is more predictive of merger; (b) the count of minimal lemma pairs that share a syntactic category is a stronger predictor of merger than the count of those with divergent syntactic categories, and (c) that the count of minimal lemma pairs with members of similar frequency is a stronger predictor of merger than that of those with more divergent frequencies. These findings support the broad hypothesis that properties of individual utterances influence long-term language change, and are consistent with findings suggesting that phonetic cues are modulated in response to lexical uncertainty within utterances.

  8. Sea Level Affecting Marshes Model (SLAMM) ‐ New functionality for predicting changes in distribution of submerged aquatic vegetation in response to sea level rise

    USGS Publications Warehouse

    Lee II, Henry; Reusser, Deborah A.; Frazier, Melanie R; McCoy, Lee M; Clinton, Patrick J.; Clough, Jonathan S.

    2014-01-01

    The “Sea‐Level Affecting Marshes Model” (SLAMM) is a moderate resolution model used to predict the effects of sea level rise on marsh habitats (Craft et al. 2009). SLAMM has been used extensively on both the west coast (e.g., Glick et al., 2007) and east coast (e.g., Geselbracht et al., 2011) of the United States to evaluate potential changes in the distribution and extent of tidal marsh habitats. However, a limitation of the current version of SLAMM, (Version 6.2) is that it lacks the ability to model distribution changes in seagrass habitat resulting from sea level rise. Because of the ecological importance of SAV habitats, U.S. EPA, USGS, and USDA partnered with Warren Pinnacle Consulting to enhance the SLAMM modeling software to include new functionality in order to predict changes in Zostera marina distribution within Pacific Northwest estuaries in response to sea level rise. Specifically, the objective was to develop a SAV model that used generally available GIS data and parameters that were predictive and that could be customized for other estuaries that have GIS layers of existing SAV distribution. This report describes the procedure used to develop the SAV model for the Yaquina Bay Estuary, Oregon, appends a statistical script based on the open source R software to generate a similar SAV model for other estuaries that have data layers of existing SAV, and describes how to incorporate the model coefficients from the site‐specific SAV model into SLAMM to predict the effects of sea level rise on Zostera marina distributions. To demonstrate the applicability of the R tools, we utilize them to develop model coefficients for Willapa Bay, Washington using site‐specific SAV data.

  9. Individual Differences in Executive Function and Central Coherence Predict Developmental Changes in Theory of Mind in Autism

    ERIC Educational Resources Information Center

    Pellicano, Elizabeth

    2010-01-01

    There is strong evidence to suggest that individuals with autism show atypicalities in multiple cognitive domains, including theory of mind (ToM), executive function (EF), and central coherence (CC). In this study, the longitudinal relationships among these 3 aspects of cognition in autism were investigated. Thirty-seven cognitively able children…

  10. Norepinephrine genes predict response time variability and methylphenidate-induced changes in neuropsychological function in attention deficit hyperactivity disorder.

    PubMed

    Kim, Bung-Nyun; Kim, Jae-Won; Cummins, Tarrant D R; Bellgrove, Mark A; Hawi, Ziarih; Hong, Soon-Beom; Yang, Young-Hui; Kim, Hyo-Jin; Shin, Min-Sup; Cho, Soo-Churl; Kim, Ji-Hoon; Son, Jung-Woo; Shin, Yun-Mi; Chung, Un-Sun; Han, Doug-Hyun

    2013-06-01

    Noradrenergic dysfunction may be associated with cognitive impairments in attention-deficit/hyperactivity disorder (ADHD), including increased response time variability, which has been proposed as a leading endophenotype for ADHD. The aim of this study was to examine the relationship between polymorphisms in the α-2A-adrenergic receptor (ADRA2A) and norepinephrine transporter (SLC6A2) genes and attentional performance in ADHD children before and after pharmacological treatment.One hundred one medication-naive ADHD children were included. All subjects were administered methylphenidate (MPH)-OROS for 12 weeks. The subjects underwent a computerized comprehensive attention test to measure the response time variability at baseline before MPH treatment and after 12 weeks. Additive regression analyses controlling for ADHD symptom severity, age, sex, IQ, and final dose of MPH examined the association between response time variability on the comprehensive attention test measures and allelic variations in single-nucleotide polymorphisms of the ADRA2A and SLC6A2 before and after MPH treatment.Increasing possession of an A allele at the G1287A polymorphism of SLC6A2 was significantly related to heightened response time variability at baseline in the sustained (P = 2.0 × 10) and auditory selective attention (P = 1.0 × 10) tasks. Response time variability at baseline increased additively with possession of the T allele at the DraI polymorphism of the ADRA2A gene in the auditory selective attention task (P = 2.0 × 10). After medication, increasing possession of a G allele at the MspI polymorphism of the ADRA2A gene was associated with increased MPH-related change in response time variability in the flanker task (P = 1.0 × 10).Our study suggested an association between norepinephrine gene variants and response time variability measured at baseline and after MPH treatment in children with ADHD. Our results add to a growing body of evidence, suggesting that response time

  11. Does change in hostility predict sexual recidivism?

    PubMed

    Pettersen, Cathrine; Nunes, Kevin L; Woods, Mandie; Maimone, Sacha; Hermann, Chantal A; Looman, Jan; Spape, Jessica

    2015-06-01

    The purpose of the study was to examine whether scores on a widely used measure of hostility--the Buss-Durkee Hostility Inventory (BDHI)--and change on this measure predicted sexual recidivism in a sample of 120 adult male incarcerated sexual offenders. Pre- and posttreatment scores, simple difference scores, and clinically significant change were examined. The majority of participants had functional scores on the BDHI prior to treatment. Of those who had dysfunctional pretreatment scores, the majority remained unchanged. Higher posttreatment scores on the Assault and Verbal Hostility subscales significantly predicted sexual recidivism. The remaining pre- and posttreatment scores as well as change scores and classifications did not significantly predict sexual recidivism. Our findings suggest that the Assault and Verbal Hostility subscales may be useful for predicting sexual recidivism but were not clearly consistent with the notion that the BDHI assesses a dynamic risk factor(s) for sexual recidivism. Due to a number of limitations of the current study, however, more rigorous research is needed before firm conclusions can be drawn.

  12. An iterative approach of protein function prediction

    PubMed Central

    2011-01-01

    Background Current approaches of predicting protein functions from a protein-protein interaction (PPI) dataset are based on an assumption that the available functions of the proteins (a.k.a. annotated proteins) will determine the functions of the proteins whose functions are unknown yet at the moment (a.k.a. un-annotated proteins). Therefore, the protein function prediction is a mono-directed and one-off procedure, i.e. from annotated proteins to un-annotated proteins. However, the interactions between proteins are mutual rather than static and mono-directed, although functions of some proteins are unknown for some reasons at present. That means when we use the similarity-based approach to predict functions of un-annotated proteins, the un-annotated proteins, once their functions are predicted, will affect the similarities between proteins, which in turn will affect the prediction results. In other words, the function prediction is a dynamic and mutual procedure. This dynamic feature of protein interactions, however, was not considered in the existing prediction algorithms. Results In this paper, we propose a new prediction approach that predicts protein functions iteratively. This iterative approach incorporates the dynamic and mutual features of PPI interactions, as well as the local and global semantic influence of protein functions, into the prediction. To guarantee predicting functions iteratively, we propose a new protein similarity from protein functions. We adapt new evaluation metrics to evaluate the prediction quality of our algorithm and other similar algorithms. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed approach in predicting unknown protein functions. Conclusions The iterative approach is more likely to reflect the real biological nature between proteins when predicting functions. A proper definition of protein similarity from protein functions is the key to predicting functions iteratively. The

  13. Contextual Factors Predict Patterns of Change in Functioning over 10 Years among Adolescents and Adults with Autism Spectrum Disorders

    ERIC Educational Resources Information Center

    Woodman, Ashley C.; Smith, Leann E.; Greenberg, Jan S.; Mailick, Marsha R.

    2016-01-01

    In the present study, we jointly employ and integrate variable- and person-centered approaches to identify groups of individuals with autism spectrum disorders (ASD) who have similar profiles of change over a period of 10 years across three critical domains of functioning: maladaptive behaviors, autism symptoms, and daily living skills. Two…

  14. Probabilistic Predictions of Regional Climate Change

    NASA Astrophysics Data System (ADS)

    Harris, G. R.; Sexton, D. M.; Booth, B. B.; Brown, K.; Collins, M.; Murphy, J. M.

    2009-12-01

    We present a methodology for quantifying the leading sources of uncertainty in climate change projections that allows more robust prediction of probability distribution functions (PDFs) for transient regional climate change than is possible, for example, with the multimodel ensemble in the the CMIP3 archive used for the IPCC Fourth Assessment. Uncertainty in equilibrium climate response has been systematically explored by varying uncertain parameters in the atmosphere, sea-ice and surface components in a ensemble of simulations with the third version of the Hadley Centre model coupled to a slab ocean. The ensemble is used to emulate the response for one million parameter combinations, ensuring robust prediction of the prior distributions of equilibrium response for this model. Posterior PDFs are estimated using a weighting scheme that calculates the likelihood for each model version, based upon its ability to reproduce a large set of observed seasonal-mean climate variables. Information from the CMIP3 simulations is used to assess the effect of structural uncertainty, and this is included as an additional variance in the weighting. The posterior distributions of equilibrium response are shown to be relatively robust to variation in key assumptions of the method. A time-scaling technique that maps equilibrium to transient change is then used to predict PDFs for transient regional climate change for specified emissions scenarios. The scaling uses a simple climate model (SCM), with global climate feedbacks and local response sampled from the equilibrium response, and other SCM parameters tuned to the response of other AOGCM ensembles. Use of the SCM allows efficient sampling of uncertainties not fully sampled by expensive GCM simulation, including uncertainty in aerosol radiative forcing, the rate of ocean heat uptake, and the strength of carbon-cycle feedbacks. Uncertainties arising from statistical components of the method, such as emulation or scaling, are

  15. Protein molecular function prediction by Bayesian phylogenomics.

    PubMed

    Engelhardt, Barbara E; Jordan, Michael I; Muratore, Kathryn E; Brenner, Steven E

    2005-10-01

    We present a statistical graphical model to infer specific molecular function for unannotated protein sequences using homology. Based on phylogenomic principles, SIFTER (Statistical Inference of Function Through Evolutionary Relationships) accurately predicts molecular function for members of a protein family given a reconciled phylogeny and available function annotations, even when the data are sparse or noisy. Our method produced specific and consistent molecular function predictions across 100 Pfam families in comparison to the Gene Ontology annotation database, BLAST, GOtcha, and Orthostrapper. We performed a more detailed exploration of functional predictions on the adenosine-5'-monophosphate/adenosine deaminase family and the lactate/malate dehydrogenase family, in the former case comparing the predictions against a gold standard set of published functional characterizations. Given function annotations for 3% of the proteins in the deaminase family, SIFTER achieves 96% accuracy in predicting molecular function for experimentally characterized proteins as reported in the literature. The accuracy of SIFTER on this dataset is a significant improvement over other currently available methods such as BLAST (75%), GeneQuiz (64%), GOtcha (89%), and Orthostrapper (11%). We also experimentally characterized the adenosine deaminase from Plasmodium falciparum, confirming SIFTER's prediction. The results illustrate the predictive power of exploiting a statistical model of function evolution in phylogenomic problems. A software implementation of SIFTER is available from the authors.

  16. PREDICTION OF NONLINEAR SPATIAL FUNCTIONALS. (R827257)

    EPA Science Inventory

    Spatial statistical methodology can be useful in the arena of environmental regulation. Some regulatory questions may be addressed by predicting linear functionals of the underlying signal, but other questions may require the prediction of nonlinear functionals of the signal. ...

  17. Protein Function Prediction: Problems and Pitfalls.

    PubMed

    Pearson, William R

    2015-09-03

    The characterization of new genomes based on their protein sets has been revolutionized by new sequencing technologies, but biologists seeking to exploit new sequence information are often frustrated by the challenges associated with accurately assigning biological functions to newly identified proteins. Here, we highlight some of the challenges in functional inference from sequence similarity. Investigators can improve the accuracy of function prediction by (1) being conservative about the evolutionary distance to a protein of known function; (2) considering the ambiguous meaning of "functional similarity," and (3) being aware of the limitations of annotations in functional databases. Protein function prediction does not offer "one-size-fits-all" solutions. Prediction strategies work better when the idiosyncrasies of function and functional annotation are better understood.

  18. Quality changes and predictive models of radial basis function neural networks for brined common carp (Cyprinus carpio) fillets during frozen storage.

    PubMed

    Kong, Chunli; Wang, Huiyi; Li, Dapeng; Zhang, Yuemei; Pan, Jinfeng; Zhu, Beiwei; Luo, Yongkang

    2016-06-15

    To investigate and predict quality of 2% brined common carp (Cyprinus carpio) fillets during frozen storage, free fatty acids (FFA), salt extractable protein (SEP), total sulfhydryl (SH) content, and Ca(2+)-ATPase activity were determined at 261 K, 253 K, and 245 K, respectively. There was a dramatic increase (P<0.05) in FFA and a sharp decrease (P<0.05) in SH at 261 K during the first 3 weeks. SEP decreased to 67.31% after 17 weeks at 245 K, whereas it took about 7 weeks and 13 weeks to decrease to the same extent at 261 K and 253 K, respectively. Ca(2+)-ATPase activity kept decreasing to 18.28% after 7 weeks at 261 K. Furthermore, radial basis function neural networks (RBFNNs) were developed to predict quality (FFA, SEP, SH, and Ca(2+)-ATPase activity) of brined carp fillets during frozen storage with relative errors all within ±5%. Thus, RBFNN is a promising method to predict quality of carp fillets during storage at 245-261 K.

  19. Hierarchical Ensemble Methods for Protein Function Prediction

    PubMed Central

    2014-01-01

    Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

  20. Predicting network functions with nested patterns

    NASA Astrophysics Data System (ADS)

    Ganter, Mathias; Kaltenbach, Hans-Michael; Stelling, Jörg

    2014-01-01

    Identifying suitable patterns in complex biological interaction networks helps understanding network functions and allows for predictions at the pattern level: by recognizing a known pattern, one can assign its previously established function. However, current approaches fail for previously unseen patterns, when patterns overlap and when they are embedded into a new network context. Here we show how to conceptually extend pattern-based approaches. We define metabolite patterns in metabolic networks that formalize co-occurrences of metabolites. Our probabilistic framework decodes the implicit information in the networks’ metabolite patterns to predict metabolic functions. We demonstrate the predictive power by identifying ‘indicator patterns’, for instance, for enzyme classification, by predicting directions of novel reactions and of known reactions in new network contexts, and by ranking candidate network extensions for gap filling. Beyond their use in improving genome annotations and metabolic network models, we expect that the concepts transfer to other network types.

  1. Predicting domains and rates of change in borderline personality disorder.

    PubMed

    Lenzenweger, Mark F; Clarkin, John F; Levy, Kenneth N; Yeomans, Frank E; Kernberg, Otto F

    2012-04-01

    What changes and how quickly these changes occur as a result of therapy in borderline personality disorder (BPD) is an important ongoing question. The features of BPD patients that are most predictive of rates of change in such patients remain largely unknown. Using the Cornell Personality Disorders Institute (CPDI) randomized controlled trial data, we sought to determine (a) the number and nature of broad domains underlying a large number of rate of change (slope) measures across many psychological, psychiatric, and psychosocial indexes, and (b) which baseline individual difference psychological features of the BPD patients correlated with these rate of change domains. We examined the latent structure of slope (rate of change) measures gleaned from individual growth curves for each subject, studied in multiwave perspective, on separate measures of anger, aggression, impulsivity, depression, global functioning, and social adjustment. Three broad domains of change rate could be discerned. These domains were reflected in factors that are described as (a) anger/aggression change ("aggressive dyscontrol"), (b) global functioning/social adjustment change ("social adjustment/self-acceptance"), and (c) anxiety/depression/impulsivity change ("conflict tolerance/behavioral control"). Factor scores were computed for each change domain and baseline measures of personality and psychodynamic features, selected a priori, were correlated with these factor scores. Multiple regression analyses revealed (a) baseline negative affectivity and aggression predicted the aggressive dyscontrol change domain, (b) baseline identity diffusion predicted the social adjustment/self-acceptance change domain, and (c) baseline social potency predicted the conflict tolerance/behavioral control change domain. These baseline predictors suggest potential research foci for understanding those aspects of BPD that change at comparable rates over time.

  2. Genetic Ancestry in Lung-Function Predictions

    PubMed Central

    Kumar, Rajesh; Seibold, Max A.; Aldrich, Melinda C.; Williams, L. Keoki; Reiner, Alex P.; Colangelo, Laura; Galanter, Joshua; Gignoux, Christopher; Hu, Donglei; Sen, Saunak; Choudhry, Shweta; Peterson, Edward L.; Rodriguez-Santana, Jose; Rodriguez-Cintron, William; Nalls, Michael A.; Leak, Tennille S.; O’Meara, Ellen; Meibohm, Bernd; Kritchevsky, Stephen B.; Li, Rongling; Harris, Tamara B.; Nickerson, Deborah A.; Fornage, Myriam; Enright, Paul; Ziv, Elad; Smith, Lewis J.; Liu, Kiang; Burchard, Esteban González

    2010-01-01

    BACKGROUND Self-identified race or ethnic group is used to determine normal reference standards in the prediction of pulmonary function. We conducted a study to determine whether the genetically determined percentage of African ancestry is associated with lung function and whether its use could improve predictions of lung function among persons who identified themselves as African American. METHODS We assessed the ancestry of 777 participants self-identified as African American in the Coronary Artery Risk Development in Young Adults (CARDIA) study and evaluated the relation between pulmonary function and ancestry by means of linear regression. We performed similar analyses of data for two independent cohorts of subjects identifying themselves as African American: 813 participants in the Health, Aging, and Body Composition (HABC) study and 579 participants in the Cardiovascular Health Study (CHS). We compared the fit of two types of models to lung-function measurements: models based on the covariates used in standard prediction equations and models incorporating ancestry. We also evaluated the effect of the ancestry-based models on the classification of disease severity in two asthma-study populations. RESULTS African ancestry was inversely related to forced expiratory volume in 1 second (FEV1) and forced vital capacity in the CARDIA cohort. These relations were also seen in the HABC and CHS cohorts. In predicting lung function, the ancestry-based model fit the data better than standard models. Ancestry-based models resulted in the reclassification of asthma severity (based on the percentage of the predicted FEV1) in 4 to 5% of participants. CONCLUSIONS Current predictive equations, which rely on self-identified race alone, may misestimate lung function among subjects who identify themselves as African American. Incorporating ancestry into normative equations may improve lung-function estimates and more accurately categorize disease severity. (Funded by the National

  3. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    PubMed Central

    Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

  4. Year 2 Report: Protein Function Prediction Platform

    SciTech Connect

    Zhou, C E

    2012-04-27

    Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fully automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.

  5. Behavioral Changes Predicting Temporal Changes in Perceived Popular Status

    ERIC Educational Resources Information Center

    Bowker, Julie C.; Rubin, Kenneth H.; Buskirk-Cohen, Allison; Rose-Krasnor, Linda; Booth-LaForce, Cathryn

    2010-01-01

    The primary objectives of this investigation were to determine the extent to which young adolescents are stable in high perceived popular status across the middle school transition and to examine whether changes in social behaviors predict the stability, gain, and loss of perceived popular status after the transition. The sample included 672 young…

  6. Managing distribution changes in time series prediction

    NASA Astrophysics Data System (ADS)

    Matias, J. M.; Gonzalez-Manteiga, W.; Taboada, J.; Ordonez, C.

    2006-07-01

    When a problem is modeled statistically, a single distribution model is usually postulated that is assumed to be valid for the entire space. Nonetheless, this practice may be somewhat unrealistic in certain application areas, in which the conditions of the process that generates the data may change; as far as we are aware, however, no techniques have been developed to tackle this problem.This article proposes a technique for modeling and predicting this change in time series with a view to improving estimates and predictions. The technique is applied, among other models, to the hypernormal distribution recently proposed. When tested on real data from a range of stock market indices the technique produces better results that when a single distribution model is assumed to be valid for the entire period of time studied.Moreover, when a global model is postulated, it is highly recommended to select the hypernormal distribution parameter in the same likelihood maximization process.

  7. On predicting changes in the geomagnetic field.

    USGS Publications Warehouse

    Alldredge, L.R.

    1987-01-01

    The present method of using constant secular variation rates to forecast magnetic components at a given site or to forecast spherical harmonic coefficients is known to be inaccurate. A new predictive method using trend and trigonometric functions fitted to known past values is used to extrapolate for a few years into the future. This provides an improvement over the usual linear extrapolation method. -from Author

  8. Predicting changes of reaction networks with partial kinetic information.

    PubMed

    Niehren, Joachim; Versari, Cristian; John, Mathias; Coutte, François; Jacques, Philippe

    2016-11-01

    We wish to predict changes of reaction networks with partial kinetic information that lead to target changes of their steady states. The changes may be either increases or decreases of influxes, reaction knockouts, or multiple changes of these two kinds. Our prime applications are knockout prediction tasks for metabolic and regulation networks. In a first step, we propose a formal modeling language for reaction networks with partial kinetic information. The modeling language has a graphical syntax reminiscent to Petri nets. Each reaction in a model comes with a partial description of its kinetics, based on a similarity relation on kinetic functions that we introduce. Such partial descriptions are able to model the regulation of existing metabolic networks for which precise kinetic knowledge is usually not available. In a second step, we develop prediction algorithms that can be applied to any reaction network modeled in our language. These algorithms perform qualitative reasoning based on abstract interpretation, by which the kinetic unknowns are abstracted away. Given a reaction network, abstract interpretation produces a finite domain constraint in a novel class. We show how to solve these finite domain constraints with an existing finite domain constraint solver, and how to interpret the solution sets as predictions of multiple reaction knockouts that lead to a desired change of the steady states. We have implemented the prediction algorithm and integrated it into a prediction tool. This journal article extends the two conference papers John et al. (2013) and Niehren et al. (2015) while adding a new prediction algorithm for multiple gene knockouts. An application to single gene knockout prediction for surfactin overproduction was presented in Coutte et al. (2015). It illustrates the adequacy of the model-based predictions made by our algorithm in the wet lab.

  9. Protein function prediction based on data fusion and functional interrelationship.

    PubMed

    Meng, Jun; Wekesa, Jael-Sanyanda; Shi, Guan-Li; Luan, Yu-Shi

    2016-04-01

    One of the challenging tasks of bioinformatics is to predict more accurate and confident protein functions from genomics and proteomics datasets. Computational approaches use a variety of high throughput experimental data, such as protein-protein interaction (PPI), protein sequences and phylogenetic profiles, to predict protein functions. This paper presents a method that uses transductive multi-label learning algorithm by integrating multiple data sources for classification. Multiple proteomics datasets are integrated to make inferences about functions of unknown proteins and use a directed bi-relational graph to assign labels to unannotated proteins. Our method, bi-relational graph based transductive multi-label function annotation (Bi-TMF) uses functional correlation and topological PPI network properties on both the training and testing datasets to predict protein functions through data fusion of the individual kernel result. The main purpose of our proposed method is to enhance the performance of classifier integration for protein function prediction algorithms. Experimental results demonstrate the effectiveness and efficiency of Bi-TMF on multi-sources datasets in yeast, human and mouse benchmarks. Bi-TMF outperforms other recently proposed methods.

  10. CAPE: Automatically Predicting Changes in Group Behavior

    NASA Astrophysics Data System (ADS)

    Sliva, Amy; Subrahmanian, V. S.; Martinez, Vanina; Simari, Gerardo

    There is now intense interest in the problem of forecasting what a group will do in the future. Past work [1, 2, 3] has built complex models of a group’s behavior and used this to predict what the group might do in the future. However, almost all past work assumes that the group will not change its past behavior. Whether the group is a group of investors, or a political party, or a terror group, there is much interest in when and how the group will change its behavior. In this paper, we develop an architecture and algorithms called CAPE to forecast the conditions under which a group will change its behavior. We have tested CAPE on social science data about the behaviors of seven terrorist groups and show that CAPE is highly accurate in its predictions—at least in this limited setting.

  11. Prediction of Chemical Function: Model Development and ...

    EPA Pesticide Factsheets

    The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

  12. Optimizing nondecomposable loss functions in structured prediction.

    PubMed

    Ranjbar, Mani; Lan, Tian; Wang, Yang; Robinovitch, Steven N; Li, Ze-Nian; Mori, Greg

    2013-04-01

    We develop an algorithm for structured prediction with nondecomposable performance measures. The algorithm learns parameters of Markov Random Fields (MRFs) and can be applied to multivariate performance measures. Examples include performance measures such as Fβ score (natural language processing), intersection over union (object category segmentation), Precision/Recall at k (search engines), and ROC area (binary classifiers). We attack this optimization problem by approximating the loss function with a piecewise linear function. The loss augmented inference forms a Quadratic Program (QP), which we solve using LP relaxation. We apply this approach to two tasks: object class-specific segmentation and human action retrieval from videos. We show significant improvement over baseline approaches that either use simple loss functions or simple scoring functions on the PASCAL VOC and H3D Segmentation datasets, and a nursing home action recognition dataset.

  13. Parental education predicts corticostriatal functionality in adulthood.

    PubMed

    Gianaros, Peter J; Manuck, Stephen B; Sheu, Lei K; Kuan, Dora C H; Votruba-Drzal, Elizabeth; Craig, Anna E; Hariri, Ahmad R

    2011-04-01

    Socioeconomic disadvantage experienced in early development predicts ill health in adulthood. However, the neurobiological pathways linking early disadvantage to adult health remain unclear. Lower parental education-a presumptive indicator of early socioeconomic disadvantage-predicts health-impairing adult behaviors, including tobacco and alcohol dependencies. These behaviors depend, in part, on the functionality of corticostriatal brain systems that 1) show developmental plasticity and early vulnerability, 2) process reward-related information, and 3) regulate impulsive decisions and actions. Hence, corticostriatal functionality in adulthood may covary directly with indicators of early socioeconomic disadvantage, particularly lower parental education. Here, we tested the covariation between parental education and corticostriatal activation and connectivity in 76 adults without confounding clinical syndromes. Corticostriatal activation and connectivity were assessed during the processing of stimuli signaling monetary gains (positive feedback [PF]) and losses (negative feedback). After accounting for participants' own education and other explanatory factors, lower parental education predicted reduced activation in anterior cingulate and dorsomedial prefrontal cortices during PF, along with reduced connectivity between these cortices and orbitofrontal and striatal areas implicated in reward processing and impulse regulation. In speculation, adult alterations in corticostriatal functionality may represent facets of a neurobiological endophenotype linked to socioeconomic conditions of early development.

  14. Predictable convergence in hemoglobin function has unpredictable molecular underpinnings.

    PubMed

    Natarajan, Chandrasekhar; Hoffmann, Federico G; Weber, Roy E; Fago, Angela; Witt, Christopher C; Storz, Jay F

    2016-10-21

    To investigate the predictability of genetic adaptation, we examined the molecular basis of convergence in hemoglobin function in comparisons involving 56 avian taxa that have contrasting altitudinal range limits. Convergent increases in hemoglobin-oxygen affinity were pervasive among high-altitude taxa, but few such changes were attributable to parallel amino acid substitutions at key residues. Thus, predictable changes in biochemical phenotype do not have a predictable molecular basis. Experiments involving resurrected ancestral proteins revealed that historical substitutions have context-dependent effects, indicating that possible adaptive solutions are contingent on prior history. Mutations that produce an adaptive change in one species may represent precluded possibilities in other species because of differences in genetic background.

  15. Methods for Predicting Job-Ability Requirements: I. Ability Requirements as a Function of Changes in the Characteristics of an Auditory Signal Identification Task.

    ERIC Educational Resources Information Center

    Wheaton, George R.; And Others

    The relationship between variations in an auditory signal identification task and consequent changes in the abilities related to identification performance was investigated. Characteristics of the signal identification task were manipulated by varying signal duration and signal-to-noise ratio. Subjects received a battery of reference ability tests…

  16. Predicting individual brain functional connectivity using a Bayesian hierarchical model.

    PubMed

    Dai, Tian; Guo, Ying

    2017-02-15

    Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual

  17. Neural activity predicts attitude change in cognitive dissonance.

    PubMed

    van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

    2009-11-01

    When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

  18. Genetically informed ecological niche models improve climate change predictions.

    PubMed

    Ikeda, Dana H; Max, Tamara L; Allan, Gerard J; Lau, Matthew K; Shuster, Stephen M; Whitham, Thomas G

    2017-01-01

    We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change.

  19. Protein function prediction using domain families

    PubMed Central

    2013-01-01

    Here we assessed the use of domain families for predicting the functions of whole proteins. These 'functional families' (FunFams) were derived using a protocol that combines sequence clustering with supervised cluster evaluation, relying on available high-quality Gene Ontology (GO) annotation data in the latter step. In essence, the protocol groups domain sequences belonging to the same superfamily into families based on the GO annotations of their parent proteins. An initial test based on enzyme sequences confirmed that the FunFams resemble enzyme (domain) families much better than do families produced by sequence clustering alone. For the CAFA 2011 experiment, we further associated the FunFams with GO terms probabilistically. All target proteins were first submitted to domain superfamily assignment, followed by FunFam assignment and, eventually, function assignment. The latter included an integration step for multi-domain target proteins. The CAFA results put our domain-based approach among the top ten of 31 competing groups and 56 prediction methods, confirming that it outperforms simple pairwise whole-protein sequence comparisons. PMID:23514456

  20. Executive functions predict conceptual learning of science.

    PubMed

    Rhodes, Sinéad M; Booth, Josephine N; Palmer, Lorna Elise; Blythe, Richard A; Delibegovic, Mirela; Wheate, Nial J

    2016-06-01

    We examined the relationship between executive functions and both factual and conceptual learning of science, specifically chemistry, in early adolescence. Sixty-three pupils in their second year of secondary school (aged 12-13 years) participated. Pupils completed tasks of working memory (Spatial Working Memory), inhibition (Stop-Signal), attention set-shifting (ID/ED), and planning (Stockings of Cambridge), from the CANTAB. They also participated in a chemistry teaching session, practical, and assessment on the topic of acids and alkalis designed specifically for this study. Executive function data were related to (1) the chemistry assessment which included aspects of factual and conceptual learning and (2) a recent school science exam. Correlational analyses between executive functions and both the chemistry assessment and science grades revealed that science achievements were significantly correlated with working memory. Linear regression analysis revealed that visuospatial working memory ability was predictive of chemistry performance. Interestingly, this relationship was observed solely in relation to the conceptual learning condition of the assessment highlighting the role of executive functions in understanding and applying knowledge about what is learned within science teaching.

  1. SORL1 predicts longitudinal cognitive change

    PubMed Central

    Reynolds, Chandra A.; Zavala, Catalina; Gatz, Margaret; Vie, Loryana; Johansson, Boo; Malmberg, Bo; Ingelsson, Erik; Prince, Jonathan A.; Pedersen, Nancy L.

    2013-01-01

    The gene encoding sortilin receptor 1 (SORL1) has been associated with Alzheimer’s disease risk. We examined 15 SORL1 variants and SNP-set risk scores in relation to longitudinal verbal, spatial, memory and perceptual speed performance, testing for age trends and sex-specific effects. Altogether, 1609 individuals from three population-based Swedish twin studies were assessed up to five times across 16 years. Controlling for APOE, multiple simple and sex-moderated associations were observed for spatial, episodic memory and verbal trajectories (p = 1.25E-03 to p = 4.83E-02). Five variants (rs11600875, rs753780, rs7105365, rs11820794, rs2070045) were associated across domains. Notably, in those homozygous for rs2070045 risk alleles, males demonstrated initially favorable performance but accelerating declines, while females showed overall lower performance. SNP-set risk scores predicted spatial (Card Rotations, p = 5.92E-03) and episodic memory trajectories (Thurstone Picture Memory, p = 3.34E-02), where higher risk scores benefitted men’s versus women’s performance up to age 75 but with accelerating declines. SORL1 is associated with cognitive aging, and may contribute differentially to change in men and women. PMID:23318115

  2. Predicting Cognitive Function from Clinical Measures of Physical Function and Health Status in Older Adults

    PubMed Central

    Bolandzadeh, Niousha; Kording, Konrad; Salowitz, Nicole; Davis, Jennifer C.; Hsu, Liang; Chan, Alison; Sharma, Devika; Blohm, Gunnar; Liu-Ambrose, Teresa

    2015-01-01

    Introduction Current research suggests that the neuropathology of dementia—including brain changes leading to memory impairment and cognitive decline—is evident years before the onset of this disease. Older adults with cognitive decline have reduced functional independence and quality of life, and are at greater risk for developing dementia. Therefore, identifying biomarkers that can be easily assessed within the clinical setting and predict cognitive decline is important. Early recognition of cognitive decline could promote timely implementation of preventive strategies. Methods We included 89 community-dwelling adults aged 70 years and older in our study, and collected 32 measures of physical function, health status and cognitive function at baseline. We utilized an L1–L2 regularized regression model (elastic net) to identify which of the 32 baseline measures were strongly predictive of cognitive function after one year. We built three linear regression models: 1) based on baseline cognitive function, 2) based on variables consistently selected in every cross-validation loop, and 3) a full model based on all the 32 variables. Each of these models was carefully tested with nested cross-validation. Results Our model with the six variables consistently selected in every cross-validation loop had a mean squared prediction error of 7.47. This number was smaller than that of the full model (115.33) and the model with baseline cognitive function (7.98). Our model explained 47% of the variance in cognitive function after one year. Discussion We built a parsimonious model based on a selected set of six physical function and health status measures strongly predictive of cognitive function after one year. In addition to reducing the complexity of the model without changing the model significantly, our model with the top variables improved the mean prediction error and R-squared. These six physical function and health status measures can be easily implemented in a

  3. Executive function performance and change in aging is predicted by apolipoprotein E, intensified by catechol-O-methyltransferase and brain-derived neurotrophic factor, and moderated by age and lifestyle.

    PubMed

    Sapkota, Shraddha; Bäckman, Lars; Dixon, Roger A

    2017-01-03

    Recent studies have reported several genetic, health, and aging interaction effects in predicting cognitive performance and change. We used an accelerated longitudinal design to examine interactions among genetic, lifestyle, and aging for executive function (EF) in non-demented older adults (n = 634; age range = 53-95 years). The polymorphisms were apolipoprotein E (APOE), catechol-O-methyltransferase (COMT), and brain-derived neurotrophic factor (BDNF). We tested (1) independent and additive effects of APOE, COMT, and BDNF and (2) APOE effect modification for COMT + BDNF, on EF performance and 9-year change as separated by age and lifestyle activities. First, APOE ε4+ carriers had poorer EF performance and steeper 9-year decline. Second, APOE ε4+ carriers with (1) BDNF Met/Met genotype and (2) increasing allelic risk in the COMT + BDNF risk panel had poorer EF performance; these effects were moderated by lifestyle activities (composite of everyday social, physical, and cognitive activities). Examining APOE effect modification for COMT + BDNF risk panel effects with other moderating factors may help identify complex neurobiological and genetic underpinnings of polygenic phenotypes such as EF in aging.

  4. Children in Psychodynamic Psychotherapy: Changes in Global Functioning

    ERIC Educational Resources Information Center

    Odhammar, Fredrik; Sundin, Eva C.; Jonson, Mattias; Carlberg, Gunnar

    2011-01-01

    This study was part of the Erica Process and Outcome Study. The aim was to investigate if children's global functioning improves after psychodynamic psychotherapy. Variables that may predict changes in global functioning were examined both statistically and qualitatively, for example, the child's age and gender; diagnosis and comorbidity;…

  5. Resting state functional connectivity predicts neurofeedback response

    PubMed Central

    Scheinost, Dustin; Stoica, Teodora; Wasylink, Suzanne; Gruner, Patricia; Saksa, John; Pittenger, Christopher; Hampson, Michelle

    2014-01-01

    Tailoring treatments to the specific needs and biology of individual patients—personalized medicine—requires delineation of reliable predictors of response. Unfortunately, these have been slow to emerge, especially in neuropsychiatric disorders. We have recently described a real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback protocol that can reduce contamination-related anxiety, a prominent symptom of many cases of obsessive-compulsive disorder (OCD). Individual response to this intervention is variable. Here we used patterns of brain functional connectivity, as measured by baseline resting-state fMRI (rs-fMRI), to predict improvements in contamination anxiety after neurofeedback training. Activity of a region of the orbitofrontal cortex (OFC) and anterior prefrontal cortex, Brodmann area (BA) 10, associated with contamination anxiety in each subject was measured in real time and presented as a neurofeedback signal, permitting subjects to learn to modulate this target brain region. We have previously reported both enhanced OFC/BA 10 control and improved anxiety in a group of subclinically anxious subjects after neurofeedback. Five individuals with contamination-related OCD who underwent the same protocol also showed improved clinical symptomatology. In both groups, these behavioral improvements were strongly correlated with baseline whole-brain connectivity in the OFC/BA 10, computed from rs-fMRI collected several days prior to neurofeedback training. These pilot data suggest that rs-fMRI can be used to identify individuals likely to benefit from rt-fMRI neurofeedback training to control contamination anxiety. PMID:25309375

  6. Towards predictive understanding of regional climate change

    NASA Astrophysics Data System (ADS)

    Xie, Shang-Ping; Deser, Clara; Vecchi, Gabriel A.; Collins, Matthew; Delworth, Thomas L.; Hall, Alex; Hawkins, Ed; Johnson, Nathaniel C.; Cassou, Christophe; Giannini, Alessandra; Watanabe, Masahiro

    2015-10-01

    Regional information on climate change is urgently needed but often deemed unreliable. To achieve credible regional climate projections, it is essential to understand underlying physical processes, reduce model biases and evaluate their impact on projections, and adequately account for internal variability. In the tropics, where atmospheric internal variability is small compared with the forced change, advancing our understanding of the coupling between long-term changes in upper-ocean temperature and the atmospheric circulation will help most to narrow the uncertainty. In the extratropics, relatively large internal variability introduces substantial uncertainty, while exacerbating risks associated with extreme events. Large ensemble simulations are essential to estimate the probabilistic distribution of climate change on regional scales. Regional models inherit atmospheric circulation uncertainty from global models and do not automatically solve the problem of regional climate change. We conclude that the current priority is to understand and reduce uncertainties on scales greater than 100 km to aid assessments at finer scales.

  7. Prediction technologies for assessment of climate change impacts

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Temperatures, precipitation, and weather patterns are changing, in response to increasing carbon dioxide in the atmosphere. With these relatively rapid changes, existing soil erosion prediction technologies that rely upon climate stationarity are potentially becoming less reliable. This is especiall...

  8. Reintroducing Environmental Change Drivers in Biodiversity-Ecosystem Functioning Research.

    PubMed

    De Laender, Frederik; Rohr, Jason R; Ashauer, Roman; Baird, Donald J; Berger, Uta; Eisenhauer, Nico; Grimm, Volker; Hommen, Udo; Maltby, Lorraine; Meliàn, Carlos J; Pomati, Francesco; Roessink, Ivo; Radchuk, Viktoriia; Van den Brink, Paul J

    2016-12-01

    For the past 20 years, research on biodiversity and ecosystem functioning (B-EF) has only implicitly considered the underlying role of environmental change. We illustrate that explicitly reintroducing environmental change drivers in B-EF research is needed to predict the functioning of ecosystems facing changes in biodiversity. Next we show how this reintroduction improves experimental control over community composition and structure, which helps to provide mechanistic insight on how multiple aspects of biodiversity relate to function and how biodiversity and function relate in food webs. We also highlight challenges for the proposed reintroduction and suggest analyses and experiments to better understand how random biodiversity changes, as studied by classic approaches in B-EF research, contribute to the shifts in function that follow environmental change.

  9. Pediatric brain injury: Can DTI scalars predict functional outcome?

    PubMed Central

    Xu, Duan; Mukherjee, Pratik; Barkovich, A James

    2013-01-01

    Diffusion imaging has made significant inroads into the clinical diagnosis of a variety of diseases by inferring changes in microstructure, namely cell membranes, myelin sheath and other structures that inhibit water diffusion. This review discusses recent progress in the use of diffusion parameters in predicting functional outcome. Studies in the literature using only scalar parameters from diffusion measurements, such as apparent diffusion coefficient (ADC) and fractional anisotropy (FA), are summarized. Other more complex mathematical models and post-processing uses are also discussed briefly. PMID:23288477

  10. Text Mining Improves Prediction of Protein Functional Sites

    PubMed Central

    Cohn, Judith D.; Ravikumar, Komandur E.

    2012-01-01

    We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

  11. A Prediction Model of the Capillary Pressure J-Function

    PubMed Central

    Xu, W. S.; Luo, P. Y.; Sun, L.; Lin, N.

    2016-01-01

    The capillary pressure J-function is a dimensionless measure of the capillary pressure of a fluid in a porous medium. The function was derived based on a capillary bundle model. However, the dependence of the J-function on the saturation Sw is not well understood. A prediction model for it is presented based on capillary pressure model, and the J-function prediction model is a power function instead of an exponential or polynomial function. Relative permeability is calculated with the J-function prediction model, resulting in an easier calculation and results that are more representative. PMID:27603701

  12. Functional recovery following stroke: Capturing changes in upper extremity function

    PubMed Central

    Simpson, Lisa A

    2015-01-01

    Background and Purpose Augmenting changes in recovery is core to the rehabilitation process following a stroke. Hence, it is essential that outcome measures are able to detect change as it occurs; a property known as responsiveness. This paper critically reviewed the responsiveness of functional outcome measures following stroke, specifically examining tools that captured upper extremity functional recovery. Methods A systematic search of the literature was undertaken to identify articles providing responsiveness data for three types of change (observed, detectable, important). Results Data from 68 articles for 14 upper extremity functional outcome measures were retrieved. Larger percent changes were required to be considered important when obtained through anchor-based methods (eg. based on patient opinion or comparative measure) compared to distribution methods (eg. statistical estimates). Larger percent changes were required to surpass the measurement error for patient-perceived functional measures (eg. Motor Activity Log) compared to lab-based performance measures (eg. Action Research Arm Test). The majority of rehabilitation interventions have similarly sized effects on patient-perceived upper extremity function versus lab-based upper extremity function. Conclusions The magnitude of important change or change that surpasses measurement error can vary substantially depending on the method of calculation. Rehabilitation treatments can affect patient perceptions of functional change as effectively as lab-based functional measures; however higher sample sizes may be required to account for the larger measurement error associated with patient-perceived functional measures. PMID:23077144

  13. LSD-induced entropic brain activity predicts subsequent personality change.

    PubMed

    Lebedev, A V; Kaelen, M; Lövdén, M; Nilsson, J; Feilding, A; Nutt, D J; Carhart-Harris, R L

    2016-09-01

    Personality is known to be relatively stable throughout adulthood. Nevertheless, it has been shown that major life events with high personal significance, including experiences engendered by psychedelic drugs, can have an enduring impact on some core facets of personality. In the present, balanced-order, placebo-controlled study, we investigated biological predictors of post-lysergic acid diethylamide (LSD) changes in personality. Nineteen healthy adults underwent resting state functional MRI scans under LSD (75µg, I.V.) and placebo (saline I.V.). The Revised NEO Personality Inventory (NEO-PI-R) was completed at screening and 2 weeks after LSD/placebo. Scanning sessions consisted of three 7.5-min eyes-closed resting-state scans, one of which involved music listening. A standardized preprocessing pipeline was used to extract measures of sample entropy, which characterizes the predictability of an fMRI time-series. Mixed-effects models were used to evaluate drug-induced shifts in brain entropy and their relationship with the observed increases in the personality trait openness at the 2-week follow-up. Overall, LSD had a pronounced global effect on brain entropy, increasing it in both sensory and hierarchically higher networks across multiple time scales. These shifts predicted enduring increases in trait openness. Moreover, the predictive power of the entropy increases was greatest for the music-listening scans and when "ego-dissolution" was reported during the acute experience. These results shed new light on how LSD-induced shifts in brain dynamics and concomitant subjective experience can be predictive of lasting changes in personality. Hum Brain Mapp 37:3203-3213, 2016. © 2016 Wiley Periodicals, Inc.

  14. Predicting the persistence of coastal wetlands to global change stressors

    USGS Publications Warehouse

    Guntenspergen, G.; McKee, K.; Cahoon, D.; Grace, J.; Megonigal, P.

    2006-01-01

    Despite progress toward understanding the response of coastal wetlands to increases in relative sea-level rise and an improved understanding of the effect of elevated CO2 on plant species allocation patterns, we are limited in our ability to predict the response of coastal wetlands to the effects associated with global change. Static simulations of the response of coastal wetlands to sea-level rise using LIDAR and GIS lack the biological and physical feedback mechanisms present in such systems. Evidence from current research suggests that biotic processes are likely to have a major influence on marsh vulnerability to future accelerated rates of sea-level rise and the influence of biotic processes likely varies depending on hydrogeomorphic setting and external stressors. We have initiated a new research approach using a series of controlled mesocosm and field experiments, landscape scale studies, a comparative network of brackish coastal wetland monitoring sites and a suite of predictive models that address critical questions regarding the vulnerability of coastal brackish wetland systems to global change. Specifically, this research project evaluates the interaction of sea level rise and elevated CO2 concentrations with flooding, nutrient enrichment and disturbance effects. The study is organized in a hierarchical structure that links mesocosm, field, landscape and biogeographic levels so as to provide important new information that recognizes that coastal wetland systems respond to multiple interacting drivers and feedback effects controlling wetland surface elevation, habitat stability and ecosystem function. We also present a new statistical modelling technique (Structural Equation Modelling) that synthesizes and integrates our environmental and biotic measures in a predictive framework that forecasts ecosystem change and informs managers to consider adaptive shifts in strategies for the sustainable management of coastal wetlands.

  15. Predicting Stages of Change in Battered Women

    ERIC Educational Resources Information Center

    Alexander, Pamela C.; Tracy, Allison; Radek, Megan; Koverola, Catherine

    2009-01-01

    Battered women's stages of change (SOCs) are examined in this study. First, confirmatory factor analysis and latent profile analysis were conducted on 754 battered women's responses on the Problems in Relationship Scale (Brown, 1998). Factor loadings were strong, and latent variable mixture modeling produces a two-class solution. Second,…

  16. Chromatin changes predict recurrence after radical prostatectomy

    PubMed Central

    Hveem, Tarjei S; Kleppe, Andreas; Vlatkovic, Ljiljana; Ersvær, Elin; Wæhre, Håkon; Nielsen, Birgitte; Kjær, Marte Avranden; Pradhan, Manohar; Syvertsen, Rolf Anders; Nesheim, John Arne; Liestøl, Knut; Albregtsen, Fritz; Danielsen, Håvard E

    2016-01-01

    Background: Pathological evaluations give the best prognostic markers for prostate cancer patients after radical prostatectomy, but the observer variance is substantial. These risk assessments should be supported and supplemented by objective methods for identifying patients at increased risk of recurrence. Markers of epigenetic aberrations have shown promising results in several cancer types and can be assessed by automatic analysis of chromatin organisation in tumour cell nuclei. Methods: A consecutive series of 317 prostate cancer patients treated with radical prostatectomy at a national hospital between 1987 and 2005 were followed for a median of 10 years (interquartile range, 7–14). On average three tumour block samples from each patient were included to account for tumour heterogeneity. We developed a novel marker, termed Nucleotyping, based on automatic assessment of disordered chromatin organisation, and validated its ability to predict recurrence after radical prostatectomy. Results: Nucleotyping predicted recurrence with a hazard ratio (HR) of 3.3 (95% confidence interval (CI), 2.1–5.1). With adjustment for clinical and pathological characteristics, the HR was 2.5 (95% CI, 1.5–4.1). An updated stratification into three risk groups significantly improved the concordance with patient outcome compared with a state-of-the-art risk-stratification tool (P<0.001). The prognostic impact was most evident for the patients who were high-risk by clinical and pathological characteristics and for patients with Gleason score 7. Conclusion: A novel assessment of epigenetic aberrations was capable of improving risk stratification after radical prostatectomy. PMID:27124335

  17. Platelet Serotonin Transporter Function Predicts Default-Mode Network Activity

    PubMed Central

    Kasess, Christian H.; Meyer, Bernhard M.; Hofmaier, Tina; Diers, Kersten; Bartova, Lucie; Pail, Gerald; Huf, Wolfgang; Uzelac, Zeljko; Hartinger, Beate; Kalcher, Klaudius; Perkmann, Thomas; Haslacher, Helmuth; Meyer-Lindenberg, Andreas; Kasper, Siegfried; Freissmuth, Michael; Windischberger, Christian; Willeit, Matthäus; Lanzenberger, Rupert; Esterbauer, Harald; Brocke, Burkhard; Moser, Ewald; Sitte, Harald H.; Pezawas, Lukas

    2014-01-01

    Background The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence. Methods A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (Vmax) was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA) to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD) activity and platelet Vmax. Results The present study demonstrates that increases in platelet Vmax significantly predict default-mode network (DMN) suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet Vmax is related to global DMN activation and not intrinsic DMN connectivity. Conclusion This study provides evidence that platelet Vmax predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal Vmax coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation. PMID:24667541

  18. Motion Plan Changes Predictably in Dyadic Reaching

    PubMed Central

    Burdet, Etienne

    2016-01-01

    Parents can effortlessly assist their child to walk, but the mechanism behind such physical coordination is still unknown. Studies have suggested that physical coordination is achieved by interacting humans who update their movement or motion plan in response to the partner’s behaviour. Here, we tested rigidly coupled pairs in a joint reaching task to observe such changes in the partners’ motion plans. However, the joint reaching movements were surprisingly consistent across different trials. A computational model that we developed demonstrated that the two partners had a distinct motion plan, which did not change with time. These results suggest that rigidly coupled pairs accomplish joint reaching movements by relying on a pre-programmed motion plan that is independent of the partner’s behaviour. PMID:27911938

  19. Changes in intentions, planning, and self-efficacy predict changes in behaviors: an application of latent true change modeling.

    PubMed

    Reuter, Tabea; Ziegelmann, Jochen P; Wiedemann, Amelie U; Geiser, Christian; Lippke, Sonia; Schüz, Benjamin; Schwarzer, Ralf

    2010-09-01

    Can latent true changes in intention, planning, and self-efficacy account for latent change in two health behaviors (physical activity as well as fruit and vegetable intake)? Baseline data on predictors and behaviors and corresponding follow-up data four weeks later were collected from 853 participants. Interindividual differences in change and change-change associations were analyzed using structural equation modeling. For both behaviors, similar prediction patterns were found: changes in intention and self-efficacy predicted changes in planning, which in turn corresponded to changes in behavior. This evidence confirms that change predicts change, which is an inherent precondition in behavior change theories.

  20. CombFunc: predicting protein function using heterogeneous data sources.

    PubMed

    Wass, Mark N; Barton, Geraint; Sternberg, Michael J E

    2012-07-01

    Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein sequence and structure to gene expression data. Here we present the CombFunc web server, which makes Gene Ontology (GO)-based protein function predictions. CombFunc incorporates ConFunc, our existing function prediction method, with other approaches for function prediction that use protein sequence, gene expression and protein-protein interaction data. In benchmarking on a set of 1686 proteins CombFunc obtains precision and recall of 0.71 and 0.64 respectively for gene ontology molecular function terms. For biological process GO terms precision of 0.74 and recall of 0.41 is obtained. CombFunc is available at http://www.sbg.bio.ic.ac.uk/combfunc.

  1. CombFunc: predicting protein function using heterogeneous data sources

    PubMed Central

    Wass, Mark N.; Barton, Geraint; Sternberg, Michael J. E.

    2012-01-01

    Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein sequence and structure to gene expression data. Here we present the CombFunc web server, which makes Gene Ontology (GO)-based protein function predictions. CombFunc incorporates ConFunc, our existing function prediction method, with other approaches for function prediction that use protein sequence, gene expression and protein–protein interaction data. In benchmarking on a set of 1686 proteins CombFunc obtains precision and recall of 0.71 and 0.64 respectively for gene ontology molecular function terms. For biological process GO terms precision of 0.74 and recall of 0.41 is obtained. CombFunc is available at http://www.sbg.bio.ic.ac.uk/combfunc. PMID:22641853

  2. Which Working Memory Functions Predict Intelligence?

    ERIC Educational Resources Information Center

    Oberauer, Klaus; Sub, Heinz-Martin; Wilhelm, Oliver; Wittmann, Werner W.

    2008-01-01

    Investigates the relationship between three factors of working memory (storage and processing, relational integration, and supervision) and four factors of intelligence (reasoning, speed, memory, and creativity) using structural equation models. Relational integration predicted reasoning ability at least as well as the storage-and-processing…

  3. Predicting Semantic Changes in Abstraction in Tutor Responses to Students

    ERIC Educational Resources Information Center

    Lipschultz, Michael; Litman, Diane; Katz, Sandra; Albacete, Patricia; Jordan, Pamela

    2014-01-01

    Post-problem reflective tutorial dialogues between human tutors and students are examined to predict when the tutor changed the level of abstraction from the student's preceding turn (i.e., used more general terms or more specific terms); such changes correlate with learning. Prior work examined lexical changes in abstraction. In this work, we…

  4. Functional brain network efficiency predicts intelligence.

    PubMed

    Langer, Nicolas; Pedroni, Andreas; Gianotti, Lorena R R; Hänggi, Jürgen; Knoch, Daria; Jäncke, Lutz

    2012-06-01

    The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

  5. Changes in Memory Prediction Accuracy: Age and Performance Effects

    ERIC Educational Resources Information Center

    Pearman, Ann; Trujillo, Amanda

    2013-01-01

    Memory performance predictions are subjective estimates of possible memory task performance. The purpose of this study was to examine possible factors related to changes in word list performance predictions made by younger and older adults. Factors included memory self-efficacy, actual performance, and perceptions of performance. The current study…

  6. Changing Functions of the University in Britain

    ERIC Educational Resources Information Center

    Denis, Ann B.

    1973-01-01

    The changing functions of the British university, that of a service organization, a business organization, a commonweal organization and a mutual-benefit organization, has made competing demands on the resources available to higher education institutions. (Author/PG)

  7. Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP

    PubMed Central

    2010-01-01

    Background A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of proteins, and gene expression. The ability of biologists to analyze and interpret such data relies on functional annotation of the included proteins, but even in highly characterized organisms many proteins can lack the functional evidence necessary to infer their biological relevance. Results Here we have applied high confidence function predictions from our automated prediction system, PFP, to three genome sequences, Escherichia coli, Saccharomyces cerevisiae, and Plasmodium falciparum (malaria). The number of annotated genes is increased by PFP to over 90% for all of the genomes. Using the large coverage of the function annotation, we introduced the functional similarity networks which represent the functional space of the proteomes. Four different functional similarity networks are constructed for each proteome, one each by considering similarity in a single Gene Ontology (GO) category, i.e. Biological Process, Cellular Component, and Molecular Function, and another one by considering overall similarity with the funSim score. The functional similarity networks are shown to have higher modularity than the protein-protein interaction network. Moreover, the funSim score network is distinct from the single GO-score networks by showing a higher clustering degree exponent value and thus has a higher tendency to be hierarchical. In addition, examining function assignments to the protein-protein interaction network and local regions of genomes has identified numerous cases where subnetworks or local regions have functionally coherent proteins. These results will help interpreting interactions of proteins and gene orders in a genome. Several examples of both analyses are highlighted. Conclusion The analyses demonstrate that applying high confidence predictions from PFP can have a significant impact

  8. Do optimism and pessimism predict physical functioning?

    PubMed

    Brenes, Gretchen A; Rapp, Stephen R; Rejeski, W Jack; Miller, Michael E

    2002-06-01

    Dispositional optimism has been shown to be related to self-report measures of health and well-being, yet little research has examined the relationship between optimism and more objective measures of functioning. The purpose of this study was to examine the relationship between optimism and pessimism and objective physical functioning. Four hundred eighty community-dwelling older adults with knee pain completed a measure of optimism and pessimism and were observed performing four daily activities (walking, lifting an object, climbing stairs, and getting into and out of a car). Results indicated that pessimism was significantly related to performance on all four tasks (p < .001), while optimism was related to performance only on the walking task (p < .05), after controlling for demographic and health variables.

  9. Early executive function predicts reasoning development.

    PubMed

    Richland, Lindsey E; Burchinal, Margaret R

    2013-01-01

    Analogical reasoning is a core cognitive skill that distinguishes humans from all other species and contributes to general fluid intelligence, creativity, and adaptive learning capacities. Yet its origins are not well understood. In the study reported here, we analyzed large-scale longitudinal data from the Study of Early Child Care and Youth Development to test predictors of growth in analogical-reasoning skill from third grade to adolescence. Our results suggest an integrative resolution to the theoretical debate regarding contributory factors arising from smaller-scale, cross-sectional experiments on analogy development. Children with greater executive-function skills (both composite and inhibitory control) and vocabulary knowledge in early elementary school displayed higher scores on a verbal analogies task at age 15 years, even after adjusting for key covariates. We posit that knowledge is a prerequisite to analogy performance, but strong executive-functioning resources during early childhood are related to long-term gains in fundamental reasoning skills.

  10. Roommate Changes in Residence Halls: Can They Be Predicted?

    ERIC Educational Resources Information Center

    Hallisey, Jacqueline N.; Harren, Vincent A.; Caple, Richard B.

    2015-01-01

    The purpose of this study was to examine the demographic and academic variables of students involved in roommate changes to determine which variables predict who will move from a room and who will stay in a room and what alternatives to current housing arrangements are selected by those who initiate the roommate changes. [This article was…

  11. Initialized near-term regional climate change prediction

    PubMed Central

    Doblas-Reyes, F. J.; Andreu-Burillo, I.; Chikamoto, Y.; García-Serrano, J.; Guemas, V.; Kimoto, M.; Mochizuki, T.; Rodrigues, L. R. L.; van Oldenborgh, G. J.

    2013-01-01

    Climate models are seen by many to be unverifiable. However, near-term climate predictions up to 10 years into the future carried out recently with these models can be rigorously verified against observations. Near-term climate prediction is a new information tool for the climate adaptation and service communities, which often make decisions on near-term time scales, and for which the most basic information is unfortunately very scarce. The Fifth Coupled Model Intercomparison Project set of co-ordinated climate-model experiments includes a set of near-term predictions in which several modelling groups participated and whose forecast quality we illustrate here. We show that climate forecast systems have skill in predicting the Earth's temperature at regional scales over the past 50 years and illustrate the trustworthiness of their predictions. Most of the skill can be attributed to changes in atmospheric composition, but also partly to the initialization of the predictions. PMID:23591882

  12. Initialized near-term regional climate change prediction.

    PubMed

    Doblas-Reyes, F J; Andreu-Burillo, I; Chikamoto, Y; García-Serrano, J; Guemas, V; Kimoto, M; Mochizuki, T; Rodrigues, L R L; van Oldenborgh, G J

    2013-01-01

    Climate models are seen by many to be unverifiable. However, near-term climate predictions up to 10 years into the future carried out recently with these models can be rigorously verified against observations. Near-term climate prediction is a new information tool for the climate adaptation and service communities, which often make decisions on near-term time scales, and for which the most basic information is unfortunately very scarce. The Fifth Coupled Model Intercomparison Project set of co-ordinated climate-model experiments includes a set of near-term predictions in which several modelling groups participated and whose forecast quality we illustrate here. We show that climate forecast systems have skill in predicting the Earth's temperature at regional scales over the past 50 years and illustrate the trustworthiness of their predictions. Most of the skill can be attributed to changes in atmospheric composition, but also partly to the initialization of the predictions.

  13. Improving structure-based function prediction using molecular dynamics

    PubMed Central

    Glazer, Dariya S.; Radmer, Randall J.; Altman, Russ B.

    2009-01-01

    Summary The number of molecules with solved three-dimensional structure but unknown function is increasing rapidly. Particularly problematic are novel folds with little detectable similarity to molecules of known function. Experimental assays can determine the functions of such molecules, but are time-consuming and expensive. Computational approaches can identify potential functional sites; however, these approaches generally rely on single static structures and do not use information about dynamics. In fact, structural dynamics can enhance function prediction: we coupled molecular dynamics simulations with structure-based function prediction algorithms that identify Ca2+ binding sites. When applied to 11 challenging proteins, both methods showed substantial improvement in performance, revealing 22 more sites in one case and 12 more in the other, with a modest increase in apparent false positives. Thus, we show that treating molecules as dynamic entities improves the performance of structure-based function prediction methods. PMID:19604472

  14. Accurate sperm morphology assessment predicts sperm function.

    PubMed

    Abu Hassan Abu, D; Franken, D R; Hoffman, B; Henkel, R

    2012-05-01

    Sperm morphology has been associated with in vitro as well as in vivo fertilisation. The study aimed to evaluate the possible relation between the percentage of spermatozoa with normal morphology and the following sperm functional assays: (i) zona-induced acrosome reaction (ZIAR); (ii) DNA integrity; (iii) chromatin condensation; (iv) sperm apoptosis; and (v) fertilisation rates. Regression analysis was employed to calculate the association between morphology and different functional tests. Normal sperm morphology correlated significantly with the percentages of live acrosome-reacted spermatozoa in the ZIAR (r = 0.518; P < 0.0001; n = 92), DNA integrity (r = -0.515; P = 0.0018; n = 34), CMA(3) -positive spermatozoa (r = -0.745; P < 0.0001; n = 92), sperm apoptosis (r = -0.395; P = 0.0206; n = 34) and necrosis (r = -0.545; P = 0.0009; n = 34). Negative correlations existed between for the acrosome reaction, and DNA integrity, while negative associations were recorded with the percentages of CMA(3) -positive spermatozoa, apoptotic and necrotic spermatozoa. Sperm morphology is related to sperm dysfunction such as poor chromatin condensation, acrosome reaction and DNA integrity. Negative and significant correlations existed between normal sperm morphology and chromatin condensation, the percentage of spermatozoa with abnormal DNA and spermatozoa with apoptotic activity. The authors do not regard sperm morphology as the only test for the diagnosis of male fertility, but sperm morphology can serve as a valuable indicator of underlying dysfunction.

  15. Anthropocene changes in desert area: Sensitivity to climate model predictions

    NASA Astrophysics Data System (ADS)

    Mahowald, Natalie M.

    2007-09-01

    Changes in desert area due to humans have important implications from a local, regional to global level. Here I focus on the latter in order to better understand estimated changes in desert dust aerosols and the associated iron deposition into oceans. Using 17 model simulations from the World Climate Research Programme's Coupled Model Intercomparison Project phase 3 multi-model dataset and the BIOME4 equilibrium vegetation model, I estimate changes in desert dust source areas due to climate change and carbon dioxide fertilization. If I assume no carbon dioxide fertilization, the mean of the model predictions is that desert areas expand from the 1880s to the 2080s, due to increased aridity. If I allow for carbon dioxide fertilization, the desert areas become smaller. Thus better understanding carbon dioxide fertilization is important for predicting desert response to climate. There is substantial spread in the model simulation predictions for regional and global averages.

  16. Predicting brain network changes in Alzheimer's disease with link prediction algorithms.

    PubMed

    Sulaimany, Sadegh; Khansari, Mohammad; Zarrineh, Peyman; Daianu, Madelaine; Jahanshad, Neda; Thompson, Paul M; Masoudi-Nejad, Ali

    2017-03-28

    Link prediction is a promising research area for modeling various types of networks and has mainly focused on predicting missing links. Link prediction methods may be valuable for describing brain connectivity, as it changes in Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI). Here, we analyzed 3-tesla whole-brain diffusion-weighted images from 202 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) - 50 healthy controls, 72 with earlyMCI (eMCI) and 38 with lateMCI (lMCI) and 42 AD patients. We introduce a novel approach for Mixed Link Prediction (MLP) to test and define the percent of predictability of each heightened stage of dementia from its previous, less impaired stage, in the simplest case. Using well-known link prediction algorithms as the core of MLP, we propose a new approach that predicts stages of cognitive impairment by simultaneously adding and removing links in the brain networks of elderly individuals. We found that the optimal algorithm, called "Adamic and Adar", had the best fit and most accurately predicted the stages of AD from their previous stage. When compared to the other link prediction algorithms, that mainly only predict the added links, our proposed approach can more inclusively simulate the brain changes during disease by both adding and removing links of the network. Our results are also in line with computational neuroimaging and clinical findings and can be improved for better results.

  17. Dopamine neurons share common response function for reward prediction error

    PubMed Central

    Eshel, Neir; Tian, Ju; Bukwich, Michael; Uchida, Naoshige

    2016-01-01

    Dopamine neurons are thought to signal reward prediction error, or the difference between actual and predicted reward. How dopamine neurons jointly encode this information, however, remains unclear. One possibility is that different neurons specialize in different aspects of prediction error; another is that each neuron calculates prediction error in the same way. We recorded from optogenetically-identified dopamine neurons in the lateral ventral tegmental area (VTA) while mice performed classical conditioning tasks. Our tasks allowed us to determine the full prediction error functions of dopamine neurons and compare them to each other. We found striking homogeneity among individual dopamine neurons: their responses to both unexpected and expected rewards followed the same function, just scaled up or down. As a result, we could describe both individual and population responses using just two parameters. Such uniformity ensures robust information coding, allowing each dopamine neuron to contribute fully to the prediction error signal. PMID:26854803

  18. Predicting C-H/pi interactions with nonlocal density functional theory.

    PubMed

    Hooper, Joe; Cooper, Valentino R; Thonhauser, Timo; Romero, Nichols A; Zerilli, Frank; Langreth, David C

    2008-04-21

    We examine the performance of a recently developed nonlocal density functional in predicting a model noncovalent interaction, namely the weak bond between an aromatic pi system and an aliphatic C--H group. The new functional is a significant improvement over traditional density functionals, providing results which compare favorably to high-level quantum-chemistry techniques, but at considerably lower computational cost. Interaction energies in several model C--H/pi systems are in good general agreement with coupled-cluster calculations, though equilibrium distances are consistently overpredicted when using the revPBE functional for exchange. The new functional predicts changes in energy upon addition of halogen substituents correctly.

  19. Changes in Pilot Behavior with Predictive System Status Information

    NASA Technical Reports Server (NTRS)

    Trujillo, Anna C.

    1998-01-01

    Research has shown a strong pilot preference for predictive information of aircraft system status in the flight deck. However, changes in pilot behavior associated with using this predictive information have not been ascertained. The study described here quantified these changes using three types of predictive information (none, whether a parameter was changing abnormally, and the time for a parameter to reach an alert range) and three initial time intervals until a parameter alert range was reached (ITIs) (1 minute, 5 minutes, and 15 minutes). With predictive information, subjects accomplished most of their tasks before an alert occurred. Subjects organized the time they did their tasks by locus-of-control with no predictive information and for the 1-minute ITI, and by aviatenavigate-communicate for the time for a parameter to reach an alert range and the 15-minute conditions. Overall, predictive information and the longer ITIs moved subjects to performing tasks before the alert actually occurred and had them more mission oriented as indicated by their tasks grouping of aviate-navigate-communicate.

  20. A new protein structure representation for efficient protein function prediction.

    PubMed

    Maghawry, Huda A; Mostafa, Mostafa G M; Gharib, Tarek F

    2014-12-01

    One of the challenging problems in bioinformatics is the prediction of protein function. Protein function is the main key that can be used to classify different proteins. Protein function can be inferred experimentally with very small throughput or computationally with very high throughput. Computational methods are sequence based or structure based. Structure-based methods produce more accurate protein function prediction. In this article, we propose a new protein structure representation for efficient protein function prediction. The representation is based on three-dimensional patterns of protein residues. In the analysis, we used protein function based on enzyme activity through six mechanistically diverse enzyme superfamilies: amidohydrolase, crotonase, haloacid dehalogenase, isoprenoid synthase type I, and vicinal oxygen chelate. We applied three different classification methods, naïve Bayes, k-nearest neighbors, and random forest, to predict the enzyme superfamily of a given protein. The prediction accuracy using the proposed representation outperforms a recently introduced representation method that is based only on the distance patterns. The results show that the proposed representation achieved prediction accuracy up to 98%, with improvement of about 10% on average.

  1. A Statistical Model of Protein Sequence Similarity and Function Similarity Reveals Overly-Specific Function Predictions

    PubMed Central

    Kolker, Eugene

    2009-01-01

    Background Predicting protein function from primary sequence is an important open problem in modern biology. Not only are there many thousands of proteins of unknown function, current approaches for predicting function must be improved upon. One problem in particular is overly-specific function predictions which we address here with a new statistical model of the relationship between protein sequence similarity and protein function similarity. Methodology Our statistical model is based on sets of proteins with experimentally validated functions and numeric measures of function specificity and function similarity derived from the Gene Ontology. The model predicts the similarity of function between two proteins given their amino acid sequence similarity measured by statistics from the BLAST sequence alignment algorithm. A novel aspect of our model is that it predicts the degree of function similarity shared between two proteins over a continuous range of sequence similarity, facilitating prediction of function with an appropriate level of specificity. Significance Our model shows nearly exact function similarity for proteins with high sequence similarity (bit score >244.7, e-value >1e−62, non-redundant NCBI protein database (NRDB)) and only small likelihood of specific function match for proteins with low sequence similarity (bit score <54.6, e-value <1e−05, NRDB). For sequence similarity ranges in between our annotation model shows an increasing relationship between function similarity and sequence similarity, but with considerable variability. We applied the model to a large set of proteins of unknown function, and predicted functions for thousands of these proteins ranging from general to very specific. We also applied the model to a data set of proteins with previously assigned, specific functions that were electronically based. We show that, on average, these prior function predictions are more specific (quite possibly overly-specific) compared to

  2. Salience Network Functional Connectivity Predicts Placebo Effects in Major Depression

    PubMed Central

    Sikora, Magdalena; Heffernan, Joseph; Avery, Erich T.; Mickey, Brian J.; Zubieta, Jon-Kar; Peciña, Marta

    2015-01-01

    Background Recent neuroimaging studies have demonstrated resting-state functional connectivity (rsFC) abnormalities among intrinsic brain networks in Major Depressive Disorder (MDD); however, their role as predictors of treatment response has not yet been explored. Here, we investigate whether network-based rsFC predicts antidepressant and placebo effects in MDD. Methods We performed a randomized controlled trial of two weeklong, identical placebos (described as having either “active” fast-acting, antidepressant effects or as “inactive”) followed by a ten-week open-label antidepressant medication treatment. Twenty-nine participants underwent a rsFC fMRI scan at the completion of each placebo condition. Networks were isolated from resting-state blood-oxygen-level-dependent signal fluctuations using independent component analysis. Baseline and placebo-induced changes in rsFC within the default-mode, salience, and executive networks were examined for associations with placebo and antidepressant treatment response. Results Increased baseline rsFC in the rostral anterior cingulate (rACC) within the salience network, a region classically implicated in the formation of placebo analgesia and the prediction of treatment response in MDD, was associated with greater response to one week of active placebo and ten weeks of antidepressant treatment. Machine learning further demonstrated that increased salience network rsFC, mainly within the rACC, significantly predicts individual responses to placebo administration. Conclusions These data demonstrate that baseline rsFC within the salience network is linked to clinical placebo responses. This information could be employed to identify patients who would benefit from lower doses of antidepressant medication or non-pharmacological approaches, or to develop biomarkers of placebo effects in clinical trials. PMID:26709390

  3. Predicting effects of environmental change on a migratory herbivore

    USGS Publications Warehouse

    Stillman, R A; Wood, K A; Gilkerson, Whelan; Elkinton, E; Black, J. M.; Ward, David H.; Petrie, M.

    2015-01-01

    Changes in climate, food abundance and disturbance from humans threaten the ability of species to successfully use stopover sites and migrate between non-breeding and breeding areas. To devise successful conservation strategies for migratory species we need to be able to predict how such changes will affect both individuals and populations. Such predictions should ideally be process-based, focusing on the mechanisms through which changes alter individual physiological state and behavior. In this study we use a process-based model to evaluate how Black Brant (Branta bernicla nigricans) foraging on common eelgrass (Zostera marina) at a stopover site (Humboldt Bay, USA), may be affected by changes in sea level, food abundance and disturbance. The model is individual-based, with empirically based parameters, and incorporates the immigration of birds into the site, tidal changes in availability of eelgrass, seasonal and depth-related changes in eelgrass biomass, foraging behavior and energetics of the birds, and their mass-dependent decisions to emigrate. The model is validated by comparing predictions to observations across a range of system properties including the time birds spent foraging, probability of birds emigrating, mean stopover duration, peak bird numbers, rates of mass gain and distribution of birds within the site: all 11 predictions were within 35% of the observed value, and 8 within 20%. The model predicted that the eelgrass within the site could potentially support up to five times as many birds as currently use the site. Future predictions indicated that the rate of mass gain and mean stopover duration were relatively insensitive to sea level rise over the next 100 years, primarily because eelgrass habitat could redistribute shoreward into intertidal mudflats within the site to compensate for higher sea levels. In contrast, the rate of mass gain and mean stopover duration were sensitive to changes in total eelgrass biomass and the percentage of time

  4. Adaptive bandwidth measurements of importance functions for speech intelligibility prediction.

    PubMed

    Whitmal, Nathaniel A; DeRoy, Kristina

    2011-12-01

    The Articulation Index (AI) and Speech Intelligibility Index (SII) predict intelligibility scores from measurements of speech and hearing parameters. One component in the prediction is the "importance function," a weighting function that characterizes contributions of particular spectral regions of speech to speech intelligibility. Previous work with SII predictions for hearing-impaired subjects suggests that prediction accuracy might improve if importance functions for individual subjects were available. Unfortunately, previous importance function measurements have required extensive intelligibility testing with groups of subjects, using speech processed by various fixed-bandwidth low-pass and high-pass filters. A more efficient approach appropriate to individual subjects is desired. The purpose of this study was to evaluate the feasibility of measuring importance functions for individual subjects with adaptive-bandwidth filters. In two experiments, ten subjects with normal-hearing listened to vowel-consonant-vowel (VCV) nonsense words processed by low-pass and high-pass filters whose bandwidths were varied adaptively to produce specified performance levels in accordance with the transformed up-down rules of Levitt [(1971). J. Acoust. Soc. Am. 49, 467-477]. Local linear psychometric functions were fit to resulting data and used to generate an importance function for VCV words. Results indicate that the adaptive method is reliable and efficient, and produces importance function data consistent with that of the corresponding AI/SII importance function.

  5. Predicting vulnerabilities of North American shorebirds to climate change.

    PubMed

    Galbraith, Hector; DesRochers, David W; Brown, Stephen; Reed, J Michael

    2014-01-01

    Despite an increase in conservation efforts for shorebirds, there are widespread declines of many species of North American shorebirds. We wanted to know whether these declines would be exacerbated by climate change, and whether relatively secure species might become at-risk species. Virtually all of the shorebird species breeding in the USA and Canada are migratory, which means climate change could affect extinction risk via changes on the breeding, wintering, and/or migratory refueling grounds, and that ecological synchronicities could be disrupted at multiple sites. To predict the effects of climate change on shorebird extinction risks, we created a categorical risk model complementary to that used by Partners-in-Flight and the U.S. Shorebird Conservation Plan. The model is based on anticipated changes in breeding, migration, and wintering habitat, degree of dependence on ecological synchronicities, migration distance, and degree of specialization on breeding, migration, or wintering habitat. We evaluated 49 species, and for 3 species we evaluated 2 distinct populations each, and found that 47 (90%) taxa are predicted to experience an increase in risk of extinction. No species was reclassified into a lower-risk category, although 6 species had at least one risk factor decrease in association with climate change. The number of species that changed risk categories in our assessment is sensitive to how much of an effect of climate change is required to cause the shift, but even at its least sensitive, 20 species were at the highest risk category for extinction. Based on our results it appears that shorebirds are likely to be highly vulnerable to climate change. Finally, we discuss both how our approach can be integrated with existing risk assessments and potential future directions for predicting change in extinction risk due to climate change.

  6. Predicting Vulnerabilities of North American Shorebirds to Climate Change

    PubMed Central

    Galbraith, Hector; DesRochers, David W.; Brown, Stephen; Reed, J. Michael

    2014-01-01

    Despite an increase in conservation efforts for shorebirds, there are widespread declines of many species of North American shorebirds. We wanted to know whether these declines would be exacerbated by climate change, and whether relatively secure species might become at–risk species. Virtually all of the shorebird species breeding in the USA and Canada are migratory, which means climate change could affect extinction risk via changes on the breeding, wintering, and/or migratory refueling grounds, and that ecological synchronicities could be disrupted at multiple sites. To predict the effects of climate change on shorebird extinction risks, we created a categorical risk model complementary to that used by Partners–in–Flight and the U.S. Shorebird Conservation Plan. The model is based on anticipated changes in breeding, migration, and wintering habitat, degree of dependence on ecological synchronicities, migration distance, and degree of specialization on breeding, migration, or wintering habitat. We evaluated 49 species, and for 3 species we evaluated 2 distinct populations each, and found that 47 (90%) taxa are predicted to experience an increase in risk of extinction. No species was reclassified into a lower–risk category, although 6 species had at least one risk factor decrease in association with climate change. The number of species that changed risk categories in our assessment is sensitive to how much of an effect of climate change is required to cause the shift, but even at its least sensitive, 20 species were at the highest risk category for extinction. Based on our results it appears that shorebirds are likely to be highly vulnerable to climate change. Finally, we discuss both how our approach can be integrated with existing risk assessments and potential future directions for predicting change in extinction risk due to climate change. PMID:25268907

  7. A survey of computational intelligence techniques in protein function prediction.

    PubMed

    Tiwari, Arvind Kumar; Srivastava, Rajeev

    2014-01-01

    During the past, there was a massive growth of knowledge of unknown proteins with the advancement of high throughput microarray technologies. Protein function prediction is the most challenging problem in bioinformatics. In the past, the homology based approaches were used to predict the protein function, but they failed when a new protein was different from the previous one. Therefore, to alleviate the problems associated with homology based traditional approaches, numerous computational intelligence techniques have been proposed in the recent past. This paper presents a state-of-the-art comprehensive review of various computational intelligence techniques for protein function predictions using sequence, structure, protein-protein interaction network, and gene expression data used in wide areas of applications such as prediction of DNA and RNA binding sites, subcellular localization, enzyme functions, signal peptides, catalytic residues, nuclear/G-protein coupled receptors, membrane proteins, and pathway analysis from gene expression datasets. This paper also summarizes the result obtained by many researchers to solve these problems by using computational intelligence techniques with appropriate datasets to improve the prediction performance. The summary shows that ensemble classifiers and integration of multiple heterogeneous data are useful for protein function prediction.

  8. A Unitary Executive Function Predicts Intelligence in Children

    ERIC Educational Resources Information Center

    Brydges, Christopher R.; Reid, Corinne L.; Fox, Allison M.; Anderson, Mike

    2012-01-01

    Executive functions (EF) and intelligence are of critical importance to success in many everyday tasks. Working memory, or updating, which is one latent variable identified in confirmatory factor analytic models of executive functions, predicts intelligence (both fluid and crystallised) in adults, but inhibition and shifting do not (Friedman et…

  9. Climate-Induced Boreal Forest Change: Predictions versus Current Observations

    NASA Technical Reports Server (NTRS)

    Soja, Amber J.; Tchebakova, Nadezda M.; French, Nancy H. F.; Flannigan, Michael D.; Shugart, Herman H.; Stocks, Brian J.; Sukhinin, Anatoly I.; Parfenova, E. I.; Chapin, F. Stuart, III; Stackhouse, Paul W., Jr.

    2007-01-01

    For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change.

  10. A large-scale evaluation of computational protein function prediction.

    PubMed

    Radivojac, Predrag; Clark, Wyatt T; Oron, Tal Ronnen; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kaßner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Boehm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas A; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    2013-03-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.

  11. Protein Structure and Function Prediction Using I-TASSER.

    PubMed

    Yang, Jianyi; Zhang, Yang

    2015-12-17

    I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets.

  12. A large-scale evaluation of computational protein function prediction

    PubMed Central

    Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    2013-01-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

  13. Predicting the response of populations to environmental change

    SciTech Connect

    Ives, A.R.

    1995-04-01

    When subject to long-term directional environmental perturbations, changes in population densities depend on the positive and negative feedbacks operating through interactions within and among species in a community. This paper develops techniques to predict the long-term responses of population densities to environmental changes using data on short-term population fluctuations driven by short-term environmental variability. In addition to giving quantitative predictions, the techniques also reveal how different qualitative patterns of species interactions either buffer or accentuate population responses to environmental trends. All of the predictions are based on regression coefficients extracted from time series data, and they can therefore be applied with a minimum of mathematical and statistical gymnastics. 48 refs., 10 figs., 4 tabs.

  14. Phylogeny Predicts Future Habitat Shifts Due to Climate Change

    PubMed Central

    Kuntner, Matjaž; Năpăruş, Magdalena; Li, Daiqin; Coddington, Jonathan A.

    2014-01-01

    Background Taxa may respond differently to climatic changes, depending on phylogenetic or ecological effects, but studies that discern among these alternatives are scarce. Here, we use two species pairs from globally distributed spider clades, each pair representing two lifestyles (generalist, specialist) to test the relative importance of phylogeny versus ecology in predicted responses to climate change. Methodology We used a recent phylogenetic hypothesis for nephilid spiders to select four species from two genera (Nephilingis and Nephilengys) that match the above criteria, are fully allopatric but combined occupy all subtropical-tropical regions. Based on their records, we modeled each species niche spaces and predicted their ecological shifts 20, 40, 60, and 80 years into the future using customized GIS tools and projected climatic changes. Conclusions Phylogeny better predicts the species current ecological preferences than do lifestyles. By 2080 all species face dramatic reductions in suitable habitat (54.8–77.1%) and adapt by moving towards higher altitudes and latitudes, although at different tempos. Phylogeny and life style explain simulated habitat shifts in altitude, but phylogeny is the sole best predictor of latitudinal shifts. Models incorporating phylogenetic relatedness are an important additional tool to predict accurately biotic responses to global change. PMID:24892737

  15. Roles for text mining in protein function prediction.

    PubMed

    Verspoor, Karin M

    2014-01-01

    The Human Genome Project has provided science with a hugely valuable resource: the blueprints for life; the specification of all of the genes that make up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what happens at a molecular level in biological organisms, and eventually to enable development of treatments for diseases where some aspect of a biological system goes awry, we must understand the functions of proteins. However, experimental characterization of protein function cannot scale to the vast amount of DNA sequence data now available. Computational protein function prediction has therefore emerged as a problem at the forefront of modern biology (Radivojac et al., Nat Methods 10(13):221-227, 2013).Within the varied approaches to computational protein function prediction that have been explored, there are several that make use of biomedical literature mining. These methods take advantage of information in the published literature to associate specific proteins with specific protein functions. In this chapter, we introduce two main strategies for doing this: association of function terms, represented as Gene Ontology terms (Ashburner et al., Nat Genet 25(1):25-29, 2000), to proteins based on information in published articles, and a paradigm called LEAP-FS (Literature-Enhanced Automated Prediction of Functional Sites) in which literature mining is used to validate the predictions of an orthogonal computational protein function prediction method.

  16. Predicting Change in Eelgrass Distribution Due to Sea Level Rise

    EPA Science Inventory

    The eelgrass species Zostera marina is the dominant estuarine seagrass on the Pacific Northwest coast of North America and provides important ecosystem services and functions. The loss of eelgrass bed acreage due to environmental pressures is of world-wide concern, yet predicted ...

  17. Adaptive functional change of the contralateral kidney after partial nephrectomy.

    PubMed

    Choi, Se Young; Yoo, Sangjun; You, Dalsan; Jeong, In Gab; Song, Cheryn; Hong, Bumsik; Hong, Jun Hyuk; Ahn, Hanjong; Kim, Choung-Soo

    2017-04-12

    Partial nephrectomy aims to maintain renal function by nephron sparing; however, functional changes in the contralateral kidney remain unknown. We evaluate the functional change in the contralateral kidney using a diethylene triamine penta-acetic acid (DTPA) renal scan and determine factors predicting contralateral kidney function after partial nephrectomy. A total of 699 patients underwent partial nephrectomy, with a DTPA scan before and after surgery to assess the separate function of each kidney. Patients were divided into three groups according to initial contralateral glomerular filtration rate (GFR; group 1: <30 ml/min/1.73 m2, group 2: 30-45 ml/min/1.73 m2, and group 3: ≧45 ml/min/1.73 m2). Multiple regression analysis was used to identify the factors associated with increased GFR of the contralateral kidney over a 4 year postoperative period. Patients in group 1 had a higher mean age and hypertension history, worse American Society of Anesthesiologists score, and larger tumor size than in the other two groups. The ipsilateral GFR changes at 4 years after partial nephrectomy were -18.9%, -3.6%, and 3.9% in groups 1, 2, and 3, respectively, while the contralateral GFR changes were 10.8%, 25.7%, and 38.8%. Age (Beta: -0.105, 95% confidence interval [CI]: -0.213; -0.011 p<0.05) and preoperative contralateral GFR (Beta: -0.256, 95% CI: -0.332; -0.050 p<0.01) were significant predictive factors for increased GFR of the contralateral kidney after 4 years. The contralateral kidney compensated for the functional loss of the ipsilateral kidney. The increase of GFR in contralateral kidney is more prominent in younger patients with decreased contralateral renal function.

  18. Predicting plasticity: acute context-dependent changes to vocal performance predict long-term age-dependent changes

    PubMed Central

    James, Logan S.

    2015-01-01

    Understanding the factors that predict and guide variation in behavioral change can lend insight into mechanisms of motor plasticity and individual differences in behavior. The performance of adult birdsong changes with age in a manner that is similar to rapid context-dependent changes to song. To reveal mechanisms of vocal plasticity, we analyzed the degree to which variation in the direction and magnitude of age-dependent changes to Bengalese finch song could be predicted by variation in context-dependent changes. Using a repeated-measures design, we found that variation in age-dependent changes to the timing, sequencing, and structure of vocal elements (“syllables”) was significantly predicted by variation in context-dependent changes. In particular, the degree to which the duration of intersyllable gaps, syllable sequencing at branch points, and fundamental frequency of syllables within spontaneous [undirected (UD)] songs changed over time was correlated with the degree to which these features changed from UD song to female-directed (FD) song in young-adult finches (FDyoung). As such, the structure of some temporal features of UD songs converged over time onto the structure of FDyoung songs. This convergence suggested that the FDyoung song could serve as a stable target for vocal motor plasticity. Consequently, we analyzed the stability of FD song and found that the temporal structure of FD song changed significantly over time in a manner similar to UD song. Because FD song is considered a state of heightened performance, these data suggest that age-dependent changes could reflect practice-related improvements in vocal motor performance. PMID:26311186

  19. Changes in Monocyte Functions of Astronauts

    NASA Technical Reports Server (NTRS)

    Kaur, I.; Simons, E.; Castro, V.; Ott, C. Mark; Pierson, Duane L.

    2004-01-01

    Monocyte cell numbers and functions, including phagocytosis, oxidative burst capacity, and degranulation and expression of related surface molecules, were studied in blood specimens from 25 astronauts and 9 healthy control subjects. Blood samples were obtained 10 days before a space flight, 3 hours after landing and 3 days after landing. The number of monocytes in astronauts did not change significantly among the three sample collection periods. Following space flight, the monocytes ability to phagocytize Escherichia coli, to exhibit an oxidative burst, and to degranulate was reduced as compared to monocytes from control subjects. These alterations in monocyte functions after space flight correlated with alterations in the expression of CD32 and CD64.

  20. Predictions of avian Plasmodium expansion under climate change

    PubMed Central

    Loiseau, Claire; Harrigan, Ryan J.; Bichet, Coraline; Julliard, Romain; Garnier, Stéphane; Lendvai, Ádám Z.; Chastel, Olivier; Sorci, Gabriele

    2013-01-01

    Vector-borne diseases are particularly responsive to changing environmental conditions. Diurnal temperature variation has been identified as a particularly important factor for the development of malaria parasites within vectors. Here, we conducted a survey across France, screening populations of the house sparrow (Passer domesticus) for malaria (Plasmodium relictum). We investigated whether variation in remotely-sensed environmental variables accounted for the spatial variation observed in prevalence and parasitemia. While prevalence was highly correlated to diurnal temperature range and other measures of temperature variation, environmental conditions could not predict spatial variation in parasitemia. Based on our empirical data, we mapped malaria distribution under climate change scenarios and predicted that Plasmodium occurrence will spread to regions in northern France, and that prevalence levels are likely to increase in locations where transmission already occurs. Our findings, based on remote sensing tools coupled with empirical data suggest that climatic change will significantly alter transmission of malaria parasites. PMID:23350033

  1. BLANNOTATOR: enhanced homology-based function prediction of bacterial proteins

    PubMed Central

    2012-01-01

    Background Automated function prediction has played a central role in determining the biological functions of bacterial proteins. Typically, protein function annotation relies on homology, and function is inferred from other proteins with similar sequences. This approach has become popular in bacterial genomics because it is one of the few methods that is practical for large datasets and because it does not require additional functional genomics experiments. However, the existing solutions produce erroneous predictions in many cases, especially when query sequences have low levels of identity with the annotated source protein. This problem has created a pressing need for improvements in homology-based annotation. Results We present an automated method for the functional annotation of bacterial protein sequences. Based on sequence similarity searches, BLANNOTATOR accurately annotates query sequences with one-line summary descriptions of protein function. It groups sequences identified by BLAST into subsets according to their annotation and bases its prediction on a set of sequences with consistent functional information. We show the results of BLANNOTATOR's performance in sets of bacterial proteins with known functions. We simulated the annotation process for 3090 SWISS-PROT proteins using a database in its state preceding the functional characterisation of the query protein. For this dataset, our method outperformed the five others that we tested, and the improved performance was maintained even in the absence of highly related sequence hits. We further demonstrate the value of our tool by analysing the putative proteome of Lactobacillus crispatus strain ST1. Conclusions BLANNOTATOR is an accurate method for bacterial protein function prediction. It is practical for genome-scale data and does not require pre-existing sequence clustering; thus, this method suits the needs of bacterial genome and metagenome researchers. The method and a web-server are available at

  2. Drought Predictability and Prediction in a Changing Climate: Assessing Current Predictive Knowledge and Capabilities, User Requirements and Research Priorities

    NASA Technical Reports Server (NTRS)

    Schubert, Siegfried

    2011-01-01

    Drought is fundamentally the result of an extended period of reduced precipitation lasting anywhere from a few weeks to decades and even longer. As such, addressing drought predictability and prediction in a changing climate requires foremost that we make progress on the ability to predict precipitation anomalies on subseasonal and longer time scales. From the perspective of the users of drought forecasts and information, drought is however most directly viewed through its impacts (e.g., on soil moisture, streamflow, crop yields). As such, the question of the predictability of drought must extend to those quantities as well. In order to make progress on these issues, the WCRP drought information group (DIG), with the support of WCRP, the Catalan Institute of Climate Sciences, the La Caixa Foundation, the National Aeronautics and Space Administration, the National Oceanic and Atmospheric Administration, and the National Science Foundation, has organized a workshop to focus on: 1. User requirements for drought prediction information on sub-seasonal to centennial time scales 2. Current understanding of the mechanisms and predictability of drought on sub-seasonal to centennial time scales 3. Current drought prediction/projection capabilities on sub-seasonal to centennial time scales 4. Advancing regional drought prediction capabilities for variables and scales most relevant to user needs on sub-seasonal to centennial time scales. This introductory talk provides an overview of these goals, and outlines the occurrence and mechanisms of drought world-wide.

  3. Prediction of Erectile Function Following Treatment for Prostate Cancer

    PubMed Central

    Alemozaffar, Mehrdad; Regan, Meredith M.; Cooperberg, Matthew R.; Wei, John T.; Michalski, Jeff M.; Sandler, Howard M.; Hembroff, Larry; Sadetsky, Natalia; Saigal, Christopher S.; Litwin, Mark S.; Klein, Eric; Kibel, Adam S.; Hamstra, Daniel A.; Pisters, Louis L.; Kuban, Deborah A.; Kaplan, Irving D.; Wood, David P.; Ciezki, Jay; Dunn, Rodney L.; Carroll, Peter R.; Sanda, Martin G.

    2013-01-01

    Context Sexual function is the health-related quality of life (HRQOL) domain most commonly impaired after prostate cancer treatment; however, validated tools to enable personalized prediction of erectile dysfunction after prostate cancer treatment are lacking. Objective To predict long-term erectile function following prostate cancer treatment based on individual patient and treatment characteristics. Design Pretreatment patient characteristics, sexual HRQOL, and treatment details measured in a longitudinal academic multicenter cohort (Prostate Cancer Outcomes and Satisfaction With Treatment Quality Assessment; enrolled from 2003 through 2006), were used to develop models predicting erectile function 2 years after treatment. A community-based cohort (community-based Cancer of the Prostate Strategic Urologic Research Endeavor [CaPSURE]; enrolled 1995 through 2007) externally validated model performance. Patients in US academic and community-based practices whose HRQOL was measured pretreatment (N = 1201) underwent follow-up after prostatectomy, external radiotherapy, or brachytherapy for prostate cancer. Sexual outcomes among men completing 2 years’ follow-up (n = 1027) were used to develop models predicting erectile function that were externally validated among 1913 patients in a community-based cohort. Main Outcome Measures Patient-reported functional erections suitable for intercourse 2 years following prostate cancer treatment. Results Two years after prostate cancer treatment, 368 (37% [95% CI, 34%–40%]) of all patients and 335 (48% [95% CI, 45%–52%]) of those with functional erections prior to treatment reported functional erections; 531 (53% [95% CI, 50%–56%]) of patients without penile prostheses reported use of medications or other devices for erectile dysfunction. Pretreatment sexual HRQOL score, age, serum prostate-specific antigen level, race/ethnicity, body mass index, and intended treatment details were associated with functional erections 2

  4. Visual Function Changes after Laser Exposure.

    DTIC Science & Technology

    1984-04-01

    change in the pigment epithelium or the bipolar or ganglion cells of the inner retina was detectable. While these investigations (6, 7, 8) suggest a good...present initially after intense levels of light exposure (24- 26). Long-term followup of visual acuity (6 mo) after solar -induced foveal damage (27... cell . The possibility that this alteration is involved with a complex and subtle retinal photoreceptor alignment function is only speculation at this

  5. Prediction of protein function from protein sequence and structure.

    PubMed

    Whisstock, James C; Lesk, Arthur M

    2003-08-01

    The sequence of a genome contains the plans of the possible life of an organism, but implementation of genetic information depends on the functions of the proteins and nucleic acids that it encodes. Many individual proteins of known sequence and structure present challenges to the understanding of their function. In particular, a number of genes responsible for diseases have been identified but their specific functions are unknown. Whole-genome sequencing projects are a major source of proteins of unknown function. Annotation of a genome involves assignment of functions to gene products, in most cases on the basis of amino-acid sequence alone. 3D structure can aid the assignment of function, motivating the challenge of structural genomics projects to make structural information available for novel uncharacterized proteins. Structure-based identification of homologues often succeeds where sequence-alone-based methods fail, because in many cases evolution retains the folding pattern long after sequence similarity becomes undetectable. Nevertheless, prediction of protein function from sequence and structure is a difficult problem, because homologous proteins often have different functions. Many methods of function prediction rely on identifying similarity in sequence and/or structure between a protein of unknown function and one or more well-understood proteins. Alternative methods include inferring conservation patterns in members of a functionally uncharacterized family for which many sequences and structures are known. However, these inferences are tenuous. Such methods provide reasonable guesses at function, but are far from foolproof. It is therefore fortunate that the development of whole-organism approaches and comparative genomics permits other approaches to function prediction when the data are available. These include the use of protein-protein interaction patterns, and correlations between occurrences of related proteins in different organisms, as

  6. Change in avian abundance predicted from regional forest inventory data

    USGS Publications Warehouse

    Twedt, Daniel J.; Tirpak, John M.; Jones-Farrand, D. Todd; Thompson, Frank R.; Uihlein, William B.; Fitzgerald, Jane A.

    2010-01-01

    An inability to predict population response to future habitat projections is a shortcoming in bird conservation planning. We sought to predict avian response to projections of future forest conditions that were developed from nationwide forest surveys within the Forest Inventory and Analysis (FIA) program. To accomplish this, we evaluated the historical relationship between silvicolous bird populations and FIA-derived forest conditions within 25 ecoregions that comprise the southeastern United States. We aggregated forest area by forest ownership, forest type, and tree size-class categories in county-based ecoregions for 5 time periods spanning 1963-2008. We assessed the relationship of forest data with contemporaneous indices of abundance for 24 silvicolous bird species that were obtained from Breeding Bird Surveys. Relationships between bird abundance and forest inventory data for 18 species were deemed sufficient as predictive models. We used these empirically derived relationships between regional forest conditions and bird populations to predict relative changes in abundance of these species within ecoregions that are anticipated to coincide with projected changes in forest variables through 2040. Predicted abundances of these 18 species are expected to remain relatively stable in over a quarter (27%) of the ecoregions. However, change in forest area and redistribution of forest types will likely result in changed abundance of some species within many ecosystems. For example, abundances of 11 species, including pine warbler (Dendroica pinus), brown-headed nuthatch (Sitta pusilla), and chuckwills- widow (Caprimulgus carolinensis), are projected to increase within more ecoregions than ecoregions where they will decrease. For 6 other species, such as blue-winged warbler (Vermivora pinus), Carolina wren (Thryothorus ludovicianus), and indigo bunting (Passerina cyanea), we projected abundances will decrease within more ecoregions than ecoregions where they will

  7. ESG: extended similarity group method for automated protein function prediction

    PubMed Central

    Chitale, Meghana; Hawkins, Troy; Park, Changsoon; Kihara, Daisuke

    2009-01-01

    Motivation: Importance of accurate automatic protein function prediction is ever increasing in the face of a large number of newly sequenced genomes and proteomics data that are awaiting biological interpretation. Conventional methods have focused on high sequence similarity-based annotation transfer which relies on the concept of homology. However, many cases have been reported that simple transfer of function from top hits of a homology search causes erroneous annotation. New methods are required to handle the sequence similarity in a more robust way to combine together signals from strongly and weakly similar proteins for effectively predicting function for unknown proteins with high reliability. Results: We present the extended similarity group (ESG) method, which performs iterative sequence database searches and annotates a query sequence with Gene Ontology terms. Each annotation is assigned with probability based on its relative similarity score with the multiple-level neighbors in the protein similarity graph. We will depict how the statistical framework of ESG improves the prediction accuracy by iteratively taking into account the neighborhood of query protein in the sequence similarity space. ESG outperforms conventional PSI-BLAST and the protein function prediction (PFP) algorithm. It is found that the iterative search is effective in capturing multiple-domains in a query protein, enabling accurately predicting several functions which originate from different domains. Availability: ESG web server is available for automated protein function prediction at http://dragon.bio.purdue.edu/ESG/ Contact: cspark@cau.ac.kr; dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19435743

  8. Changes in Neutrophil Functions in Astronauts

    NASA Technical Reports Server (NTRS)

    Kaur, Indreshpal; Simons, Elizabeth R.; Castro, Victoria; Pierson, Duane L.

    2002-01-01

    Neutrophil functions (phagocytosis, oxidative burst, degranulation) and expression of surface markers involved in these functions were studied in 25 astronauts before and after 4 space shuttle missions. Space flight duration ranged from 5 to 11 days. Blood specimens were obtained 10 days before launch (preflight or L-10), immediately after landing (landing or R+0), and again at 3 days after landing (postflight or R+3). Blood samples were also collected from 9 healthy low-stressed subjects at 3 time points simulating a 10-day shuttle mission. The number of neutrophils increased at landing by 85 percent when compared to the preflight numbers. Neutrophil functions were studied in whole blood using flow cytometric methods. Phagocytosis of E.coli-FITC and oxidative burst capacity of the neutrophils following the 9 to 11 day missions were lower at all three sampling points than the mean values for control subjects. Phagocytosis and oxidative burst capacity of the astronauts was decreased even 10-days before space flight. Mission duration appears to be a factor in phagocytic and oxidative functions. In contrast, following the short-duration (5-days) mission, these functions were unchanged from control values. No consistent changes in degranulation were observed following either short or medium length space missions. The expression of CD16, CD32, CD11a, CD11b, CD11c, L-selectin and CD36 was measured and found to be variable. Specifically, CD16 and CD32 did not correlate with the changes in oxidative burst and phagocytosis. We can conclude from this study that the stresses associated with space flight can alter the important functions of neutrophils.

  9. Predicting IQ change from brain structure: A cross-validation study

    PubMed Central

    Price, C.J.; Ramsden, S.; Hope, T.M.H.; Friston, K.J.; Seghier, M.L.

    2013-01-01

    Procedures that can predict cognitive abilities from brain imaging data are potentially relevant to educational assessments and studies of functional anatomy in the developing brain. Our aim in this work was to quantify the degree to which IQ change in the teenage years could be predicted from structural brain changes. Two well-known k-fold cross-validation analyses were applied to data acquired from 33 healthy teenagers – each tested at Time 1 and Time 2 with a 3.5 year interval. One approach, a Leave-One-Out procedure, predicted IQ change for each subject on the basis of structural change in a brain region that was identified from all other subjects (i.e., independent data). This approach predicted 53% of verbal IQ change and 14% of performance IQ change. The other approach used half the sample, to identify regions for predicting IQ change in the other half (i.e., a Split half approach); however – unlike the Leave-One-Out procedure – regions identified using half the sample were not significant. We discuss how these out-of-sample estimates compare to in-sample estimates; and draw some recommendations for k-fold cross-validation procedures when dealing with small datasets that are typical in the neuroimaging literature. PMID:23567505

  10. Predicting IQ change from brain structure: a cross-validation study.

    PubMed

    Price, C J; Ramsden, S; Hope, T M H; Friston, K J; Seghier, M L

    2013-07-01

    Procedures that can predict cognitive abilities from brain imaging data are potentially relevant to educational assessments and studies of functional anatomy in the developing brain. Our aim in this work was to quantify the degree to which IQ change in the teenage years could be predicted from structural brain changes. Two well-known k-fold cross-validation analyses were applied to data acquired from 33 healthy teenagers - each tested at Time 1 and Time 2 with a 3.5 year interval. One approach, a Leave-One-Out procedure, predicted IQ change for each subject on the basis of structural change in a brain region that was identified from all other subjects (i.e., independent data). This approach predicted 53% of verbal IQ change and 14% of performance IQ change. The other approach used half the sample, to identify regions for predicting IQ change in the other half (i.e., a Split half approach); however--unlike the Leave-One-Out procedure--regions identified using half the sample were not significant. We discuss how these out-of-sample estimates compare to in-sample estimates; and draw some recommendations for k-fold cross-validation procedures when dealing with small datasets that are typical in the neuroimaging literature.

  11. Predicting protein function by frequent functional association pattern mining in protein interaction networks.

    PubMed

    Cho, Young-Rae; Zhang, Aidong

    2010-01-01

    Predicting protein function from protein interaction networks has been challenging because of the complexity of functional relationships among proteins. Most previous function prediction methods depend on the neighborhood of or the connected paths to known proteins. However, their accuracy has been limited due to the functional inconsistency of interacting proteins. In this paper, we propose a novel approach for function prediction by identifying frequent patterns of functional associations in a protein interaction network. A set of functions that a protein performs is assigned into the corresponding node as a label. A functional association pattern is then represented as a labeled subgraph. Our frequent labeled subgraph mining algorithm efficiently searches the functional association patterns that occur frequently in the network. It iteratively increases the size of frequent patterns by one node at a time by selective joining, and simplifies the network by a priori pruning. Using the yeast protein interaction network, our algorithm found more than 1400 frequent functional association patterns. The function prediction is performed by matching the subgraph, including the unknown protein, with the frequent patterns analogous to it. By leave-one-out cross validation, we show that our approach has better performance than previous link-based methods in terms of prediction accuracy. The frequent functional association patterns generated in this study might become the foundations of advanced analysis for functional behaviors of proteins in a system level.

  12. Caregiver Confidence: Does It Predict Changes in Disability among Elderly Home Care Recipients?

    ERIC Educational Resources Information Center

    Li, Lydia W.; McLaughlin, Sara J.

    2012-01-01

    Purpose of the study: The primary aim of this investigation was to determine whether caregiver confidence in their care recipients' functional capabilities predicts changes in the performance of activities of daily living (ADL) among elderly home care recipients. A secondary aim was to explore how caregiver confidence and care recipient functional…

  13. SitesIdentify: a protein functional site prediction tool

    PubMed Central

    2009-01-01

    Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify), based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/ PMID:19922660

  14. Biochemical functional predictions for protein structures of unknown or uncertain function.

    PubMed

    Mills, Caitlyn L; Beuning, Penny J; Ondrechen, Mary Jo

    2015-01-01

    With the exponential growth in the determination of protein sequences and structures via genome sequencing and structural genomics efforts, there is a growing need for reliable computational methods to determine the biochemical function of these proteins. This paper reviews the efforts to address the challenge of annotating the function at the molecular level of uncharacterized proteins. While sequence- and three-dimensional-structure-based methods for protein function prediction have been reviewed previously, the recent trends in local structure-based methods have received less attention. These local structure-based methods are the primary focus of this review. Computational methods have been developed to predict the residues important for catalysis and the local spatial arrangements of these residues can be used to identify protein function. In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function. Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function. These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations.

  15. Biochemical functional predictions for protein structures of unknown or uncertain function

    PubMed Central

    Mills, Caitlyn L.; Beuning, Penny J.; Ondrechen, Mary Jo

    2015-01-01

    With the exponential growth in the determination of protein sequences and structures via genome sequencing and structural genomics efforts, there is a growing need for reliable computational methods to determine the biochemical function of these proteins. This paper reviews the efforts to address the challenge of annotating the function at the molecular level of uncharacterized proteins. While sequence- and three-dimensional-structure-based methods for protein function prediction have been reviewed previously, the recent trends in local structure-based methods have received less attention. These local structure-based methods are the primary focus of this review. Computational methods have been developed to predict the residues important for catalysis and the local spatial arrangements of these residues can be used to identify protein function. In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function. Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function. These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations. PMID:25848497

  16. 3D-Fun: predicting enzyme function from structure.

    PubMed

    von Grotthuss, Marcin; Plewczynski, Dariusz; Vriend, Gert; Rychlewski, Leszek

    2008-07-01

    The 'omics' revolution is causing a flurry of data that all needs to be annotated for it to become useful. Sequences of proteins of unknown function can be annotated with a putative function by comparing them with proteins of known function. This form of annotation is typically performed with BLAST or similar software. Structural genomics is nowadays also bringing us three dimensional structures of proteins with unknown function. We present here software that can be used when sequence comparisons fail to determine the function of a protein with known structure but unknown function. The software, called 3D-Fun, is implemented as a server that runs at several European institutes and is freely available for everybody at all these sites. The 3D-Fun servers accept protein coordinates in the standard PDB format and compare them with all known protein structures by 3D structural superposition using the 3D-Hit software. If structural hits are found with proteins with known function, these are listed together with their function and some vital comparison statistics. This is conceptually very similar in 3D to what BLAST does in 1D. Additionally, the superposition results are displayed using interactive graphics facilities. Currently, the 3D-Fun system only predicts enzyme function but an expanded version with Gene Ontology predictions will be available soon. The server can be accessed at http://3dfun.bioinfo.pl/ or at http://3dfun.cmbi.ru.nl/.

  17. Impacts and predictions of coastal change during hurricanes

    USGS Publications Warehouse

    Stockdon, Hilary; Sallenger, Abby

    2010-01-01

    Beaches serve as a natural barrier between the ocean and inland communities, ecosystems, and resources. These dynamic environments move and change in response to winds, waves, and currents. During a powerful hurricane, changes to beaches can be large, and the results are sometimes catastrophic. Lives are lost, communities are destroyed, and millions of dollars are spent on rebuilding. There is a clear need to identify areas of our coastline that are likely to experience extreme and devastating erosion during a hurricane. It is also important to determine risk levels associated with development in areas where the land shifts and moves with each landfalling storm. The U.S. Geological Survey (USGS) provides scientific support for hurricane planning and response. Using observations of beach changes and models of waves and storm surge, we are predicting how the coast will respond to hurricanes and identifying areas vulnerable to extreme coastal changes.

  18. Beyond genotype: serotonin transporter epigenetic modification predicts human brain function.

    PubMed

    Nikolova, Yuliya S; Koenen, Karestan C; Galea, Sandro; Wang, Chiou-Miin; Seney, Marianne L; Sibille, Etienne; Williamson, Douglas E; Hariri, Ahmad R

    2014-09-01

    We examined epigenetic regulation in regards to behaviorally and clinically relevant human brain function. Specifically, we found that increased promoter methylation of the serotonin transporter gene predicted increased threat-related amygdala reactivity and decreased mRNA expression in postmortem amygdala tissue. These patterns were independent of functional genetic variation in the same region. Furthermore, the association with amygdala reactivity was replicated in a second cohort and was robust to both sampling methods and age.

  19. Predictability of Genetic Interactions from Functional Gene Modules

    PubMed Central

    Young, Jonathan H.; Marcotte, Edward M.

    2016-01-01

    Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal. PMID:28007839

  20. Factors predicting mood changes in oral contraceptive pill users

    PubMed Central

    2013-01-01

    Background Over 100 million women worldwide are using oral contraceptives pills (OCP) and mood changes were being as the primary reason for OCP discontinuation. The purpose of this study was to determine the prevalence and predicting factors of mood changes in oral contraceptive pills users. Methods This was a cross-sectional study of 500 women aged 15–49 years old using low dose (LD) pills attending family planning centers in Ahwaz, Iran. Data were collected via face-to-face interviews using a structured questionnaire including items on demographic, self-efficacy and mood change. Both univarate and multiple logistic regression analyses were performed to assess the relationship between reported mood change and the independent variables. Results In all 406 women reported that they did experience OCP side effects. Of these, 37.7% of women (n =153) reported mood changes due to OCP use. The results of multiple logistic regression revealed that place of living (OR =2.57, 95% CI = 1.06-6.20, p =0.03), not receiving information on OCP side effects (OR =1.80, 95% CI = 1.15-2.80, p =0.009), and lower self-efficacy (OR = 0.87, 95% CI = 0.80-0.94, p =0.001) were significant predictors of mood changes. Conclusion The findings from this study indicated that the prevalence of reported mood changes due to OCP use among Iranian women appeared to be consistent with other studies. In addition the findings showed that receiving information on OCP side effects from health care workers and self-efficacy were important predicting factors for mood changes. Indeed implementing educational programs and improving self-efficacy among women are recommended. PMID:24015872

  1. Functional consequences of realistic biodiversity changes in a marine ecosystem.

    PubMed

    Bracken, Matthew E S; Friberg, Sara E; Gonzalez-Dorantes, Cirse A; Williams, Susan L

    2008-01-22

    Declines in biodiversity have prompted concern over the consequences of species loss for the goods and services provided by natural ecosystems. However, relatively few studies have evaluated the functional consequences of realistic, nonrandom changes in biodiversity. Instead, most designs have used randomly selected assemblages from a local species pool to construct diversity gradients. It is therefore difficult, based on current evidence, to predict the functional consequences of realistic declines in biodiversity. In this study, we used tide pool microcosms to demonstrate that the effects of real-world changes in biodiversity may be very different from those of random diversity changes. Specifically, we measured the relationship between the diversity of a seaweed assemblage and its ability to use nitrogen, a key limiting nutrient in nearshore marine systems. We quantified nitrogen uptake using both experimental and model seaweed assemblages and found that natural increases in diversity resulted in enhanced rates of nitrogen use, whereas random diversity changes had no effect on nitrogen uptake. Our results suggest that understanding the real-world consequences of declining biodiversity will require addressing changes in species performance along natural diversity gradients and understanding the relationships between species' susceptibility to loss and their contributions to ecosystem functioning.

  2. firestar--advances in the prediction of functionally important residues.

    PubMed

    Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L

    2011-07-01

    firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php.

  3. STRING: a database of predicted functional associations between proteins.

    PubMed

    von Mering, Christian; Huynen, Martijn; Jaeggi, Daniel; Schmidt, Steffen; Bork, Peer; Snel, Berend

    2003-01-01

    Functional links between proteins can often be inferred from genomic associations between the genes that encode them: groups of genes that are required for the same function tend to show similar species coverage, are often located in close proximity on the genome (in prokaryotes), and tend to be involved in gene-fusion events. The database STRING is a precomputed global resource for the exploration and analysis of these associations. Since the three types of evidence differ conceptually, and the number of predicted interactions is very large, it is essential to be able to assess and compare the significance of individual predictions. Thus, STRING contains a unique scoring-framework based on benchmarks of the different types of associations against a common reference set, integrated in a single confidence score per prediction. The graphical representation of the network of inferred, weighted protein interactions provides a high-level view of functional linkage, facilitating the analysis of modularity in biological processes. STRING is updated continuously, and currently contains 261 033 orthologs in 89 fully sequenced genomes. The database predicts functional interactions at an expected level of accuracy of at least 80% for more than half of the genes; it is online at http://www.bork.embl-heidelberg.de/STRING/.

  4. Ontology-Based Prediction and Prioritization of Gene Functional Annotations.

    PubMed

    Chicco, Davide; Masseroli, Marco

    2016-01-01

    Genes and their protein products are essential molecular units of a living organism. The knowledge of their functions is key for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and therapies. The association of a gene or protein with its functions, described by controlled terms of biomolecular terminologies or ontologies, is named gene functional annotation. Very many and valuable gene annotations expressed through terminologies and ontologies are available. Nevertheless, they might include some erroneous information, since only a subset of annotations are reviewed by curators. Furthermore, they are incomplete by definition, given the rapidly evolving pace of biomolecular knowledge. In this scenario, computational methods that are able to quicken the annotation curation process and reliably suggest new annotations are very important. Here, we first propose a computational pipeline that uses different semantic and machine learning methods to predict novel ontology-based gene functional annotations; then, we introduce a new semantic prioritization rule to categorize the predicted annotations by their likelihood of being correct. Our tests and validations proved the effectiveness of our pipeline and prioritization of predicted annotations, by selecting as most likely manifold predicted annotations that were later confirmed.

  5. Predicting transfer performance: a comparison of competing function learning models.

    PubMed

    McDaniel, Mark A; Dimperio, Eric; Griego, Jacqueline A; Busemeyer, Jerome R

    2009-01-01

    The population of linear experts (POLE) model suggests that function learning and transfer are mediated by activation of a set of prestored linear functions that together approximate the given function (Kalish, Lewandowsky, & Kruschke, 2004). In the extrapolation-association (EXAM) model, an exemplar-based architecture associates trained input values with their paired output values. Transfer incorporates a linear rule-based response mechanism (McDaniel & Busemeyer, 2005). Learners were trained on a functional relationship defined by 2 linear-function segments with mirror slopes. In Experiment 1, 1 segment was densely trained and 1 was sparsely trained; in Experiment 2, both segments were trained equally, but the 2 segments were widely separated. Transfer to new input values was tested. For each model, training performance for each individual participant was fit, and transfer predictions were generated. POLE generally better fit the training data than did EXAM, but EXAM was more accurate at predicting (and fitting) transfer behaviors. It was especially telling that in Experiment 2 the transfer pattern was more consistent with EXAM's but not POLE's predictions, even though the presentation of salient linear segments during training dovetailed with POLE's approach.

  6. Predicting Protein Function via Semantic Integration of Multiple Networks.

    PubMed

    Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

    2016-01-01

    Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

  7. Protein function prediction using guilty by association from interaction networks.

    PubMed

    Piovesan, Damiano; Giollo, Manuel; Ferrari, Carlo; Tosatto, Silvio C E

    2015-12-01

    Protein function prediction from sequence using the Gene Ontology (GO) classification is useful in many biological problems. It has recently attracted increasing interest, thanks in part to the Critical Assessment of Function Annotation (CAFA) challenge. In this paper, we introduce Guilty by Association on STRING (GAS), a tool to predict protein function exploiting protein-protein interaction networks without sequence similarity. The assumption is that whenever a protein interacts with other proteins, it is part of the same biological process and located in the same cellular compartment. GAS retrieves interaction partners of a query protein from the STRING database and measures enrichment of the associated functional annotations to generate a sorted list of putative functions. A performance evaluation based on CAFA metrics and a fair comparison with optimized BLAST similarity searches is provided. The consensus of GAS and BLAST is shown to improve overall performance. The PPI approach is shown to outperform similarity searches for biological process and cellular compartment GO predictions. Moreover, an analysis of the best practices to exploit protein-protein interaction networks is also provided.

  8. Disorganized symptoms and executive functioning predict impaired social functioning in subjects at risk for psychosis.

    PubMed

    Eslami, Ali; Jahshan, Carol; Cadenhead, Kristin S

    2011-01-01

    Predictors of social functioning deficits were assessed in 22 individuals "at risk" for psychosis. Disorganized symptoms and executive functioning predicted social functioning at follow-up. Early intervention efforts that focus on social and cognitive skills are indicated in this vulnerable population.

  9. Structure-based Methods for Computational Protein Functional Site Prediction

    PubMed Central

    Dukka, B KC

    2013-01-01

    Due to the advent of high throughput sequencing techniques and structural genomic projects, the number of gene and protein sequences has been ever increasing. Computational methods to annotate these genes and proteins are even more indispensable. Proteins are important macromolecules and study of the function of proteins is an important problem in structural bioinformatics. This paper discusses a number of methods to predict protein functional site especially focusing on protein ligand binding site prediction. Initially, a short overview is presented on recent advances in methods for selection of homologous sequences. Furthermore, a few recent structural based approaches and sequence-and-structure based approaches for protein functional sites are discussed in details. PMID:24688745

  10. Implicit Self-Evaluations Predict Changes in Implicit Partner Evaluations

    PubMed Central

    McNulty, James K.; Baker, Levi R.; Olson, Michael A.

    2014-01-01

    Do people who feel good about themselves have better relations with others? Although the notion that they do is central to both classic and modern theories, there is little strong evidence to support it. We argue that one reason for the lack of evidence is that prior research has relied exclusively on explicit measures of self- and relationship evaluations. The current longitudinal study of newlywed couples used explicit measures of self-, relationship, and partner evaluations as well as implicit measures of self- and partner evaluations to examine the link between self-evaluations and changes in relationship evaluations over the first three years of marriage. Whereas explicit self-evaluations were unrelated to changes in all interpersonal measures, implicit self-evaluations positively predicted changes in implicit partner evaluations. This finding joins others in highlighting the importance of automatic processes and implicit measures to the study of close interpersonal relationships. PMID:24958686

  11. Predicting the effects of climate change on marine communities and the consequences for fisheries

    NASA Astrophysics Data System (ADS)

    Jennings, Simon; Brander, Keith

    2010-02-01

    Climate effects on the structure and function of marine communities have received scant attention. The few existing approaches for predicting climate effects suggest that community responses might be predicted from the responses of component populations. These approaches require a very complex understanding of ecological interactions among populations. An alternate and informative parallel process is to ask whether it is possible to make predictions about community level responses to climate that are independent of knowledge about the identity and dynamics of component populations. We propose that it is possible to make such predictions, based on knowledge of the processes that determine the size-structure of communities. We suggest that theory that relates metabolic scaling, predator-prey interactions and energy transfer in size-based food webs, allows the size-structure and productivity of communities across a range of trophic levels to be predicted, provided that predictions of the effects of climate on primary production are available. One simple application of the community-focused predictions is to ask whether predictions of the size composition and abundance of populations for alternate climate scenarios are compatible with predictions for the size composition and relative abundance of communities. More sophisticated treatments could predict the effects of climate scenarios on multiple interacting populations and compare their combined size-abundance structure and production with that predicted for the community under the same climate scenario. The main weakness of the community approach is that the methods predict abundance and production by size-class rather than taxonomic group, and society would be particularly concerned if climate driven changes had a strong effect on the relative production of fishable and non-fishable species in the community. The main strength of the community approach is that it provides widely applicable 'null' models for assessing

  12. A review of protein function prediction under machine learning perspective.

    PubMed

    Bernardes, Juliana S; Pedreira, Carlos E

    2013-08-01

    Protein function prediction is one of the most challenging problems in the post-genomic era. The number of newly identified proteins has been exponentially increasing with the advances of the high-throughput techniques. However, the functional characterization of these new proteins was not incremented in the same proportion. To fill this gap, a large number of computational methods have been proposed in the literature. Early approaches have explored homology relationships to associate known functions to the newly discovered proteins. Nevertheless, these approaches tend to fail when a new protein is considerably different (divergent) from previously known ones. Accordingly, more accurate approaches, that use expressive data representation and explore sophisticate computational techniques are required. Regarding these points, this review provides a comprehensible description of machine learning approaches that are currently applied to protein function prediction problems. We start by defining several problems enrolled in understanding protein function aspects, and describing how machine learning can be applied to these problems. We aim to expose, in a systematical framework, the role of these techniques in protein function inference, sometimes difficult to follow up due to the rapid evolvement of the field. With this purpose in mind, we highlight the most representative contributions, the recent advancements, and provide an insightful categorization and classification of machine learning methods in functional proteomics.

  13. How does a lower predictability of lane changes affect performance in the Lane Change Task?

    PubMed

    Petzoldt, Tibor; Krems, Josef F

    2014-07-01

    The Lane Change Task (LCT) is an established method to assess driver distraction caused by secondary tasks. In the LCT ISO standard, "course following and maneuvering" and "event detection" are mentioned as central task properties. Especially event detection seems to be a reasonable feature, as research suggests that distraction has profound effects on drivers' reactions to sudden, unexpected events. However, closer inspection of the LCT reveals that the events to be detected (lane change signs) and the required response are highly predictable. To investigate how the LCT's distraction assessment of secondary tasks might change if lane change events and responses were less predictable, we implemented three different versions of the LCT - an "original" one, a second one with lowered predictability of event position, and a third one with lowered predictability of event position and response. We tested each of these implementations with the same set of visual and cognitive secondary tasks of varying demand. The results showed that a decrease in predictability resulted in overall degraded performance in the LCT when using the basic lane change model for analysis. However, all secondary task conditions suffered equally. No differential effects were found. We conclude that although an ISO conforming implementation of the LCT might not be excessively valid regarding its depiction of safety relevant events, the results obtained are nevertheless comparable to what would be found in settings of higher validity.

  14. Predicting plants -modeling traits as a function of environment

    NASA Astrophysics Data System (ADS)

    Franklin, Oskar

    2016-04-01

    A central problem in understanding and modeling vegetation dynamics is how to represent the variation in plant properties and function across different environments. Addressing this problem there is a strong trend towards trait-based approaches, where vegetation properties are functions of the distributions of functional traits rather than of species. Recently there has been enormous progress in in quantifying trait variability and its drivers and effects (Van Bodegom et al. 2012; Adier et al. 2014; Kunstler et al. 2015) based on wide ranging datasets on a small number of easily measured traits, such as specific leaf area (SLA), wood density and maximum plant height. However, plant function depends on many other traits and while the commonly measured trait data are valuable, they are not sufficient for driving predictive and mechanistic models of vegetation dynamics -especially under novel climate or management conditions. For this purpose we need a model to predict functional traits, also those not easily measured, and how they depend on the plants' environment. Here I present such a mechanistic model based on fitness concepts and focused on traits related to water and light limitation of trees, including: wood density, drought response, allocation to defense, and leaf traits. The model is able to predict observed patterns of variability in these traits in relation to growth and mortality, and their responses to a gradient of water limitation. The results demonstrate that it is possible to mechanistically predict plant traits as a function of the environment based on an eco-physiological model of plant fitness. References Adier, P.B., Salguero-Gómez, R., Compagnoni, A., Hsu, J.S., Ray-Mukherjee, J., Mbeau-Ache, C. et al. (2014). Functional traits explain variation in plant lifehistory strategies. Proc. Natl. Acad. Sci. U. S. A., 111, 740-745. Kunstler, G., Falster, D., Coomes, D.A., Hui, F., Kooyman, R.M., Laughlin, D.C. et al. (2015). Plant functional traits

  15. Concurrent and Predictive Relations between Hormone Levels and Social-Emotional Functioning in Early Adolescence.

    ERIC Educational Resources Information Center

    Nottelmann, Editha D.; And Others

    Hormone levels and changes in hormone levels were evaluated three times across a 1-year period as concurrent and predictive correlates of the socio-emotional functioning of 56 boys 10- to 14-years-old and 52 girls 9- to 14-years-old who represented the five stages of Tanner's criteria of pubertal development. The hormone measures were serum levels…

  16. Predicting changes in adjustment using repeated measures of sociometric status.

    PubMed

    Mayeux, Lara; Bellmore, Amy D; Cillessen, Antonius H N

    2007-12-01

    The authors' goals in the study were to investigate the possible gains made by including multiple assessments of status in the prediction of change in psychosocial adjustment and to compare the effectiveness of continuous and categorical measures of peer status in predicting adjustment. The authors obtained continuous and categorical measures of status (social preference and rejected status) for 644 Grade 4 students at 3 points within 1 school year (fall, winter, and spring). The authors measured peer, teacher, and self-report indexes of social adjustment (including aggression, anxiety, and sociability) in Grades 4 and 5. Both measures of peer status at all 3 time points in Grade 4 were significant predictors of adjustment in Grade 5, controlling for Grade 4 levels, with the midyear (i.e., winter) assessment showing a slight predictive advantage over the fall and spring assessments. Children who were classified as peer rejected over multiple assessments had more social adjustment problems in the next school year than did children who were classified as peer rejected at 1 time point only. The authors discuss these findings in terms of the utility of multiple assessments of both continuous and categorical measures of peer status for predicting later outcomes.

  17. Challenges in predicting climate change impacts on pome fruit phenology

    NASA Astrophysics Data System (ADS)

    Darbyshire, Rebecca; Webb, Leanne; Goodwin, Ian; Barlow, E. W. R.

    2014-08-01

    Climate projection data were applied to two commonly used pome fruit flowering models to investigate potential differences in predicted full bloom timing. The two methods, fixed thermal time and sequential chill-growth, produced different results for seven apple and pear varieties at two Australian locations. The fixed thermal time model predicted incremental advancement of full bloom, while results were mixed from the sequential chill-growth model. To further investigate how the sequential chill-growth model reacts under climate perturbed conditions, four simulations were created to represent a wider range of species physiological requirements. These were applied to five Australian locations covering varied climates. Lengthening of the chill period and contraction of the growth period was common to most results. The relative dominance of the chill or growth component tended to predict whether full bloom advanced, remained similar or was delayed with climate warming. The simplistic structure of the fixed thermal time model and the exclusion of winter chill conditions in this method indicate it is unlikely to be suitable for projection analyses. The sequential chill-growth model includes greater complexity; however, reservations in using this model for impact analyses remain. The results demonstrate that appropriate representation of physiological processes is essential to adequately predict changes to full bloom under climate perturbed conditions with greater model development needed.

  18. Predicting evolutionary responses to climate change in the sea.

    PubMed

    Munday, Philip L; Warner, Robert R; Monro, Keyne; Pandolfi, John M; Marshall, Dustin J

    2013-12-01

    An increasing number of short-term experimental studies show significant effects of projected ocean warming and ocean acidification on the performance on marine organisms. Yet, it remains unclear if we can reliably predict the impact of climate change on marine populations and ecosystems, because we lack sufficient understanding of the capacity for marine organisms to adapt to rapid climate change. In this review, we emphasise why an evolutionary perspective is crucial to understanding climate change impacts in the sea and examine the approaches that may be useful for addressing this challenge. We first consider what the geological record and present-day analogues of future climate conditions can tell us about the potential for adaptation to climate change. We also examine evidence that phenotypic plasticity may assist marine species to persist in a rapidly changing climate. We then outline the various experimental approaches that can be used to estimate evolutionary potential, focusing on molecular tools, quantitative genetics, and experimental evolution, and we describe the benefits of combining different approaches to gain a deeper understanding of evolutionary potential. Our goal is to provide a platform for future research addressing the evolutionary potential for marine organisms to cope with climate change.

  19. White matter morphometric changes uniquely predict children's reading acquisition.

    PubMed

    Myers, Chelsea A; Vandermosten, Maaike; Farris, Emily A; Hancock, Roeland; Gimenez, Paul; Black, Jessica M; Casto, Brandi; Drahos, Miroslav; Tumber, Mandeep; Hendren, Robert L; Hulme, Charles; Hoeft, Fumiko

    2014-10-01

    This study examined whether variations in brain development between kindergarten and Grade 3 predicted individual differences in reading ability at Grade 3. Structural MRI measurements indicated that increases in the volume of two left temporo-parietal white matter clusters are unique predictors of reading outcomes above and beyond family history, socioeconomic status, and cognitive and preliteracy measures at baseline. Using diffusion MRI, we identified the left arcuate fasciculus and superior corona radiata as key fibers within the two clusters. Bias-free regression analyses using regions of interest from prior literature revealed that volume changes in temporo-parietal white matter, together with preliteracy measures, predicted 56% of the variance in reading outcomes. Our findings demonstrate the important contribution of developmental differences in areas of left dorsal white matter, often implicated in phonological processing, as a sensitive early biomarker for later reading abilities, and by extension, reading difficulties.

  20. Protein function prediction using local 3D templates.

    PubMed

    Laskowski, Roman A; Watson, James D; Thornton, Janet M

    2005-08-19

    The prediction of a protein's function from its 3D structure is becoming more and more important as the worldwide structural genomics initiatives gather pace and continue to solve 3D structures, many of which are of proteins of unknown function. Here, we present a methodology for predicting function from structure that shows great promise. It is based on 3D templates that are defined as specific 3D conformations of small numbers of residues. We use four types of template, covering enzyme active sites, ligand-binding residues, DNA-binding residues and reverse templates. The latter are templates generated from the target structure itself and scanned against a representative subset of all known protein structures. Together, the templates provide a fairly thorough coverage of the known structures and ensure that if there is a match to a known structure it is unlikely to be missed. A new scoring scheme provides a highly sensitive means of discriminating between true positive and false positive template matches. In all, the methodology provides a powerful new tool for function prediction to complement those already in use.

  1. Predicting when climate-driven phenotypic change affects population dynamics.

    PubMed

    McLean, Nina; Lawson, Callum R; Leech, Dave I; van de Pol, Martijn

    2016-06-01

    Species' responses to climate change are variable and diverse, yet our understanding of how different responses (e.g. physiological, behavioural, demographic) relate and how they affect the parameters most relevant for conservation (e.g. population persistence) is lacking. Despite this, studies that observe changes in one type of response typically assume that effects on population dynamics will occur, perhaps fallaciously. We use a hierarchical framework to explain and test when impacts of climate on traits (e.g. phenology) affect demographic rates (e.g. reproduction) and in turn population dynamics. Using this conceptual framework, we distinguish four mechanisms that can prevent lower-level responses from impacting population dynamics. Testable hypotheses were identified from the literature that suggest life-history and ecological characteristics which could predict when these mechanisms are likely to be important. A quantitative example on birds illustrates how, even with limited data and without fully-parameterized population models, new insights can be gained; differences among species in the impacts of climate-driven phenological changes on population growth were not explained by the number of broods or density dependence. Our approach helps to predict the types of species in which climate sensitivities of phenotypic traits have strong demographic and population consequences, which is crucial for conservation prioritization of data-deficient species.

  2. Postpartum Sexual Functioning and Its Predicting Factors among Iranian Women

    PubMed Central

    Rezaei, Nazanin; Azadi, Arman; Sayehmiri, Kourosh; Valizadeh, Reza

    2017-01-01

    Background Many women experience sexual dysfunction following childbirth but this has not been well investigated in Iran. The aim of this study was to evaluate women’s sexual function in the postpartum period in Iran. It also sought to determine predicting factors associated with their sexual function. Methods This was a cross-sectional study among 380 postpartum women attending 10 urban health centers in Ilam province in southwestern Iran. Participants were selected using random cluster sampling. Data was collected using the female sexual function index (FSFI) and a checklist of socio-demographic and maternal status for each of the women. Sexual dysfunction was classified according to an FSFI score of ≤ 28. Data were analysed using SPSS version 22. Results The majority of participants (76.3%) had sexual dysfunction. Primiparity (adjusted odds ratio (aOR): 1.78 (95% Confidence Interval (CI): 1.11, 2.94); P = 0.006) and exclusive breastfeeding (aOR: 2.47 (95% CI: 1.21, 5.03); P = 0.012) were associated with increased odds of experiencing sexual dysfunction in the postpartum period. Other factors such as age, type of delivery, education, time since delivery and family income did not predict women’s postpartum sexual function. Conclusion This study confirmed findings of previous studies on factors that may have an adverse effect on new mothers’ sexual function in the postpartum period. However the effect of type of delivery on postpartum sexual function remains unclear. PMID:28381932

  3. Quantitative assessment of protein function prediction from metagenomics shotgun sequences.

    PubMed

    Harrington, E D; Singh, A H; Doerks, T; Letunic, I; von Mering, C; Jensen, L J; Raes, J; Bork, P

    2007-08-28

    To assess the potential of protein function prediction in environmental genomics data, we analyzed shotgun sequences from four diverse and complex habitats. Using homology searches as well as customized gene neighborhood methods that incorporate intergenic and evolutionary distances, we inferred specific functions for 76% of the 1.4 million predicted ORFs in these samples (83% when nonspecific functions are considered). Surprisingly, these fractions are only slightly smaller than the corresponding ones in completely sequenced genomes (83% and 86%, respectively, by using the same methodology) and considerably higher than previously thought. For as many as 75,448 ORFs (5% of the total), only neighborhood methods can assign functions, illustrated here by a previously undescribed gene associated with the well characterized heme biosynthesis operon and a potential transcription factor that might regulate a coupling between fatty acid biosynthesis and degradation. Our results further suggest that, although functions can be inferred for most proteins on earth, many functions remain to be discovered in numerous small, rare protein families.

  4. Predicting Species-environment Relationships with Functional Traits for the Understory Flora of Wisconsin

    NASA Astrophysics Data System (ADS)

    Ash, J.; Li, D.; Johnson, S.; Rogers, D. A.; Waller, D. M.

    2015-12-01

    Understanding the processes that structure species' abundance patterns is a central problem in ecology, both for explaining current species' distributions and predicting future changes. Environmental gradients affect species' distribution patterns with these responses likely depending on species' functional traits. Thus, tracking shifts in species' traits can provide insight into the mechanisms by which species respond to dynamic environmental conditions. We examined how functional traits are associated with long-term changes in the distribution and abundance of understory plants in Wisconsin forests over the last 50+ years. We relied on detailed surveys and resurveys of the same Wisconsin forest plots, data on 12 functional traits, and site-level environmental variables including soil and climate conditions. We then related changes in the abundance of 293 species across a network of 249 sites to these environmental variables and explored whether functional traits served to predict these relationships using multilevel models. Species abundance patterns were strongly related to variation in environmental conditions among sites, but species appear to be responding to distinct sets of environmental variables. Functional traits only weakly predicted these species-environment relationships, limiting our ability to generalize these results to other systems. Nonetheless, understanding how traits interact with environmental gradients to structure species distribution patterns helps us to disentangle the drivers of ecological change across diverse landscapes.

  5. Changes in monocyte functions of astronauts.

    PubMed

    Kaur, Indreshpal; Simons, Elizabeth R; Castro, Victoria A; Ott, C Mark; Pierson, Duane L

    2005-11-01

    As part of the systematic evaluation of the innate immune system for long duration missions, this study focused on the antimicrobial functions of monocytes in astronauts participating in spaceflight. The study included four space shuttle missions and 25 astronauts. Nine non-astronauts served as controls. Blood specimens were collected 10 days before launch, within 3h after landing, and again 3 days after landing. The number of monocytes did not differ significantly over the interval sampled in both the astronaut or control groups. However, following 5-11 days of spaceflight, the astronauts' monocytes exhibited reductions in ability to engulf Escherichia coli, elicit an oxidative burst, and degranulate. The phagocytic index was significantly reduced following spaceflight when compared to control values. This reduction in phagocytosis was accompanied by changes in the expression of two surface markers involved in phagocytosis, CD32 and CD64. Levels of cortisol, epinephrine, and norepinephrine after spaceflight did not increase over preflight values.

  6. Catchment Prediction In Changing Environments (CAPICHE): A collaborative experiment in an open water science laboratory

    NASA Astrophysics Data System (ADS)

    Hutton, Christopher; Wagener, Thorsten; Freer, Jim; Han, Dawei

    2015-04-01

    Predicting the function of hydrological systems under near-stationary conditions faces a number of challenges due to incomplete system understanding, and uncertainty in models and measurements. However, due to changes in climate, land use/land cover, and water demand, the hydrological function of many catchments cannot be considered as stationary. Such changes make modelling catchment systems more difficult, as models need to account for non-stationary forcing and boundary conditions, which in turn can change internal catchment function, and the states and processes that dominate hydrological response. In addition, such models may need to be used to make predictions beyond a range of conditions for which they were originally calibrated. Despite these problems, deriving accurate hydrological predictions under changing conditions is increasingly important for future water resource and flood hazard assessment. Simulating catchments under changing conditions may require more complex distributed models in order to adequately represent spatial changes in boundary conditions (e.g. land cover change). However, the potential for complex models to address these issues cannot be realised in many places because of data problems, which may result from a lack of data, data access issues, and time-consuming problems in bringing diverse sources of data together and into a useable format. A greater understanding of the link between model complexity and data is required to make appropriate modelling choices. Virtual water science laboratories offer the ideal opportunity to explore the issues of model complexity and data availability in the context of predictions under changing environments because they: (1) provide an opportunity to share open data; (2) provide a platform to compare different models; (3) facilitate collaboration between different modelling research groups. This paper introduces a new collaborative experiment, conducted in an open virtual water science laboratory as

  7. Plant functional traits predict green roof ecosystem services.

    PubMed

    Lundholm, Jeremy; Tran, Stephanie; Gebert, Luke

    2015-02-17

    Plants make important contributions to the services provided by engineered ecosystems such as green roofs. Ecologists use plant species traits as generic predictors of geographical distribution, interactions with other species, and ecosystem functioning, but this approach has been little used to optimize engineered ecosystems. Four plant species traits (height, individual leaf area, specific leaf area, and leaf dry matter content) were evaluated as predictors of ecosystem properties and services in a modular green roof system planted with 21 species. Six indicators of ecosystem services, incorporating thermal, hydrological, water quality, and carbon sequestration functions, were predicted by the four plant traits directly or indirectly via their effects on aggregate ecosystem properties, including canopy density and albedo. Species average height and specific leaf area were the most useful traits, predicting several services via effects on canopy density or growth rate. This study demonstrates that easily measured plant traits can be used to select species to optimize green roof performance across multiple key services.

  8. PROSNET: INTEGRATING HOMOLOGY WITH MOLECULAR NETWORKS FOR PROTEIN FUNCTION PREDICTION

    PubMed Central

    Wang, Sheng; Qu, Meng

    2016-01-01

    Automated annotation of protein function has become a critical task in the post-genomic era. Network-based approaches and homology-based approaches have been widely used and recently tested in large-scale community-wide assessment experiments. It is natural to integrate network data with homology information to further improve the predictive performance. However, integrating these two heterogeneous, high-dimensional and noisy datasets is non-trivial. In this work, we introduce a novel protein function prediction algorithm ProSNet. An integrated heterogeneous network is first built to include molecular networks of multiple species and link together homologous proteins across multiple species. Based on this integrated network, a dimensionality reduction algorithm is introduced to obtain compact low-dimensional vectors to encode proteins in the network. Finally, we develop machine learning classification algorithms that take the vectors as input and make predictions by transferring annotations both within each species and across different species. Extensive experiments on five major species demonstrate that our integration of homology with molecular networks substantially improves the predictive performance over existing approaches. PMID:27896959

  9. Systematic prediction of gene function in Arabidopsis thaliana using a probabilistic functional gene network

    PubMed Central

    Hwang, Sohyun; Rhee, Seung Y; Marcotte, Edward M; Lee, Insuk

    2012-01-01

    AraNet is a functional gene network for the reference plant Arabidopsis and has been constructed in order to identify new genes associated with plant traits. It is highly predictive for diverse biological pathways and can be used to prioritize genes for functional screens. Moreover, AraNet provides a web-based tool with which plant biologists can efficiently discover novel functions of Arabidopsis genes (http://www.functionalnet.org/aranet/). This protocol explains how to conduct network-based prediction of gene functions using AraNet and how to interpret the prediction results. Functional discovery in plant biology is facilitated by combining candidate prioritization by AraNet with focused experimental tests. PMID:21886106

  10. Optimizing Non-Decomposable Loss Functions in Structured Prediction

    PubMed Central

    Ranjbar, Mani; Lan, Tian; Wang, Yang; Robinovitch, Steven N.; Li, Ze-Nian; Mori, Greg

    2012-01-01

    We develop an algorithm for structured prediction with non-decomposable performance measures. The algorithm learns parameters of Markov random fields and can be applied to multivariate performance measures. Examples include performance measures such as Fβ score (natural language processing), intersection over union (object category segmentation), Precision/Recall at k (search engines) and ROC area (binary classifiers). We attack this optimization problem by approximating the loss function with a piecewise linear function. The loss augmented inference forms a quadratic program (QP), which we solve using LP relaxation. We apply this approach to two tasks: object class-specific segmentation and human action retrieval from videos. We show significant improvement over baseline approaches that either use simple loss functions or simple scoring functions on the PASCAL VOC and H3D Segmentation datasets, and a nursing home action recognition dataset. PMID:22868650

  11. Change in BMI Accurately Predicted by Social Exposure to Acquaintances

    PubMed Central

    Oloritun, Rahman O.; Ouarda, Taha B. M. J.; Moturu, Sai; Madan, Anmol; Pentland, Alex (Sandy); Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R2. This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends. PMID

  12. High Precision Prediction of Functional Sites in Protein Structures

    PubMed Central

    Buturovic, Ljubomir; Wong, Mike; Tang, Grace W.; Altman, Russ B.; Petkovic, Dragutin

    2014-01-01

    We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta. PMID:24632601

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

    PubMed

    Widder, Stefanie; Allen, Rosalind J; Pfeiffer, Thomas; Curtis, Thomas P; Wiuf, Carsten; Sloan, William T; Cordero, Otto X; Brown, Sam P; Momeni, Babak; Shou, Wenying; Kettle, Helen; Flint, Harry J; Haas, Andreas F; Laroche, Béatrice; Kreft, Jan-Ulrich; Rainey, Paul B; Freilich, Shiri; Schuster, Stefan; Milferstedt, Kim; van der Meer, Jan R; Groβkopf, Tobias; Huisman, Jef; Free, Andrew; Picioreanu, Cristian; Quince, Christopher; Klapper, Isaac; Labarthe, Simon; Smets, Barth F; Wang, Harris; Soyer, Orkun S

    2016-11-01

    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 with mathematical model building. We discuss specific examples where model-experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.

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

    PubMed Central

    Widder, Stefanie; Allen, Rosalind J; Pfeiffer, Thomas; Curtis, Thomas P; Wiuf, Carsten; Sloan, William T; Cordero, Otto X; Brown, Sam P; Momeni, Babak; Shou, Wenying; Kettle, Helen; Flint, Harry J; Haas, Andreas F; Laroche, Béatrice; Kreft, Jan-Ulrich; Rainey, Paul B; Freilich, Shiri; Schuster, Stefan; Milferstedt, Kim; van der Meer, Jan R; Groβkopf, Tobias; Huisman, Jef; Free, Andrew; Picioreanu, Cristian; Quince, Christopher; Klapper, Isaac; Labarthe, Simon; Smets, Barth F; Wang, Harris; Soyer, Orkun 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 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 with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved. PMID:27022995

  15. Should we believe model predictions of future climate change? (Invited)

    NASA Astrophysics Data System (ADS)

    Knutti, R.

    2009-12-01

    As computers get faster and our understanding of the climate system improves, climate models to predict the future are getting more complex by including more and more processes, and they are run at higher and higher resolution to resolve more of the small scale processes. As a result, some of the simulated features and structures, e.g. ocean eddies or tropical cyclones look surprisingly real. But are these deceptive? A pattern can look perfectly real but be in the wrong place. So can the current global models really provide the kind of information on local scales and on the quantities (e.g. extreme events) that the decision maker would need to know to invest for example in adaptation? A closer look indicates that evaluating skill of climate models and quantifying uncertainties in predictions is very difficult. This presentation shows that while models are improving in simulating the climate features we observe (e.g. the present day mean state, or the El Nino Southern Oscillation), the spread from multiple models in predicting future changes is often not decreasing. The main problem is that (unlike with weather forecasts for example) we cannot evaluate the model on a prediction (for example for the year 2100) and we have to use the present, or past changes as metrics of skills. But there are infinite ways of testing a model, and many metrics used to test models do not clearly relate to the prediction. Therefore there is little agreement in the community on metrics to separate ‘good’ and ‘bad’ models, and there is a concern that model development, evaluation and posterior weighting or ranking of models are all using the same datasets. While models are continuously improving in representing what we believe to be the key processes, many models also share ideas, parameterizations or even pieces of model code. The current models can therefore not be considered independent. Robustness of a model simulated result is often interpreted as increasing the confidence

  16. An application of site response functions to ground motion prediction

    NASA Astrophysics Data System (ADS)

    Tsuda, K.; Archuleta, R.; Steidl, J.; Koketsu, K.

    2006-12-01

    The prediction of ground motion from large future earthquakes is very important for hazard mitigation in urban areas of Japan. Because the observed ground motions are affected by three factors; the seismic source, attenuation (quality factor) of seismic wave propagation inside the earth, and the effects of the local surface geology, understanding each factor is essential for the ground motion prediction. The effect of surface geology (local soil conditions) on ground motions was documented as early as the 1906 San Francisco earthquake. The correlation between soil type and the degree of damage was again recognized in the 1923 Kanto earthquake. Additionally, accelerometer records from almost all recent large events also have reinforced the role of site effects in the level of strong shaking. Because most cities in Japan are located on thick sedimentary basins, accounting for site response is essential for realistic predictions of ground motion. However, predicting ground motion has uncertainties that arise from all three factors: source, path, and site. The analysis of well-recorded data from dense seismograph arrays can reduce these uncertainties for ground motion prediction. The new technique presented here provides a site response correlation function for estimation of the spatial distribution of site response. This function is based on the known site responses at instrumented sites and is used to estimate the site response at a site for which there is no instrumental records. We initially predict the level of ground motion by using this estimate with the assumption of linear wave propagation. This method is applied to the data from a relatively dense seismic array located near the city of Sendai, Japan by using moderate sized earthquakes with small ground motion levels to estimate linear site response. The array consists of 29 stations: 20 managed by Tohoku Institute of Technology, 6 by Building Research Institute, and 3 by NIED within an area of 20 x 30 km

  17. Predicting the Impacts of Climate Change on Central American Agriculture

    NASA Astrophysics Data System (ADS)

    Winter, J. M.; Ruane, A. C.; Rosenzweig, C.

    2011-12-01

    Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.

  18. Does Change on the MOLEST and RAPE Scales Predict Sexual Recidivism?

    PubMed

    Nunes, Kevin L; Pettersen, Cathrine; Hermann, Chantal A; Looman, Jan; Spape, Jessica

    2016-08-01

    The purpose of the current study was to examine whether the MOLEST and RAPE scales and change on these measures predicted sexual recidivism in a sample of 146 adult male sexual offenders who participated in a high-intensity treatment program while incarcerated. The majority of subjects had functional scores on the MOLEST and RAPE scales prior to treatment. Of those who had dysfunctional pre-treatment scores, the majority made significant gains. However, the MOLEST and RAPE scales did not significantly predict sexual recidivism. This was the case for pre-treatment scores, post-treatment scores, and change scores. Our findings are generally not consistent with the view that these measures assess dynamic risk factors for sexual recidivism. However, this is the first published study to examine the predictive validity of these scales and more rigorous research is needed before firm conclusions can be drawn.

  19. Predicting implementation from organizational readiness for change: a study protocol

    PubMed Central

    2011-01-01

    Background There is widespread interest in measuring organizational readiness to implement evidence-based practices in clinical care. However, there are a number of challenges to validating organizational measures, including inferential bias arising from the halo effect and method bias - two threats to validity that, while well-documented by organizational scholars, are often ignored in health services research. We describe a protocol to comprehensively assess the psychometric properties of a previously developed survey, the Organizational Readiness to Change Assessment. Objectives Our objective is to conduct a comprehensive assessment of the psychometric properties of the Organizational Readiness to Change Assessment incorporating methods specifically to address threats from halo effect and method bias. Methods and Design We will conduct three sets of analyses using longitudinal, secondary data from four partner projects, each testing interventions to improve the implementation of an evidence-based clinical practice. Partner projects field the Organizational Readiness to Change Assessment at baseline (n = 208 respondents; 53 facilities), and prospectively assesses the degree to which the evidence-based practice is implemented. We will conduct predictive and concurrent validities using hierarchical linear modeling and multivariate regression, respectively. For predictive validity, the outcome is the change from baseline to follow-up in the use of the evidence-based practice. We will use intra-class correlations derived from hierarchical linear models to assess inter-rater reliability. Two partner projects will also field measures of job satisfaction for convergent and discriminant validity analyses, and will field Organizational Readiness to Change Assessment measures at follow-up for concurrent validity (n = 158 respondents; 33 facilities). Convergent and discriminant validities will test associations between organizational readiness and different aspects of job

  20. A set of nearest neighbor parameters for predicting the enthalpy change of RNA secondary structure formation

    PubMed Central

    Lu, Zhi John; Turner, Douglas H.; Mathews, David H.

    2006-01-01

    A complete set of nearest neighbor parameters to predict the enthalpy change of RNA secondary structure formation was derived. These parameters can be used with available free energy nearest neighbor parameters to extend the secondary structure prediction of RNA sequences to temperatures other than 37°C. The parameters were tested by predicting the secondary structures of sequences with known secondary structure that are from organisms with known optimal growth temperatures. Compared with the previous set of enthalpy nearest neighbor parameters, the sensitivity of base pair prediction improved from 65.2 to 68.9% at optimal growth temperatures ranging from 10 to 60°C. Base pair probabilities were predicted with a partition function and the positive predictive value of structure prediction is 90.4% when considering the base pairs in the lowest free energy structure with pairing probability of 0.99 or above. Moreover, a strong correlation is found between the predicted melting temperatures of RNA sequences and the optimal growth temperatures of the host organism. This indicates that organisms that live at higher temperatures have evolved RNA sequences with higher melting temperatures. PMID:16982646

  1. Early Improvement in Psychosocial Function Predicts Longer-Term Symptomatic Remission in Depressed Patients

    PubMed Central

    Jha, Manish K.; Minhajuddin, Abu; Greer, Tracy L.; Carmody, Thomas; Rush, Augustus John

    2016-01-01

    The goal of this study was to evaluate the relationship between early change in psychosocial function independent of depression severity and longer-term symptomatic remission. Participants of Combining Medications to Enhance Depression Outcomes trial were randomly selected for model selection (n = 334) and validation (n = 331). Changes in psychosocial function (Work and Social Adjustment Scale, WSAS) from baseline to week 6 were assessed and two data-driven sub-groups of WSAS change were identified in the randomly selected model selection half. Results of analyses to predict symptomatic remission at 3 and 7 months were validated for these sub-groups in the second half (validation sample). From baseline to week 6, psychosocial function improved significantly even after adjusting for depression severity at each visit and select baseline variables (age, gender, race, ethnicity, education, income, employment, depression onset before age 18, anxious features, and suicidal ideation), treatment-arm, and WSAS score. The WSAS change patterns identified two (early improvement and gradual change) subgroups. After adjusting for baseline variables and remission status at week 6, participants with early improvement in the second half (validation sample) had greater remission rates than those with gradual change at both 3 (3.3 times) and 7 months (2.3 times) following acute treatment initiation. In conclusion, early improvement in psychosocial function provides a clinically meaningful prediction of longer-term symptomatic remission, independent of depression symptom severity. PMID:28030546

  2. Multitrophic functional diversity predicts ecosystem functioning in experimental assemblages of estuarine consumers.

    PubMed

    Lefcheck, Jonathan S; Duffy, J Emmett

    2015-11-01

    The use of functional traits to explain how biodiversity affects ecosystem functioning has attracted intense interest, yet few studies have a priori altered functional diversity, especially in multitrophic communities. Here, we manipulated multivariate functional diversity of estuarine grazers and predators within multiple levels of species richness to test how species richness and functional diversity predicted ecosystem functioning in a multitrophic food web. Community functional diversity was a better predictor than species richness for the majority of ecosystem properties, based on generalized linear mixed-effects models. Combining inferences from eight traits into a single multivariate index increased prediction accuracy of these models relative to any individual trait. Structural equation modeling revealed that functional diversity of both grazers and predators was important in driving final biomass within trophic levels, with stronger effects observed for predators. We also show that different species drove different ecosystem responses, with evidence for both sampling effects and complementarity. Our study extends experimental investigations of functional trait diversity to a multilevel food web, and demonstrates that functional diversity can be more accurate and effective than species richness in predicting community biomass in a food web context.

  3. Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

    PubMed Central

    Wong, Aloysius; Gehring, Chris; Irving, Helen R.

    2015-01-01

    Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers. PMID:26106597

  4. Predicting impacts of climate change on Fasciola hepatica risk.

    PubMed

    Fox, Naomi J; White, Piran C L; McClean, Colin J; Marion, Glenn; Evans, Andy; Hutchings, Michael R

    2011-01-10

    Fasciola hepatica (liver fluke) is a physically and economically devastating parasitic trematode whose rise in recent years has been attributed to climate change. Climate has an impact on the free-living stages of the parasite and its intermediate host Lymnaea truncatula, with the interactions between rainfall and temperature having the greatest influence on transmission efficacy. There have been a number of short term climate driven forecasts developed to predict the following season's infection risk, with the Ollerenshaw index being the most widely used. Through the synthesis of a modified Ollerenshaw index with the UKCP09 fine scale climate projection data we have developed long term seasonal risk forecasts up to 2070 at a 25 km square resolution. Additionally UKCIP gridded datasets at 5 km square resolution from 1970-2006 were used to highlight the climate-driven increase to date. The maps show unprecedented levels of future fasciolosis risk in parts of the UK, with risk of serious epidemics in Wales by 2050. The seasonal risk maps demonstrate the possible change in the timing of disease outbreaks due to increased risk from overwintering larvae. Despite an overall long term increase in all regions of the UK, spatio-temporal variation in risk levels is expected. Infection risk will reduce in some areas and fluctuate greatly in others with a predicted decrease in summer infection for parts of the UK due to restricted water availability. This forecast is the first approximation of the potential impacts of climate change on fasciolosis risk in the UK. It can be used as a basis for indicating where active disease surveillance should be targeted and where the development of improved mitigation or adaptation measures is likely to bring the greatest benefits.

  5. Timing Correlations in Proteins Predict Functional Modules and Dynamic Allostery.

    PubMed

    Lin, Milo M

    2016-04-20

    How protein structure encodes functionality is not fully understood. For example, long-range intraprotein communication can occur without measurable conformational change and is often not captured by existing structural correlation functions. It is shown here that important functional information is encoded in the timing of protein motions, rather than motion itself. I introduce the conditional activity function to quantify such timing correlations among the degrees of freedom within proteins. For three proteins, the conditional activities between side-chain dihedral angles were computed using the output of microseconds-long atomistic simulations. The new approach demonstrates that a sparse fraction of side-chain pairs are dynamically correlated over long distances (spanning protein lengths up to 7 nm), in sharp contrast to structural correlations, which are short-ranged (<1 nm). Regions of high self- and inter-side-chain dynamical correlations are found, corresponding to experimentally determined functional modules and allosteric connections, respectively.

  6. Models for predicting objective function weights in prostate cancer IMRT

    SciTech Connect

    Boutilier, Justin J. Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.

    2015-04-15

    Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

  7. Community-Wide Evaluation of Computational Function Prediction.

    PubMed

    Friedberg, Iddo; Radivojac, Predrag

    2017-01-01

    A biological experiment is the most reliable way of assigning function to a protein. However, in the era of high-throughput sequencing, scientists are unable to carry out experiments to determine the function of every single gene product. Therefore, to gain insights into the activity of these molecules and guide experiments, we must rely on computational means to functionally annotate the majority of sequence data. To understand how well these algorithms perform, we have established a challenge involving a broad scientific community in which we evaluate different annotation methods according to their ability to predict the associations between previously unannotated protein sequences and Gene Ontology terms. Here we discuss the rationale, benefits, and issues associated with evaluating computational methods in an ongoing community-wide challenge.

  8. Cognitive Function and Prediction of Dementia in Old Age.

    ERIC Educational Resources Information Center

    La Rue, Asenath; Jarvik, Lissy F.

    1987-01-01

    Examined longitudinal changes in cognitive functioning for aging twins. Found that those who were considered demented in old age had achieved lower test scores 20 years prior to diagnosis and experienced greater declines in vocabulary and forward digit span over time than those without dementia. Suggests that dementia may develop very slowly.…

  9. Multidimensional prediction of treatment response to antidepressants with cognitive control and functional MRI.

    PubMed

    Crane, Natania A; Jenkins, Lisanne M; Bhaumik, Runa; Dion, Catherine; Gowins, Jennifer R; Mickey, Brian J; Zubieta, Jon-Kar; Langenecker, Scott A

    2017-02-01

    Predicting treatment response for major depressive disorder can provide a tremendous benefit for our overstretched health care system by reducing number of treatments and time to remission, thereby decreasing morbidity. The present study used neural and performance predictors during a cognitive control task to predict treatment response (% change in Hamilton Depression Rating Scale pre- to post-treatment). Forty-nine individuals diagnosed with major depressive disorder were enrolled with intent to treat in the open-label study; 36 completed treatment, had useable data, and were included in most data analyses. Participants included in the data analysis sample received treatment with escitalopram (n = 22) or duloxetine (n = 14) for 10 weeks. Functional MRI and performance during a Parametric Go/No-go test were used to predict per cent reduction in Hamilton Depression Rating Scale scores after treatment. Haemodynamic response function-based contrasts and task-related independent components analysis (subset of sample: n = 29) were predictors. Independent components analysis component beta weights and haemodynamic response function modelling activation during Commission errors in the rostral and dorsal anterior cingulate, mid-cingulate, dorsomedial prefrontal cortex, and lateral orbital frontal cortex predicted treatment response. In addition, more commission errors on the task predicted better treatment response. Together in a regression model, independent component analysis, haemodynamic response function-modelled, and performance measures predicted treatment response with 90% accuracy (compared to 74% accuracy with clinical features alone), with 84% accuracy in 5-fold, leave-one-out cross-validation. Convergence between performance markers and functional magnetic resonance imaging, including novel independent component analysis techniques, achieved high accuracy in prediction of treatment response for major depressive disorder. The strong link to a task paradigm

  10. Marijuana Use Predicts Cognitive Performance on Tasks of Executive Function

    PubMed Central

    Dahlgren, Mary Kathryn; Sagar, Kelly A.; Racine, Megan T.; Dreman, Meredith W.; Gruber, Staci A.

    2016-01-01

    Objective: Despite growing evidence that chronic marijuana use is associated with cognitive impairment, particularly when use is initiated at an early age, national trends demonstrate significant decreases in the perceived risk of marijuana corresponding with increased use, especially among youth. The current study assessed the impact of marijuana use on executive function and whether patterns of marijuana use, including earlier age at onset, higher frequency, and increased magnitude of use, predict impairment. Method: Forty-four chronic, heavy marijuana smokers (37 male, 7 female) and 32 healthy, nonsmoking control participants (20 male, 12 female) recruited from the Greater Boston area completed two assessments of executive function: the Stroop Color Word Test and Wisconsin Card Sorting Test (WCST). Results: Marijuana smokers had poorer executive function relative to control participants, a between-group difference that was primarily driven by individuals with early onset of marijuana use (before age 16; n = 21); significance remained even when controlling for frequency and magnitude of use. Further, earlier age at marijuana onset and increased marijuana use predicted poorer neurocognitive performance, and perseverative errors on the WCST significantly predicted marijuana group membership. Conclusions: These findings underscore the impact of early onset of marijuana use on executive function impairment independent of increased frequency and magnitude of use. In addition, poorer performance on the WCST may serve as a neuropsychological marker for heavy marijuana users. These results highlight the need for additional research to identify predictors associated with early marijuana use, as exposure to marijuana during a period of developmental vulnerability may result in negative cognitive consequences. PMID:26997188

  11. Traumatic Brain Injury and Neuronal Functionality Changes in Sensory Cortex

    PubMed Central

    Carron, Simone F.; Alwis, Dasuni S.; Rajan, Ramesh

    2016-01-01

    Traumatic brain injury (TBI), caused by direct blows to the head or inertial forces during relative head-brain movement, can result in long-lasting cognitive and motor deficits which can be particularly consequential when they occur in young people with a long life ahead. Much is known of the molecular and anatomical changes produced in TBI but much less is known of the consequences of these changes to neuronal functionality, especially in the cortex. Given that much of our interior and exterior lives are dependent on responsiveness to information from and about the world around us, we have hypothesized that a significant contributor to the cognitive and motor deficits seen after TBI could be changes in sensory processing. To explore this hypothesis, and to develop a model test system of the changes in neuronal functionality caused by TBI, we have examined neuronal encoding of simple and complex sensory input in the rat’s exploratory and discriminative tactile system, the large face macrovibrissae, which feeds to the so-called “barrel cortex” of somatosensory cortex. In this review we describe the short-term and long-term changes in the barrel cortex encoding of whisker motion modeling naturalistic whisker movement undertaken by rats engaged in a variety of tasks. We demonstrate that the most common form of TBI results in persistent neuronal hyperexcitation specifically in the upper cortical layers, likely due to changes in inhibition. We describe the types of cortical inhibitory neurons and their roles and how selective effects on some of these could produce the particular forms of neuronal encoding changes described in TBI, and then generalize to compare the effects on inhibition seen in other forms of brain injury. From these findings we make specific predictions as to how non-invasive extra-cranial electrophysiology can be used to provide the high-precision information needed to monitor and understand the temporal evolution of changes in neuronal

  12. Traumatic Brain Injury and Neuronal Functionality Changes in Sensory Cortex.

    PubMed

    Carron, Simone F; Alwis, Dasuni S; Rajan, Ramesh

    2016-01-01

    Traumatic brain injury (TBI), caused by direct blows to the head or inertial forces during relative head-brain movement, can result in long-lasting cognitive and motor deficits which can be particularly consequential when they occur in young people with a long life ahead. Much is known of the molecular and anatomical changes produced in TBI but much less is known of the consequences of these changes to neuronal functionality, especially in the cortex. Given that much of our interior and exterior lives are dependent on responsiveness to information from and about the world around us, we have hypothesized that a significant contributor to the cognitive and motor deficits seen after TBI could be changes in sensory processing. To explore this hypothesis, and to develop a model test system of the changes in neuronal functionality caused by TBI, we have examined neuronal encoding of simple and complex sensory input in the rat's exploratory and discriminative tactile system, the large face macrovibrissae, which feeds to the so-called "barrel cortex" of somatosensory cortex. In this review we describe the short-term and long-term changes in the barrel cortex encoding of whisker motion modeling naturalistic whisker movement undertaken by rats engaged in a variety of tasks. We demonstrate that the most common form of TBI results in persistent neuronal hyperexcitation specifically in the upper cortical layers, likely due to changes in inhibition. We describe the types of cortical inhibitory neurons and their roles and how selective effects on some of these could produce the particular forms of neuronal encoding changes described in TBI, and then generalize to compare the effects on inhibition seen in other forms of brain injury. From these findings we make specific predictions as to how non-invasive extra-cranial electrophysiology can be used to provide the high-precision information needed to monitor and understand the temporal evolution of changes in neuronal functionality

  13. Multiscale prediction of patient-specific platelet function under flow.

    PubMed

    Flamm, Matthew H; Colace, Thomas V; Chatterjee, Manash S; Jing, Huiyan; Zhou, Songtao; Jaeger, Daniel; Brass, Lawrence F; Sinno, Talid; Diamond, Scott L

    2012-07-05

    During thrombotic or hemostatic episodes, platelets bind collagen and release ADP and thromboxane A(2), recruiting additional platelets to a growing deposit that distorts the flow field. Prediction of clotting function under hemodynamic conditions for a patient's platelet phenotype remains a challenge. A platelet signaling phenotype was obtained for 3 healthy donors using pairwise agonist scanning, in which calcium dye-loaded platelets were exposed to pairwise combinations of ADP, U46619, and convulxin to activate the P2Y(1)/P2Y(12), TP, and GPVI receptors, respectively, with and without the prostacyclin receptor agonist iloprost. A neural network model was trained on each donor's pairwise agonist scanning experiment and then embedded into a multiscale Monte Carlo simulation of donor-specific platelet deposition under flow. The simulations were compared directly with microfluidic experiments of whole blood flowing over collagen at 200 and 1000/s wall shear rate. The simulations predicted the ranked order of drug sensitivity for indomethacin, aspirin, MRS-2179 (a P2Y(1) inhibitor), and iloprost. Consistent with measurement and simulation, one donor displayed larger clots and another presented with indomethacin resistance (revealing a novel heterozygote TP-V241G mutation). In silico representations of a subject's platelet phenotype allowed prediction of blood function under flow, essential for identifying patient-specific risks, drug responses, and novel genotypes.

  14. Functional traits predict relationship between plant abundance dynamic and long-term climate warming

    PubMed Central

    Soudzilovskaia, Nadejda A.; Elumeeva, Tatiana G.; Onipchenko, Vladimir G.; Shidakov, Islam I.; Salpagarova, Fatima S.; Khubiev, Anzor B.; Tekeev, Dzhamal K.; Cornelissen, Johannes H. C.

    2013-01-01

    Predicting climate change impact on ecosystem structure and services is one of the most important challenges in ecology. Until now, plant species response to climate change has been described at the level of fixed plant functional types, an approach limited by its inflexibility as there is much interspecific functional variation within plant functional types. Considering a plant species as a set of functional traits greatly increases our possibilities for analysis of ecosystem functioning and carbon and nutrient fluxes associated therewith. Moreover, recently assembled large-scale databases hold comprehensive per-species data on plant functional traits, allowing a detailed functional description of many plant communities on Earth. Here, we show that plant functional traits can be used as predictors of vegetation response to climate warming, accounting in our test ecosystem (the species-rich alpine belt of Caucasus mountains, Russia) for 59% of variability in the per-species abundance relation to temperature. In this mountain belt, traits that promote conservative leaf water economy (higher leaf mass per area, thicker leaves) and large investments in belowground reserves to support next year’s shoot buds (root carbon content) were the best predictors of the species increase in abundance along with temperature increase. This finding demonstrates that plant functional traits constitute a highly useful concept for forecasting changes in plant communities, and their associated ecosystem services, in response to climate change. PMID:24145400

  15. Selenium deficiency risk predicted to increase under future climate change.

    PubMed

    Jones, Gerrad D; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P; Seneviratne, Sonia I; Smith, Pete; Winkel, Lenny H E

    2017-03-14

    Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980-1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate-soil interactions. Using moderate climate-change scenarios for 2080-2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate-soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.

  16. Selenium deficiency risk predicted to increase under future climate change

    PubMed Central

    Jones, Gerrad D.; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P.; Seneviratne, Sonia I.; Smith, Pete; Winkel, Lenny H. E.

    2017-01-01

    Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980–1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate–soil interactions. Using moderate climate-change scenarios for 2080–2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate–soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change. PMID:28223487

  17. GOPred: GO Molecular Function Prediction by Combined Classifiers

    PubMed Central

    Saraç, Ömer Sinan; Atalay, Volkan; Cetin-Atalay, Rengul

    2010-01-01

    Functional protein annotation is an important matter for in vivo and in silico biology. Several computational methods have been proposed that make use of a wide range of features such as motifs, domains, homology, structure and physicochemical properties. There is no single method that performs best in all functional classification problems because information obtained using any of these features depends on the function to be assigned to the protein. In this study, we portray a novel approach that combines different methods to better represent protein function. First, we formulated the function annotation problem as a classification problem defined on 300 different Gene Ontology (GO) terms from molecular function aspect. We presented a method to form positive and negative training examples while taking into account the directed acyclic graph (DAG) structure and evidence codes of GO. We applied three different methods and their combinations. Results show that combining different methods improves prediction accuracy in most cases. The proposed method, GOPred, is available as an online computational annotation tool (http://kinaz.fen.bilkent.edu.tr/gopred). PMID:20824206

  18. Changes in neutrophil functions in astronauts.

    PubMed

    Kaur, Indreshpal; Simons, Elizabeth R; Castro, Victoria A; Mark Ott, C; Pierson, Duane L

    2004-09-01

    Exploration class human spaceflight missions will require astronauts with robust immune systems. Innate immunity will be an essential element for the healthcare maintenance of astronauts during these lengthy expeditions. This study investigated neutrophil phagocytosis, oxidative burst, and degranulation of 25 astronauts after four space shuttle missions and in nine healthy control subjects. Space flight duration ranged from 5 to 11 days. Blood specimens were obtained 10 days before launch, immediately after landing, and 3 days after landing. The number of neutrophils increased by 85% at landing compared to preflight levels. The mean values for phagocytosis of Escherichia coli and oxidative burst capacity in neutrophils from astronauts on the 5-day mission were not significantly different from those observed in neutrophils from the control subjects. Before and after 9- to 11-day missions, however, phagocytosis and oxidative burst capacities were significantly lower than control mean values. No consistent changes in degranulation or expression of surface markers were observed before or after any of the space missions. This study indicates that neutrophil phagocytic and oxidative functions are affected by factors associated with space flight and this relationship may depend on mission duration.

  19. Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity

    PubMed Central

    Khalsa, Sakh; Mayhew, Stephen D.; Przezdzik, Izabela; Wilson, Rebecca; Hale, Joanne; Goldstone, Aimee; Bagary, Manny; Bagshaw, Andrew P.

    2016-01-01

    Study Objectives: We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN). Methods: Resting state functional magnetic resonance imaging (fMRI) study using seed-based FC analysis combined with 14-d wrist actigraphy, sleep diaries, and subjective questionnaires (N = 33 healthy adults, mean age 34.3, standard deviation ± 11.6 y). Data were statistically analyzed using multiple linear regression. Fourteen consecutive days of wrist actigraphy in participant's home environment and fMRI scanning on day 14 at the Birmingham University Imaging Centre. Seed-based FC analysis on ICNs from resting-state fMRI data and multiple linear regression analysis performed for each ICN seed and target. cTST was used to predict FC (controlling for age). Results: cTST was specific predictor of intranetwork FC when the mesial prefrontal cortex (MPFC) region of the DMN was used as a seed for FC, with a positive correlation between FC and cTST observed. No significant relationship between FC and cTST was seen for any pair of nodes not including the MPFC. Internetwork FC between the DMN (MPFC) and SN (right anterior insula) was also predicted by cTST, with a negative correlation observed between FC and cTST. Conclusions: This study improves understanding of the relationship between intranetwork and internetwork functional connectivity of intrinsically connected networks (ICNs) in relation to habitual sleep quality and duration. The cumulative amount of sleep that participants achieved over a 14-d period was significantly predictive of intranetwork and inter-network functional connectivity of ICNs, an observation that may underlie the link

  20. iStable: off-the-shelf predictor integration for predicting protein stability changes

    PubMed Central

    2013-01-01

    Background Mutation of a single amino acid residue can cause changes in a protein, which could then lead to a loss of protein function. Predicting the protein stability changes can provide several possible candidates for the novel protein designing. Although many prediction tools are available, the conflicting prediction results from different tools could cause confusion to users. Results We proposed an integrated predictor, iStable, with grid computing architecture constructed by using sequence information and prediction results from different element predictors. In the learning model, several machine learning methods were evaluated and adopted the support vector machine as an integrator, while not just choosing the majority answer given by element predictors. Furthermore, the role of the sequence information played was analyzed in our model, and an 11-window size was determined. On the other hand, iStable is available with two different input types: structural and sequential. After training and cross-validation, iStable has better performance than all of the element predictors on several datasets. Under different classifications and conditions for validation, this study has also shown better overall performance in different types of secondary structures, relative solvent accessibility circumstances, protein memberships in different superfamilies, and experimental conditions. Conclusions The trained and validated version of iStable provides an accurate approach for prediction of protein stability changes. iStable is freely available online at: http://predictor.nchu.edu.tw/iStable. PMID:23369171

  1. Exponential Functions, Rates of Change, and the Multiplicative Unit.

    ERIC Educational Resources Information Center

    Confrey, Jere; Smith, Erick

    1994-01-01

    Describes a covariational, rather than correspondence, approach to functions that emphasizes rate of change. Proposes three ways of understanding rate of change in relation to exponential functions. (Contains 41 references.) (Author/MKR)

  2. Predicting taxonomic and functional structure of microbial communities in acid mine drainage

    PubMed Central

    Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

    2016-01-01

    Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray–Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural

  3. Prediction of functional residues in water channels and related proteins.

    PubMed Central

    Froger, A.; Tallur, B.; Thomas, D.; Delamarche, C.

    1998-01-01

    In this paper, we present an updated classification of the ubiquitous MIP (Major Intrinsic Protein) family proteins, including 153 fully or partially sequenced members available in public databases. Presently, about 30 of these proteins have been functionally characterized, exhibiting essentially two distinct types of channel properties: (1) specific water transport by the aquaporins, and (2) small neutral solutes transport, such as glycerol by the glycerol facilitators. Sequence alignments were used to predict amino acids and motifs discriminant in channel specificity. The protein sequences were also analyzed using statistical tools (comparisons of means and correspondence analysis). Five key positions were clearly identified where the residues are specific for each functional subgroup and exhibit high dissimilar physico-chemical properties. Moreover, we have found that the putative channels for small neutral solutes clearly differ from the aquaporins by the amino acid content and the length of predicted loop regions, suggesting a substrate filter function for these loops. From these results, we propose a signature pattern for water transport. PMID:9655351

  4. Abrupt Climate Change: A Magnetic Coupling Model (MCM) Prediction.

    NASA Astrophysics Data System (ADS)

    Ely, John T. A.

    2002-04-01

    Recent findings [p.8 ISBN 0-309-07434-7] show major climate changes often occur in a decade. This is another of many MCM predictions (see refs). All of them tested from 1968 to date have been proven, including: Global warming is real and driven by fossil fuel (1970's); This CO2 forcing has ended Major Ice Ages; All Major and Minor Ice Ages are caused by decreases in existing (primarily subvisible and other thin, especially newly forming) cirrus at mid to high geomagnetic latitudes; Ionization of the atmosphere near 250 grams per square cm depth by GCR (galactic cosmic ray protons circa 1 gev) cause cirrus depression; Ice cores and other proxy records show ice ages exhibit increased beryllium-10, carbon-14, etc, due to GCR. As noted in the Mar and Apr abstracts, the MCM predictable climate ended in 2000, following over 30 yrs of our ignoring its easily testable warnings re fossil fuel. Hence, we now face the somber question of whether human intervention is still possible in a CO2 Runaway and sea level rise that may be on a decade time scale. [Ely, Session A8, APS Mtg, Seattle, Mar 01; Ely, Session H14.013, APS Mtg, Apr 01; MCM pub list http://faculty.washington.edu/ely/MCM.html

  5. Soda consumption during ad libitum food intake predicts weight change.

    PubMed

    Bundrick, Sarah C; Thearle, Marie S; Venti, Colleen A; Krakoff, Jonathan; Votruba, Susanne B

    2014-03-01

    Soda consumption may contribute to weight gain over time. Objective data were used to determine whether soda consumption predicts weight gain or changes in glucose regulation over time. Subjects without diabetes (128 men, 75 women; mean age 34.3±8.9 years; mean body mass index 32.5±7.4; mean percentage body fat 31.6%±8.6%) self-selected their food from an ad libitum vending machine system for 3 days. Mean daily energy intake was calculated from food weight. Energy consumed from soda was recorded as were food choices that were low in fat (<20% of calories from fat) or high in simple sugars (>30%). Food choices were expressed as percentage of daily energy intake. A subset of 85 subjects had measurement of follow-up weights and oral glucose tolerance (57 men, 28 women; mean follow-up time=2.5±2.1 years, range 6 months to 9.9 years). Energy consumed from soda was negatively related to age (r=-0.27, P=0.0001) and choosing low-fat foods (r=-0.35, P<0.0001), but positively associated with choosing solid foods high in simple sugars (r=0.45, P<0.0001) and overall average daily energy intake (r=0.46, P<0.0001). Energy intake from food alone did not differ between individuals who did and did not consume beverage calories (P=0.11). Total daily energy intake had no relationship with change in weight (P=0.29) or change in glucose regulation (P=0.38) over time. However, energy consumed from soda correlated with change in weight (r=0.21, P=0.04). This relationship was unchanged after adjusting for follow-up time and initial weight. Soda consumption is a marker for excess energy consumption and is associated with weight gain.

  6. Soda Consumption During Ad Libitum Food Intake Predicts Weight Change

    PubMed Central

    Bundrick, Sarah C.; Thearle, Marie S.; Venti, Colleen A.; Krakoff, Jonathan; Votruba, Susanne B.

    2013-01-01

    Soda consumption may contribute to weight gain over time. Objective data were used to determine whether soda consumption predicts weight gain or changes in glucose regulation over time. Subjects without diabetes (128 men, 75 women; mean age 34.3±8.9 years; mean body mass index [BMI] 32.5±7.4; mean percentage body fat 31.6%±8.6%) self-selected their food from an ad libitum vending machine system for 3 days. Mean daily energy intake was calculated from food weight. Energy consumed from soda was recorded as were food choices that were low in fat (<20%) or high in simple sugars (>30%). Food choices were expressed as percentage of daily energy intake. A subset of 85 subjects had measurement of follow-up weights and oral glucose tolerance (57 men, 28 women; mean follow-up time=2.5±2.1 years, range 6 months to 9.9 years). Energy consumed from soda was negatively related to age (r=–0.27, P=0.0001), and choosing low-fat foods (r=−0.35, P<0.0001), but positively associated with choosing solid foods high in simple sugars (r=0.45, P<0.0001) and overall average daily energy intake (r=0.46, P<0.0001). Energy intake from food alone did not differ between individuals who did and did not consume beverage calories (P=0.11). Total daily energy intake had no relationship with change in weight (P=0.29) or change in glucose regulation (P=0.38) over time. However, energy consumed from soda correlated with change in weight (r=0.21, P=0.04). This relationship was unchanged after adjusting for follow-up time and initial weight. Soda consumption is a marker for excess energy consumption and is associated with weight gain. PMID:24321742

  7. Prediction of Dislocation Cores in Aluminum from Density Functional Theory

    NASA Astrophysics Data System (ADS)

    Woodward, C.; Trinkle, D. R.; Hector, L. G., Jr.; Olmsted, D. L.

    2008-02-01

    The strain field of isolated screw and edge dislocation cores in aluminum are calculated using density-functional theory and a flexible boundary condition method. Nye tensor density contours and differential displacement fields are used to accurately bound Shockley partial separation distances. Our results of 5 7.5 Å (screw) and 7.0 9.5 Å (edge) eliminate uncertainties resulting from the wide range of previous results based on Peierls-Nabarro and atomistic methods. Favorable agreement of the predicted cores with limited experimental measurements demonstrates the need for quantum mechanical treatment of dislocation cores.

  8. Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

    PubMed

    Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D

    2017-03-06

    Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial-scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalise community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water-plant-functional-group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 697 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed models achieved acceptable predictive performance, with correct classification rates in the range 0.68 - 0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. This article is protected by copyright. All rights reserved.

  9. Defining Predictive Probability Functions for Species Sampling Models.

    PubMed

    Lee, Jaeyong; Quintana, Fernando A; Müller, Peter; Trippa, Lorenzo

    2013-01-01

    We review the class of species sampling models (SSM). In particular, we investigate the relation between the exchangeable partition probability function (EPPF) and the predictive probability function (PPF). It is straightforward to define a PPF from an EPPF, but the converse is not necessarily true. In this paper we introduce the notion of putative PPFs and show novel conditions for a putative PPF to define an EPPF. We show that all possible PPFs in a certain class have to define (unnormalized) probabilities for cluster membership that are linear in cluster size. We give a new necessary and sufficient condition for arbitrary putative PPFs to define an EPPF. Finally, we show posterior inference for a large class of SSMs with a PPF that is not linear in cluster size and discuss a numerical method to derive its PPF.

  10. Predicting Infrared Spectra of Nerve Agents Using Density Functional Theory

    NASA Astrophysics Data System (ADS)

    Zhang, Y.-P.; Wang, H.-T.; Zheng, W.-P.; Sun, C.; Bai, Y.; Guo, X.-D.; Sun, H.

    2016-09-01

    Vibration frequencies of four nerve agents and two simulators are calculated using B3LYP coupled with ten basis sets. To evaluate the accuracy of calculated spectra, root mean square error (RMSE) and weighted cross-correlation average (WCCA) are considered. The evaluation shows that B3LYP/6-311+g(d,p) performs best in predicting infrared spectra, and polarization functions are found to be more important than diffusion functions in spectra simulation. Moreover, B3LYP calculation underestimates frequencies related to the P atom. The WCCA metric derives 1.008 as a unique scaling factor for calculated frequencies. The results indicate that the WCCA metric can identify six agents based on calculated spectra.

  11. Greater attention problems during childhood predict poorer executive functioning in late adolescence.

    PubMed

    Friedman, Naomi P; Haberstick, Brett C; Willcutt, Erik G; Miyake, Akira; Young, Susan E; Corley, Robin P; Hewitt, John K

    2007-10-01

    Attention problems (behavior problems including inattention, disorganization, impulsivity, and hyperactivity) are widely thought to reflect deficits in executive functions (EFs). However, it is unclear whether attention problems differentially relate to distinct EFs and how developmental stability and change predict levels of EFs in late adolescence. We investigated, in an unselected sample, how teacher-rated attention problems from ages 7 to 14 years related to three correlated but separable EFs, measured as latent variables at age 17. Attention problems at all ages significantly predicted later levels of response inhibition and working memory updating, and to some extent set shifting; the relation to inhibiting was stronger than the relations to the other EFs or IQ. Growth models indicated that attention problems were quite stable in this age range, and it was the initial levels of problems, rather than their changes across time, that predicted later EFs. These results support the hypothesis that attention problems primarily reflect difficulties with response inhibition.

  12. Influence of predicted climage change elements on Z. ...

    EPA Pesticide Factsheets

    Global climate change (GCC) is expected to have pronounced impacts on estuarine and marine habitats including sea level rise, increased storm intensity, increased air and water temperatures, changes in upwelling dynamics and ocean acidification. All of these elements are likely to impact the growth and potential distribution of the non-indigenous seagrass Zostera japonica both within the State of Washington and within the region. Understanding how Z. japonica will respond to GCC requires a thorough understanding of plant physiology and predictions of GCC effects. Furthermore, Washington State is proposing to list Z. japonica as a “noxious weed” which will allow the state to use herbicide controls for management. We present data from manipulative experiments designed to better understand how Z. japonica photosynthetic physiology responds to temperature, salinity and light. We found that Z. japonica is well adapted to moderate temperatures and salinity with maximum photosynthesis of salinity of 20. The Coos Bay population had greater Pmax and saturation irradiance (Ik) than the Padilla bay population (p < 0.001) and tolerates daily exposure to both freshwater and marine water, suggesting that this population tolerates fairly extreme environmental fluctuations. Extreme temperatures (35 °C) were generally lethal to Z. japonica populations from Padilla, Coos and Yaquina Bays. High salinity (35) had lower mortality than either salinity of 5 or 20 (p = 0.0

  13. Predicting Schizophrenia Patients’ Real World Behavior with Specific Neuropsychological and Functional Capacity Measures

    PubMed Central

    Bowie, Christopher R.; Leung, Winnie W.; Reichenberg, Abraham; McClure, Margaret M.; Patterson, Thomas L.; Heaton, Robert K.; Harvey, Philip D.

    2008-01-01

    Background Significant neuropsychological (NP) and functional deficits are found in most schizophrenia patients. Previous studies have left question as to whether global NP impairment or discrete domains affect functional outcomes, and none have addressed distinctions within and between ability and performance domains. This study examined the different predictive relationships between NP domains, functional competence, social competence, symptoms, and real world behavior in domains of work skills, interpersonal relationships, and community activities. Methods 222 schizophrenic outpatients were tested with an NP battery and performance-based measures of functional and social competence and rated for positive, negative, and depressive symptoms. Case managers generated ratings of three functional disability domains. Results Four cognitive factors were derived from factor analysis. Path analyses revealed both direct and mediated effects of NP on real world outcomes. All NP domains predicted functional competence, but only processing speed and attention/working memory predicted social competence. Both competence measures mediated the effects of NP on community activities and work skills, but only social competence predicted interpersonal behaviors. The attention/working memory domain was directly related to work skills, executive functions had a direct effect on interpersonal behaviors and processing speed had direct effects on all three real world behaviors. Symptoms were directly related to outcomes, with fewer relationships with competence. Conclusions Differential predictors of functional competence and performance were found from discrete NP domains. Separating competence and performance provides a more precise perspective on correlates of disability. Changes in specific NP or functional skills might improve specific outcomes, rather than promoting global functional improvement. PMID:17662256

  14. Prediction of detailed enzyme functions and identification of specificity determining residues by random forests.

    PubMed

    Nagao, Chioko; Nagano, Nozomi; Mizuguchi, Kenji

    2014-01-01

    Determining enzyme functions is essential for a thorough understanding of cellular processes. Although many prediction methods have been developed, it remains a significant challenge to predict enzyme functions at the fourth-digit level of the Enzyme Commission numbers. Functional specificity of enzymes often changes drastically by mutations of a small number of residues and therefore, information about these critical residues can potentially help discriminate detailed functions. However, because these residues must be identified by mutagenesis experiments, the available information is limited, and the lack of experimentally verified specificity determining residues (SDRs) has hindered the development of detailed function prediction methods and computational identification of SDRs. Here we present a novel method for predicting enzyme functions by random forests, EFPrf, along with a set of putative SDRs, the random forests derived SDRs (rf-SDRs). EFPrf consists of a set of binary predictors for enzymes in each CATH superfamily and the rf-SDRs are the residue positions corresponding to the most highly contributing attributes obtained from each predictor. EFPrf showed a precision of 0.98 and a recall of 0.89 in a cross-validated benchmark assessment. The rf-SDRs included many residues, whose importance for specificity had been validated experimentally. The analysis of the rf-SDRs revealed both a general tendency that functionally diverged superfamilies tend to include more active site residues in their rf-SDRs than in less diverged superfamilies, and superfamily-specific conservation patterns of each functional residue. EFPrf and the rf-SDRs will be an effective tool for annotating enzyme functions and for understanding how enzyme functions have diverged within each superfamily.

  15. Predicting Offshore Swarm Rate Changes by Volumetric Strain Changes in Izu Peninsula, Japan

    NASA Astrophysics Data System (ADS)

    Kumazawa, T.; Ogata, Y.; Kimura, Y.; Maeda, K.; Kobayashi, A.

    2014-12-01

    The eastern offshore of Izu peninsula is one of the well known volcanic active regions in Japan, where magma intrusions have been observed several times since 1980s monitored by strain-meters located nearby. Major swarm activities have been synchronously associated with coseismic and preseismic significant sizes of a volumetric strain changes (Earthquake Research Committee, 2010). We investigated the background seismicity changes during these earthquake swarms using the nonstationary ETAS model (Kumazawa and Ogata, 2013), and have found the followings. The modified volumetric strain change data by removing the effect of earth tides and precipitation as well as removing coseismic jumps have much higher cross-correlations to the background rates of the ETAS model than to the whole seismicity rate change of the ETAS, and further the strain changes precede the background seismicity by lag of about a day. This relation suggests an enhanced prediction of earthquakes in this region using volumetric strain measurements. Thus we propose an extended ETAS model where the background seismicity rate is predicted by the time series of preceding volumetric strain changes. Our numerical results for Izu region show consistent outcomes throughout the major swarms in this region. References Earthquake Research Committee (2010). Report on "Prediction of seismic activity in the Izu Eastern Region" (in Japanese), http://www.jishin.go.jp/main/yosoku/izu/index.htm Kumazawa, T. and Ogata, Y. (2013). Quantitative description of induced seismic activity before and after the 2011 Tohoku-Oki earthquake by nonstationary ETAS model, J Geophys.Res. 118, 6165-6182.

  16. Dynamic Predictions of Semi-Arid Land Cover Change

    NASA Astrophysics Data System (ADS)

    Foster-Wittig, T. A.

    2011-12-01

    Savannas make up about 18% of the global landmass and contain about 22% of the world's population (Falkenmark and Rockstrom, 2008). They are unique ecosystems in that they consist of both grass and trees. Depending on the land use, amount of precipitation, herbivory, and fire frequency, either trees or grasses can be more prevalent than the other (Sankaran et al., 2005). Savannas in sub-Saharan Africa are usually considered water-limited ecosystems due to the seasonal rainfall. It has been shown that the vegetation responds on a short timescale to the rainfall (Scanlon et al, 2002). Therefore, savannas are foreseen as vulnerable ecosystems to future changes in the land use and climate change (Sankaran et al, 2005). The goal of this research is to quantify the vulnerability of this ecosystem by projecting future changes in the savanna structure due to land use and climate change through the use of a dynamic vegetation model. This research will provide a better understanding of the relationship between precipitation and vegetation in savannas through the use of a Vegetation Dynamics Model developed to predict surface water fluxes and vegetation dynamics in water-limited ecosystems (Williams and Albertson, 2005). In this project, it will be used to model leaf area index (LAI) for point locations within sub-Saharan Africa between Kenya and Botswana with a range of annual rainfall and savanna type. With this model, future projections are developed for what can be anticipated in the future for the savanna structure based on three climate change scenarios; (1) decreased depth, (2) decreased frequency, and (3) decreased wet season length. The effect of the climate change scenarios on the plant water stress and plant water uptake will be analyzed in order to understand the dynamic effects of precipitation on vegetation. Therefore, this will allow conclusions to be drawn about how mean precipitation and a changing climate effect the sensitivity of savanna vegetation. It is

  17. Graphlet kernels for prediction of functional residues in protein structures.

    PubMed

    Vacic, Vladimir; Iakoucheva, Lilia M; Lonardi, Stefano; Radivojac, Predrag

    2010-01-01

    We introduce a novel graph-based kernel method for annotating functional residues in protein structures. A structure is first modeled as a protein contact graph, where nodes correspond to residues and edges connect spatially neighboring residues. Each vertex in the graph is then represented as a vector of counts of labeled non-isomorphic subgraphs (graphlets), centered on the vertex of interest. A similarity measure between two vertices is expressed as the inner product of their respective count vectors and is used in a supervised learning framework to classify protein residues. We evaluated our method on two function prediction problems: identification of catalytic residues in proteins, which is a well-studied problem suitable for benchmarking, and a much less explored problem of predicting phosphorylation sites in protein structures. The performance of the graphlet kernel approach was then compared against two alternative methods, a sequence-based predictor and our implementation of the FEATURE framework. On both tasks, the graphlet kernel performed favorably; however, the margin of difference was considerably higher on the problem of phosphorylation site prediction. While there is data that phosphorylation sites are preferentially positioned in intrinsically disordered regions, we provide evidence that for the sites that are located in structured regions, neither the surface accessibility alone nor the averaged measures calculated from the residue microenvironments utilized by FEATURE were sufficient to achieve high accuracy. The key benefit of the graphlet representation is its ability to capture neighborhood similarities in protein structures via enumerating the patterns of local connectivity in the corresponding labeled graphs.

  18. Functional Embedding Predicts the Variability of Neural Activity

    PubMed Central

    Mišić, Bratislav; Vakorin, Vasily A.; Paus, Tomáš; McIntosh, Anthony R.

    2011-01-01

    Neural activity is irregular and unpredictable, yet little is known about why this is the case and how this property relates to the functional architecture of the brain. Here we show that the variability of a region’s activity systematically varies according to its topological role in functional networks. We recorded the resting-state electroencephalogram (EEG) and constructed undirected graphs of functional networks. We measured the centrality of each node in terms of the number of connections it makes (degree), the ease with which the node can be reached from other nodes in the network (efficiency) and the tendency of the node to occupy a position on the shortest paths between other pairs of nodes in the network (betweenness). As a proxy for variability, we estimated the information content of neural activity using multiscale entropy analysis. We found that the rate at which information was generated was largely predicted by centrality. Namely, nodes with greater degree, betweenness, and efficiency were more likely to have high information content, while peripheral nodes had relatively low information content. These results suggest that the variability of regional activity reflects functional embedding. PMID:22164135

  19. Risk prediction for myocardial infarction via generalized functional regression models.

    PubMed

    Ieva, Francesca; Paganoni, Anna M

    2016-08-01

    In this paper, we propose a generalized functional linear regression model for a binary outcome indicating the presence/absence of a cardiac disease with multivariate functional data among the relevant predictors. In particular, the motivating aim is the analysis of electrocardiographic traces of patients whose pre-hospital electrocardiogram (ECG) has been sent to 118 Dispatch Center of Milan (the Italian free-toll number for emergencies) by life support personnel of the basic rescue units. The statistical analysis starts with a preprocessing of ECGs treated as multivariate functional data. The signals are reconstructed from noisy observations. The biological variability is then removed by a nonlinear registration procedure based on landmarks. Thus, in order to perform a data-driven dimensional reduction, a multivariate functional principal component analysis is carried out on the variance-covariance matrix of the reconstructed and registered ECGs and their first derivatives. We use the scores of the Principal Components decomposition as covariates in a generalized linear model to predict the presence of the disease in a new patient. Hence, a new semi-automatic diagnostic procedure is proposed to estimate the risk of infarction (in the case of interest, the probability of being affected by Left Bundle Brunch Block). The performance of this classification method is evaluated and compared with other methods proposed in literature. Finally, the robustness of the procedure is checked via leave-j-out techniques.

  20. Prediction of functional aerobic capacity without exercise testing

    NASA Technical Reports Server (NTRS)

    Jackson, A. S.; Blair, S. N.; Mahar, M. T.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.

    1990-01-01

    The purpose of this study was to develop functional aerobic capacity prediction models without using exercise tests (N-Ex) and to compare the accuracy with Astrand single-stage submaximal prediction methods. The data of 2,009 subjects (9.7% female) were randomly divided into validation (N = 1,543) and cross-validation (N = 466) samples. The validation sample was used to develop two N-Ex models to estimate VO2peak. Gender, age, body composition, and self-report activity were used to develop two N-Ex prediction models. One model estimated percent fat from skinfolds (N-Ex %fat) and the other used body mass index (N-Ex BMI) to represent body composition. The multiple correlations for the developed models were R = 0.81 (SE = 5.3 ml.kg-1.min-1) and R = 0.78 (SE = 5.6 ml.kg-1.min-1). This accuracy was confirmed when applied to the cross-validation sample. The N-Ex models were more accurate than what was obtained from VO2peak estimated from the Astrand prediction models. The SEs of the Astrand models ranged from 5.5-9.7 ml.kg-1.min-1. The N-Ex models were cross-validated on 59 men on hypertensive medication and 71 men who were found to have a positive exercise ECG. The SEs of the N-Ex models ranged from 4.6-5.4 ml.kg-1.min-1 with these subjects.(ABSTRACT TRUNCATED AT 250 WORDS).

  1. Habitual fat intake predicts memory function in younger women.

    PubMed

    Gibson, E Leigh; Barr, Suzanne; Jeanes, Yvonne M

    2013-01-01

    High intakes of fat have been linked to greater cognitive decline in old age, but such associations may already occur in younger adults. We tested memory and learning in 38 women (25 to 45 years old), recruited for a larger observational study in women with polycystic ovary syndrome. These women varied in health status, though not significantly between cases (n = 23) and controls (n = 15). Performance on tests sensitive to medial temporal lobe function (CANTABeclipse, Cambridge Cognition Ltd, Cambridge, UK), i.e., verbal memory, visuo-spatial learning, and delayed pattern matching (DMS), were compared with intakes of macronutrients from 7-day diet diaries and physiological indices of metabolic syndrome. Partial correlations were adjusted for age, activity, and verbal IQ (National Adult Reading Test). Greater intakes of saturated and trans fats, and higher saturated to unsaturated fat ratio (Sat:UFA), were associated with more errors on the visuo-spatial task and with poorer word recall and recognition. Unexpectedly, higher UFA intake predicted poorer performance on the word recall and recognition measures. Fasting insulin was positively correlated with poorer word recognition only, whereas higher blood total cholesterol was associated only with visuo-spatial learning errors. None of these variables predicted performance on a DMS test. The significant nutrient-cognition relationships were tested for mediation by total energy intake: saturated and trans fat intakes, and Sat:UFA, remained significant predictors specifically of visuo-spatial learning errors, whereas total fat and UFA intakes now predicted only poorer word recall. Examination of associations separately for monounsaturated (MUFA) and polyunsaturated fats suggested that only MUFA intake was predictive of poorer word recall. Saturated and trans fats, and fasting insulin, may already be associated with cognitive deficits in younger women. The findings need extending but may have important implications for

  2. Understanding and predicting changes in North Atlantic Sea Surface Temperature

    NASA Astrophysics Data System (ADS)

    Yeager, S. G.

    model mean overturning and gyre circulations, and which explain the model response to surface momentum and buoyancy forcing perturbations, are investigated in terms of mean and time-varying vorticity balances. The significant effect of bottom vortex stretching, noted in previous studies, is shown here to play a key role in a variety of time-dependent phenomena, such as the covariation of overturning and gyre circulations, the variation of the barotropic streamfunction in the intergyre-gyre region, and changes in AMOC associated with momentum forcing perturbations. We show that latitudinal changes in the AMOC vorticity balance explains the attenuation of buoyancy-forced signals south of Cape Hatteras, and that the dominant frictional balance near the Equator greatly inhibits the propagation of AMOC variability signals from one hemisphere to the other. The long persistence of buoyancy-forced, high-latitude circulation anomalies results in significant predictability of SST in the subpolar gyre. This is demonstrated with an analysis of initialized, fully coupled retrospective predictions of the mid-1990s warming in that region. The atmospheric response is shown to be relatively unimportant on timescales of up to 10 years, but skill for longer lead times is inhibited by an incorrect heat flux feedback in the North Atlantic in the coupled CESM1.

  3. Pacific Walrus and climate change: observations and predictions.

    PubMed

    Maccracken, James G

    2012-08-01

    The extent and duration of sea-ice habitats used by Pacific walrus (Odobenus rosmarus divergens) are diminishing resulting in altered walrus behavior, mortality, and distribution. I document changes that have occurred over the past several decades and make predictions to the end of the 21st century. Climate models project that sea ice will monotonically decline resulting in more ice-free summers of longer duration. Several stressors that may impact walruses are directly influenced by sea ice. How these stressors materialize were modeled as most likely-case, worst-case, and best-case scenarios for the mid- and late-21st century, resulting in four comprehensive working hypotheses that can help identify and prioritize management and research projects, identify comprehensive mitigation actions, and guide monitoring programs to track future developments and adjust programs as needed. In the short term, the most plausible hypotheses predict a continuing northward shift in walrus distribution, increasing use of coastal haulouts in summer and fall, and a population reduction set by the carrying capacity of the near shore environment and subsistence hunting. Alternatively, under worst-case conditions, the population will decline to a level where the probability of extinction is high. In the long term, walrus may seasonally abandon the Bering and Chukchi Seas for sea-ice refugia to the northwest and northeast, ocean warming and pH decline alter walrus food resources, and subsistence hunting exacerbates a large population decline. However, conditions that reverse current trends in sea ice loss cannot be ruled out. Which hypothesis comes to fruition depends on how the stressors develop and the success of mitigation measures. Best-case scenarios indicate that successful mitigation of unsustainable harvests and terrestrial haulout-related mortalities can be effective. Management and research should focus on monitoring, elucidating effects, and mitigation, while ultimately

  4. Pacific Walrus and climate change: observations and predictions

    PubMed Central

    MacCracken, James G

    2012-01-01

    The extent and duration of sea-ice habitats used by Pacific walrus (Odobenus rosmarus divergens) are diminishing resulting in altered walrus behavior, mortality, and distribution. I document changes that have occurred over the past several decades and make predictions to the end of the 21st century. Climate models project that sea ice will monotonically decline resulting in more ice-free summers of longer duration. Several stressors that may impact walruses are directly influenced by sea ice. How these stressors materialize were modeled as most likely-case, worst-case, and best-case scenarios for the mid- and late-21st century, resulting in four comprehensive working hypotheses that can help identify and prioritize management and research projects, identify comprehensive mitigation actions, and guide monitoring programs to track future developments and adjust programs as needed. In the short term, the most plausible hypotheses predict a continuing northward shift in walrus distribution, increasing use of coastal haulouts in summer and fall, and a population reduction set by the carrying capacity of the near shore environment and subsistence hunting. Alternatively, under worst-case conditions, the population will decline to a level where the probability of extinction is high. In the long term, walrus may seasonally abandon the Bering and Chukchi Seas for sea-ice refugia to the northwest and northeast, ocean warming and pH decline alter walrus food resources, and subsistence hunting exacerbates a large population decline. However, conditions that reverse current trends in sea ice loss cannot be ruled out. Which hypothesis comes to fruition depends on how the stressors develop and the success of mitigation measures. Best-case scenarios indicate that successful mitigation of unsustainable harvests and terrestrial haulout-related mortalities can be effective. Management and research should focus on monitoring, elucidating effects, and mitigation, while ultimately

  5. Predicted changes in energy demands for heating and cooling due to climate change

    NASA Astrophysics Data System (ADS)

    Dolinar, Mojca; Vidrih, Boris; Kajfež-Bogataj, Lučka; Medved, Sašo

    In the last 3 years in Slovenia we experienced extremely hot summers and demand for cooling the buildings have risen significantly. Since climate change scenarios predict higher temperatures for the whole country and for all seasons, we expect that energy demand for heating would decrease while demand for cooling would increase. An analysis for building with permitted energy demand and for low-energy demand building in two typical urban climates in Slovenia was performed. The transient systems simulation program (TRNSYS) was used for simulation of the indoor conditions and the energy use for heating and cooling. Climate change scenarios were presented in form of “future” Test Reference Years (TRY). The time series of hourly data for all meteorological variables for different scenarios were chosen from actual measurements, using the method of highest likelihood. The climate change scenarios predicted temperature rise (+1 °C and +3 °C) and solar radiation increase (+3% and +6%). With the selection of these scenarios we covered the spectra of possible predicted climate changes in Slovenia. The results show that energy use for heating would decrease from 16% to 25% (depends on the intensity of warming) in subalpine region, while in Mediterranean region the rate of change would not be significant. In summer time we would need up to six times more energy for cooling in subalpine region and approximately two times more in Mediterranean region. low-energy building proved to be very economical in wintertime while on average higher energy consumption for cooling is expected in those buildings in summertime. In case of significant warmer and more solar energy intensive climate, the good isolated buildings are more efficient than standard buildings. TRY proved not to be efficient for studying extreme conditions like installed power of the cooling system.

  6. Emotion regulation predicts change of perceived health in patients with rheumatoid arthritis

    PubMed Central

    van Middendorp, H; Geenen, R; Sorbi, M; van Doornen, L J P; Bijlsma, J

    2005-01-01

    Methods: Sixty six patients (44 female, 22 male; mean (SD) age 57.7 (11.6) years) participated in a prospective study. Hierarchical regression analysis was used to predict change of perceived health between study entry and follow up (1½ years later) from the emotion regulation styles ambiguity, control, orientation, and expression at study entry. Results: Valuing and intensely experiencing emotions (emotional orientation) predicted a decrease of positive affect. Difficulty recognising and expressing emotions (ambiguity) predicted an increase of perceived disease activity. Emotion regulation showed no associations with change of negative affect and social and physical functioning. Conclusions: Two styles of emotion regulation were shown to have a significant though modest role in the prediction of perceived health change in patients with RA. This suggests that the monitoring of emotion regulation may help to identify patients who are at risk for a reduction of perceived health. If our findings were confirmed by experimental research, improving emotion regulation skills might favourably affect perceived health. PMID:15958762

  7. A novel neural response algorithm for protein function prediction

    PubMed Central

    2012-01-01

    Background Large amounts of data are being generated by high-throughput genome sequencing methods. But the rate of the experimental functional characterization falls far behind. To fill the gap between the number of sequences and their annotations, fast and accurate automated annotation methods are required. Many methods, such as GOblet, GOFigure, and Gotcha, are designed based on the BLAST search. Unfortunately, the sequence coverage of these methods is low as they cannot detect the remote homologues. Adding to this, the lack of annotation specificity advocates the need to improve automated protein function prediction. Results We designed a novel automated protein functional assignment method based on the neural response algorithm, which simulates the neuronal behavior of the visual cortex in the human brain. Firstly, we predict the most similar target protein for a given query protein and thereby assign its GO term to the query sequence. When assessed on test set, our method ranked the actual leaf GO term among the top 5 probable GO terms with accuracy of 86.93%. Conclusions The proposed algorithm is the first instance of neural response algorithm being used in the biological domain. The use of HMM profiles along with the secondary structure information to define the neural response gives our method an edge over other available methods on annotation accuracy. Results of the 5-fold cross validation and the comparison with PFP and FFPred servers indicate the prominent performance by our method. The program, the dataset, and help files are available at http://www.jjwanglab.org/NRProF/. PMID:23046521

  8. Predicting the Responses of Soil Nitrite-Oxidizers to Multi-Factorial Global Change: A Trait-Based Approach

    PubMed Central

    Le Roux, Xavier; Bouskill, Nicholas J.; Niboyet, Audrey; Barthes, Laure; Dijkstra, Paul; Field, Chris B.; Hungate, Bruce A.; Lerondelle, Catherine; Pommier, Thomas; Tang, Jinyun; Terada, Akihiko; Tourna, Maria; Poly, Franck

    2016-01-01

    Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global change scenarios for central California) on the potential activity, abundance and dominant taxa of soil nitrite-oxidizing bacteria (NOB). Using a trait-based model, we then tested whether categorizing NOB into a few functional groups unified by physiological traits enables understanding and predicting how soil NOB respond to global environmental change. Contrasted responses to global change treatments were observed between three main NOB functional types. In particular, putatively mixotrophic Nitrobacter, rare under most treatments, became dominant under the ‘High CO2+Nitrogen+Precipitation’ treatment. The mechanistic trait-based model, which simulated ecological niches of NOB types consistent with previous ecophysiological reports, helped predicting the observed effects of global change on NOB and elucidating the underlying biotic and abiotic controls. Our results are a starting point for representing the overwhelming diversity of soil bacteria by a few functional types that can be incorporated into models of terrestrial ecosystems and biogeochemical processes. PMID:27242680

  9. Climate change forecasts, long-term spatio-temporal prediction and the resilience of dry ecosystems

    NASA Astrophysics Data System (ADS)

    Shafran-Natan, Rakefet; Svoray, Tal; Avi, Perevolotsky

    2010-05-01

    Primary production is an important indicator to climatic changes in drylands, while reduction in productivity has many consequences on ecosystem functioning. We suggest that the response of dry ecosystems to climate change should lead to a change in spatial patterns of grasses without a substantial change in ecosystem resilience. We used field data and a recently published spatio-temporally explicit model to study factors affecting long-term variation in primary production in two dry ecosystems: semi-arid (SAE) and Mediterranean (DME) dominated by annual vegetation. The model was operated in both patch and landscape scales and was executed along 30 years (1979-2008) at SAE and along 21 years (1986-1990; 1993-2008) at DME. Model predictions were validated against samples that were harvested in each site at the end of the growing season, over 15 seasons (1994-2008) at SAE (0.63

  10. Grade 12 French Students' use of a Thermodynamic Model for Predicting the Direction of Incomplete Chemical Changes

    NASA Astrophysics Data System (ADS)

    Kermen, Isabelle; Méheut, Martine

    2011-09-01

    The authors of the current chemistry curriculum-implemented in Grade 12 in France-provided a criterion of change allowing prediction of direction of chemical changes and pointed out the difference to be made between experimental facts and models. A study analysing part of the curriculum content and the effects of teaching this content on students' reasoning was conducted. The content analysis presents the functioning of the thermodynamic model, which highlights the links to be made between the experimental situation and the model when predicting the direction of a chemical change. This functioning specifies the role of the chemical equation and that of the criterion of change (comparing the reaction quotient to the equilibrium constant) and stresses the crucial points that may lead to misunderstandings. Written tests were administered to students after teaching them to determine how they predicted the direction of a chemical change, and whether they made a relevant choice between using the chemical equation and using the criterion of change and a clear distinction between the experimental situation and the thermodynamic model. Few students had a good understanding of the respective roles of the criterion and the chemical equation. A majority used the criterion to predict the direction of chemical changes relevantly, but correct answers were not widespread. Two particular mistakes, the modification of the expression of the reaction quotient and the prediction of a change despite a missing reactant, revealed that students do not properly understand the difference and the relationship between the experimental situation and the thermodynamic model.

  11. Does obesity predict functional outcome in the dysvascular amputee?

    PubMed

    Kalbaugh, Corey A; Taylor, Spence M; Kalbaugh, Brooke A; Halliday, Matthew; Daniel, Grace; Cass, Anna L; Blackhurst, Dawn W; Cull, David L; Langan, Eugene M; Carsten, Christopher G; York, John W; Snyder, Bruce A; Youkey, Jerry R

    2006-08-01

    Limited information is available concerning the effects of obesity on the functional outcomes of patients requiring major lower limb amputation because of peripheral arterial disease (PAD). The purpose of this study was to examine the predictive ability of body mass index (BMI) to determine functional outcome in the dysvascular amputee. To do this, 434 consecutive patients (mean age, 65.8 +/- 13.3, 59% male, 71.4% diabetic) undergoing major limb amputation (225 below-knee amputation, 27 through-knee amputation, 132 above-knee amputation, and 50 bilateral) as a complication of PAD from January 1998 through May 2004 were analyzed according to preoperative BMI. BMI was classified according to the four-group Center for Disease Control system: underweight, 0 to 18.4 kg/m2; normal, 18.5 to 24.9 kg/m2; overweight, 25 to 29.9 kg/m2; and obese, > or = 30 kg/m2. Outcome parameters measured included prosthetic usage, maintenance of ambulation, survival, and maintenance of independent living status. The chi2 test for association was used to examine prosthesis wear. Kaplan-Meier curves were constructed to assess maintenance of ambulation, survival, and maintenance of independent living status. Multivariate analysis using the multiple logistic regression model and a Cox proportional hazards model were used to predict variables independently associated with prosthetic use and ambulation, survival, and independence, respectively. Overall prosthetic usage and 36-month ambulation, survival, and independent living status for the entire cohort was 48.6 per cent, 42.8 per cent, 48.1 per cent, 72.3 per cent, and for patients with normal BMI was 41.5 per cent, 37.4 per cent, 45.6 per cent, and 69.5 per cent, respectively. There was no statistically significant difference in outcomes for overweight patients (59.2%, 50.7%, 52.5%, and 75%) or obese patients (51.8%, 46.2%, 49.7%, and 75%) when compared with normal patients. Although there were significantly poorer outcomes for underweight

  12. Functional innovation from changes in protein domains and their combinations.

    PubMed

    Lees, Jonathan G; Dawson, Natalie L; Sillitoe, Ian; Orengo, Christine A

    2016-06-01

    Domains are the functional building blocks of proteins. In this work we discuss how domains can contribute to the evolution of new functions. Domains themselves can evolve through various mechanisms, altering their intrinsic function. Domains can also facilitate functional innovations by combining with other domains to make novel proteins. We discuss the mechanisms by which domain and domain combinations support functional innovations. We highlight interesting examples where changes in domain combination promote changes at the domain level.

  13. Predicting the Effect of Changing Precipitation Extremes and Land Cover Change on Urban Water Quality

    NASA Astrophysics Data System (ADS)

    SUN, N.; Yearsley, J. R.; Lettenmaier, D. P.

    2013-12-01

    Recent research shows that precipitation extremes in many of the largest U.S. urban areas have increased over the last 60 years. These changes have important implications for stormwater runoff and water quality, which in urban areas are dominated by the most extreme precipitation events. We assess the potential implications of changes in extreme precipitation and changing land cover in urban and urbanizing watersheds at the regional scale using a combination of hydrology and water quality models. Specifically, we describe the integration of a spatially distributed hydrological model - the Distributed Hydrology Soil Vegetation Model (DHSVM), the urban water quality model in EPA's Storm Water Management Model (SWMM), the semi-Lagrangian stream temperature model RBM10, and dynamical and statistical downscaling methods applied to global climate predictions. Key output water quality parameters include total suspended solids (TSS), toal nitrogen, total phosphorous, fecal coliform bacteria and stream temperature. We have evaluated the performance of the modeling system in the highly urbanized Mercer Creek watershed in the rapidly growing Bellevue urban area in WA, USA. The results suggest that the model is able to (1) produce reasonable streamflow predictions at fine temporal and spatial scales; (2) provide spatially distributed water temperature predictions that mostly agree with observations throughout a complex stream network, and characterize impacts of climate, landscape, near-stream vegetation change on stream temperature at local and regional scales; and (3) capture plausibly the response of water quality constituents to varying magnitude of precipitation events in urban environments. Next we will extend the scope of the study from the Mercer Creek watershed to include the entire Puget Sound Basin, WA, USA.

  14. Predicted habitat shifts of Pacific top predators in a changing climate

    NASA Astrophysics Data System (ADS)

    Hazen, Elliott L.; Jorgensen, Salvador; Rykaczewski, Ryan R.; Bograd, Steven J.; Foley, David G.; Jonsen, Ian D.; Shaffer, Scott A.; Dunne, John P.; Costa, Daniel P.; Crowder, Larry B.; Block, Barbara A.

    2013-03-01

    To manage marine ecosystems proactively, it is important to identify species at risk and habitats critical for conservation. Climate change scenarios have predicted an average sea surface temperature (SST) rise of 1-6°C by 2100 (refs , ), which could affect the distribution and habitat of many marine species. Here we examine top predator distribution and diversity in the light of climate change using a database of 4,300 electronic tags deployed on 23 marine species from the Tagging of Pacific Predators project, and output from a global climate model to 2100. On the basis of models of observed species distribution as a function of SST, chlorophyll a and bathymetry, we project changes in species-specific core habitat and basin-scale patterns of biodiversity. We predict up to a 35% change in core habitat for some species, significant differences in rates and patterns of habitat change across guilds, and a substantial northward displacement of biodiversity across the North Pacific. For already stressed species, increased migration times and loss of pelagic habitat could exacerbate population declines or inhibit recovery. The impending effects of climate change stress the urgency of adaptively managing ecosystems facing multiple threats.

  15. Individualized Prediction of Changes in 6-Minute Walk Distance for Patients with Duchenne Muscular Dystrophy

    PubMed Central

    Goemans, Nathalie; vanden Hauwe, Marleen; Signorovitch, James; Swallow, Elyse; Song, Jinlin

    2016-01-01

    Background Deficits in ambulatory function progress at heterogeneous rates among individuals with Duchenne muscular dystrophy (DMD). The resulting inherent variability in ambulatory outcomes has complicated the design of drug efficacy trials and clouded the interpretation of trial results. We developed a prediction model for 1-year change in the six minute walk distance (6MWD) among DMD patients, and compared its predictive value to that of commonly used prognostic factors (age, baseline 6MWD, and steroid use). Methods Natural history data were collected from DMD patients at routine follow up visits approximately every 6 months over the course of 2–5 years. Assessments included ambulatory function and steroid use. The annualized change in 6MWD (Δ6MWD) was studied between all pairs of visits separated by 8–16 months. Prediction models were developed using multivariable regression for repeated measures, and evaluated using cross-validation. Results Among n = 191 follow-up intervals (n = 39 boys), mean starting age was 9.4 years, mean starting 6MWD was 351.8 meters, and 75% had received steroids for at least one year. Over the subsequent 8–16 months, mean Δ6MWD was -37.0 meters with a standard deviation (SD) of 93.7 meters. Predictions based on a composite of age, baseline 6MWD, and steroid use explained 28% of variation in Δ6MWD (R2 = 0.28, residual SD = 79.4 meters). A broadened prognostic model, adding timed 10-meter walk/run, 4-stair climb, and rise from supine, as well as height and weight, significantly improved prediction, explaining 59% of variation in Δ6MWD after cross-validation (R2 = 0.59, residual SD = 59.7 meters). Conclusions A prognostic model incorporating timed function tests significantly improved prediction of 1-year changes in 6MWD. Explained variation was more than doubled compared to predictions based only on age, baseline 6MWD, and steroid use. There is significant potential for composite prognostic models to inform DMD clinical trials

  16. Predicted equations for ventilatory function among Kuching (Sarawak, Malaysia) population.

    PubMed

    Djojodibroto, R D; Pratibha, G; Kamaluddin, B; Manjit, S S; Sumitabha, G; Kumar, A Deva; Hashami, B

    2009-12-01

    Spirometry data of 869 individuals (males and females) between the ages of 10 to 60 years were analyzed. The analysis yielded the following conclusions: 1. The pattern of Forced Vital Capacity (FVC) and Forced Expiratory Volume in One Second (FEV1) for the selected subgroups seems to be gender dependant: in males, the highest values were seen in the Chinese, followed by the Malay, and then the Dayak; in females, the highest values were seen in the Chinese, followed by the Dayak, and then the Malay. 2. Smoking that did not produce respiratory symptom was not associated with a decline in lung function, in fact we noted higher values in smokers as compared to nonsmokers. 3. Prediction formulae (54 in total) are worked out for FVC & FEV1 for the respective gender and each of the selected subgroups.

  17. Link prediction boosted psychiatry disorder classification for functional connectivity network

    NASA Astrophysics Data System (ADS)

    Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

    2017-02-01

    Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

  18. A yeast functional screen predicts new candidate ALS disease genes

    PubMed Central

    Couthouis, Julien; Hart, Michael P.; Shorter, James; DeJesus-Hernandez, Mariely; Erion, Renske; Oristano, Rachel; Liu, Annie X.; Ramos, Daniel; Jethava, Niti; Hosangadi, Divya; Epstein, James; Chiang, Ashley; Diaz, Zamia; Nakaya, Tadashi; Ibrahim, Fadia; Kim, Hyung-Jun; Solski, Jennifer A.; Williams, Kelly L.; Mojsilovic-Petrovic, Jelena; Ingre, Caroline; Boylan, Kevin; Graff-Radford, Neill R.; Dickson, Dennis W.; Clay-Falcone, Dana; Elman, Lauren; McCluskey, Leo; Greene, Robert; Kalb, Robert G.; Lee, Virginia M.-Y.; Trojanowski, John Q.; Ludolph, Albert; Robberecht, Wim; Andersen, Peter M.; Nicholson, Garth A.; Blair, Ian P.; King, Oliver D.; Bonini, Nancy M.; Van Deerlin, Vivianna; Rademakers, Rosa; Mourelatos, Zissimos; Gitler, Aaron D.

    2011-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating and universally fatal neurodegenerative disease. Mutations in two related RNA-binding proteins, TDP-43 and FUS, that harbor prion-like domains, cause some forms of ALS. There are at least 213 human proteins harboring RNA recognition motifs, including FUS and TDP-43, raising the possibility that additional RNA-binding proteins might contribute to ALS pathogenesis. We performed a systematic survey of these proteins to find additional candidates similar to TDP-43 and FUS, followed by bioinformatics to predict prion-like domains in a subset of them. We sequenced one of these genes, TAF15, in patients with ALS and identified missense variants, which were absent in a large number of healthy controls. These disease-associated variants of TAF15 caused formation of cytoplasmic foci when expressed in primary cultures of spinal cord neurons. Very similar to TDP-43 and FUS, TAF15 aggregated in vitro and conferred neurodegeneration in Drosophila, with the ALS-linked variants having a more severe effect than wild type. Immunohistochemistry of postmortem spinal cord tissue revealed mislocalization of TAF15 in motor neurons of patients with ALS. We propose that aggregation-prone RNA-binding proteins might contribute very broadly to ALS pathogenesis and the genes identified in our yeast functional screen, coupled with prion-like domain prediction analysis, now provide a powerful resource to facilitate ALS disease gene discovery. PMID:22065782

  19. Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

    SciTech Connect

    Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

    2015-04-02

    The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO22+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K1 values are significantly overestimated. Accurate predictions of the absolute log K1 values (root mean square deviation from experiment < 1.0 for log K1 values ranging from 0 to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.

  20. Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

    DOE PAGES

    Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

    2015-04-02

    The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO22+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K1 values are significantly overestimated. Accurate predictions of the absolute log K1 values (root mean square deviation from experiment < 1.0 for log K1 values ranging from 0more » to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.« less

  1. Application of Functional Use Predictions to Aid in Structure ...

    EPA Pesticide Factsheets

    Humans are potentially exposed to thousands of anthropogenic chemicals in commerce. Recent work has shown that the bulk of this exposure may occur in near-field indoor environments (e.g., home, school, work, etc.). Advances in suspect screening analyses (SSA) now allow an improved understanding of the chemicals present in these environments. However, due to the nature of suspect screening techniques, investigators are often left with chemical formula predictions, with the possibility of many chemical structures matching to each formula. Here, newly developed quantitative structure-use relationship (QSUR) models are used to identify potential exposure sources for candidate structures. Previously, a suspect screening workflow was introduced and applied to house dust samples collected from the U.S. Department of Housing and Urban Development’s American Healthy Homes Survey (AHHS) [Rager, et al., Env. Int. 88 (2016)]. This workflow utilized the US EPA’s Distributed Structure-Searchable Toxicity (DSSTox) Database to link identified molecular features to molecular formulas, and ultimately chemical structures. Multiple QSUR models were applied to support the evaluation of candidate structures. These QSURs predict the likelihood of a chemical having a functional use commonly associated with consumer products having near-field use. For 3,228 structures identified as possible chemicals in AHHS house dust samples, we were able to obtain the required descriptors to appl

  2. Striatum-medial prefrontal cortex connectivity predicts developmental changes in reinforcement learning.

    PubMed

    van den Bos, Wouter; Cohen, Michael X; Kahnt, Thorsten; Crone, Eveline A

    2012-06-01

    During development, children improve in learning from feedback to adapt their behavior. However, it is still unclear which neural mechanisms might underlie these developmental changes. In the current study, we used a reinforcement learning model to investigate neurodevelopmental changes in the representation and processing of learning signals. Sixty-seven healthy volunteers between ages 8 and 22 (children: 8-11 years, adolescents: 13-16 years, and adults: 18-22 years) performed a probabilistic learning task while in a magnetic resonance imaging scanner. The behavioral data demonstrated age differences in learning parameters with a stronger impact of negative feedback on expected value in children. Imaging data revealed that the neural representation of prediction errors was similar across age groups, but functional connectivity between the ventral striatum and the medial prefrontal cortex changed as a function of age. Furthermore, the connectivity strength predicted the tendency to alter expectations after receiving negative feedback. These findings suggest that the underlying mechanisms of developmental changes in learning are not related to differences in the neural representation of learning signals per se but rather in how learning signals are used to guide behavior and expectations.

  3. Prediction of glass durability as a function of environmental conditions

    SciTech Connect

    Jantzen, C M

    1988-01-01

    A thermodynamic model of glass durability is applied to natural, ancient, and nuclear waste glasses. The durabilities of over 150 different natural and man-made glasses, including actual ancient Roman and Islamic glasses (Jalame ca. 350 AD, Nishapur 10-11th century AD and Gorgon 9-11th century AD), are compared. Glass durability is a function of the thermodynamic hydration free energy, ..delta..G/sub hyd/, which can be calculated from glass composition and solution pH. The durability of the most durable nuclear waste glasses examined was /approximately/10/sup 6/ years. The least durable waste glass formulations were comparable in durability to the most durable simulated medieval window glasses of /approximately/10/sup 3/ years. In this manner, the durability of nuclear waste glasses has been interpolated to be /approximately/10/sup 6/ years and no less than 10/sup 3/ years. Hydration thermodynamics have been shown to be applicable to the dissolution of glass in various natural environments. Groundwater-glass interactions relative to geologic disposal of nuclear waste, hydration rind dating of obsidians, andor other archeological studies can be modeled, e.g., the relative durabilities of six simulated medieval window glasses have been correctly predicted for both laboratory (one month) and burial (5 years) experiments. Effects of solution pH on glass dissolution has been determined experimentally for the 150 different glasses and can be predicted theoretically by hydration thermodynamics. The effects of solution redox on dissolution of glass matrix elements such as SI and B have shown to be minimal. The combined effects of solution pH and Eh have been described and unified by construction of thermodynamically calculated Pourbaix (pH-Eh) diagrams for glass dissolution. The Pourbaix diagrams have been quantified to describe glass dissolution as a function of environmental conditions by use of the data derived from hydration thermodynamics. 56 refs., 7 figs.

  4. Planning versus action: Different decision-making processes predict plans to change one's diet versus actual dietary behavior.

    PubMed

    Kiviniemi, Marc T; Brown-Kramer, Carolyn R

    2015-05-01

    Most health decision-making models posit that deciding to engage in a health behavior involves forming a behavioral intention which then leads to actual behavior. However, behavioral intentions and actual behavior may not be functionally equivalent. Two studies examined whether decision-making factors predicting dietary behaviors were the same as or distinct from those predicting intentions. Actual dietary behavior was proximally predicted by affective associations with the behavior. By contrast, behavioral intentions were predicted by cognitive beliefs about behaviors, with no contribution of affective associations. This dissociation has implications for understanding individual regulation of health behaviors and for behavior change interventions.

  5. Variability in functional brain networks predicts expertise during action observation.

    PubMed

    Amoruso, Lucía; Ibáñez, Agustín; Fonseca, Bruno; Gadea, Sebastián; Sedeño, Lucas; Sigman, Mariano; García, Adolfo M; Fraiman, Ricardo; Fraiman, Daniel

    2017-02-01

    Observing an action performed by another individual activates, in the observer, similar circuits as those involved in the actual execution of that action. This activation is modulated by prior experience; indeed, sustained training in a particular motor domain leads to structural and functional changes in critical brain areas. Here, we capitalized on a novel graph-theory approach to electroencephalographic data (Fraiman et al., 2016) to test whether variability in functional brain networks implicated in Tango observation can discriminate between groups differing in their level of expertise. We found that experts and beginners significantly differed in the functional organization of task-relevant networks. Specifically, networks in expert Tango dancers exhibited less variability and a more robust functional architecture. Notably, these expertise-dependent effects were captured within networks derived from electrophysiological brain activity recorded in a very short time window (2s). In brief, variability in the organization of task-related networks seems to be a highly sensitive indicator of long-lasting training effects. This finding opens new methodological and theoretical windows to explore the impact of domain-specific expertise on brain plasticity, while highlighting variability as a fruitful measure in neuroimaging research.

  6. Amphibian gut microbiota shifts differentially in community structure but converges on habitat-specific predicted functions

    PubMed Central

    Bletz, Molly C.; Goedbloed, Daniel J.; Sanchez, Eugenia; Reinhardt, Timm; Tebbe, Christoph C.; Bhuju, Sabin; Geffers, Robert; Jarek, Michael; Vences, Miguel; Steinfartz, Sebastian

    2016-01-01

    Complex microbial communities inhabit vertebrate digestive systems but thorough understanding of the ecological dynamics and functions of host-associated microbiota within natural habitats is limited. We investigate the role of environmental conditions in shaping gut and skin microbiota under natural conditions by performing a field survey and reciprocal transfer experiments with salamander larvae inhabiting two distinct habitats (ponds and streams). We show that gut and skin microbiota are habitat-specific, demonstrating environmental factors mediate community structure. Reciprocal transfer reveals that gut microbiota, but not skin microbiota, responds differentially to environmental change. Stream-to-pond larvae shift their gut microbiota to that of pond-to-pond larvae, whereas pond-to-stream larvae change to a community structure distinct from both habitat controls. Predicted functions, however, match that of larvae from the destination habitats in both cases. Thus, microbial function can be matched without taxonomic coherence and gut microbiota appears to exhibit metagenomic plasticity. PMID:27976718

  7. Multi-parameter prediction of drivers' lane-changing behaviour with neural network model.

    PubMed

    Peng, Jinshuan; Guo, Yingshi; Fu, Rui; Yuan, Wei; Wang, Chang

    2015-09-01

    Accurate prediction of driving behaviour is essential for an active safety system to ensure driver safety. A model for predicting lane-changing behaviour is developed from the results of naturalistic on-road experiment for use in a lane-changing assistance system. Lane changing intent time window is determined via visual characteristics extraction of rearview mirrors. A prediction index system for left lane changes was constructed by considering drivers' visual search behaviours, vehicle operation behaviours, vehicle motion states, and driving conditions. A back-propagation neural network model was developed to predict lane-changing behaviour. The lane-change-intent time window is approximately 5 s long, depending on the subjects. The proposed model can accurately predict drivers' lane changing behaviour for at least 1.5 s in advance. The accuracy and time series characteristics of the model are superior to the use of turn signals in predicting lane-changing behaviour.

  8. Local functional descriptors for surface comparison based binding prediction

    PubMed Central

    2012-01-01

    Background Molecular recognition in proteins occurs due to appropriate arrangements of physical, chemical, and geometric properties of an atomic surface. Similar surface regions should create similar binding interfaces. Effective methods for comparing surface regions can be used in identifying similar regions, and to predict interactions without regard to the underlying structural scaffold that creates the surface. Results We present a new descriptor for protein functional surfaces and algorithms for using these descriptors to compare protein surface regions to identify ligand binding interfaces. Our approach uses descriptors of local regions of the surface, and assembles collections of matches to compare larger regions. Our approach uses a variety of physical, chemical, and geometric properties, adaptively weighting these properties as appropriate for different regions of the interface. Our approach builds a classifier based on a training corpus of examples of binding sites of the target ligand. The constructed classifiers can be applied to a query protein providing a probability for each position on the protein that the position is part of a binding interface. We demonstrate the effectiveness of the approach on a number of benchmarks, demonstrating performance that is comparable to the state-of-the-art, with an approach with more generality than these prior methods. Conclusions Local functional descriptors offer a new method for protein surface comparison that is sufficiently flexible to serve in a variety of applications. PMID:23176080

  9. TU-G-BRA-03: Predicting Radiation Therapy Induced Ventilation Changes Using 4DCT Jacobian Calculations

    SciTech Connect

    Patton, T; Du, K; Bayouth, J; Christensen, G; Reinhardt, J

    2015-06-15

    Purpose: Longitudinal changes in lung ventilation following radiation therapy can be mapped using four-dimensional computed tomography(4DCT) and image registration. This study aimed to predict ventilation changes caused by radiation therapy(RT) as a function of pre-RT ventilation and delivered dose. Methods: 4DCT images were acquired before and 3 months after radiation therapy for 13 subjects. Jacobian ventilation maps were calculated from the 4DCT images, warped to a common coordinate system, and a Jacobian ratio map was computed voxel-by-voxel as the ratio of post-RT to pre-RT Jacobian calculations. A leave-one-out method was used to build a response model for each subject: post-RT to pre-RT Jacobian ratio data and dose distributions of 12 subjects were applied to the subject’s pre-RT Jacobian map to predict the post-RT Jacobian. The predicted Jacobian map was compared to the actual post-RT Jacobian map to evaluate efficacy. Within this cohort, 8 subjects had repeat pre-RT scans that were compared as a reference for no ventilation change. Maps were compared using gamma pass rate criteria of 2mm distance-to-agreement and 6% ventilation difference. Gamma pass rates were compared using paired t-tests to determine significant differences. Further analysis masked non-radiation induced changes by excluding voxels below specified dose thresholds. Results: Visual inspection demonstrates the predicted post-RT ventilation map is similar to the actual map in magnitude and distribution. Quantitatively, the percentage of voxels in agreement when excluding voxels receiving below specified doses are: 74%/20Gy, 73%/10Gy, 73%/5Gy, and 71%/0Gy. By comparison, repeat scans produced 73% of voxels within the 6%/2mm criteria. The agreement of the actual post-RT maps with the predicted maps was significantly better than agreement with pre-RT maps (p<0.02). Conclusion: This work validates that significant changes to ventilation post-RT can be predicted. The differences between the

  10. Functional connectivity during rested wakefulness predicts vulnerability to sleep deprivation.

    PubMed

    Yeo, B T Thomas; Tandi, Jesisca; Chee, Michael W L

    2015-05-01

    Significant inter-individual differences in vigilance decline following sleep deprivation exist. We characterized functional connectivity in 68 healthy young adult participants in rested wakefulness and following a night of total sleep deprivation. After whole brain signal regression, functionally connected cortical networks during the well-rested state exhibited reduced correlation following sleep deprivation, suggesting that highly integrated brain regions become less integrated during sleep deprivation. In contrast, anti-correlations in the well-rested state became less so following sleep deprivation, suggesting that highly segregated networks become less segregated during sleep deprivation. Subjects more resilient to vigilance decline following sleep deprivation showed stronger anti-correlations among several networks. The weaker anti-correlations overlapped with connectivity alterations following sleep deprivation. Resilient individuals thus evidence clearer separation of highly segregated cortical networks in the well-rested state. In contrast to corticocortical connectivity, subcortical-cortical connectivity was comparable across resilient and vulnerable groups despite prominent state-related changes in both groups. Because sleep deprivation results in a significant elevation of whole brain signal amplitude, the aforesaid signal changes and group contrasts may be masked in analyses omitting their regression, suggesting possible value in regressing whole brain signal in certain experimental contexts.

  11. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    DOE PAGES

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2016-01-19

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Köhler theory to predict themore » effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.« less

  12. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    NASA Astrophysics Data System (ADS)

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2016-01-01

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Köhler theory to predict the effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid-liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.

  13. A data mining based approach to predict spatiotemporal changes in satellite images

    NASA Astrophysics Data System (ADS)

    Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben

    2011-06-01

    The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

  14. Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

    NASA Technical Reports Server (NTRS)

    Crane, Robert G.; Hewitson, Bruce

    1990-01-01

    Model simulations of global climate change are seen as an essential component of any program aimed at understanding human impact on the global environment. A major weakness of current general circulation models (GCMs), however, is their inability to predict reliably the regional consequences of a global scale change, and it is these regional scale predictions that are necessary for studies of human/environmental response. This research is directed toward the development of a methodology for the validation of the synoptic scale climatology of GCMs. This is developed with regard to the Goddard Institute for Space Studies (GISS) GCM Model 2, with the specific objective of using the synoptic circulation form a doubles CO2 simulation to estimate regional climate change over North America, south of Hudson Bay. This progress report is specifically concerned with validating the synoptic climatology of the GISS GCM, and developing the transfer function to derive grid-point temperatures from the synoptic circulation. Principal Components Analysis is used to characterize the primary modes of the spatial and temporal variability in the observed and simulated climate, and the model validation is based on correlations between component loadings, and power spectral analysis of the component scores. The results show that the high resolution GISS model does an excellent job of simulating the synoptic circulation over the U.S., and that grid-point temperatures can be predicted with reasonable accuracy from the circulation patterns.

  15. Predicting changes in cardiac myocyte contractility during early drug discovery with in vitro assays

    SciTech Connect

    Morton, M.J.; Armstrong, D.; Abi Gerges, N.; Bridgland-Taylor, M.; Pollard, C.E.; Bowes, J.; Valentin, J.-P.

    2014-09-01

    Cardiovascular-related adverse drug effects are a major concern for the pharmaceutical industry. Activity of an investigational drug at the L-type calcium channel could manifest in a number of ways, including changes in cardiac contractility. The aim of this study was to define which of the two assay technologies – radioligand-binding or automated electrophysiology – was most predictive of contractility effects in an in vitro myocyte contractility assay. The activity of reference and proprietary compounds at the L-type calcium channel was measured by radioligand-binding assays, conventional patch-clamp, automated electrophysiology, and by measurement of contractility in canine isolated cardiac myocytes. Activity in the radioligand-binding assay at the L-type Ca channel phenylalkylamine binding site was most predictive of an inotropic effect in the canine cardiac myocyte assay. The sensitivity was 73%, specificity 83% and predictivity 78%. The radioligand-binding assay may be run at a single test concentration and potency estimated. The least predictive assay was automated electrophysiology which showed a significant bias when compared with other assay formats. Given the importance of the L-type calcium channel, not just in cardiac function, but also in other organ systems, a screening strategy emerges whereby single concentration ligand-binding can be performed early in the discovery process with sufficient predictivity, throughput and turnaround time to influence chemical design and address a significant safety-related liability, at relatively low cost. - Highlights: • The L-type calcium channel is a significant safety liability during drug discovery. • Radioligand-binding to the L-type calcium channel can be measured in vitro. • The assay can be run at a single test concentration as part of a screening cascade. • This measurement is highly predictive of changes in cardiac myocyte contractility.

  16. Ageing increases reliance on sensorimotor prediction through structural and functional differences in frontostriatal circuits.

    PubMed

    Wolpe, Noham; Ingram, James N; Tsvetanov, Kamen A; Geerligs, Linda; Kievit, Rogier A; Henson, Richard N; Wolpert, Daniel M; Rowe, James B

    2016-10-03

    The control of voluntary movement changes markedly with age. A critical component of motor control is the integration of sensory information with predictions of the consequences of action, arising from internal models of movement. This leads to sensorimotor attenuation-a reduction in the perceived intensity of sensations from self-generated compared with external actions. Here we show that sensorimotor attenuation occurs in 98% of adults in a population-based cohort (n=325; 18-88 years; the Cambridge Centre for Ageing and Neuroscience). Importantly, attenuation increases with age, in proportion to reduced sensory sensitivity. This effect is associated with differences in the structure and functional connectivity of the pre-supplementary motor area (pre-SMA), assessed with magnetic resonance imaging. The results suggest that ageing alters the balance between the sensorium and predictive models, mediated by the pre-SMA and its connectivity in frontostriatal circuits. This shift may contribute to the motor and cognitive changes observed with age.

  17. Prediction of Changes in Vegetation Distribution Under Climate Change Scenarios Using Modis Dataset

    NASA Astrophysics Data System (ADS)

    Hirayama, Hidetake; Tomita, Mizuki; Hara, Keitarou

    2016-06-01

    The distribution of vegetation is expected to change under the influence of climate change. This study utilizes vegetation maps derived from Terra/MODIS data to generate a model of current climate conditions suitable to beech-dominated deciduous forests, which are the typical vegetation of Japan's cool temperate zone. This model will then be coordinated with future climate change scenarios to predict the future distribution of beech forests. The model was developed by using the presence or absence of beech forest as the dependent variable. Four climatic variables; mean minimum daily temperature of the coldest month (TMC) warmth index (WI) winter precipitation (PRW) and summer precipitation (PRS): and five geophysical variables; topography (TOPO), surface geology (GEOL), soil (SOIL), slope aspect (ASP), and inclination (INCL); were adopted as independent variables. Previous vegetation distribution studies used point data derived from field surveys. The remote sensing data utilized in this study, however, should permit collecting of greater amounts of data, and also frequent updating of data and distribution maps. These results will hopefully show that use of remote sensing data can provide new insights into our understanding of how vegetation distribution will be influenced by climate change.

  18. Changing currents: a strategy for understanding and predicting the changing ocean circulation.

    PubMed

    Bryden, Harry L; Robinson, Carol; Griffiths, Gwyn

    2012-12-13

    Within the context of UK marine science, we project a strategy for ocean circulation research over the next 20 years. We recommend a focus on three types of research: (i) sustained observations of the varying and evolving ocean circulation, (ii) careful analysis and interpretation of the observed climate changes for comparison with climate model projections, and (iii) the design and execution of focused field experiments to understand ocean processes that are not resolved in coupled climate models so as to be able to embed these processes realistically in the models. Within UK-sustained observations, we emphasize smart, cost-effective design of the observational network to extract maximum information from limited field resources. We encourage the incorporation of new sensors and new energy sources within the operational environment of UK-sustained observational programmes to bridge the gap that normally separates laboratory prototype from operational instrument. For interpreting the climate-change records obtained through a variety of national and international sustained observational programmes, creative and dedicated UK scientists should lead efforts to extract the meaningful signals and patterns of climate change and to interpret them so as to project future changes. For the process studies, individual scientists will need to work together in team environments to combine observational and process modelling results into effective improvements in the coupled climate models that will lead to more accurate climate predictions.

  19. Genomic islands predict functional adaptation in marine actinobacteria

    SciTech Connect

    Penn, Kevin; Jenkins, Caroline; Nett, Markus; Udwary, Daniel; Gontang, Erin; McGlinchey, Ryan; Foster, Brian; Lapidus, Alla; Podell, Sheila; Allen, Eric; Moore, Bradley; Jensen, Paul

    2009-04-01

    Linking functional traits to bacterial phylogeny remains a fundamental but elusive goal of microbial ecology 1. Without this information, it becomes impossible to resolve meaningful units of diversity and the mechanisms by which bacteria interact with each other and adapt to environmental change. Ecological adaptations among bacterial populations have been linked to genomic islands, strain-specific regions of DNA that house functionally adaptive traits 2. In the case of environmental bacteria, these traits are largely inferred from bioinformatic or gene expression analyses 2, thus leaving few examples in which the functions of island genes have been experimentally characterized. Here we report the complete genome sequences of Salinispora tropica and S. arenicola, the first cultured, obligate marine Actinobacteria 3. These two species inhabit benthic marine environments and dedicate 8-10percent of their genomes to the biosynthesis of secondary metabolites. Despite a close phylogenetic relationship, 25 of 37 secondary metabolic pathways are species-specific and located within 21 genomic islands, thus providing new evidence linking secondary metabolism to ecological adaptation. Species-specific differences are also observed in CRISPR sequences, suggesting that variations in phage immunity provide fitness advantages that contribute to the cosmopolitan distribution of S. arenicola 4. The two Salinispora genomes have evolved by complex processes that include the duplication and acquisition of secondary metabolite genes, the products of which provide immediate opportunities for molecular diversification and ecological adaptation. Evidence that secondary metabolic pathways are exchanged by Horizontal Gene Transfer (HGT) yet are fixed among globally distributed populations 5 supports a functional role for their products and suggests that pathway acquisition represents a previously unrecognized force driving bacterial diversification

  20. Lung function indices for predicting mortality in COPD

    PubMed Central

    Boutou, Afroditi K.; Shrikrishna, Dinesh; Tanner, Rebecca J.; Smith, Cayley; Kelly, Julia L.; Ward, Simon P.; Polkey, Michael I.; Hopkinson, Nicholas S.

    2013-01-01

    Chronic obstructive pulmonary disease (COPD) is characterised by high morbidity and mortality. It remains unknown which aspect of lung function carries the most prognostic information and if simple spirometry is sufficient. Survival was assessed in COPD outpatients whose data had been added prospectively to a clinical audit database from the point of first full lung function testing including spirometry, lung volumes, gas transfer and arterial blood gases. Variables univariately associated with survival were entered into a multivariate Cox proportional hazard model. 604 patients were included (mean±sd age 61.9±9.7 years; forced expiratory volume in 1 s 37±18.1% predicted; 62.9% males); 229 (37.9%) died during a median follow-up of 83 months. Median survival was 91.9 (95% CI 80.8–103) months with survival rates at 3 and 5 years 0.83 and 0.66, respectively. Carbon monoxide transfer factor % pred quartiles (best quartile (>51%): HR 0.33, 95% CI 0.172–0.639; and second quartile (51–37.3%): HR 0.52, 95% CI 0.322–0.825; versus lowest quartile (<27.9%)), age (HR 1.04, 95% CI 1.02–1.06) and arterial oxygen partial pressure (HR 0.85, 95% CI 0.77–0.94) were the only parameters independently associated with mortality. Measurement of gas transfer provides additional prognostic information compared to spirometry in patients under hospital follow-up and could be considered routinely. PMID:23349449

  1. Immunologic changes occurring at kindergarten entry predict respiratory illnesses after the Loma Prieta earthquake.

    PubMed

    Boyce, W T; Chesterman, E A; Martin, N; Folkman, S; Cohen, F; Wara, D

    1993-10-01

    Previous studies in adult populations have demonstrated alterations in immune function after psychologically stressful events, and pediatric research has shown significant associations between stress and various childhood morbidities. However, no previous work has examined stress-related immune changes in children and subsequent illness experience. Twenty children were enrolled in a study on immunologic changes after kindergarten entry and their prospective relationship to respiratory illness (RI) experience. Midway through a 12-week RI data collection period, the October 17, 1989 Loma Prieta earthquake occurred. The timing of this event created a natural experiment enabling us to study possible associations between immunologic changes at kindergarten entry, the intensity of earthquake-related stress for children and parents, and changes in RI incidence over the 6 weeks after the earthquake. Immunologic changes were measured using helper (CD4+)-suppressor (CD8+) cell ratios, lymphocyte responses to pokeweed mitogen, and type-specific antibody responses to Pneumovax, in blood sampled 1 week before and 1 week after school entry. RI incidence was assessed using home health diaries and telephone interviews completed every 2 weeks. RIs per child varied from none to six. Six children showed an increase in RI incidence after the earthquake; five experienced a decline. Changes in helper-suppressor cell ratios and pokeweed mitogen response predicted changes in RI incidence in the postearthquake period (r = .43, .46; p < .05). Children showing upregulation of immune parameters at school entry sustained a significant increase in RI incidence after the earthquake.(ABSTRACT TRUNCATED AT 250 WORDS)

  2. Making predictions in a changing world-inference, uncertainty, and learning.

    PubMed

    O'Reilly, Jill X

    2013-01-01

    To function effectively, brains need to make predictions about their environment based on past experience, i.e., they need to learn about their environment. The algorithms by which learning occurs are of interest to neuroscientists, both in their own right (because they exist in the brain) and as a tool to model participants' incomplete knowledge of task parameters and hence, to better understand their behavior. This review focusses on a particular challenge for learning algorithms-how to match the rate at which they learn to the rate of change in the environment, so that they use as much observed data as possible whilst disregarding irrelevant, old observations. To do this algorithms must evaluate whether the environment is changing. We discuss the concepts of likelihood, priors and transition functions, and how these relate to change detection. We review expected and estimation uncertainty, and how these relate to change detection and learning rate. Finally, we consider the neural correlates of uncertainty and learning. We argue that the neural correlates of uncertainty bear a resemblance to neural systems that are active when agents actively explore their environments, suggesting that the mechanisms by which the rate of learning is set may be subject to top down control (in circumstances when agents actively seek new information) as well as bottom up control (by observations that imply change in the environment).

  3. An insula-frontostriatal network mediates flexible cognitive control by adaptively predicting changing control demands

    PubMed Central

    Jiang, Jiefeng; Beck, Jeffrey; Heller, Katherine; Egner, Tobias

    2015-01-01

    The anterior cingulate and lateral prefrontal cortices have been implicated in implementing context-appropriate attentional control, but the learning mechanisms underlying our ability to flexibly adapt the control settings to changing environments remain poorly understood. Here we show that human adjustments to varying control demands are captured by a reinforcement learner with a flexible, volatility-driven learning rate. Using model-based functional magnetic resonance imaging, we demonstrate that volatility of control demand is estimated by the anterior insula, which in turn optimizes the prediction of forthcoming demand in the caudate nucleus. The caudate's prediction of control demand subsequently guides the implementation of proactive and reactive attentional control in dorsal anterior cingulate and dorsolateral prefrontal cortices. These data enhance our understanding of the neuro-computational mechanisms of adaptive behaviour by connecting the classic cingulate-prefrontal cognitive control network to a subcortical control-learning mechanism that infers future demands by flexibly integrating remote and recent past experiences. PMID:26391305

  4. Functional identity and diversity of animals predict ecosystem functioning better than species-based indices.

    PubMed

    Gagic, Vesna; Bartomeus, Ignasi; Jonsson, Tomas; Taylor, Astrid; Winqvist, Camilla; Fischer, Christina; Slade, Eleanor M; Steffan-Dewenter, Ingolf; Emmerson, Mark; Potts, Simon G; Tscharntke, Teja; Weisser, Wolfgang; Bommarco, Riccardo

    2015-02-22

    Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se.

  5. Predicting regional neurodegeneration from the healthy brain functional connectome.

    PubMed

    Zhou, Juan; Gennatas, Efstathios D; Kramer, Joel H; Miller, Bruce L; Seeley, William W

    2012-03-22

    Neurodegenerative diseases target large-scale neural networks. Four competing mechanistic hypotheses have been proposed to explain network-based disease patterning: nodal stress, transneuronal spread, trophic failure, and shared vulnerability. Here, we used task-free fMRI to derive the healthy intrinsic connectivity patterns seeded by brain regions vulnerable to any of five distinct neurodegenerative diseases. These data enabled us to investigate how intrinsic connectivity in health predicts region-by-region vulnerability to disease. For each illness, specific regions emerged as critical network "epicenters" whose normal connectivity profiles most resembled the disease-associated atrophy pattern. Graph theoretical analyses in healthy subjects revealed that regions with higher total connectional flow and, more consistently, shorter functional paths to the epicenters, showed greater disease-related vulnerability. These findings best fit a transneuronal spread model of network-based vulnerability. Molecular pathological approaches may help clarify what makes each epicenter vulnerable to its targeting disease and how toxic protein species travel between networked brain structures.

  6. Gene function prediction based on the Gene Ontology hierarchical structure.

    PubMed

    Cheng, Liangxi; Lin, Hongfei; Hu, Yuncui; Wang, Jian; Yang, Zhihao

    2014-01-01

    The information of the Gene Ontology annotation is helpful in the explanation of life science phenomena, and can provide great support for the research of the biomedical field. The use of the Gene Ontology is gradually affecting the way people store and understand bioinformatic data. To facilitate the prediction of gene functions with the aid of text mining methods and existing resources, we transform it into a multi-label top-down classification problem and develop a method that uses the hierarchical relationships in the Gene Ontology structure to relieve the quantitative imbalance of positive and negative training samples. Meanwhile the method enhances the discriminating ability of classifiers by retaining and highlighting the key training samples. Additionally, the top-down classifier based on a tree structure takes the relationship of target classes into consideration and thus solves the incompatibility between the classification results and the Gene Ontology structure. Our experiment on the Gene Ontology annotation corpus achieves an F-value performance of 50.7% (precision: 52.7% recall: 48.9%). The experimental results demonstrate that when the size of training set is small, it can be expanded via topological propagation of associated documents between the parent and child nodes in the tree structure. The top-down classification model applies to the set of texts in an ontology structure or with a hierarchical relationship.

  7. Predicting ecological changes on benthic estuarine assemblages through decadal climate trends along Brazilian Marine Ecoregions

    NASA Astrophysics Data System (ADS)

    Bernardino, Angelo F.; Netto, Sérgio A.; Pagliosa, Paulo R.; Barros, Francisco; Christofoletti, Ronaldo A.; Rosa Filho, José S.; Colling, André; Lana, Paulo C.

    2015-12-01

    Estuaries are threatened coastal ecosystems that support relevant ecological functions worldwide. The predicted global climate changes demand actions to understand, anticipate and avoid further damage to estuarine habitats. In this study we reviewed data on polychaete assemblages, as a surrogate for overall benthic communities, from 51 estuaries along five Marine Ecoregions of Brazil (Amazonia, NE Brazil, E Brazil, SE Brazil and Rio Grande). We critically evaluated the adaptive capacity and ultimately the resilience to decadal changes in temperature and rainfall of the polychaete assemblages. As a support for theoretical predictions on changes linked to global warming we compared the variability of benthic assemblages across the ecoregions with a 40-year time series of temperature and rainfall data. We found a significant upward trend in temperature during the last four decades at all marine ecoregions of Brazil, while rainfall increase was restricted to the SE Brazil ecoregion. Benthic assemblages and climate trends varied significantly among and within ecoregions. The high variability in climate patterns in estuaries within the same ecoregion may lead to correspondingly high levels of noise on the expected responses of benthic fauna. Nonetheless, we expect changes in community structure and productivity of benthic species at marine ecoregions under increasing influence of higher temperatures, extreme events and pollution.

  8. Aggressive behavior and change in salivary testosterone concentrations predict willingness to engage in a competitive task.

    PubMed

    Carré, Justin M; McCormick, Cheryl M

    2008-08-01

    The current study investigated relationships among aggressive behavior, change in salivary testosterone concentrations, and willingness to engage in a competitive task. Thirty-eight male participants provided saliva samples before and after performing the Point Subtraction Aggression Paradigm (a laboratory measure that provides opportunity for aggressive and defensive behavior while working for reward; all three involve pressing specific response keys). Baseline testosterone concentrations were not associated with aggressive responding. However, aggressive responding (but not point reward or point protection responding) predicted the pre- to post-PSAP change in testosterone: Those with the highest aggressive responding had the largest percent increase in testosterone concentrations. Together, aggressive responding and change in testosterone predicted willingness to compete following the PSAP. Controlling for aggression, men who showed a rise in testosterone were more likely to choose to compete again (p=0.03) and controlling for testosterone change, men who showed the highest level of aggressive responding were more likely to choose the non-competitive task (p=0.02). These results indicate that situation-specific aggressive behavior and testosterone responsiveness are functionally relevant predictors of future social behavior.

  9. Error estimates for density-functional theory predictions of surface energy and work function

    NASA Astrophysics Data System (ADS)

    De Waele, Sam; Lejaeghere, Kurt; Sluydts, Michael; Cottenier, Stefaan

    2016-12-01

    Density-functional theory (DFT) predictions of materials properties are becoming ever more widespread. With increased use comes the demand for estimates of the accuracy of DFT results. In view of the importance of reliable surface properties, this work calculates surface energies and work functions for a large and diverse test set of crystalline solids. They are compared to experimental values by performing a linear regression, which results in a measure of the predictable and material-specific error of the theoretical result. Two of the most prevalent functionals, the local density approximation (LDA) and the Perdew-Burke-Ernzerhof parametrization of the generalized gradient approximation (PBE-GGA), are evaluated and compared. Both LDA and GGA-PBE are found to yield accurate work functions with error bars below 0.3 eV, rivaling the experimental precision. LDA also provides satisfactory estimates for the surface energy with error bars smaller than 10%, but GGA-PBE significantly underestimates the surface energy for materials with a large correlation energy.

  10. Ways that Social Change Predicts Personal Quality of Life

    ERIC Educational Resources Information Center

    Cheung, Chau-Kiu; Leung, Kwok

    2010-01-01

    A notable way that social change affects personal quality of life would rely on the person's experience with social change. This experience may influence societal quality of life and quality of work life, which may in turn affect personal quality of life. Additionally, the experience of social change is possibly less detrimental to personal…

  11. Plant physiological models of heat, water and photoinhibition stress for climate change modelling and agricultural prediction

    NASA Astrophysics Data System (ADS)

    Nicolas, B.; Gilbert, M. E.; Paw U, K. T.

    2015-12-01

    Soil-Vegetation-Atmosphere Transfer (SVAT) models are based upon well understood steady state photosynthetic physiology - the Farquhar-von Caemmerer-Berry model (FvCB). However, representations of physiological stress and damage have not been successfully integrated into SVAT models. Generally, it has been assumed that plants will strive to conserve water at higher temperatures by reducing stomatal conductance or adjusting osmotic balance, until potentially damaging temperatures and the need for evaporative cooling become more important than water conservation. A key point is that damage is the result of combined stresses: drought leads to stomatal closure, less evaporative cooling, high leaf temperature, less photosynthetic dissipation of absorbed energy, all coupled with high light (photosynthetic photon flux density; PPFD). This leads to excess absorbed energy by Photosystem II (PSII) and results in photoinhibition and damage, neither are included in SVAT models. Current representations of photoinhibition are treated as a function of PPFD, not as a function of constrained photosynthesis under heat or water. Thus, it seems unlikely that current models can predict responses of vegetation to climate variability and change. We propose a dynamic model of damage to Rubisco and RuBP-regeneration that accounts, mechanistically, for the interactions between high temperature, light, and constrained photosynthesis under drought. Further, these predictions are illustrated by key experiments allowing model validation. We also integrated this new framework within the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA). Preliminary results show that our approach can be used to predict reasonable photosynthetic dynamics. For instances, a leaf undergoing one day of drought stress will quickly decrease its maximum quantum yield of PSII (Fv/Fm), but it won't recover to unstressed levels for several days. Consequently, cumulative effect of photoinhibition on photosynthesis can cause

  12. Stress induced changes in testis function.

    PubMed

    López-Calderón, A; Ariznavarreta, C; González-Quijano, M I; Tresguerres, J A; Calderón, M D

    1991-01-01

    The mechanism through which chronic stress inhibits the hypothalamic-pituitary-testicular axis has been investigated. Chronic restraint stress decreases testosterone secretion, an effect that is associated with a decrease in plasma gonadotropin levels. In chronically stressed rats there was a decrease in hypothalamic luteinizing hormone-releasing hormone (LHRH) content and the response on plasma gonadotropins to LHRH administration was enhanced. Thus the inhibitory effect of chronic stress on plasma LH and FSH levels seems not to be due to a reduction in pituitary responsiveness to LHRH, but rather to a modification in LHRH secretion. It has been suggested that beta-endorphin might interfere with hypothalamic LHRH secretion during stress. Chronic immobilization did not modify hypothalamic beta-endorphin, while an increase in pituitary beta-endorphin secretion was observed. Since we cannot exclude that changes in beta-endorphin secreted by the pituitary or other opioids may play some role in the stress-induced decrease in LHRH secretion, the effect of naltrexone administration on plasma gonadotropin was studied in chronically stressed rats. Naltrexone treatment did not modify the decrease in plasma concentrations of LH or FSH. These findings suggest that the inhibitory effect of restraint on the testicular axis is exerted at hypothalamic level by some mechanism other than opioids.

  13. Changes in social functioning and circulating oxytocin and vasopressin following the migration to a new country.

    PubMed

    Gouin, Jean-Philippe; Pournajafi-Nazarloo, Hossein; Carter, C Sue

    2015-02-01

    Prior studies have reported associations between plasma oxytocin and vasopressin and markers of social functioning. However, because most human studies have used cross-sectional designs, it is unclear whether plasma oxytocin and vasopressin influences social functioning or whether social functioning modulates the production and peripheral release of these peptides. In order to address this question, we followed individuals who experienced major changes in social functioning subsequent to the migration to a new country. In this study, 59 new international students were recruited shortly after arrival in the host country and reassessed 2 and 5 months later. At each assessment participants provided information on their current social functioning and blood samples for oxytocin and vasopressin analysis. Results indicated that changes in social functioning were not related to changes in plasma oxytocin. Instead, baseline oxytocin predicted changes in social relationship satisfaction, social support, and loneliness over time. In contrast, plasma vasopressin changed as a function of social integration. Baseline vasopressin was not related to changes in social functioning over time. These results emphasize the different roles of plasma oxytocin and vasopressin in responses to changes in social functioning in humans.

  14. Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

    PubMed

    Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

    2016-05-01

    Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios.

  15. Comparative analysis of grapevine whole-genome gene predictions, functional annotation, categorization and integration of the predicted gene sequences

    PubMed Central

    2012-01-01

    Background The first draft assembly and gene prediction of the grapevine genome (8X base coverage) was made available to the scientific community in 2007, and functional annotation was developed on this gene prediction. Since then additional Sanger sequences were added to the 8X sequences pool and a new version of the genomic sequence with superior base coverage (12X) was produced. Results In order to more efficiently annotate the function of the genes predicted in the new assembly, it is important to build on as much of the previous work as possible, by transferring 8X annotation of the genome to the 12X version. The 8X and 12X assemblies and gene predictions of the grapevine genome were compared to answer the question, “Can we uniquely map 8X predicted genes to 12X predicted genes?” The results show that while the assemblies and gene structure predictions are too different to make a complete mapping between them, most genes (18,725) showed a one-to-one relationship between 8X predicted genes and the last version of 12X predicted genes. In addition, reshuffled genomic sequence structures appeared. These highlight regions of the genome where the gene predictions need to be taken with caution. Based on the new grapevine gene functional annotation and in-depth functional categorization, twenty eight new molecular networks have been created for VitisNet while the existing networks were updated. Conclusions The outcomes of this study provide a functional annotation of the 12X genes, an update of VitisNet, the system of the grapevine molecular networks, and a new functional categorization of genes. Data are available at the VitisNet website (http://www.sdstate.edu/ps/research/vitis/pathways.cfm). PMID:22554261

  16. Cue predictability changes scaling in eye-movement fluctuations.

    PubMed

    Wallot, Sebastian; Coey, Charles A; Richardson, Michael J

    2015-10-01

    Recent research has provided evidence for scaling-relations in eye-movement fluctuations, but not much is known about what these scaling relations imply about cognition or eye-movement control. Generally, scaling relations in behavioral and neurophysiological data have been interpreted as an indicator for the coordination of neurophysiological and cognitive processes. In this study, we investigated the effect of predictability in timing and gaze-direction on eye-movement fluctuations. Participants performed a simple eye-movement task, in which a visual cue prompted their gaze to different locations on a spatial layout, and the predictability about temporal and directional aspects of the cue were manipulated. The results showed that scaling exponents in eye-movements decreased with predictability and were related to the participants' perceived effort during the task. In relation to past research, these findings suggest that scaling exponents reflect a relative demand for voluntary control during task performance.

  17. The direct segment of the arcuate fasciculus is predictive of longitudinal reading change.

    PubMed

    Gullick, Margaret M; Booth, James R

    2015-06-01

    Structural coherence across the arcuate fasciculus has previously been related to reading skill, but the arcuate may be divisible into distinct subtracts which support different functions. Here, we examine longitudinal data from 30 children between the ages of 8 and 14 to determine whether initial coherence in any of the arcuate's subsections is predictive of changes in reading across a longitudinal interval of approximately three years. The arcuate was divided using probabilistic tractography; mean fractional anisotropy across each subtract was extracted for each participant. Time 1 to Time 2 change in reading skill (identification, fluency score average) was significantly and uniquely predicted by only direct fronto-temporal arcuate segment coherence. Participants with lower direct segment FA demonstrated decreases in reading scores, potentially reflecting lessened improvements due to continued inefficient processing. These results were consistent in the older and younger halves of the sample. As such, we demonstrate that it is specifically the direct segment of the arcuate that may support and be predictive of reading skill both initially and longitudinally across development.

  18. Relating Phylogenetic and Functional Diversity among Denitrifiers and Quantifying their Capacity to Predict Community Functioning.

    PubMed

    Salles, Joana Falcão; Le Roux, Xavier; Poly, Franck

    2012-01-01

    Genetic diversity of phylogenetic or functional markers is widely used as a proxy of microbial diversity. However, it remains unclear to what extent functional diversity (FD), gene sequence diversity and community functioning are linked. For a range of denitrifying bacteria, we analyzed the relationships between (i) the similarity of functional traits evaluated from metabolic profiles (BIOLOG plates) or from N(2)O accumulation patterns on different carbon sources and (ii) the similarity of phylogenetic (16S rRNA gene) or functional (nir gene) markers. We also calculated different proxies for the diversity of denitrifier community based on taxa richness, phylogenetic (16S rRNA gene) or functional similarities (based either on metabolic profiles or N(2)O accumulation patterns), and evaluated their performance in inferring the functioning of assembled denitrifying communities. For individual strains, the variation in the 16S rRNA gene sequence was weakly correlated with the variation in metabolic patterns (ρ = 0.35) and was not related to N(2)O accumulation. The latter was correlated with the similarity of nitrite reductase residues. When nir genes were analyzed separately, the similarity in amino acids coded by the nirS genes was highly correlated with the observed patterns of N(2)O accumulation (ρ = 0.62), whereas nirK amino acid residues were unrelated to N(2)O accumulation. For bacterial assemblages, phylogenetic diversity (average similarity among species in a community) and mean community dissimilarity (average distance between species) calculated using 16S rRNA gene sequences, and FD measures associated with metabolic profiles, poorly predicted the variation in the functioning of assembled communities (≤15%). In contrast, the proxies of FD based on N(2)O accumulation patterns performed better and explained from 23 to 42% of the variation in denitrification. Amongst those, community niche was the best metric, indicating the importance of

  19. The conformational signature of arrestin3 predicts its trafficking and signaling functions

    PubMed Central

    Lee, Mi-Hye; Appleton, Kathryn M.; Strungs, Erik G.; Kwon, Joshua Y.; Morinelli, Thomas A.; Peterson, Yuri K.; Laporte, Stephane A.; Luttrell, Louis M.

    2016-01-01

    Arrestins are cytosolic proteins that regulate G protein-coupled receptor (GPCR) desensitization, internalization, trafficking, and signaling1,2. Arrestin recruitment uncouples GPCRs from heterotrimeric G proteins, and targets them for internalization via clathrin-coated pits3,4. Arrestins also function as ligand-regulated scaffolds that recruit multiple non-G protein effectors into GPCR-based ‘signalsomes’5,6. While the dominant function(s) of arrestins vary between receptors, the mechanism whereby different GPCRs specify divergent arrestin functions is not understood. Using a panel of intramolecular FlAsH-BRET reporters7 to monitor conformational changes in arrestin3, we show here that GPCRs impose distinctive arrestin ‘conformational signatures’ that reflect the stability of the receptor-arrestin complex and role of arrestin3 in activating or dampening downstream signaling events. The predictive value of these signatures extends to structurally distinct ligands activating the same GPCR, such that the innate properties of the ligand are reflected as changes in arrestin3 conformation. Our findings demonstrate that information about ligand-receptor conformation is encoded within the population average arrestin3 conformation, and provide insight into how different GPCRs can use a common effector for different purposes. This approach may have application in the characterization and development of functionally selective GPCR ligands8,9 and in identifying factors that dictate arrestin conformation and function. PMID:27007854

  20. Non-linear Regression and Machine Learning for Streamflow Prediction and Climate Change Impact Analysis

    NASA Astrophysics Data System (ADS)

    Shortridge, J.; Guikema, S.; Zaitchik, B. F.

    2015-12-01

    In the past decade, machine-learning methods for empirical rainfall-runoff modeling have seen extensive development. However, the majority of research has focused on a small number of methods, such as artificial neural networks, while not considering other approaches for non-parametric regression that have been developed in recent years. These methods may be able to achieve comparable predictive accuracy to ANN's and more easily provide physical insights into the system of interest through evaluation of covariate influence. Additionally, these methods could provide a straightforward, computationally efficient way of evaluating climate change impacts in basins where data to support physical hydrologic models is limited. In this paper, we use multiple regression and machine-learning approaches to predict monthly streamflow in five highly-seasonal rivers in the highlands of Ethiopia. We find that generalized additive models, random forests, and cubist models achieve better predictive accuracy than ANNs in many basins assessed and are also able to outperform physical models developed for the same region. We discuss some challenges that could hinder the use of such models for climate impact assessment, such as biases resulting from model formulation and prediction under extreme climate conditions, and suggest methods for preventing and addressing these challenges. Finally, we demonstrate how predictor variable influence can be assessed to provide insights into the physical functioning of data-sparse watersheds.

  1. Functional brain network modularity predicts response to cognitive training after brain injury

    PubMed Central

    Chen, Anthony J.-W.; Novakovic-Agopian, Tatjana; Gratton, Caterina; Nomura, Emi M.; D'Esposito, Mark

    2015-01-01

    Objective: We tested the value of measuring modularity, a graph theory metric indexing the relative extent of integration and segregation of distributed functional brain networks, for predicting individual differences in response to cognitive training in patients with brain injury. Methods: Patients with acquired brain injury (n = 11) participated in 5 weeks of cognitive training and a comparison condition (brief education) in a crossover intervention study design. We quantified the measure of functional brain network organization, modularity, from functional connectivity networks during a state of tonic attention regulation measured during fMRI scanning before the intervention conditions. We examined the relationship of baseline modularity with pre- to posttraining changes in neuropsychological measures of attention and executive control. Results: The modularity of brain network organization at baseline predicted improvement in attention and executive function after cognitive training, but not after the comparison intervention. Individuals with higher baseline modularity exhibited greater improvements with cognitive training, suggesting that a more modular baseline network state may contribute to greater adaptation in response to cognitive training. Conclusions: Brain network properties such as modularity provide valuable information for understanding mechanisms that influence rehabilitation of cognitive function after brain injury, and may contribute to the discovery of clinically relevant biomarkers that could guide rehabilitation efforts. PMID:25788557

  2. Risk of severe asthma episodes predicted from fluctuation analysis of airway function.

    PubMed

    Frey, Urs; Brodbeck, Tanja; Majumdar, Arnab; Taylor, D Robin; Town, G Ian; Silverman, Michael; Suki, Béla

    2005-12-01

    Asthma is an increasing health problem worldwide, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible. We analyse the time series of peak expiratory flows, a standard measurement of airway function that has been assessed twice daily in a large asthmatic population during a long-term crossover clinical trial. Here we introduce an approach to predict the risk of worsening airflow obstruction by calculating the conditional probability that, given the current airway condition, a severe obstruction will occur within 30 days. We find that, compared with a placebo, a regular long-acting bronchodilator (salmeterol) that is widely used to improve asthma control decreases the risk of airway obstruction. Unexpectedly, however, a regular short-acting beta2-agonist bronchodilator (albuterol) increases this risk. Furthermore, we find that the time series of peak expiratory flows show long-range correlations that change significantly with disease severity, approaching a random process with increased variability in the most severe cases. Using a nonlinear stochastic model, we show that both the increased variability and the loss of correlations augment the risk of unstable airway function. The characterization of fluctuations in airway function provides a quantitative basis for objective risk prediction of asthma episodes and for evaluating the effectiveness of therapy.

  3. Predicting functional alternative splicing by measuring RNA selection pressure from multigenome alignments.

    PubMed

    Lu, Hongchao; Lin, Lan; Sato, Seiko; Xing, Yi; Lee, Christopher J

    2009-12-01

    High-throughput methods such as EST sequencing, microarrays and deep sequencing have identified large numbers of alternative splicing (AS) events, but studies have shown that only a subset of these may be functional. Here we report a sensitive bioinformatics approach that identifies exons with evidence of a strong RNA selection pressure ratio (RSPR)--i.e., evolutionary selection against mutations that change only the mRNA sequence while leaving the protein sequence unchanged--measured across an entire evolutionary family, which greatly amplifies its predictive power. Using the UCSC 28 vertebrate genome alignment, this approach correctly predicted half to three-quarters of AS exons that are known binding targets of the NOVA splicing regulatory factor, and predicted 345 strongly selected alternative splicing events in human, and 262 in mouse. These predictions were strongly validated by several experimental criteria of functional AS such as independent detection of the same AS event in other species, reading frame-preservation, and experimental evidence of tissue-specific regulation: 75% (15/20) of a sample of high-RSPR exons displayed tissue specific regulation in a panel of ten tissues, vs. only 20% (4/20) among a sample of low-RSPR exons. These data suggest that RSPR can identify exons with functionally important splicing regulation, and provides biologists with a dataset of over 600 such exons. We present several case studies, including both well-studied examples (GRIN1) and novel examples (EXOC7). These data also show that RSPR strongly outperforms other approaches such as standard sequence conservation (which fails to distinguish amino acid selection pressure from RNA selection pressure), or pairwise genome comparison (which lacks adequate statistical power for predicting individual exons).

  4. VR-BFDT: A variance reduction based binary fuzzy decision tree induction method for protein function prediction.

    PubMed

    Golzari, Fahimeh; Jalili, Saeed

    2015-07-21

    In protein function prediction (PFP) problem, the goal is to predict function of numerous well-sequenced known proteins whose function is not still known precisely. PFP is one of the special and complex problems in machine learning domain in which a protein (regarded as instance) may have more than one function simultaneously. Furthermore, the functions (regarded as classes) are dependent and also are organized in a hierarchical structure in the form of a tree or directed acyclic graph. One of the common learning methods proposed for solving this problem is decision trees in which, by partitioning data into sharp boundaries sets, small changes in the attribute values of a new instance may cause incorrect change in predicted label of the instance and finally misclassification. In this paper, a Variance Reduction based Binary Fuzzy Decision Tree (VR-BFDT) algorithm is proposed to predict functions of the proteins. This algorithm just fuzzifies the decision boundaries instead of converting the numeric attributes into fuzzy linguistic terms. It has the ability of assigning multiple functions to each protein simultaneously and preserves the hierarchy consistency between functional classes. It uses the label variance reduction as splitting criterion to select the best "attribute-value" at each node of the decision tree. The experimental results show that the overall performance of the proposed algorithm is promising.

  5. Predicting climate change impacts on polar bear litter size.

    PubMed

    Molnár, Péter K; Derocher, Andrew E; Klanjscek, Tin; Lewis, Mark A

    2011-02-08

    Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40-73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55-100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22-67% and 44-100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population.

  6. What measure of interpersonal dependency predicts changes in social support?

    PubMed

    Shahar, Golan

    2008-01-01

    One of the most intriguing characteristics of interpersonal dependency is its ability to predict elevated levels of social support. Yet studies of interpersonal dependency use various measures to assess this effect. In this study, I compared 3 commonly used measures of interpersonal dependency in terms of their prediction of social support: Hirschfield's Interpersonal Dependency Inventory (IDI; Hirschfeld et al., 1977), the dependency factor of the Depressive Experiences Questionnaire (DEQ; Blatt, D'Afflitti, & Quinlan, 1976), and the Dependency subscale of the Personal Style Inventory (PSI; Robins et al., 1994). A total of 152 undergraduates were administered these measures as well as measures of depressive symptoms and social support a week prior to their first exam period and a week after this period (interval time = 8 weeks). DEQ-dependency predicted an increase in social support, whereas PSI-Dependency and IDI predicted a decrease in social support over time. DEQ-dependency appears to capture better than the other 2 measures the dialectic tension between risk and resilience in interpersonal dependency.

  7. Dangerous Mindsets: How Beliefs about Intelligence Predict Motivational Change

    ERIC Educational Resources Information Center

    Haimovitz, Kyla; Wormington, Stephanie V.; Corpus, Jennifer Henderlong

    2011-01-01

    The present study examined how beliefs about intelligence, as mediated by ability-validation goals, predicted whether students lost or maintained levels of intrinsic motivation over the course of a single academic year. 978 third- through eighth-grade students were surveyed in the fall about their theories concerning the malleability of…

  8. Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy.

    PubMed

    Khambhati, Ankit N; Bassett, Danielle S; Oommen, Brian S; Chen, Stephanie H; Lucas, Timothy H; Davis, Kathryn A; Litt, Brian

    2017-01-01

    Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How does the epileptic network perpetuate dysfunction during baseline periods? To address this question, we developed an unsupervised machine learning technique to disentangle patterns of functional interactions between brain regions, or subgraphs, from dynamic functional networks constructed from approximately 100 h of intracranial recordings in each of 22 neocortical epilepsy patients. Using this approach, we found: (1) subgraphs from ictal (seizure) and interictal (baseline) epochs are topologically similar, (2) interictal subgraph topology and dynamics can predict brain regions that generate seizures, and (3) subgraphs undergo slower and more coordinated fluctuations during ictal epochs compared to interictal epochs. Our observations suggest that seizures mark a critical shift away from interictal states that is driven by changes in the dynamical expression of strongly interacting components of the epileptic network.

  9. Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy

    PubMed Central

    Bassett, Danielle S.; Oommen, Brian S.; Chen, Stephanie H.; Lucas, Timothy H.

    2017-01-01

    Abstract Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How does the epileptic network perpetuate dysfunction during baseline periods? To address this question, we developed an unsupervised machine learning technique to disentangle patterns of functional interactions between brain regions, or subgraphs, from dynamic functional networks constructed from approximately 100 h of intracranial recordings in each of 22 neocortical epilepsy patients. Using this approach, we found: (1) subgraphs from ictal (seizure) and interictal (baseline) epochs are topologically similar, (2) interictal subgraph topology and dynamics can predict brain regions that generate seizures, and (3) subgraphs undergo slower and more coordinated fluctuations during ictal epochs compared to interictal epochs. Our observations suggest that seizures mark a critical shift away from interictal states that is driven by changes in the dynamical expression of strongly interacting components of the epileptic network. PMID:28303256

  10. Enhancing the Executive Functions of 3-Year-Olds in the Dimensional Change Card Sort Task

    ERIC Educational Resources Information Center

    Perone, Sammy; Molitor, Stephen J.; Buss, Aaron T.; Spencer, John P.; Samuelson, Larissa K.

    2015-01-01

    Executive functions enable flexible thinking, something young children are notoriously bad at. For instance, in the dimensional change card sort (DCCS) task, 3-year-olds can sort cards by one dimension (shape), but continue to sort by this dimension when asked to switch (to color). This study tests a prediction of a dynamic neural field model that…

  11. Predicted responses of invasive mammal communities to climate-related changes in mast frequency in forest ecosystems.

    PubMed

    Tompkins, Daniel M; Byrom, Andrea E; Pech, Roger P

    2013-07-01

    Predicting the dynamics and impacts of multiple invasive species can be complex because ecological relationships, which occur among several trophic levels, are often incompletely understood. Further, the complexity of these trophic relationships exacerbates our inability to predict climate change effects on invaded ecosystems. We explore the hypothesis that interactions between two global change drivers, invasive vertebrates and climate change, will potentially make matters worse for native biodiversity. In New Zealand beech (Nothofagus spp.) forests, a highly irruptive invasive mammal community is driven by multi-annual resource pulses of beech seed (masting). Because mast frequency is predicted to increase with climate change, we use this as a model system to explore the extent to which such effects may influence invasive vertebrate communities, and the implications of such interactions for native biodiversity and its management. We build on an established model of trophic interactions in the system, combining it with a logistic probability mast function, the parameters of which were altered to simulate either contemporary conditions or conditions of more or less frequent masting. The model predicts that increased mast frequency will lead to populations of a top predator (the stoat) and a mesopredator (the ship rat) becoming less irruptive and being maintained at appreciably higher average abundances in this forest type. In addition, the ability of both current and in-development management approaches to suppress invasive mammals is predicted to be compromised. Because invasive mammals are key drivers of native fauna extinction in New Zealand, with the additional loss of associated functions such as pollination and seed dispersal, these predictions imply potentially serious adverse impacts of climate change for the conservation of biodiversity and ecosystem function. Our study also highlights the importance of long-term monitoring data for assessing and managing

  12. Successional changes in functional composition contrast for dry and wet tropical forest.

    PubMed

    Lohbeck, Madelon; Poorter, Lourens; Lebrija-Trejos, Edwin; Martínez-Ramos, Miguel; Meave, Jorge A; Paz, Horacio; Pérez-García, Eduardo A; Romero-Pérez, I Eunice; Tauro, Alejandra; Bongers, Frans

    2013-06-01

    We tested whether and how functional composition changes with succession in dry deciduous and wet evergreen forests of Mexico. We hypothesized that compositional changes during succession in dry forest were mainly determined by increasing water availability leading to community functional changes from conservative to acquisitive strategies, and in wet forest by decreasing light availability leading to changes from acquisitive to conservative strategies. Research was carried out in 15 dry secondary forest plots (5-63 years after abandonment) and 17 wet secondary forest plots (< 1-25 years after abandonment). Community-level functional traits were represented by community-weighted means based on 11 functional traits measured on 132 species. Successional changes in functional composition are more marked in dry forest than in wet forest and largely characterized by different traits. During dry forest succession, conservative traits related to drought tolerance and drought avoidance decreased, as predicted. Unexpectedly acquisitive leaf traits also decreased, whereas seed size and dependence on biotic dispersal increased. In wet forest succession, functional composition changed from acquisitive to conservative leaf traits, suggesting light availability as the main driver of changes. Distinct suites of traits shape functional composition changes in dry and wet forest succession, responding to different environmental filters.

  13. Abrupt climate change and thermohaline circulation: mechanisms and predictability.

    PubMed

    Marotzke, J

    2000-02-15

    The ocean's thermohaline circulation has long been recognized as potentially unstable and has consequently been invoked as a potential cause of abrupt climate change on all timescales of decades and longer. However, fundamental aspects of thermohaline circulation changes remain poorly understood.

  14. Predicting Change in Postpartum Depression: An Individual Growth Curve Approach.

    ERIC Educational Resources Information Center

    Buchanan, Trey

    Recently, methodologists interested in examining problems associated with measuring change have suggested that developmental researchers should focus upon assessing change at both intra-individual and inter-individual levels. This study used an application of individual growth curve analysis to the problem of maternal postpartum depression.…

  15. Do temporal changes in vegetation structure additional to time since fire predict changes in bird occurrence?

    PubMed

    Lindenmayer, David B; Candy, Steven G; MacGregor, Christopher I; Banks, Sam C; Westgate, Martin; Ikin, Karen; Pierson, Jennifer; Tulloch, Ayesha; Barton, Philip

    2016-10-01

    Fire is a major ecological process in ecosystems globally. Its impacts on fauna can be both direct (e.g., mortality) and indirect (e.g., altered habitat), resulting in population recovery being driven by several possible mechanisms. Separating direct from indirect impacts of fire on faunal population recovery can be valuable in guiding management of biodiversity in fire-prone environments. However, resolving the influence of direct and indirect processes remains a key challenge because many processes affecting fauna can change concomitantly with time since fire. We explore the mechanisms influencing bird response to fire by posing the question, can temporal changes in vegetation structure predict changes in bird occurrence on sites, and can these be separated from other temporal changes using the surrogate of time since fire? We conducted a 12-yr study of bird and vegetation responses to fire at 124 sites across six vegetation classes in Booderee National Park, Australia. Approximately half of these sites, established in 2002, were burned by a large (>3000 ha) wildfire in 2003. To disentangle collinear effects of temporal changes in vegetation and direct demographic effects on population recovery that are subsumed by time since fire, we incorporated both longitudinal and cross-sectional vegetation effects in addition to time since fire within logistic structural equation models. We identified temporal changes in vegetation structure and richness of plant and bird species that characterized burned and unburned sites in all vegetation classes. For nine bird species, a significant component of the year trend was driven by temporal trends in one of three vegetation variables (number of understory or midstory plant species, or midstory cover). By contrast, we could not separate temporal effects between time since fire and vegetation attributes for bird species richness, reporting rate, and the occurrence of 11 other bird species. Our findings help identify species for

  16. Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins

    PubMed Central

    2012-01-01

    Background Advancements in function prediction algorithms are enabling large scale computational annotation for newly sequenced genomes. With the increase in the number of functionally well characterized proteins it has been observed that there are many proteins involved in more than one function. These proteins characterized as moonlighting proteins show varied functional behavior depending on the cell type, localization in the cell, oligomerization, multiple binding sites, etc. The functional diversity shown by moonlighting proteins may have significant impact on the traditional sequence based function prediction methods. Here we investigate how well diverse functions of moonlighting proteins can be predicted by some existing function prediction methods. Results We have analyzed the performances of three major sequence based function prediction methods, PSI-BLAST, the Protein Function Prediction (PFP), and the Extended Similarity Group (ESG) on predicting diverse functions of moonlighting proteins. In predicting discrete functions of a set of 19 experimentally identified moonlighting proteins, PFP showed overall highest recall among the three methods. Although ESG showed the highest precision, its recall was lower than PSI-BLAST. Recall by PSI-BLAST greatly improved when BLOSUM45 was used instead of BLOSUM62. Conclusion We have analyzed the performances of PFP, ESG, and PSI-BLAST in predicting the functional diversity of moonlighting proteins. PFP shows overall better performance in predicting diverse moonlighting functions as compared with PSI-BLAST and ESG. Recall by PSI-BLAST greatly improved when BLOSUM45 was used. This analysis indicates that considering weakly similar sequences in prediction enhances the performance of sequence based AFP methods in predicting functional diversity of moonlighting proteins. The current study will also motivate development of novel computational frameworks for automatic identification of such proteins. PMID:23173871

  17. Distinct Functional Connectivities Predict Clinical Response with Emotion Regulation Therapy

    PubMed Central

    Fresco, David M.; Roy, Amy K.; Adelsberg, Samantha; Seeley, Saren; García-Lesy, Emmanuel; Liston, Conor; Mennin, Douglas S.

    2017-01-01

    Despite the success of available medical and psychosocial treatments, a sizable subgroup of individuals with commonly co-occurring disorders, generalized anxiety disorder (GAD) and major depressive disorder (MDD), fail to make sufficient treatment gains thereby prolonging their deficits in life functioning and satisfaction. Clinically, these patients often display temperamental features reflecting heightened sensitivity to underlying motivational systems related to threat/safety and reward/loss (e.g., somatic anxiety) as well as inordinate negative self-referential processing (e.g., worry, rumination). This profile may reflect disruption in two important neural networks associated with emotional/motivational salience (e.g., salience network) and self-referentiality (e.g., default network, DN). Emotion Regulation Therapy (ERT) was developed to target this hypothesized profile and its neurobehavioral markers. In the present study, 22 GAD patients (with and without MDD) completed resting state MRI scans before receiving 16 sessions of ERT. To test study these hypotheses, we examined the associations between baseline patterns of intrinsic functional connectivity (iFC) of the insula and of hubs within the DN (anterior and dorsal medial prefrontal cortex [MPFC] and posterior cingulate cortex [PCC]) and treatment-related changes in worry, somatic anxiety symptoms and decentering. Results suggest that greater treatment linked reductions in worry were associated with iFC clusters in both the insular and parietal cortices. Greater treatment linked gains in decentering, a metacognitive process that involves the capacity to observe items that arise in the mind with healthy psychological distance that is targeted by ERT, was associated with iFC clusters in the anterior and posterior DN. The current study adds to the growing body of research implicating disruptions in the default and salience networks as promising targets of treatment for GAD with and without co-occurring MDD

  18. Distinct Functional Connectivities Predict Clinical Response with Emotion Regulation Therapy.

    PubMed

    Fresco, David M; Roy, Amy K; Adelsberg, Samantha; Seeley, Saren; García-Lesy, Emmanuel; Liston, Conor; Mennin, Douglas S

    2017-01-01

    Despite the success of available medical and psychosocial treatments, a sizable subgroup of individuals with commonly co-occurring disorders, generalized anxiety disorder (GAD) and major depressive disorder (MDD), fail to make sufficient treatment gains thereby prolonging their deficits in life functioning and satisfaction. Clinically, these patients often display temperamental features reflecting heightened sensitivity to underlying motivational systems related to threat/safety and reward/loss (e.g., somatic anxiety) as well as inordinate negative self-referential processing (e.g., worry, rumination). This profile may reflect disruption in two important neural networks associated with emotional/motivational salience (e.g., salience network) and self-referentiality (e.g., default network, DN). Emotion Regulation Therapy (ERT) was developed to target this hypothesized profile and its neurobehavioral markers. In the present study, 22 GAD patients (with and without MDD) completed resting state MRI scans before receiving 16 sessions of ERT. To test study these hypotheses, we examined the associations between baseline patterns of intrinsic functional connectivity (iFC) of the insula and of hubs within the DN (anterior and dorsal medial prefrontal cortex [MPFC] and posterior cingulate cortex [PCC]) and treatment-related changes in worry, somatic anxiety symptoms and decentering. Results suggest that greater treatment linked reductions in worry were associated with iFC clusters in both the insular and parietal cortices. Greater treatment linked gains in decentering, a metacognitive process that involves the capacity to observe items that arise in the mind with healthy psychological distance that is targeted by ERT, was associated with iFC clusters in the anterior and posterior DN. The current study adds to the growing body of research implicating disruptions in the default and salience networks as promising targets of treatment for GAD with and without co-occurring MDD.

  19. Early Brain changes May Help Predict Autism Among High-Risk Infants

    MedlinePlus

    ... Media Resources Interviews & Selected Staff Profiles Multimedia Early brain changes may help predict autism among high-risk ... Share this: Page Content NIH-funded researchers link brain changes at 6 and 12 months of age ...

  20. A linear regression model for predicting PNW estuarine temperatures in a changing climate

    EPA Science Inventory

    Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...

  1. Can Functional Cardiac Age be Predicted from ECG in a Normal Healthy Population

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd; Starc, Vito; Leban, Manja; Sinigoj, Petra; Vrhovec, Milos

    2011-01-01

    In a normal healthy population, we desired to determine the most age-dependent conventional and advanced ECG parameters. We hypothesized that changes in several ECG parameters might correlate with age and together reliably characterize the functional age of the heart. Methods: An initial study population of 313 apparently healthy subjects was ultimately reduced to 148 subjects (74 men, 84 women, in the range from 10 to 75 years of age) after exclusion criteria. In all subjects, ECG recordings (resting 5-minute 12-lead high frequency ECG) were evaluated via custom software programs to calculate up to 85 different conventional and advanced ECG parameters including beat-to-beat QT and RR variability, waveform complexity, and signal-averaged, high-frequency and spatial/spatiotemporal ECG parameters. The prediction of functional age was evaluated by multiple linear regression analysis using the best 5 univariate predictors. Results: Ignoring what were ultimately small differences between males and females, the functional age was found to be predicted (R2= 0.69, P < 0.001) from a linear combination of 5 independent variables: QRS elevation in the frontal plane (p<0.001), a new repolarization parameter QTcorr (p<0.001), mean high frequency QRS amplitude (p=0.009), the variability parameter % VLF of RRV (p=0.021) and the P-wave width (p=0.10). Here, QTcorr represents the correlation between the calculated QT and the measured QT signal. Conclusions: In apparently healthy subjects with normal conventional ECGs, functional cardiac age can be estimated by multiple linear regression analysis of mostly advanced ECG results. Because some parameters in the regression formula, such as QTcorr, high frequency QRS amplitude and P-wave width also change with disease in the same direction as with increased age, increased functional age of the heart may reflect subtle age-related pathologies in cardiac electrical function that are usually hidden on conventional ECG.

  2. Soil ecosystem functioning under climate change: plant species and community effects.

    PubMed

    Kardol, Paul; Cregger, Melissa A; Campany, Courtney E; Classen, Aimee T

    2010-03-01

    direct impact of atmospheric and climate change on soil ecosystem functioning, and hence, these indirect effects should be taken into account when predicting the manner in which global change will alter ecosystem functioning.

  3. Transitional states in marine fisheries: adapting to predicted global change.

    PubMed

    MacNeil, M Aaron; Graham, Nicholas A J; Cinner, Joshua E; Dulvy, Nicholas K; Loring, Philip A; Jennings, Simon; Polunin, Nicholas V C; Fisk, Aaron T; McClanahan, Tim R

    2010-11-27

    Global climate change has the potential to substantially alter the production and community structure of marine fisheries and modify the ongoing impacts of fishing. Fish community composition is already changing in some tropical, temperate and polar ecosystems, where local combinations of warming trends and higher environmental variation anticipate the changes likely to occur more widely over coming decades. Using case studies from the Western Indian Ocean, the North Sea and the Bering Sea, we contextualize the direct and indirect effects of climate change on production and biodiversity and, in turn, on the social and economic aspects of marine fisheries. Climate warming is expected to lead to (i) yield and species losses in tropical reef fisheries, driven primarily by habitat loss; (ii) community turnover in temperate fisheries, owing to the arrival and increasing dominance of warm-water species as well as the reduced dominance and departure of cold-water species; and (iii) increased diversity and yield in Arctic fisheries, arising from invasions of southern species and increased primary production resulting from ice-free summer conditions. How societies deal with such changes will depend largely on their capacity to adapt--to plan and implement effective responses to change--a process heavily influenced by social, economic, political and cultural conditions.

  4. Do Executive Functions Predict Binge-Drinking Patterns? Evidence from a Longitudinal Study in Young Adulthood

    PubMed Central

    Bø, Ragnhild; Billieux, Joël; Gjerde, Line C.; Eilertsen, Espen M.; Landrø, Nils I.

    2017-01-01

    Background: Impairments in executive functions (EFs) are related to binge drinking in young adulthood, but research on how EFs influence future binge drinking is lacking. The aim of the current report is therefore to investigate the association between various EFs and later severity of, and change in, binge drinking over a prolonged period during young adulthood. Methods: At baseline, 121 students reported on their alcohol habits (Alcohol use disorder identification test; Alcohol use questionnaire). Concurrently, EFs [working memory, reversal, set-shifting, response inhibition, response monitoring and decision-making (with ambiguity and implicit risk)] were assessed. Eighteen months later, information on alcohol habits for 103 of the participants were gathered. Data were analyzed by means of multilevel regression modeling. Results: Future severity of binge drinking was uniquely predicted by performance on the Information sampling task, assessing risky decision-making (β = -1.86, 95% CI: -3.69, -0.04). None of the study variables predicted severity or change in binge drinking. Conclusion: Future severity of binge drinking was associated with making risky decisions in the prospect for gain, suggesting reward hypersensitivity. Future studies should aim at clarifying whether there is a causal association between decision-making style and binge drinking. Performance on all executive tasks was unrelated to change in binge drinking patterns; however, the finding was limited by overall small changes, and needs to be confirmed with longer follow-up periods.

  5. Functional Traits Help Predict Post-Disturbance Demography of Tropical Trees

    PubMed Central

    Flores, Olivier; Hérault, Bruno; Delcamp, Matthieu; Garnier, Éric; Gourlet-Fleury, Sylvie

    2014-01-01

    How tropical tree species respond to disturbance is a central issue of forest ecology, conservation and resource management. We define a hierarchical model to investigate how functional traits measured in control plots relate to the population change rate and to demographic rates for recruitment and mortality after disturbance by logging operations. Population change and demographic rates were quantified on a 12-year period after disturbance and related to seven functional traits measured in control plots. The model was calibrated using a Bayesian Network approach on 53 species surveyed in permanent forest plots (37.5 ha) at Paracou in French Guiana. The network analysis allowed us to highlight both direct and indirect relationships among predictive variables. Overall, 89% of interspecific variability in the population change rate after disturbance were explained by the two demographic rates, the recruitment rate being the most explicative variable. Three direct drivers explained 45% of the variability in recruitment rates, including leaf phosphorus concentration, with a positive effect, and seed size and wood density with negative effects. Mortality rates were explained by interspecific variability in maximum diameter only (25%). Wood density, leaf nitrogen concentration, maximum diameter and seed size were not explained by variables in the analysis and thus appear as independent drivers of post-disturbance demography. Relationships between functional traits and demographic parameters were consistent with results found in undisturbed forests. Functional traits measured in control conditions can thus help predict the fate of tropical tree species after disturbance. Indirect relationships also suggest how different processes interact to mediate species demographic response. PMID:25226586

  6. The Prediction of Jet Noise Ground Effects Using an Acoustic Analogy and a Tailored Green's Function

    NASA Technical Reports Server (NTRS)

    Miller, Steven A. E.

    2013-01-01

    An assessment of an acoustic analogy for the mixing noise component of jet noise in the presence of an infinite surface is presented. The reflection of jet noise by the ground changes the distribution of acoustic energy and is characterized by constructive and destructive interference patterns. The equivalent sources are modeled based on the two-point cross- correlation of the turbulent velocity fluctuations and a steady Reynolds-Averaged Navier-Stokes (RANS) solution. Propagation effects, due to reflection by the surface and refaction by the jet shear layer, are taken into account by calculating the vector Green's function of the linearized Euler equations (LEE). The vector Green's function of the LEE is written in relation to Lilley's equation; that is, approximated with matched asymptotic solutions and the Green's function of the convective Helmholtz equation. The Green's function of the convective Helmholtz equation for an infinite flat plane with impedance is the Weyl-van der Pol equation. Predictions are compared with an unheated Mach 0.95 jet produced by a nozzle with an exit diameter of 0.3302 meters. Microphones are placed at various heights and distances from the nozzle exit in the peak jet noise direction above an acoustically hard and an asphalt surface. The predictions are shown to accurately capture jet noise ground effects that are characterized by constructive and destructive interference patterns in the mid- and far-field and capture overall trends in the near-field.

  7. Functional consequences of climate change-induced plant species loss in a tallgrass prairie.

    PubMed

    Craine, Joseph M; Nippert, Jesse B; Towne, E Gene; Tucker, Sally; Kembel, Steven W; Skibbe, Adam; McLauchlan, Kendra K

    2011-04-01

    Future climate change is likely to reduce the floristic diversity of grasslands. Yet the potential consequences of climate-induced plant species losses for the functioning of these ecosystems are poorly understood. We investigated how climate change might alter the functional composition of grasslands for Konza Prairie, a diverse tallgrass prairie in central North America. With species-specific climate envelopes, we show that a reduction in mean annual precipitation would preferentially remove species that are more abundant in the more productive lowland positions at Konza. As such, decreases in precipitation could reduce productivity not only by reducing water availability but by also removing species that inhabit the most productive areas and respond the most to climate variability. In support of this prediction, data on species abundance at Konza over 16 years show that species that are more abundant in lowlands than uplands are preferentially reduced in years with low precipitation. Climate change is likely to also preferentially remove species from particular functional groups and clades. For example, warming is forecast to preferentially remove perennials over annuals as well as Cyperaceae species. Despite these predictions, climate change is unlikely to unilaterally alter the functional composition of the tallgrass prairie flora, as many functional traits such as physiological drought tolerance and maximum photosynthetic rates showed little relationship with climate envelope parameters. In all, although climatic drying would indirectly alter grassland productivity through species loss patterns, the insurance afforded by biodiversity to ecosystem function is likely to be sustained in the face of climate change.

  8. Prediction of Chemical Function: Model Development and Application

    EPA Science Inventory

    The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (...

  9. Predicting and understanding ecosystem responses to climate change at continental scales

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Climate is changing around the world across a range of scales from local to global, but ecological consequences remain difficult to understand and predict. Such predictions are complicated by changes in connectivity of resources, in particular water, nutrients, and propagules, that influence the way...

  10. Transitional states in marine fisheries: adapting to predicted global change

    PubMed Central

    MacNeil, M. Aaron; Graham, Nicholas A. J.; Cinner, Joshua E.; Dulvy, Nicholas K.; Loring, Philip A.; Jennings, Simon; Polunin, Nicholas V. C.; Fisk, Aaron T.; McClanahan, Tim R.

    2010-01-01

    Global climate change has the potential to substantially alter the production and community structure of marine fisheries and modify the ongoing impacts of fishing. Fish community composition is already changing in some tropical, temperate and polar ecosystems, where local combinations of warming trends and higher environmental variation anticipate the changes likely to occur more widely over coming decades. Using case studies from the Western Indian Ocean, the North Sea and the Bering Sea, we contextualize the direct and indirect effects of climate change on production and biodiversity and, in turn, on the social and economic aspects of marine fisheries. Climate warming is expected to lead to (i) yield and species losses in tropical reef fisheries, driven primarily by habitat loss; (ii) community turnover in temperate fisheries, owing to the arrival and increasing dominance of warm-water species as well as the reduced dominance and departure of cold-water species; and (iii) increased diversity and yield in Arctic fisheries, arising from invasions of southern species and increased primary production resulting from ice-free summer conditions. How societies deal with such changes will depend largely on their capacity to adapt—to plan and implement effective responses to change—a process heavily influenced by social, economic, political and cultural conditions. PMID:20980322

  11. A model to predict bladder shapes from changes in bladder and rectal filling.

    PubMed

    Lotz, Heidi T; Remeijer, Peter; van Herk, Marcel; Lebesque, Joos V; de Bois, Josien A; Zijp, Lambert J; Moonen, Luc M

    2004-06-01

    The purpose of this study is to develop a model that quantifies in three dimensions changes in bladder shape due to changes in bladder and/or rectal volume. The new technique enables us to predict changes in bladder shape over a short period of time, based on known urinary inflow. Shortly prior to the treatment, the patient will be scanned using a cone beam CT scanner (x-ray volume imager) that is integrated with the linear accelerator. After (automated) delineation of the bladder, the model will be used to predict the short-term shape changes of the bladder for the time interval between image acquisition and dose delivery. The model was developed using multiple daily CT scans of the pelvic area of 19 patients. For each patient, the rigid bony structure in follow-up scans was matched to that of the planning CT scan, and the outer bladder and rectal wall were delineated. Each bladder wall was subdivided in 2500 domains. A fixed reference point inside the bladder was used to calculate for each bladder structure a "Mercator-like" 2D scalar map (similar to a height map of the globe), containing the distances from this reference point to each domain on the bladder wall. Subsequently, for all bladder shapes of a patient and for all domains on the wall individually, the distance to the reference point was fitted by a linear function of both bladder and rectal volume. The model uses an existing bladder structure to create a new structure via expansion (or contraction), until the expressed volume is reached. To evaluate the predictive power of the model, the jack-knife method was used. The errors in the fitting procedure depended on the part of the bladder and range from 0 to 0.5 cm (0.2 cm on average). It was found that a volume increase of 150 cc can lead to a displacement up to about 2.5 cm of the cranial part of the bladder. With the model, the uncertainty in the position of the bladder wall can be reduced down to a maximum value of about 0.5 cm in case the bladder

  12. Method of predicting a change in an economy

    DOEpatents

    Pryor, Richard J; Basu, Nipa

    2006-01-10

    An economy whose activity is to be predicted comprises a plurality of decision makers. Decision makers include, for example, households, government, industry, and banks. The decision makers are represented by agents, where an agent can represent one or more decision makers. Each agent has decision rules that determine the agent's actions. Each agent can affect the economy by affecting variable conditions characteristic of the economy or the internal state of other agents. Agents can communicate actions through messages. On a multiprocessor computer, the agents can be assigned to processing elements.

  13. Predicting potential effects of climate change on Ozark Highlands streams

    SciTech Connect

    Willson, G.D.; Rabeni, C.F.; Galat, D.L. )

    1993-06-01

    The Ozark Highlands biogeographic area centers on two National Park Service units: Ozark National Scenic Riverways in Missouri and Buffalo National River in Arkansas. The Ozark Highlands is part of a national network of 20 research sites established to determine the potential influence of global change on ecosystems and their adaptability. The Ozark Highlands program will integrate historic and proxy stream flows, fluvial geomorphology, and trophic-level responses in streams to model aquatic systems under mid-continent, climate change scenarios. Climate change in Ozarks streams will likely alter hydrologic/geomorphic patterns and disrupt community structure and ecological processes. Initially, the program has focused on defining variation inherent in stream systems and how ecological processes and biota respond to that variability.

  14. Predicting the Response of Electricity Load to Climate Change

    SciTech Connect

    Sullivan, Patrick; Colman, Jesse; Kalendra, Eric

    2015-07-28

    Our purpose is to develop a methodology to quantify the impact of climate change on electric loads in the United States. We perform simple linear regression, assisted by geospatial smoothing, on paired temperature and load time-series to estimate the heating- and coolinginduced sensitivity to temperature across 300 transmission zones and 16 seasonal and diurnal time periods. The estimated load sensitivities can be coupled with climate scenarios to quantify the potential impact of climate change on load, with a primary application being long-term electricity scenarios. The method allows regional and seasonal differences in climate and load response to be reflected in the electricity scenarios. While the immediate product of this analysis was designed to mesh with the spatial and temporal resolution of a specific electricity model to enable climate change scenarios and analysis with that model, we also propose that the process could be applied for other models and purposes.

  15. Neuroendocrine control of photoperiodic changes in immune function

    PubMed Central

    Weil, Zachary M.; Borniger, Jeremy C.; Cisse, Yasmine M.; Abi Salloum, Bachir A.; Nelson, Randy J.

    2014-01-01

    Seasonal variation in immune function putatively maximizes survival and reproductive success. Day length (photoperiod) is the most potent signal for time of year. Animals typically organize breeding, growth, and behavior to adapt to spatial and temporal niches. Outside the tropics individuals monitor photoperiod to support adaptations favoring survival and reproductive success. Changes in day length allow anticipation of seasonal changes in temperature and food availability that are critical for reproductive success. Immune function is typically bolstered during winter, whereas reproduction and growth are favored during summer. We provide an overview of how photoperiod influences neuronal function and melatonin secretion, how melatonin acts directly and indirectly to govern seasonal changes in immune function, and the manner by which other neuroendocrine effectors such as glucocorticoids, prolactin, thyroid, and sex steroid hormones modulate seasonal variations in immune function. Potential future research avenues include commensal gut microbiota and light pollution influences on photoperiodic responses. PMID:25456047

  16. Cloud prediction of protein structure and function with PredictProtein for Debian.

    PubMed

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

  17. Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

    PubMed Central

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome. PMID:23971032

  18. Concomitant prediction of function and fold at the domain level with GO-based profiles

    PubMed Central

    2013-01-01

    Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required. We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function. PMID:23514233

  19. Predicting Transfer Performance: A Comparison of Competing Function Learning Models

    ERIC Educational Resources Information Center

    McDaniel, Mark A.; Dimperio, Eric; Griego, Jacqueline A.; Busemeyer, Jerome R.

    2009-01-01

    The population of linear experts (POLE) model suggests that function learning and transfer are mediated by activation of a set of prestored linear functions that together approximate the given function (Kalish, Lewandowsky, & Kruschke, 2004). In the extrapolation-association (EXAM) model, an exemplar-based architecture associates trained input…

  20. Predictors and Predictive Effects of Attitudinal Inconsistency Towards Organizational Change

    DTIC Science & Technology

    2012-03-01

    starts. Such an arduous path of progress has financial implications for organizations, psychological implications for the individuals in its path...emphasis has revealed that facing change triggers highly complex psychological processes leading to uncertain ends. For instance, employees may...prolific science of social psychology . However, several recent critiques have argued that these psychological excursions have transpired in an eclectic

  1. Improving models to predict phenological responses to global change

    SciTech Connect

    Richardson, Andrew D.

    2015-11-25

    The term phenology describes both the seasonal rhythms of plants and animals, and the study of these rhythms. Plant phenological processes, including, for example, when leaves emerge in the spring and change color in the autumn, are highly responsive to variation in weather (e.g. a warm vs. cold spring) as well as longer-term changes in climate (e.g. warming trends and changes in the timing and amount of rainfall). We conducted a study to investigate the phenological response of northern peatland communities to global change. Field work was conducted at the SPRUCE experiment in northern Minnesota, where we installed 10 digital cameras. Imagery from the cameras is being used to track shifts in plant phenology driven by elevated carbon dioxide and elevated temperature in the different SPRUCE experimental treatments. Camera imagery and derived products (“greenness”) is being posted in near-real time on a publicly available web page (http://phenocam.sr.unh.edu/webcam/gallery/). The images will provide a permanent visual record of the progression of the experiment over the next 10 years. Integrated with other measurements collected as part of the SPRUCE program, this study is providing insight into the degree to which phenology may mediate future shifts in carbon uptake and storage by peatland ecosystems. In the future, these data will be used to develop improved models of vegetation phenology, which will be tested against ground observations collected by a local collaborator.

  2. Environmental change and hedonic cost functions for automobiles.

    PubMed

    Berry, S; Kortum, S; Pakes, A

    1996-11-12

    This paper focuses on how changes in the economic and regulatory environment have affected production costs and product characteristics in the automobile industry. We estimate "hedonic cost functions" that relate product-level costs to their characteristics. Then we examine how this cost surface has changed over time and how these changes relate to changes in gas prices and in emission standard regulations. We also briefly consider the related questions of how changes in automobile characteristics, and in the rate of patenting, are related to regulations and gas prices.

  3. Functional brain imaging predicts public health campaign success.

    PubMed

    Falk, Emily B; O'Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

    2016-02-01

    Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a 'self-localizer' defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400,000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R(2) up to 0.65) and (ii) this relationship depends on message content-self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns.

  4. Functional brain imaging predicts public health campaign success

    PubMed Central

    O’Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

    2016-01-01

    Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a ‘self-localizer’ defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400 000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R2 up to 0.65) and (ii) this relationship depends on message content—self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns. PMID:26400858

  5. A Quantum Annealing Computer Team Addresses Climate Change Predictability

    NASA Technical Reports Server (NTRS)

    Halem, M. (Principal Investigator); LeMoigne, J.; Dorband, J.; Lomonaco, S.; Yesha, Ya.; Simpson, D.; Clune, T.; Pelissier, C.; Nearing, G.; Gentine, P.; Fang, B.; Shehab, A.; Radov, Asen; Tikak, N.; Prouty, Roy; Harrison, Kenneth

    2016-01-01

    The near confluence of the successful launch of the Orbiting Carbon Observatory2 on July 2, 2014 and the acceptance on August 20, 2015 by Google, NASA Ames Research Center and USRA of a 1152 qubit D-Wave 2X Quantum Annealing Computer (QAC), offered an exceptional opportunity to explore the potential of this technology to address the scientific prediction of global annual carbon uptake by land surface processes. At UMBC,we have collected and processed 20 months of global Level 2 light CO2 data as well as fluorescence data. In addition we have collected ARM data at 2sites in the US and Ameriflux data at more than 20 stations. J. Dorband has developed and implemented a multi-hidden layer Boltzmann Machine (BM) algorithm on the QAC. Employing the BM, we are calculating CO2 fluxes by training collocated OCO-2 level 2 CO2 data with ARM ground station tower data to infer to infer measured CO2 flux data. We generate CO2 fluxes with a regression analysis using these BM derived weights on the level 2 CO2 data for three Ameriflux sites distinct from the ARM stations. P. Gentine has negotiated for the access of K34 Ameriflux data in the Amazon and is applying a neural net to infer the CO2 fluxes. N. Talik validated the accuracy of the BM performance on the QAC against a restricted BM implementation on the IBM Softlayer Cloud with the Nvidia co-processors utilizing the same data sets. G. Nearing and K. Harrison have extended the GSFC LIS model with the NCAR Noah photosynthetic parameterization and have run a 10 year global prediction of the net ecosystem exchange. C. Pellisier is preparing a BM implementation of the Kalman filter data assimilation of CO2 fluxes. At UMBC, R. Prouty is conducting OSSE experiments with the LISNoah model on the IBM iDataPlex to simulate the impact of CO2 fluxes to improve the prediction of global annual carbon uptake. J. LeMoigne and D. Simpson have developed a neural net image registration system that will be used for MODIS ENVI and will be

  6. Microbial response to simulated global change is phylogenetically conserved and linked with functional potential.

    PubMed

    Amend, Anthony S; Martiny, Adam C; Allison, Steven D; Berlemont, Renaud; Goulden, Michael L; Lu, Ying; Treseder, Kathleen K; Weihe, Claudia; Martiny, Jennifer B H

    2016-01-01

    The high diversity of microbial communities hampers predictions about their responses to global change. Here we investigate the potential for using a phylogenetic, trait-based framework to capture the response of bacteria and fungi to global change manipulations. Replicated grassland plots were subjected to 3+ years of drought and nitrogen fertilization. The responses of leaf litter bacteria and fungi to these simulated changes were significantly phylogenetically conserved. Proportional changes in abundance were highly correlated among related organisms, such that relatives with approximately 5% ribosomal DNA genetic distance showed similar responses to the treatments. A microbe's change in relative abundance was significantly correlated between the treatments, suggesting a compromise between numerical abundance in undisturbed environments and resistance to change in general, independent of disturbance type. Lineages in which at least 90% of the microbes shared the same response were circumscribed at a modest phylogenetic depth (τD 0.014-0.021), but significantly larger than randomized simulations predict. In several clades, phylogenetic depth of trait consensus was higher. Fungal response to drought was more conserved than was response to nitrogen fertilization, whereas bacteria responded equally to both treatments. Finally, we show that a bacterium's response to the manipulations is correlated with its potential functional traits (measured here as the number of glycoside hydrolase genes encoding the capacity to degrade different types of carbohydrates). Together, these results suggest that a phylogenetic, trait-based framework may be useful for predicting shifts in microbial composition and functioning in the face of global change.

  7. Predicting the accuracy of facial affect recognition: the interaction of child maltreatment and intellectual functioning.

    PubMed

    Shenk, Chad E; Putnam, Frank W; Noll, Jennie G

    2013-02-01

    Previous research demonstrates that both child maltreatment and intellectual performance contribute uniquely to the accurate identification of facial affect by children and adolescents. The purpose of this study was to extend this research by examining whether child maltreatment affects the accuracy of facial recognition differently at varying levels of intellectual functioning. A sample of maltreated (n=50) and nonmaltreated (n=56) adolescent females, 14 to 19 years of age, was recruited to participate in this study. Participants completed demographic and study-related questionnaires and interviews to control for potential psychological and psychiatric confounds such as symptoms of posttraumatic stress disorder, negative affect, and difficulties in emotion regulation. Participants also completed an experimental paradigm that recorded responses to facial affect displays starting in a neutral expression and changing into a full expression of one of six emotions: happiness, sadness, anger, disgust, fear, or surprise. Hierarchical multiple regression assessed the incremental advantage of evaluating the interaction between child maltreatment and intellectual functioning. Results indicated that the interaction term accounted for a significant amount of additional variance in the accurate identification of facial affect after controlling for relevant covariates and main effects. Specifically, maltreated females with lower levels of intellectual functioning were least accurate in identifying facial affect displays, whereas those with higher levels of intellectual functioning performed as well as nonmaltreated females. These results suggest that maltreatment and intellectual functioning interact to predict the recognition of facial affect, with potential long-term consequences for the interpersonal functioning of maltreated females.

  8. The prediction of EEG signals using a feedback-structured adaptive rational function filter.

    PubMed

    Kim, H S; Kim, T S; Choi, Y H; Park, S H

    2000-08-01

    In this article, we present a feedback-structured adaptive rational function filter based on a recursive modified Gram-Schmidt algorithm and apply it to the prediction of an EEG signal that has nonlinear and nonstationary characteristics. For the evaluation of the prediction performance, the proposed filter is compared with other methods, where a single-step prediction and a multi-step prediction are considered for a short-term prediction, and the prediction performance is assessed in normalized mean square error. The experimental results show that the proposed filter shows better performance than other methods considered for the short-term prediction of EEG signals.

  9. Change in maternal depressive mood: unique contributions to adolescent functioning over time.

    PubMed

    Thomas, A M; Forehand, R; Neighbors, B

    1995-01-01

    There is substantial evidence of the relationship between maternal depressive mood and problematic child functioning. The vast majority of studies in this area concentrate on cross-sectional designs and depressive mood at one point in time. In contrast to the existing literature, the goal of this study was to investigate the relation of change in maternal depressed mood across time and adolescent functioning, including the possible moderating effects of gender of the adolescent and the marital status of parents. Regression analyses indicated that increased depressed mood across one year predicted teacher report of higher levels of externalizing and internalizing problems and lower levels of social competence, above that which could be predicted from the initial assessment of depressed mood. With one exception, neither gender nor parental marital status qualified the findings. The results suggest that static levels of maternal depressive mood are not sufficient for forecasting adolescent functioning. Future research needs also to consider change in such mood.

  10. Accurate perception of negative emotions predicts functional capacity in schizophrenia.

    PubMed

    Abram, Samantha V; Karpouzian, Tatiana M; Reilly, James L; Derntl, Birgit; Habel, Ute; Smith, Matthew J

    2014-04-30

    Several studies suggest facial affect perception (FAP) deficits in schizophrenia are linked to poorer social functioning. However, whether reduced functioning is associated with inaccurate perception of specific emotional valence or a global FAP impairment remains unclear. The present study examined whether impairment in the perception of specific emotional valences (positive, negative) and neutrality were uniquely associated with social functioning, using a multimodal social functioning battery. A sample of 59 individuals with schizophrenia and 41 controls completed a computerized FAP task, and measures of functional capacity, social competence, and social attainment. Participants also underwent neuropsychological testing and symptom assessment. Regression analyses revealed that only accurately perceiving negative emotions explained significant variance (7.9%) in functional capacity after accounting for neurocognitive function and symptoms. Partial correlations indicated that accurately perceiving anger, in particular, was positively correlated with functional capacity. FAP for positive, negative, or neutral emotions were not related to social competence or social attainment. Our findings were consistent with prior literature suggesting negative emotions are related to functional capacity in schizophrenia. Furthermore, the observed relationship between perceiving anger and performance of everyday living skills is novel and warrants further exploration.

  11. Functional MRI in Awake Dogs Predicts Suitability for Assistance Work

    PubMed Central

    Berns, Gregory S.; Brooks, Andrew M.; Spivak, Mark; Levy, Kerinne

    2017-01-01

    The overall goal of this work was to measure the efficacy of fMRI for predicting whether a dog would be a successful service dog. The training and imaging were performed in 49 dogs entering service training at 17–21 months of age. 33 dogs completed service training and were matched with a person, while 10 were released for behavioral reasons (4 were selected as breeders and 2 were released for medical reasons.) After 2 months of training, fMRI responses were measured while each dog observed hand signals indicating either reward or no reward and given by both a familiar handler and a stranger. Using anatomically defined ROIs in the caudate, amygdala, and visual cortex, we developed a classifier based on the dogs’ subsequent training outcomes. The classifier had a positive predictive value of 94% and a negative predictive value of 67%. The area under the ROC curve was 0.91 (0.80 with 4-fold cross-validation, P = 0.01), indicating a significant predictive capability. The magnitude of response in the caudate was positively correlated with a successful outcome, while the response in the amygdala depended on the interaction with the visual cortex during the stranger condition and was negatively correlated with outcome (higher being associated with failure). These results suggest that, as indexed by caudate activity, successful service dogs generalize associations to hand signals regardless who gives them but without excessive arousal as measured in the amygdala. PMID:28266550

  12. Functional MRI in Awake Dogs Predicts Suitability for Assistance Work

    NASA Astrophysics Data System (ADS)

    Berns, Gregory S.; Brooks, Andrew M.; Spivak, Mark; Levy, Kerinne

    2017-03-01

    The overall goal of this work was to measure the efficacy of fMRI for predicting whether a dog would be a successful service dog. The training and imaging were performed in 49 dogs entering service training at 17–21 months of age. 33 dogs completed service training and were matched with a person, while 10 were released for behavioral reasons (4 were selected as breeders and 2 were released for medical reasons.) After 2 months of training, fMRI responses were measured while each dog observed hand signals indicating either reward or no reward and given by both a familiar handler and a stranger. Using anatomically defined ROIs in the caudate, amygdala, and visual cortex, we developed a classifier based on the dogs’ subsequent training outcomes. The classifier had a positive predictive value of 94% and a negative predictive value of 67%. The area under the ROC curve was 0.91 (0.80 with 4-fold cross-validation, P = 0.01), indicating a significant predictive capability. The magnitude of response in the caudate was positively correlated with a successful outcome, while the response in the amygdala depended on the interaction with the visual cortex during the stranger condition and was negatively correlated with outcome (higher being associated with failure). These results suggest that, as indexed by caudate activity, successful service dogs generalize associations to hand signals regardless who gives them but without excessive arousal as measured in the amygdala.

  13. Functional MRI in Awake Dogs Predicts Suitability for Assistance Work.

    PubMed

    Berns, Gregory S; Brooks, Andrew M; Spivak, Mark; Levy, Kerinne

    2017-03-07

    The overall goal of this work was to measure the efficacy of fMRI for predicting whether a dog would be a successful service dog. The training and imaging were performed in 49 dogs entering service training at 17-21 months of age. 33 dogs completed service training and were matched with a person, while 10 were released for behavioral reasons (4 were selected as breeders and 2 were released for medical reasons.) After 2 months of training, fMRI responses were measured while each dog observed hand signals indicating either reward or no reward and given by both a familiar handler and a stranger. Using anatomically defined ROIs in the caudate, amygdala, and visual cortex, we developed a classifier based on the dogs' subsequent training outcomes. The classifier had a positive predictive value of 94% and a negative predictive value of 67%. The area under the ROC curve was 0.91 (0.80 with 4-fold cross-validation, P = 0.01), indicating a significant predictive capability. The magnitude of response in the caudate was positively correlated with a successful outcome, while the response in the amygdala depended on the interaction with the visual cortex during the stranger condition and was negatively correlated with outcome (higher being associated with failure). These results suggest that, as indexed by caudate activity, successful service dogs generalize associations to hand signals regardless who gives them but without excessive arousal as measured in the amygdala.

  14. Structure and functioning of dryland ecosystems in a changing world.

    PubMed

    Maestre, Fernando T; Eldridge, David J; Soliveres, Santiago; Kéfi, Sonia; Delgado-Baquerizo, Manuel; Bowker, Matthew A; García-Palacios, Pablo; Gaitán, Juan; Gallardo, Antonio; Lázaro, Roberto; Berdugo, Miguel

    2016-11-01

    Understanding how drylands respond to ongoing environmental change is extremely important for global sustainability. Here we review how biotic attributes, climate, grazing pressure, land cover change and nitrogen deposition affect the functioning of drylands at multiple spatial scales. Our synthesis highlights the importance of biotic attributes (e.g. species richness) in maintaining fundamental ecosystem processes such as primary productivity, illustrate how N deposition and grazing pressure are impacting ecosystem functioning in drylands worldwide, and highlight the importance of the traits of woody species as drivers of their expansion in former grasslands. We also emphasize the role of attributes such as species richness and abundance in controlling the responses of ecosystem functioning to climate change. This knowledge is essential to guide conservation and restoration efforts in drylands, as biotic attributes can be actively managed at the local scale to increase ecosystem resilience to global change.

  15. Global Change and the Function and Distribution of Wetlands

    USGS Publications Warehouse

    Middleton, Beth A.

    2012-01-01

    The Global Change Ecology and Wetlands book series will highlight the latest research from the world leaders in the field of climate change in wetlands. Global Change and the Function and Distribution of Wetlands highlights information of importance to wetland ecologists.  The chapters include syntheses of international studies on the effects of drought on function and regeneration in wetlands, sea level rise and the distribution of mangrove swamps, former distributions of swamp species and future lessons from paleoecology, and shifts in atmospheric emissions across geographical regions in wetlands.  Overall, the book will contribute to a better understanding of the potential effects of climate change on world wetland distribution and function.

  16. Structure and functioning of dryland ecosystems in a changing world

    PubMed Central

    Maestre, Fernando T.; Eldridge, David J.; Soliveres, Santiago; Kéfi, Sonia; Delgado-Baquerizo, Manuel; Bowker, Matthew A.; García-Palacios, Pablo; Gaitán, Juan; Gallardo, Antonio; Lázaro, Roberto; Berdugo, Miguel

    2017-01-01

    Understanding how drylands respond to ongoing environmental change is extremely important for global sustainability. Here we review how biotic attributes, climate, grazing pressure, land cover change and nitrogen deposition affect the functioning of drylands at multiple spatial scales. Our synthesis highlights the importance of biotic attributes (e.g. species richness) in maintaining fundamental ecosystem processes such as primary productivity, illustrate how N deposition and grazing pressure are impacting ecosystem functioning in drylands worldwide, and highlight the importance of the traits of woody species as drivers of their expansion in former grasslands. We also emphasize the role of attributes such as species richness and abundance in controlling the responses of ecosystem functioning to climate change. This knowledge is essential to guide conservation and restoration efforts in drylands, as biotic attributes can be actively managed at the local scale to increase ecosystem resilience to global change. PMID:28239303

  17. Executive Function Predicts Artificial Language Learning in Children and Adults

    ERIC Educational Resources Information Center

    Kapa, Leah Lynn

    2013-01-01

    Prior research has established an executive function advantage among bilinguals as compared to monolingual peers. These non-linguistic cognitive advantages are largely assumed to result from the experience of managing two linguistic systems. However, the possibility remains that the relationship between bilingualism and executive function is…

  18. DOES EXPOSURE TO STRESSORS PREDICT CHANGES IN PHYSIOLOGICAL DYSREGULATION?

    PubMed Central

    Glei, Dana A.; Goldman, Noreen; Wu, Chih-Hsun; Weinstein, Maxine

    2013-01-01

    Background The allostatic load framework implies that cumulative exposure to stressors results in multi-system physiological dysregulation. Purpose To investigate the effect of stress burden on subsequent changes (2000-2006) in physiological dysregulation. Methods Data came from a population-based cohort study in Taiwan (n=521, aged 54+ in 2000, re-examined in 2006). Measures of stressful events and chronic strain were based on questions asked in 1996, 1999, and 2000. A measure of trauma was based on exposure to the 1999 earthquake. Dysregulation was based on 17 biomarkers (e.g., metabolic, inflammatory, neuroendocrine). Results There were some small effects among men: chronic strain was associated with subsequent increases in dysregulation (standardized β=0.08, 95% CI = 0.01 to 0.20), particularly inflammation; life events were also associated with increased inflammation (β=0.10, CI = 0.01 to 0.26). There were no significant effects in women. Conclusions We found weak evidence that stress burden is associated with changes in dysregulation. PMID:23526059

  19. Physiological Factors Contributing to Postflight Changes in Functional Performance

    NASA Technical Reports Server (NTRS)

    Bloomberg, J. J.; Feedback, D. L.; Feiverson, A. H.; Lee, S. M. C.; Mulavara, A. P.; Peters, B. T.; Platts, S. H.; Reschke, M. F.; Ryder, J.; Spiering, B. A.; Stenger, M. B.; Wood, S.; Lawrence, E.; Arzeno, N.

    2009-01-01

    Astronauts experience alterations in multiple physiological systems due to exposure to the microgravity conditions of space flight. These physiological changes include sensorimotor disturbances, cardiovascular deconditioning and loss of muscle mass and strength. These changes might affect the ability of crewmembers to perform critical mission tasks immediately after landing on lunar and Martian surfaces. To date, changes in functional performance have not been systematically studied or correlated with physiological changes. To understand how changes in physiological function impact functional performance an interdisciplinary pre/postflight testing regimen (Functional Task Test, FTT) has been developed that systematically evaluates both astronaut postflight functional performance and related physiological changes. The overall objectives of the FTT are to: Develop a set of functional tasks that represent critical mission tasks for Constellation. Determine the ability to perform these tasks after flight. Identify the key physiological factors that contribute to functional decrements. Use this information to develop targeted countermeasures. The functional test battery was designed to address high priority tasks identified by the Constellation program as critical for mission success. The set of functional tests making up the FTT include the: 1) Seat Egress and Walk Test, 2) Ladder Climb Test, 3) Recovery from Fall/Stand Test, 4) Rock Translation Test, 5) Jump Down Test, 6) Torque Generation Test, and 7) Construction Activity Board Test. Corresponding physiological measures include assessments of postural and gait control, dynamic visual acuity, fine motor control, plasma volume, orthostatic intolerance, upper and lower body muscle strength, power, fatigue, control and neuromuscular drive. Crewmembers will perform both functional and physiological tests before and after short (Shuttle) and long-duration (ISS) space flight. Data will be collected on R+0 (Shuttle only), R

  20. Predicting Future Years of Life, Health, and Functional Ability

    PubMed Central

    Diehr, Paula; Diehr, Michael; Arnold, Alice; Yee, Laura M.; Odden, Michelle C.; Hirsch, Calvin H; Thielke, Stephen; Psaty, Bruce M.; Johnson, W. Craig; Kizer, MD, Jorge R.; Newman, Anne

    2015-01-01

    Objective: To create personalized estimates of future health and ability status for older adults. Method: Data came from the Cardiovascular Health Study (CHS), a large longitudinal study. Outcomes included years of life, years of healthy life (based on self-rated health), years of able life (based on activities of daily living), and years of healthy and able life. We developed regression estimates using the demographic and health characteristics that best predicted the four outcomes. Internal and external validity were assessed. Results: A prediction equation based on 11 variables accounted for about 40% of the variability for each outcome. Internal validity was excellent, and external validity was satisfactory. The resulting CHS Healthy Life Calculator (CHSHLC) is available at http://healthylifecalculator.org. Conclusion: CHSHLC provides a well-documented estimate of future years of healthy and able life for older adults, who may use it in planning for the future. PMID:28138467

  1. Biodiversity decreases disease through predictable changes in host community competence.

    PubMed

    Johnson, Pieter T J; Preston, Daniel L; Hoverman, Jason T; Richgels, Katherine L D

    2013-02-14

    Accelerating rates of species extinctions and disease emergence underscore the importance of understanding how changes in biodiversity affect disease outcomes. Over the past decade, a growing number of studies have reported negative correlations between host biodiversity and disease risk, prompting suggestions that biodiversity conservation could promote human and wildlife health. Yet the generality of the diversity-disease linkage remains conjectural, in part because empirical evidence of a relationship between host competence (the ability to maintain and transmit infections) and the order in which communities assemble has proven elusive. Here we integrate high-resolution field data with multi-scale experiments to show that host diversity inhibits transmission of the virulent pathogen Ribeiroia ondatrae and reduces amphibian disease as a result of consistent linkages among species richness, host composition and community competence. Surveys of 345 wetlands indicated that community composition changed nonrandomly with species richness, such that highly competent hosts dominated in species-poor assemblages whereas more resistant species became progressively more common in diverse assemblages. As a result, amphibian species richness strongly moderated pathogen transmission and disease pathology among 24,215 examined hosts, with a 78.4% decline in realized transmission in richer assemblages. Laboratory and mesocosm manipulations revealed an approximately 50% decrease in pathogen transmission and host pathology across a realistic diversity gradient while controlling for host density, helping to establish mechanisms underlying the diversity-disease relationship and their consequences for host fitness. By revealing a consistent link between species richness and community competence, these findings highlight the influence of biodiversity on infection risk and emphasize the benefit of a community-based approach to understanding infectious diseases.

  2. Intrinsic functional connectivity predicts individual differences in distractibility.

    PubMed

    Poole, Victoria N; Robinson, Meghan E; Singleton, Omar; DeGutis, Joseph; Milberg, William P; McGlinchey, Regina E; Salat, David H; Esterman, Michael

    2016-06-01

    Distractor suppression, the ability to filter and ignore task-irrelevant information, is critical for efficient task performance. While successful distractor suppression relies on a balance of activity in neural networks responsible for attention maintenance (dorsal attention network; DAN), reorientation (ventral attention network; VAN), and internal thought (default mode network, DMN), the degree to which intrinsic connectivity within and between these networks contributes to individual differences in distractor suppression ability is not well-characterized. For the purposes of understanding these interactions, the current study collected resting-state fMRI data from 32 Veterans and, several months later (7±5 months apart), performance on the additional singleton paradigm, a measure of distractor suppression. Using multivariate support vector regression models composed of resting state connectivity between regions of the DAN, VAN, and DMN, and a leave-one-subject-out cross-validation procedure, we were able to predict an individual's task performance, yielding a significant correlation between the actual and predicted distractor suppression (r=0.48, p=0.0053). Network-level analyses revealed that greater within-network DMN connectivity was predictive of better distractor suppression, while greater connectivity between the DMN and attention networks was predictive of poorer distractor suppression. The strongest connection hubs were determined to be the right frontal eye field and temporoparietal junction of the DAN and VAN, respectively, and medial (ventromedial prefrontal and posterior cingulate cortices) and bilateral prefrontal regions of the DMN. These results are amongst a small but growing number of studies demonstrating that resting state connectivity is related to stable individual differences in cognitive ability, and suggest that greater integrity and independence of the DMN is related to better attentional ability.

  3. Predicting functional capacity during treadmill testing independent of exercise protocol.

    PubMed

    Foster, C; Crowe, A J; Daines, E; Dumit, M; Green, M A; Lettau, S; Thompson, N N; Weymier, J

    1996-06-01

    Clinically useful estimates of VO2max from treadmill tests (GXT) may be made using protocol-specific equations. In many cases, GXT may proceed more effectively if the clinician is free to adjust speed and grade independent of a specific protocol. We sought to determine whether VO2max could be predicted from the estimated steady-state VO2 of the terminal exercise stage. Seventy clinically stable individuals performed GXT with direct measurement of VO2. Exercise was incremented each minute to optimize clinical examination. Measured VO2max was compared to the estimated steady-state VO2 of the terminal stage based on ACSM equations. Equations for walking or running were used based on the patient's observed method of ambulation. The measured VO2max was always less than the ACSM estimate, with a regular relationship between measured and estimated VO2max. No handrail support: VO2max = 0.869.ACSM -0.07; R2 = 0.955, SEE = 4.8 ml.min-1.kg-1 (N = 30). With handrail support: VO2max = 0.694.ACSM + 3.33; R2 = 0.833, SEE = 4.4 ml.min-1.kg-1 (N = 40). The equations were cross-validated with 20 patients. The correlation between predicted and observed values was r = 0.98 and 0.97 without and with handrail support, respectively. The mean absolute prediction error (3.1 and 4.1 ml.min-1.kg-1) were similar to protocol-specific equations. We conclude that VO2max can be predicted independent of treadmill protocol with approximately the same error as protocol-specific equations.

  4. Per capita interactions and stress tolerance drive stress-induced changes in biodiversity effects on ecosystem functions

    PubMed Central

    Baert, Jan M.; Janssen, Colin R.; Sabbe, Koen; De Laender, Frederik

    2016-01-01

    Environmental stress changes the relationship between biodiversity and ecosystem functions, but the underlying mechanisms are poorly understood. Because species interactions shape biodiversity–ecosystem functioning relationships, changes in per capita interactions under stress (as predicted by the stress gradient hypothesis) can be an important driver of stress-induced changes in these relationships. To test this hypothesis, we measure productivity in microalgae communities along a diversity and herbicide gradient. On the basis of additive partitioning and a mechanistic community model, we demonstrate that changes in per capita interactions do not explain effects of herbicide stress on the biodiversity–productivity relationship. Instead, assuming that the per capita interactions remain unaffected by stress, causing species densities to only change through differences in stress tolerance, suffices to predict the stress-induced changes in the biodiversity–productivity relationship and community composition. We discuss how our findings set the stage for developing theory on how environmental stress changes biodiversity effects on ecosystem functions. PMID:27534986

  5. Per capita interactions and stress tolerance drive stress-induced changes in biodiversity effects on ecosystem functions.

    PubMed

    Baert, Jan M; Janssen, Colin R; Sabbe, Koen; De Laender, Frederik

    2016-08-18

    Environmental stress changes the relationship between biodiversity and ecosystem functions, but the underlying mechanisms are poorly understood. Because species interactions shape biodiversity-ecosystem functioning relationships, changes in per capita interactions under stress (as predicted by the stress gradient hypothesis) can be an important driver of stress-induced changes in these relationships. To test this hypothesis, we measure productivity in microalgae communities along a diversity and herbicide gradient. On the basis of additive partitioning and a mechanistic community model, we demonstrate that changes in per capita interactions do not explain effects of herbicide stress on the biodiversity-productivity relationship. Instead, assuming that the per capita interactions remain unaffected by stress, causing species densities to only change through differences in stress tolerance, suffices to predict the stress-induced changes in the biodiversity-productivity relationship and community composition. We discuss how our findings set the stage for developing theory on how environmental stress changes biodiversity effects on ecosystem functions.

  6. Design Property Network-Based Change Propagation Prediction Approach for Mechanical Product Development

    NASA Astrophysics Data System (ADS)

    Ma, Songhua; Jiang, Zhaoliang; Liu, Wenping; Huang, Chuanzhen

    2017-03-01

    Design changes are unavoidable during mechanical product development; whereas the avalanche propagation of design change imposes severely negative impacts on the design cycle. To improve the validity of the change propagation prediction, a mathematical programming model is presented to predict the change propagation impact quantitatively. As the foundation of change propagation prediction, a design change analysis model(DCAM) is built in the form of design property network. In DCAM, the connections of the design properties are identified as the design specification, which conform to the small-world network theory. To quantify the change propagation impact, change propagation intensity(CPI) is defined as a quantitative and much more objective assessment metric. According to the characteristics of DCAM, CPI is defined and indicated by four assessment factors: propagation likelihood, node degree, long-chain linkage, and design margin. Furthermore, the optimal change propagation path is searched with the evolutionary ant colony optimization(ACO) algorithm, which corresponds to the minimized maximum of accumulated CPI. In practice, the change impact of a gear box is successfully analyzed. The proposed change propagation prediction method is verified to be efficient and effective, which could provide different results according to various the initial changes.

  7. Predictability Effects on Durations of Content and Function Words in Conversational English

    SciTech Connect

    Bell, Alan; Brenier, Jason; Gregory, Michelle L.; girand, cynthia; Jurafsky, Daniel

    2009-01-01

    Content and function word duration are affected differently by their frequency and predictability. Regression analyses of conversational speech show that content words are shorter when they are more frequent, but function words are not. Repeated content words are shorter, but function words are not. Furthermore, function words have shorter pronunciations, after controlling for frequency and predictability. both content and function words are strongly affected by predictability from the word following them, and only very frequent function words show sensitivity to predictability from the preceding word. The results support the view that content and function words are accessed by different production mechanisms. We argue that words’ form differences due to frequency or repetition stem from their faster or slower lexical access, mediated by a general mechanism that coordinates the pace of higher-level planning and the execution of the articulatory plan.

  8. The Functional Integration in the Sensory-Motor System Predicts Aging in Healthy Older Adults.

    PubMed

    He, Hui; Luo, Cheng; Chang, Xin; Shan, Yan; Cao, Weifang; Gong, Jinnan; Klugah-Brown, Benjamin; Bobes, Maria A; Biswal, Bharat; Yao, Dezhong

    2016-01-01

    Healthy aging is typically accompanied by a decrease in the motor capacity. Although the disrupted neural representations and performance of movement have been observed in older age in previous studies, the relationship between the functional integration of sensory-motor (SM) system and aging could be further investigated. In this study, we examine the impact of healthy aging on the resting-state functional connectivity (rsFC) of the SM system, and investigate as to how aging is affecting the rsFC in SM network. The SM network was identified and evaluated in 52 healthy older adults and 51 younger adults using two common data analytic approaches: independent component analysis and seed-based functional connectivity (seed at bilateral M1 and S1). We then evaluated whether the altered rsFC of the SM network could delineate trajectories of the age of older adults using a machine learning methodology. Compared with the younger adults, the older demonstrated reduced functional integration with increasing age in the mid-posterior insula of SM network and increased rsFC among the sensorimotor cortex. Moreover, the reduction in the rsFC of mid-posterior insula is associated with the age of older adults. Critically, the analysis based on two-aspect connectivity-based prediction frameworks revealed that the age of older adults could be reliably predicted by this reduced rsFC. These findings further indicated that healthy aging has a marked influence on the SM system that would be associated with a reorganization of SM system with aging. Our findings provide further insight into changes in sensorimotor function in the aging brain.

  9. The Functional Integration in the Sensory-Motor System Predicts Aging in Healthy Older Adults

    PubMed Central

    He, Hui; Luo, Cheng; Chang, Xin; Shan, Yan; Cao, Weifang; Gong, Jinnan; Klugah-Brown, Benjamin; Bobes, Maria A.; Biswal, Bharat; Yao, Dezhong

    2017-01-01

    Healthy aging is typically accompanied by a decrease in the motor capacity. Although the disrupted neural representations and performance of movement have been observed in older age in previous studies, the relationship between the functional integration of sensory-motor (SM) system and aging could be further investigated. In this study, we examine the impact of healthy aging on the resting-state functional connectivity (rsFC) of the SM system, and investigate as to how aging is affecting the rsFC in SM network. The SM network was identified and evaluated in 52 healthy older adults and 51 younger adults using two common data analytic approaches: independent component analysis and seed-based functional connectivity (seed at bilateral M1 and S1). We then evaluated whether the altered rsFC of the SM network could delineate trajectories of the age of older adults using a machine learning methodology. Compared with the younger adults, the older demonstrated reduced functional integration with increasing age in the mid-posterior insula of SM network and increased rsFC among the sensorimotor cortex. Moreover, the reduction in the rsFC of mid-posterior insula is associated with the age of older adults. Critically, the analysis based on two-aspect connectivity-based prediction frameworks revealed that the age of older adults could be reliably predicted by this reduced rsFC. These findings further indicated that healthy aging has a marked influence on the SM system that would be associated with a reorganization of SM system with aging. Our findings provide further insight into changes in sensorimotor function in the aging brain. PMID:28111548

  10. Computational prediction of functional abortive RNA in E. coli.

    PubMed

    Marcus, Jeremy I; Hassoun, Soha; Nair, Nikhil U

    2017-03-24

    Failure by RNA polymerase to break contacts with promoter DNA results in release of bound RNA and re-initiation of transcription. These abortive RNAs were assumed to be non-functional but have recently been shown to affect termination in bacteriophage T7. Little is known about the functional role of these RNA in other genetic models. Using a computational approach, we investigated whether abortive RNA could exert function in E. coli. Fragments generated from 3780 transcription units were used as query sequences within their respective transcription units to search for possible binding sites. Sites that fell within known regulatory features were then ranked based upon the free energy of hybridization to the abortive. We further hypothesize about mechanisms of regulatory action for a select number of likely matches. Future experimental validation of these putative abortive-mRNA pairs may confirm our findings and promote exploration of functional abortive RNAs (faRNAs) in natural and synthetic systems.

  11. Dissociable changes in functional network topology underlie early category learning and development of automaticity.

    PubMed

    Soto, Fabian A; Bassett, Danielle S; Ashby, F Gregory

    2016-11-01

    Recent work has shown that multimodal association areas-including frontal, temporal, and parietal cortex-are focal points of functional network reconfiguration during human learning and performance of cognitive tasks. On the other hand, neurocomputational theories of category learning suggest that the basal ganglia and related subcortical structures are focal points of functional network reconfiguration during early learning of some categorization tasks but become less so with the development of automatic categorization performance. Using a combination of network science and multilevel regression, we explore how changes in the connectivity of small brain regions can predict behavioral changes during training in a visual categorization task. We find that initial category learning, as indexed by changes in accuracy, is predicted by increasingly efficient integrative processing in subcortical areas, with higher functional specialization, more efficient integration across modules, but a lower cost in terms of redundancy of information processing. The development of automaticity, as indexed by changes in the speed of correct responses, was predicted by lower clustering (particularly in subcortical areas), higher strength (highest in cortical areas), and higher betweenness centrality. By combining neurocomputational theories and network scientific methods, these results synthesize the dissociative roles of multimodal association areas and subcortical structures in the development of automaticity during category learning.

  12. Late-life Depressive Symptoms: Prediction Models of Change

    PubMed Central

    García-Peña, Carmen; Wagner, Fernando A.; Sánchez-García, Sergio; Espinel-Bermúdez, Claudia; Juárez-Cedillo, Teresa; Pérez-Zepeda, Mario; Arango-Lopera, Victoria; Franco-Marina, Francisco; Ramírez-Aldana, Ricardo; Gallo, Joseph

    2013-01-01

    Background Depression is a well-recognised problem in the elderly. The aim of this study was to determine the factors associated with predictors of change in depressive symptoms, both in subjects with and without baseline significant depressive symptoms. Methods Longitudinal study of community-dwelling elderly people (>60 years or older), baseline evaluations, and two additional evaluations were reported. Depressive symptoms were measured using a 30-item Geriatric Depression Scale, and a score of 11 was used as cutoff point for significant depressive symptoms in order to stratify the analyses in two groups: with significant depressive symptoms and without significant depressive symptoms. Sociodemographic data, social support, anxiety, cognition, positive affect, control locus, activities of daily living, recent traumatic life events, physical activity, comorbidities, and quality of life were evaluated. Multi-level generalised estimating equation model was used to assess the impact on the trajectory of depressive symptoms. Results 7,882 subjects were assessed, with 29.42% attrition. At baseline assessment, mean age was 70.96 years, 61.15% were women. Trajectories of depressive symptoms had a decreasing trend. Stronger associations in those with significant depressive symptoms, were social support (OR .971, p<.001), chronic pain (OR 2.277, p<.001) and higher locus of control (OR .581, p<.001). In contrast for those without baseline significant depressive symptoms anxiety and a higher locus of control were the strongest associations. Conclusions New insights into late-life depression are provided, with special emphasis in differentiated factors influencing the trajectory when stratifying regarding basal status of significant depressive symptoms. Limitations The study has not included clinical evaluations and nutritional assessments PMID:23731940

  13. Are Structural Changes Induced by Lithium in the HIV Brain Accompanied by Changes in Functional Connectivity?

    PubMed Central

    Schmidt, Christoph; Lehmann, Thomas; Zhu, Tong; Zhong, Jianhui; Leistritz, Lutz; Schifitto, Giovanni

    2015-01-01

    Lithium therapy has been shown to affect imaging measures of brain function and microstructure in human immunodeficiency virus (HIV)-infected subjects with cognitive impairment. The aim of this proof-of-concept study was to explore whether changes in brain microstructure also entail changes in functional connectivity. Functional MRI data of seven cognitively impaired HIV infected individuals enrolled in an open-label lithium study were included in the connectivity analysis. Seven regions of interest (ROI) were defined based on previously observed lithium induced microstructural changes measured by Diffusion Tensor Imaging. Generalized partial directed coherence (gPDC), based on time-variant multivariate autoregressive models, was used to quantify the degree of connectivity between the selected ROIs. Statistical analyses using a linear mixed model showed significant differences in the average node strength between pre and post lithium therapy conditions. Specifically, we found that lithium treatment in this population induced changes suggestive of increased strength in functional connectivity. Therefore, by exploiting the information about the strength of functional interactions provided by gPDC we can quantify the connectivity changes observed in relation to a given intervention. Furthermore, in conditions where the intervention is associated with clinical changes, we suggest that this methodology could enable an interpretation of such changes in the context of disease or treatment induced modulations in functional networks. PMID:26436895

  14. Annualized functional change in Alzheimer's disease participants and normal controls.

    PubMed

    Weiner, Myron; Fields, Julie; Hynan, Linda; Cullum, C M

    2008-09-01

    The rate of functional change in persons with mild Alzheimer's disease (AD) was compared to that of cognitively normal elderly control subjects. A comparison of annualized rates of change on the Test of Everyday Functional Abilities (TEFA) was carried out, along with a brief measure of instrumental activities of daily living skills, in persons with mild AD (Mini-Mental State Exam score >20) and cognitively normal elderly controls. Persons with AD (N = 30) showed an 8.5 % (3.5 point) annualized decline in TEFA scores over an average of 1.2 years; there was no decline in a group of elderly normal controls (N = 20) over an average of 1.5 years. Persons with mild AD showed functional changes over the course of a year on a direct measure of instrumental activities of daily living; a comparable group of normally aging persons did not.

  15. Integrated protein function prediction by mining function associations, sequences, and protein–protein and gene–gene interaction networks

    PubMed Central

    Cao, Renzhi; Cheng, Jianlin

    2016-01-01

    Motivations Protein function prediction is an important and challenging problem in bioinformatics and computational biology. Functionally relevant biological information such as protein sequences, gene expression, and protein–protein interactions has been used mostly separately for protein function prediction. One of the major challenges is how to effectively integrate multiple sources of both traditional and new information such as spatial gene–gene interaction networks generated from chromosomal conformation data together to improve protein function prediction. Results In this work, we developed three different probabilistic scores (MIS, SEQ, and NET score) to combine protein sequence, function associations, and protein–protein interaction and spatial gene–gene interaction networks for protein function prediction. The MIS score is mainly generated from homologous proteins found by PSI-BLAST search, and also association rules between Gene Ontology terms, which are learned by mining the Swiss-Prot database. The SEQ score is generated from protein sequences. The NET score is generated from protein–protein interaction and spatial gene–gene interaction networks. These three scores were combined in a new Statistical Multiple Integrative Scoring System (SMISS) to predict protein function. We tested SMISS on the data set of 2011 Critical Assessment of Function Annotation (CAFA). The method performed substantially better than three base-line methods and an advanced method based on protein profile–sequence comparison, profile–profile comparison, and domain co-occurrence networks according to the maximum F-measure. PMID:26370280

  16. General functioning predicts reward and punishment learning in schizophrenia.

    PubMed

    Somlai, Zsuzsanna; Moustafa, Ahmed A; Kéri, Szabolcs; Myers, Catherine E; Gluck, Mark A

    2011-04-01

    Previous studies investigating feedback-driven reinforcement learning in patients with schizophrenia have provided mixed results. In this study, we explored the clinical predictors of reward and punishment learning using a probabilistic classification learning task. Patients with schizophrenia (n=40) performed similarly to healthy controls (n=30) on the classification learning task. However, more severe negative and general symptoms were associated with lower reward-learning performance, whereas poorer general psychosocial functioning was correlated with both lower reward- and punishment-learning performances. Multiple linear regression analyses indicated that general psychosocial functioning was the only significant predictor of reinforcement learning performance when education, antipsychotic dose, and positive, negative and general symptoms were included in the analysis. These results suggest a close relationship between reinforcement learning and general psychosocial functioning in schizophrenia.

  17. Exploring aggregate economic damage functions due to climate change

    SciTech Connect

    Dowlatabadi, H.; Kandlikar, M.; Patwardhan, A.

    1994-12-31

    A number of issues need to be considered when developing aggregated economic damage functions due to climate change. These include: (i) identification of production processes vulnerable to climate change, (ii) an understanding of the mechanism of vulnerability, (iii) the rate of technological advance and diffusion (iv) the issue of detection of damages and availability of response options. In this paper we will explore the implications of these considerations with the aid of an illustrative model. The findings suggest that there is a significant upward bias in damage functions calculated without consideration of these issues. Furthermore, this systematic bias is larger as climate change increases. We believe the approach explored here is a more suitable model for adoption in future integrated assessments of climate change.

  18. Utility of Urinary Biomarkers in Predicting Loss of Residual Renal Function: The balANZ Trial

    PubMed Central

    Cho, Yeoungjee; Johnson, David W.; Vesey, David A.; Hawley, Carmel M.; Clarke, Margaret; Topley, Nicholas

    2015-01-01

    ♦ Background: The ability of urinary biomarkers to predict residual renal function (RRF) decline in peritoneal dialysis (PD) patients has not been defined. The present study aimed to explore the utility of established biomarkers from kidney injury models for predicting loss of RRF in incident PD patients, and to evaluate the impact on RRF of using neutral-pH PD solution low in glucose degradation products. ♦ Methods: The study included 50 randomly selected participants from the balANZ trial who had completed 24 months of follow-up. A change in glomerular filtration rate (GFR) was used as the primary clinical outcome measure. In a mixed-effects general linear model, baseline measurements of 18 novel urinary biomarkers and albumin were used to predict GFR change. The model was further used to evaluate the impact of biocompatible PD solution on RRF, adjusted for each biomarker. ♦ Results: Baseline albuminuria was not a useful predictor of change in RRF in PD patients (p = 0.84). Only clusterin was a significant predictor of GFR decline in the whole population (p = 0.04, adjusted for baseline GFR and albuminuria). However, the relationship was no longer apparent when albuminuria was removed from the model (p = 0.31). When the effect of the administered PD solutions was examined using a model adjusted for PD solution type, baseline albuminuria, and GFR, higher baseline urinary concentrations of trefoil factor 3 (TFF3, p = 0.02), kidney injury molecule 1 (KIM-1, p = 0.04), and interferon γ-induced protein 10 (IP-10, p = 0.03) were associated with more rapid decline of RRF in patients receiving conventional PD solution compared with biocompatible PD solution. ♦ Conclusions: Higher urinary levels of kidney injury biomarkers (TFF3, KIM-1, IP-10) at baseline predicted significantly slower RRF decline in patients receiving biocompatible PD solutions. Findings from the present investigation should help to guide future studies to validate the utility of urinary

  19. Property Predictions for Nitrate Salts with Nitroxy-Functionalized Cations

    DTIC Science & Technology

    2011-05-01

    unstable”* to be employed as rocket propellant ingredients (Dunn, 1952; Naoum and Ulrich , 1929; Medard, 1954; Urbanski, 1965). The EQBR and SERDP efforts...from models that combine the B3LYP hybrid functional ( Becke , 1993; Lee et al., 1988; Stephens et al., 1994; Vosko et al., 1980) with a 6-31+G(d,p), 6...1989, 122, 1963–1967. Becke , A. D. Density-Functional Thermochemistry. 3. The Role of Exact Exchange. Journal of Chemical Physics 1993, 98, 5648

  20. Prediction-Market-Based Quantification of Climate Change Consensus and Uncertainty

    NASA Astrophysics Data System (ADS)

    Boslough, M.

    2012-12-01

    Intrade is an online trading exchange that includes climate prediction markets. One such family of contracts can be described as "Global temperature anomaly for 2012 to be greater than x °C or more," where the figure x ranges in increments of .05 from .30 to 1.10 (relative to the 1951-1980 base period), based on data published by NASA GISS. Each market will settle at 10.00 if the published global temperature anomaly for 2012 is equal to or greater than x, and will otherwise settle at 0.00. Similar contracts will be available for 2013. Global warming hypotheses can be cast as probabilistic predictions for future temperatures. The first modern such climate prediction is that of Broecker (1975), whose temperatures are easily separable from his CO2 growth scenario—which he overestimated—by interpolating his table of temperature as a function of CO2 concentration and projecting the current trend into the near future. For the current concentration of 395 ppm, Broecker's equilibrium temperature anomaly prediction relative to pre-industrial is 1.05 °C, or about 0.75 °C relative to the GISS base period. His neglect of lag in response to the changes in radiative forcing was partially compensated by his low sensitivity of 2.4 °C, leading to a slight overestimate. Simple linear extrapolation of the current trend since 1975 yields an estimate of .65 ± .09 °C (net warming of .95 °C) for anthropogenic global warming with a normal distribution of random natural variability. To evaluate an extreme case, we can estimate the prediction Broecker would have made if he had used the Lindzen & Choi (2009) climate sensitivity of 0.5 °C. The net post-industrial warming by 2012 would have been 0.21 °C, for an expected change of -0.09 from the GISS base period. This is the temperature to which the Earth would be expected to revert if the observed warming since the 19th century was merely due to random natural variability that coincidentally mimicked Broecker's anthropogenic

  1. In vitro function of the aryl hydrocarbon receptor predicts in ...

    EPA Pesticide Factsheets

    Differences in sensitivity to dioxin-like compounds (DLCs) among species and taxa presents a major challenge to ecological risk assessments. Activation of the aryl hydrocarbon receptor (AHR) regulates adverse effects associated with exposure to DLCs in vertebrates. Prior investigations demonstrated that sensitivity to activation of the AHR1 (50% effect concentration; EC50) in an in vitro luciferase reporter gene (LRG) assay was predictive of the sensitivity of embryos (lethal dose to cause 50% lethality; LD50) across all species of birds for all DLCs. However, nothing was known about whether sensitivity to activation of the AHR is predictive of sensitivity of embryos of fishes to DLCs. Therefore, this study investigated in vitro sensitivities of AHR1s and AHR2s to the model DLC, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), among eight species of fish of known sensitivities of embryos to TCDD. AHR1s and AHR2s of all fishes were activated by TCDD in vitro. There was no significant linear relationship between in vitro sensitivity of AHR1 and in vivo sensitivity among the investigated fishes (R2 = 0.33, p = 0.23). However, there was a significant linear relationship between in vitro sensitivity of AHR2 and in vivo sensitivity among the investigated fishes (R2 = 0.97, p = < 0.0001). The linear relationship between in vitro sensitivity of AHR2 and in vivo sensitivity of embryos among fishes was compared to the previously generated linear relationship between in vitro s

  2. Timing and Prediction of Climate Change and Hydrological Impacts: Periodicity in Natural Variations

    EPA Science Inventory

    Hydrological impacts from climate change are of principal interest to water resource policy-makers and practicing engineers, and predictive climatic models have been extensively investigated to quantify the impacts. In palaeoclmatic investigations, climate proxy evidence has une...

  3. Heart Rate Change When Standing Up Might Predict Older Adult's Death Risk

    MedlinePlus

    ... Change When Standing Up Might Predict Older Adult's Death Risk People with slower heart rate recovery had ... they stand up might reveal their risk of death over the next several years, a new study ...

  4. Ageing increases reliance on sensorimotor prediction through structural and functional differences in frontostriatal circuits

    PubMed Central

    Wolpe, Noham; Ingram, James N.; Tsvetanov, Kamen A.; Geerligs, Linda; Kievit, Rogier A.; Henson, Richard N.; Wolpert, Daniel M.; Tyler, Lorraine K.; Brayne, Carol; Bullmore, Edward; Calder, Andrew; Cusack, Rhodri; Dalgleish, Tim; Duncan, John; Matthews, Fiona E.; Marslen-Wilson, William; Shafto, Meredith A.; Campbell, Karen; Cheung, Teresa; Davis, Simon; McCarrey, Anna; Mustafa, Abdur; Price, Darren; Samu, David; Taylor, Jason R.; Treder, Matthias; van Belle, Janna; Williams, Nitin; Bates, Lauren; Emery, Tina; Erzinçlioglu, Sharon; Gadie, Andrew; Gerbase, Sofia; Georgieva, Stanimira; Hanley, Claire; Parkin, Beth; Troy, David; Auer, Tibor; Correia, Marta; Gao, Lu; Green, Emma; Henriques, Rafael; Allen, Jodie; Amery, Gillian; Amunts, Liana; Barcroft, Anne; Castle, Amanda; Dias, Cheryl; Dowrick, Jonathan; Fair, Melissa; Fisher, Hayley; Goulding, Anna; Grewal, Adarsh; Hale, Geoff; Hilton, Andrew; Johnson, Frances; Johnston, Patricia; Kavanagh-Williamson, Thea; Kwasniewska, Magdalena; McMinn, Alison; Norman, Kim; Penrose, Jessica; Roby, Fiona; Rowland, Diane; Sargeant, John; Squire, Maggie; Stevens, Beth; Stoddart, Aldabra; Stone, Cheryl; Thompson, Tracy; Yazlik, Ozlem; Barnes, Dan; Dixon, Marie; Hillman, Jaya; Mitchell, Joanne; Villis, Laura; Rowe, James B.

    2016-01-01

    The control of voluntary movement changes markedly with age. A critical component of motor control is the integration of sensory information with predictions of the consequences of action, arising from internal models of movement. This leads to sensorimotor attenuation—a reduction in the perceived intensity of sensations from self-generated compared with external actions. Here we show that sensorimotor attenuation occurs in 98% of adults in a population-based cohort (n=325; 18–88 years; the Cambridge Centre for Ageing and Neuroscience). Importantly, attenuation increases with age, in proportion to reduced sensory sensitivity. This effect is associated with differences in the structure and functional connectivity of the pre-supplementary motor area (pre-SMA), assessed with magnetic resonance imaging. The results suggest that ageing alters the balance between the sensorium and predictive models, mediated by the pre-SMA and its connectivity in frontostriatal circuits. This shift may contribute to the motor and cognitive changes observed with age. PMID:27694879

  5. Predicting Improvement in Depression Across Therapies Using Indicators of Romantic Relationship Functioning: A Preliminary Investigation.

    PubMed

    Woods, Sarah B; Priest, Jacob B; Denton, Wayne H

    2015-01-01

    Depression is a common presenting problem, often affected by couple interactions in unique ways. However, research in the area of romantic relationship functioning and depression often replicates previous research or consists of literature reviews, limiting the clinical relevancy. The purpose of this preliminary study is to expand the research on the effects of relational processes on depression treatment outcomes. We tested whether initiator tendency, attachment anxiety, attachment avoidance, and marital satisfaction predicted improvement in depression for women with Major Depressive Disorder enrolled in a depression treatment clinical trial (n = 17). Women completed treatments of either pharmacotherapy or combined Emotionally Focused Therapy for couples and pharmacotherapy. We found that higher baseline levels of partner initiator tendency resulted in less change in depression (worse outcomes), regardless of treatment type and that higher baseline levels of attachment avoidance predicted better depression outcomes in treatment. Marital satisfaction, however, was not linked to change in depression. Initiator tendency is discussed as a critical romantic relationship factor for depression treatment outcomes.

  6. Predator functional response changed by induced defenses in prey.

    PubMed

    Hammill, Edd; Petchey, Owen L; Anholt, Bradley R

    2010-12-01

    Functional responses play a central role in the nature and stability of predator-prey population dynamics. Here we investigate how induced defenses affect predator functional responses. In experimental communities, prey (Paramecium) expressed two previously undocumented inducible defenses--a speed reduction and a width increase--in response to nonlethal exposure to predatory Stenostomum. Nonlethal exposure also changed the shape of the predator's functional response from Type II to Type III, consistent with changes in the density dependence of attack rates. Handling times were also affected by prey defenses, increasing at least sixfold. These changes show that induced changes in prey have a real defensive function. At low prey densities, induction led to lower attack success; at high prey densities, attack rates were actually higher for induced prey. However, induction increased handling times sufficiently that consumption rates of defended prey were lower than those of undefended prey. Modification of attack rate and handling time has important potential consequences for population dynamics; Type III functional responses can increase the stability of population dynamics and persistence because predation on small populations is low, allowing a relict population to survive. Simulations of a predator-prey population dynamic model revealed the stabilizing potential of the Type III response.

  7. Predicting Change in Career Indecision from a Self-Psychology Perspective.

    ERIC Educational Resources Information Center

    Robbins, Steven B.

    1987-01-01

    Proposes a hierarchical model based on self-psychology that predicts a reduction in career indecision after a career intervention. Tested model's validity in a study of college students (N=107). Study showed model partially supported with goal instability, self-esteem, and interest pattern predicting change in career indecision level after career…

  8. Aqueous acidities of primary benzenesulfonamides: Quantum chemical predictions based on density functional theory and SMD.

    PubMed

    Aidas, Kęstutis; Lanevskij, Kiril; Kubilius, Rytis; Juška, Liutauras; Petkevičius, Daumantas; Japertas, Pranas

    2015-11-05

    Aqueous pK(a) of selected primary benzenesulfonamides are predicted in a systematic manner using density functional theory methods and the SMD solvent model together with direct and proton exchange thermodynamic cycles. Some test calculations were also performed using high-level composite CBS-QB3 approach. The direct scheme generally does not yield a satisfactory agreement between calculated and measured acidities due to a severe overestimation of the Gibbs free energy changes of the gas-phase deprotonation reaction by the used exchange-correlation functionals. The relative pK(a) values calculated using proton exchange method compare to experimental data very well in both qualitative and quantitative terms, with a mean absolute error of about 0.4 pK(a) units. To achieve this accuracy, we find it mandatory to perform geometry optimization of the neutral and anionic species in the gas and solution phases separately, because different conformations are stabilized in these two cases. We have attempted to evaluate the effect of the conformer-averaged free energies in the pK(a) predictions, and the general conclusion is that this procedure is highly too costly as compared with the very small improvement we have gained.

  9. Changes in Cue Configuration Reduce the Impact of Interfering Information in a Predictive Learning Task

    PubMed Central

    Cubillas, Carmelo P.; Vadillo, Miguel A.; Matute, Helena

    2017-01-01

    Decades of research in extinction and interference show that contexts can play a critical role at disambiguating the meaning of cues that have been paired with different outcomes at different times. For instance, if a cue x is followed by outcome 1 in the first phase of an experiment and by outcome 2 in a second phase, responses to cue x tend to be consistent with outcome 2 when tested in a context similar to that of the second phase of the experiment. However, if participants are taken back to the original context of the first phase (i.e., ABA renewal) or to a completely new context (i.e., ABC or AAB renewal), their responses to x tend to be more consistent with outcome 1. Although the role of physical and temporal contexts has been well studied, other factors that can also modulate the selective retrieval of information after interference have received less attention. The present series of experiments shows how changes in cue configuration can modulate responding in a similar manner. Across five experiments using a human predictive learning task, we found that adding, removing or replacing elements from a compound cue that had undergone an interference treatment gave rise to a recovery of responding akin to that observed after context changes in AAB renewal. These results are consistent with those of previous studies exploring the effect of changes of cue configuration on interference. Taken together, these studies suggest that a change in cue configuration can have the functional properties of a context change, a finding with important implications for formal models of configural learning and for classical accounts of interference and information retrieval. PMID:28111562

  10. Changes in Cue Configuration Reduce the Impact of Interfering Information in a Predictive Learning Task.

    PubMed

    Cubillas, Carmelo P; Vadillo, Miguel A; Matute, Helena

    2016-01-01

    Decades of research in extinction and interference show that contexts can play a critical role at disambiguating the meaning of cues that have been paired with different outcomes at different times. For instance, if a cue x is followed by outcome 1 in the first phase of an experiment and by outcome 2 in a second phase, responses to cue x tend to be consistent with outcome 2 when tested in a context similar to that of the second phase of the experiment. However, if participants are taken back to the original context of the first phase (i.e., ABA renewal) or to a completely new context (i.e., ABC or AAB renewal), their responses to x tend to be more consistent with outcome 1. Although the role of physical and temporal contexts has been well studied, other factors that can also modulate the selective retrieval of information after interference have received less attention. The present series of experiments shows how changes in cue configuration can modulate responding in a similar manner. Across five experiments using a human predictive learning task, we found that adding, removing or replacing elements from a compound cue that had undergone an interference treatment gave rise to a recovery of responding akin to that observed after context changes in AAB renewal. These results are consistent with those of previous studies exploring the effect of changes of cue configuration on interference. Taken together, these studies suggest that a change in cue configuration can have the functional properties of a context change, a finding with important implications for formal models of configural learning and for classical accounts of interference and information retrieval.

  11. Can Brief Tests of Mental Status Predict Functional Behavioral Impairment?

    ERIC Educational Resources Information Center

    Hershey, Douglas A.; And Others

    Although criteria for the diagnosis, prognosis, and treatment of Alzheimer's disease (AD) have become better defined, few research findings have appeared in the literature which characterize the degenerative course of the disease. Of particular interest to both clinicians and researchers would be a study focusing on changes in the patient's…

  12. Determining the Importance of Calibration for Predicting Relative Changes in Streamflow from Land Use/Cover Changes

    NASA Astrophysics Data System (ADS)

    Niraula, R.; Meixner, T.; Norman, L. M.

    2012-12-01

    Human-induced land use/cover (LULC) change and climate change can have significant impacts on water quantity and quality. Prediction of impacts due to anticipated LULC and climate change on water in arid and semi-arid regions are crucial to understand due to scarce water resources. Watershed models are often used to analyze the effects of land use/cover and climate change on water resources, commonly in terms of relative changes; and provide important information for decision making. These models are often calibrated and validated with available data which can be time consuming and sometimes even very difficult. The objective of this study is to quantify the variation of estimated relative changes in streamflow associated with LULC with uncalibrated, single outlet calibrated and spatially-calibrated watershed model. Soil and Water Assessment Tool (SWAT) was applied in an uncalibrated, single outlet calibrated, and spatially-calibrated (at 7 USGS stream-gaging stations) mode to compare and quantify the relative change in terms of magnitude and direction of flow in a 9000 km2 semi-arid Santa Cruz watershed on the border of southern Arizona, United States, and northern Sonora, Mexico. While the average annual precipitation over the whole watershed is approximately 430 mm, the average annual discharge ranges between 0.17 and 2.64 m3/s. The effect due to three LULC scenarios, where urbanization is expected to increase from ~12% in 1999 to range of 35-40% in 2050 was analyzed. For the 7 USGS stations, all 3 calibration scenarios demonstrated an increase in predicted flow but magnitude of predicted change varied. The uncalibrated model predicted the increase from 4% to 15%, the single-outlet calibrated model predicted between 5% and 105%, and the spatially-calibrated model predicted the increase to be between 4% and 170%. While the results were similar between uncalibrated and single outlet calibration at some stations, the results were more similar to single outlet and

  13. Predicting Adaptive Functioning of Mentally Retarded Persons in Community Settings.

    ERIC Educational Resources Information Center

    Hull, John T.; Thompson, Joy C.

    1980-01-01

    The impact of a variety of individual, residential, and community variables on adaptive functioning of 369 retarded persons (18 to 73 years old) was examined using a multiple regression analysis. Individual characteristics (especially IQ) accounted for 21 percent of the variance, while environmental variables, primarily those related to…

  14. Predicting verbal fluency using Word Reading: Implications for premorbid functioning.

    PubMed

    Davis, Andrew S; Finch, W Holmes; Drapeau, Christopher; Nogin, Margarita; E Moss, Lauren; Moore, Brittney

    2016-01-01

    The estimation of premorbid general intellectual functioning using word reading tests has a rich history of validation and is a common assessment practice for neuropsychologists. What is less well-researched is the approach used to estimate premorbid functioning of non-intellectual domains, such as executive functions, including verbal fluency. The current study evaluated this relationship with 41 adult college students who completed the Word Reading subtest of the Wechsler Individual Achievement Test-Second Edition (WIAT-II) and the Verbal Fluency test from the Delis-Kaplan Executive Function System (D-KEFS). Path analysis indicated that only Letter Fluency (a measure of phonemic fluency) was statistically significantly related to Word Reading and the relationship was somewhat weak. The relationship between Category Fluency (a measure of semantic fluency) and Category Switching (a measure of verbal fluency cognitive set-shifting) to Word Reading was nonsignificant. Participants also completed the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III), and as expected a strong relationship was found between Word Reading and the Verbal IQ (VIQ), Performance IQ (PIQ), and Full Scale Intelligence Quotient (FSIQ). Results of this study strongly suggest that caution be exercised when extrapolating an estimate of premorbid verbal fluency abilities from measures of word reading.

  15. An Innovative Network to Improve Sea Ice Prediction in a Changing Arctic

    DTIC Science & Technology

    2015-09-30

    Changing Arctic Cecilia M. Bitz Atmospheric Sciences MS351640 University of Washington Seattle, WA 98196-1640 phone: (206) 543-1339 fax...include modeling to place recent sea ice change into system-wide context. We will use models and observations to ask whether “2007–2012 is the New Normal... Climate Predictability Inititiative. Bitz also served on an NRC study group on Subseasonal to Seasonal Prediction, resulting in a report that is

  16. Prediction of synergistic transcription factors by function conservation

    PubMed Central

    Hu, Zihua; Hu, Boyu; Collins, James F

    2007-01-01

    Background Previous methods employed for the identification of synergistic transcription factors (TFs) are based on either TF enrichment from co-regulated genes or phylogenetic footprinting. Despite the success of these methods, both have limitations. Results We propose a new strategy to identify synergistic TFs by function conservation. Rather than aligning the regulatory sequences from orthologous genes and then identifying conserved TF binding sites (TFBSs) in the alignment, we developed computational approaches to implement the novel strategy. These methods include combinatorial TFBS enrichment utilizing distance constraints followed by enrichment of overlapping orthologous genes from human and mouse, whose regulatory sequences contain the enriched TFBS combinations. Subsequently, integration of function conservation from both TFBS and overlapping orthologous genes was achieved by correlation analyses. These techniques have been used for genome-wide promoter analyses, which have led to the identification of 51 homotypic TF combinations; the validity of these approaches has been exemplified by both known TF-TF interactions and function coherence analyses. We further provide computational evidence that our novel methods were able to identify synergistic TFs to a much greater extent than phylogenetic footprinting. Conclusion Function conservation based on the concordance of combinatorial TFBS enrichment along with enrichment of overlapping orthologous genes has been proven to be a successful means for the identification of synergistic TFs. This approach avoids the limitations of phylogenetic footprinting as it does not depend upon sequence alignment. It utilizes existing gene annotation data, such as those available in GO, thus providing an alternative method for functional TF discovery and annotation. PMID:18053230

  17. An efficient perturbation method to predict the functionally key sites of glutamine binding protein.

    PubMed

    Lv, Dashuai; Wang, Cunxin; Li, Chunhua; Tan, Jianjun; Zhang, Xiaoyi

    2017-04-01

    Glutamine-Binding Protein (GlnBP) of Escherichia coli, an important member of the periplasmic binding protein family, is responsible for the first step in the active transport of glutamine across the cytoplasmic membrane. In this work, the functionally key regulation sites of GlnBP were identified by utilizing a perturbation method proposed by our group, in which the residues whose perturbations markedly change the binding free energy between GlnBP and glutamine are considered to be functionally key residues. The results show that besides the substrate binding sites, some other residues distant from the binding pocket, including the ones in the hinge regions between the two domains, the front- and back- door channels and the exposed region, are important for the function of glutamine binding and transport. The predicted results are well consistent with the theoretical and experimental data, which indicates that our method is an effective approach to identify the key residues important for both ligand binding and long-range allosteric signal transmission. This work can provide some insights into the function performance of GlnBP and the physical mechanism of its allosteric regulation.

  18. Ability of Lower-Extremity Injury Severity Scores to Predict Functional Outcome After Limb Salvage

    PubMed Central

    Ly, Thuan V.; Travison, Thomas G.; Castillo, Renan C.; Bosse, Michael J.; MacKenzie, Ellen J.

    2008-01-01

    measured by a change in the scores in either the physical or the psychosocial domain of the Sickness Impact Profile. Conclusions: Currently available injury severity scores are not predictive of the functional recovery of patients who undergo successful limb reconstruction. Level of Evidence: Prognostic Level I. See Instructions to Authors for a complete description of levels of evidence. PMID:18676906

  19. Changes in bird functional diversity across multiple land uses: interpretations of functional redundancy depend on functional group identity.

    PubMed

    Luck, Gary W; Carter, Andrew; Smallbone, Lisa

    2013-01-01

    Examinations of the impact of land-use change on functional diversity link changes in ecological community structure driven by land modification with the consequences for ecosystem function. Yet, most studies have been small-scale, experimental analyses and primarily focussed on plants. There is a lack of research on fauna communities and at large-scales across multiple land uses. We assessed changes in the functional diversity of bird communities across 24 land uses aligned along an intensification gradient. We tested the hypothesis that functional diversity is higher in less intensively used landscapes, documented changes in diversity using four diversity metrics, and examined how functional diversity varied with species richness to identify levels of functional redundancy. Functional diversity, measured using a dendogram-based metric, increased from high to low intensity land uses, but observed values did not differ significantly from randomly-generated expected values. Values for functional evenness and functional divergence did not vary consistently with land-use intensification, although higher than expected values were mostly recorded in high intensity land uses. A total of 16 land uses had lower than expected values for functional dispersion and these were mostly low intensity native vegetation sites. Relations between functional diversity and bird species richness yielded strikingly different patterns for the entire bird community vs. particular functional groups. For all birds and insectivores, functional evenness, divergence and dispersion showed a linear decline with increasing species richness suggesting substantial functional redundancy across communities. However, for nectarivores, frugivores and carnivores, there was a significant hump-shaped or non-significant positive linear relationship between these functional measures and species richness indicating less redundancy. Hump-shaped relationships signify that the most functionally diverse

  20. Changes in Bird Functional Diversity across Multiple Land Uses: Interpretations of Functional Redundancy Depend on Functional Group Identity

    PubMed Central

    Luck, Gary W.; Carter, Andrew; Smallbone, Lisa

    2013-01-01

    Examinations of the impact of land-use change on functional diversity link changes in ecological community structure driven by land modification with the consequences for ecosystem function. Yet, most studies have been small-scale, experimental analyses and primarily focussed on plants. There is a lack of research on fauna communities and at large-scales across multiple land uses. We assessed changes in the functional diversity of bird communities across 24 land uses aligned along an intensification gradient. We tested the hypothesis that functional diversity is higher in less intensively used landscapes, documented changes in diversity using four diversity metrics, and examined how functional diversity varied with species richness to identify levels of functional redundancy. Functional diversity, measured using a dendogram-based metric, increased from high to low intensity land uses, but observed values did not differ significantly from randomly-generated expected values. Values for functional evenness and functional divergence did not vary consistently with land-use intensification, although higher than expected values were mostly recorded in high intensity land uses. A total of 16 land uses had lower than expected values for functional dispersion and these were mostly low intensity native vegetation sites. Relations between functional diversity and bird species richness yielded strikingly different patterns for the entire bird community vs. particular functional groups. For all birds and insectivores, functional evenness, divergence and dispersion showed a linear decline with increasing species richness suggesting substantial functional redundancy across communities. However, for nectarivores, frugivores and carnivores, there was a significant hump-shaped or non-significant positive linear relationship between these functional measures and species richness indicating less redundancy. Hump-shaped relationships signify that the most functionally diverse

  1. Predicting Functional Status Following Amputation After Lower Extremity Bypass

    PubMed Central

    Suckow, Bjoern D.; Goodney, Philip P.; Cambria, Robert A.; Bertges, Daniel J.; Eldrup-Jorgensen, Jens; Indes, Jeffrey E.; Schanzer, Andres; Stone, David H.; Kraiss, Larry W.; Cronenwett, Jack L.

    2012-01-01

    Background Some patients who undergo lower extremity bypass (LEB) for critical limb ischemia ultimately require amputation. The functional outcome achieved by these patients after amputation is not well known. Therefore, we sought to characterize the functional outcome of patients who undergo amputation after LEB, and to describe the pre- and perioperative factors associated with independent ambulation at home after lower extremity amputation. Methods Within a cohort of 3,198 patients who underwent an LEB between January, 2003 and December, 2008, we studied 436 patients who subsequently received an above-knee (AK), below-knee (BK), or minor (forefoot or toe) ipsilateral or contralateral amputation. Our main outcome measure consisted of a “good functional outcome,” defined as living at home and ambulating independently. We calculated univariate and multivariate associations among patient characteristics and our main outcome measure, as well as overall survival. Results Of the 436 patients who underwent amputation within the first year following LEB, 224 of 436 (51.4%) had a minor amputation, 105 of 436 (24.1%) had a BK amputation, and 107 of 436 (24.5%) had an AK amputation. The majority of AK (75 of 107, 72.8%) and BK amputations (72 of 105, 70.6%) occurred in the setting of bypass graft thrombosis, whereas nearly all minor amputations (200 of 224, 89.7%) occurred with a patent bypass graft. By life-table analysis at 1 year, we found that the proportion of surviving patients with a good functional outcome varied by the presence and extent of amputation (proportion surviving with good functional outcome = 88% no amputation, 81% minor amputation, 55% BK amputation, and 45% AK amputation, p = 0.001). Among those analyzed at long-term follow-up, survival was slightly lower for those who had a minor amputation when compared with those who did not receive an amputation after LEB (81 vs. 88%, p = 0.02). Survival among major amputation patients did not significantly

  2. Microbial community functional change during vertebrate carrion decomposition.

    PubMed

    Pechal, Jennifer L; Crippen, Tawni L; Tarone, Aaron M; Lewis, Andrew J; Tomberlin, Jeffery K; Benbow, M Eric

    2013-01-01

    Microorganisms play a critical role in the decomposition of organic matter, which contributes to energy and nutrient transformation in every ecosystem. Yet, little is known about the functional activity of epinecrotic microbial communities associated with carrion. The objective of this study was to provide a description of the carrion associated microbial community functional activity using differential carbon source use throughout decomposition over seasons, between years and when microbial communities were isolated from eukaryotic colonizers (e.g., necrophagous insects). Additionally, microbial communities were identified at the phyletic level using high throughput sequencing during a single study. We hypothesized that carrion microbial community functional profiles would change over the duration of decomposition, and that this change would depend on season, year and presence of necrophagous insect colonization. Biolog EcoPlates™ were used to measure the variation in epinecrotic microbial community function by the differential use of 29 carbon sources throughout vertebrate carrion decomposition. Pyrosequencing was used to describe the bacterial community composition in one experiment to identify key phyla associated with community functional changes. Overall, microbial functional activity increased throughout decomposition in spring, summer and winter while it decreased in autumn. Additionally, microbial functional activity was higher in 2011 when necrophagous arthropod colonizer effects were tested. There were inconsistent trends in the microbial function of communities isolated from remains colonized by necrophagous insects between 2010 and 2011, suggesting a greater need for a mechanistic understanding of the process. These data indicate that functional analyses can be implemented in carrion studies and will be important in understanding the influence of microbial communities on an essential ecosystem process, carrion decomposition.

  3. Microbial Community Functional Change during Vertebrate Carrion Decomposition

    PubMed Central

    Pechal, Jennifer L.; Crippen, Tawni L.; Tarone, Aaron M.; Lewis, Andrew J.; Tomberlin, Jeffery K.; Benbow, M. Eric

    2013-01-01

    Microorganisms play a critical role in the decomposition of organic matter, which contributes to energy and nutrient transformation in every ecosystem. Yet, little is known about the functional activity of epinecrotic microbial communities associated with carrion. The objective of this study was to provide a description of the carrion associated microbial community functional activity using differential carbon source use throughout decomposition over seasons, between years and when microbial communities were isolated from eukaryotic colonizers (e.g., necrophagous insects). Additionally, microbial communities were identified at the phyletic level using high throughput sequencing during a single study. We hypothesized that carrion microbial community functional profiles would change over the duration of decomposition, and that this change would depend on season, year and presence of necrophagous insect colonization. Biolog EcoPlates™ were used to measure the variation in epinecrotic microbial community function by the differential use of 29 carbon sources throughout vertebrate carrion decomposition. Pyrosequencing was used to describe the bacterial community composition in one experiment to identify key phyla associated with community functional changes. Overall, microbial functional activity increased throughout decomposition in spring, summer and winter while it decreased in autumn. Additionally, microbial functional activity was higher in 2011 when necrophagous arthropod colonizer effects were tested. There were inconsistent trends in the microbial function of communities isolated from remains colonized by necrophagous insects between 2010 and 2011, suggesting a greater need for a mechanistic understanding of the process. These data indicate that functional analyses can be implemented in carrion studies and will be important in understanding the influence of microbial communities on an essential ecosystem process, carrion decomposition. PMID:24265741

  4. Phytoplankton traits predict ecosystem function in a global set of lakes.

    PubMed

    Zwart, Jacob A; Solomon, Christopher T; Jones, Stuart E

    2015-08-01

    Predicting ecosystem function from environmental conditions is a central goal of ecosystem ecology. However, many traditional ecosystem models are tailored for specific regions or ecosystem types, requiring several regional models to predict the same function. Alternatively, trait-based approaches have been effectively used to predict community structure in both terrestrial and aquatic environments and ecosystem function in a limited number of terrestrial examples. Here, we test the efficacy of a trait-based model in predicting gross primary production (GPP) in lake ecosystems. We incorporated data from >1000 United States lakes along with laboratory-generated phytoplankton trait data to build a trait-based model of GPP and then validated the model with GPP observations from a separate set of globally distributed lakes. The trait-based model performed as well as or outperformed two ecosystem models both spatially and temporally, demonstrating the efficacy of trait-based models for predicting ecosystem function over a range of environmental conditions.

  5. Association between binge eating disorder and changes in cognitive functioning following bariatric surgery.

    PubMed

    Lavender, Jason M; Alosco, Michael L; Spitznagel, Mary Beth; Strain, Gladys; Devlin, Michael; Cohen, Ronald; Paul, Robert; Crosby, Ross D; Mitchell, James E; Wonderlich, Stephen A; Gunstad, John

    2014-12-01

    Evidence suggests that both obesity and binge eating disorder (BED) may be associated with deficits in cognitive functioning. The purpose of this study was to examine whether a lifetime history of BED would be associated with changes in several domains of cognitive functioning (attention, executive function, language, and memory) following bariatric surgery. Participants were 68 bariatric surgery patients who completed a computerized battery of cognitive tests within 30 days prior to undergoing surgery and again at a 12-Month postoperative follow-up. Results revealed that on the whole, participants displayed improvements from baseline to follow-up in attention, executive function, and memory, even after controlling for diagnostic history of depression; no changes were observed for language. However, individuals with and without a history of BED did not differ in changes in body mass index or in the degree of improvement in cognitive functioning from baseline to follow-up. Such results suggest that a history of BED does not influence changes in cognitive functioning following bariatric surgery. Future research will be needed to further clarify the role of BED in predicting cognitive function over time.

  6. Dynamic Associations of Change in Physical Activity and Change in Cognitive Function: Coordinated Analyses of Four Longitudinal Studies

    PubMed Central

    Lindwall, Magnus; Cimino, Cynthia R.; Gibbons, Laura E.; Mitchell, Meghan B.; Benitez, Andreana; Brown, Cassandra L.; Kennison, Robert F.; Shirk, Steven D.; Atri, Alireza; Robitaille, Annie; MacDonald, Stuart W. S.; Zelinski, Elizabeth M.; Willis, Sherry L.; Schaie, K. Warner; Johansson, Boo; Praetorius, Marcus; Dixon, Roger A.; Mungas, Dan M.; Hofer, Scott M.; Piccinin, Andrea M.

    2012-01-01

    The present study used a coordinated analyses approach to examine the association of physical activity and cognitive change in four longitudinal studies. A series of multilevel growth models with physical activity included both as a fixed (between-person) and time-varying (within-person) predictor of four domains of cognitive function (reasoning, memory, fluency, and semantic knowledge) was used. Baseline physical activity predicted fluency, reasoning and memory in two studies. However, there was a consistent pattern of positive relationships between time-specific changes in physical activity and time-specific changes in cognition, controlling for expected linear trajectories over time, across all four studies. This pattern was most evident for the domains of reasoning and fluency. PMID:23029615

  7. Changes in brain functional network connectivity after stroke

    PubMed Central

    Li, Wei; Li, Yapeng; Zhu, Wenzhen; Chen, Xi

    2014-01-01

    Studies have shown that functional network connection models can be used to study brain network changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlated to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea-lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke. PMID:25206743

  8. Predicting future changes in Muskegon River Watershed game fish distributions under future land cover alteration and climate change scenarios

    USGS Publications Warehouse

    Steen, Paul J.; Wiley, Michael J.; Schaeffer, Jeffrey S.

    2010-01-01

    Future alterations in land cover and climate are likely to cause substantial changes in the ranges of fish species. Predictive distribution models are an important tool for assessing the probability that these changes will cause increases or decreases in or the extirpation of species. Classification tree models that predict the probability of game fish presence were applied to the streams of the Muskegon River watershed, Michigan. The models were used to study three potential future scenarios: (1) land cover change only, (2) land cover change and a 3°C increase in air temperature by 2100, and (3) land cover change and a 5°C increase in air temperature by 2100. The analysis indicated that the expected change in air temperature and subsequent change in water temperatures would result in the decline of coldwater fish in the Muskegon watershed by the end of the 21st century while cool- and warmwater species would significantly increase their ranges. The greatest decline detected was a 90% reduction in the probability that brook trout Salvelinus fontinalis would occur in Bigelow Creek. The greatest increase was a 276% increase in the probability that northern pike Esox lucius would occur in the Middle Branch River. Changes in land cover are expected to cause large changes in a few fish species, such as walleye Sander vitreus and Chinook salmon Oncorhynchus tshawytscha, but not to drive major changes in species composition. Managers can alter stream environmental conditions to maximize the probability that species will reside in particular stream reaches through application of the classification tree models. Such models represent a good way to predict future changes, as they give quantitative estimates of the n-dimensional niches for particular species.

  9. Predicted impacts of climate change on malaria transmission in West Africa

    NASA Astrophysics Data System (ADS)

    Yamana, T. K.; Eltahir, E. A. B.

    2014-12-01

    Increases in temperature and changes in precipitation due to climate change are expected to alter the spatial distribution of malaria transmission. This is especially true in West Africa, where malaria prevalence follows the current north-south gradients in temperature and precipitation. We assess the skill of GCMs at simulating past and present climate in West Africa in order to select the most credible climate predictions for the periods 2030-2060 and 2070-2100. We then use the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a mechanistic model of malaria transmission, to translate the predicted changes in climate into predicted changes availability of mosquito breeding sites, mosquito populations, and malaria prevalence. We investigate the role of acquired immunity in determining a population's response to changes in exposure to the malaria parasite.

  10. Positive Selection or Free to Vary? Assessing the Functional Significance of Sequence Change Using Molecular Dynamics

    PubMed Central

    Allison, Jane R.; Lechner, Marcus; Hoeppner, Marc P.; Poole, Anthony M.

    2016-01-01

    Evolutionary arms races between pathogens and their hosts may be manifested as selection for rapid evolutionary change of key genes, and are sometimes detectable through sequence-level analyses. In the case of protein-coding genes, such analyses frequently predict that specific codons are under positive selection. However, detecting positive selection can be non-trivial, and false positive predictions are a common concern in such analyses. It is therefore helpful to place such predictions within a structural and functional context. Here, we focus on the p19 protein from tombusviruses. P19 is a homodimer that sequesters siRNAs, thereby preventing the host RNAi machinery from shutting down viral infection. Sequence analysis of the p19 gene is complicated by the fact that it is constrained at the sequence level by overprinting of a viral movement protein gene. Using homology modeling, in silico mutation and molecular dynamics simulations, we assess how non-synonymous changes to two residues involved in forming the dimer interface—one invariant, and one predicted to be under positive selection—impact molecular function. Interestingly, we find that both observed variation and potential variation (where a non-synonymous change to p19 would be synonymous for the overprinted movement protein) does not significantly impact protein structure or RNA binding. Consequently, while several methods identify residues at the dimer interface as being under positive selection, MD results suggest they are functionally indistinguishable from a site that is free to vary. Our analyses serve as a caveat to using sequence-level analyses in isolation to detect and assess positive selection, and emphasize the importance of also accounting for how non-synonymous changes impact structure and function. PMID:26871901

  11. Individual differences in cognitive functioning predict effectiveness of a heads-up lane departure warning for younger and older drivers.

    PubMed

    Aksan, Nazan; Sager, Lauren; Hacker, Sarah; Lester, Benjamin; Dawson, Jeffrey; Rizzo, Matthew; Ebe, Kazutoshi; Foley, James

    2017-02-01

    The effectiveness of an idealized lane departure warning (LDW) was evaluated in an interactive fixed base driving simulator. Thirty-eight older (mean age=77years) and 40 younger drivers (mean age=35years) took four different drives/routes similar in road culture composition and hazards encountered with and without LDW. The four drives were administered over visits separated approximately by two weeks to examine changes in long-term effectiveness of LDW. Performance metrics were number of LDW activations and average correction time to each LDW. LDW reduced correction time to re-center the vehicle by 1.34s on average (95% CI=1.12-1.57s) but did not reduce the number of times the drivers drifted enough in their lanes to activate the system (LDW activations). The magnitude of reductions in average correction RT was similar for older and younger drivers and did not change with repeated exposures across visits. The contribution of individual differences in basic visual and motor function, as well as cognitive function to safety gains from LDW was also examined. Cognitive speed of processing predicted lane keeping performance for older and younger drivers. Differences in memory, visuospatial construction, and executive function tended to predict performance differences among older but not younger drivers. Cognitive functioning did not predict changes in the magnitude of safety benefits from LDW over time. Implications are discussed with respect to real-world safety systems.

  12. Change You Can Believe In: Changes in Goal Setting During Emerging and Young Adulthood Predict Later Adult Well-Being

    PubMed Central

    Hill, Patrick L.; Jackson, Joshua J.; Roberts, Brent W.; Lapsley, Daniel K.; Brandenberger, Jay W.

    2013-01-01

    A widely held assumption is that changes in one’s goals and motives for life during emerging and young adulthood have lasting influences on well-being into adulthood. However, this claim has yet to receive rigorous empirical testing. The current study examined the effects of prosocial and occupational goal change during college on adult well-being in a 17-year study of goal setting (N = 416). Using a latent growth model across three time points, both level and growth in goal setting predicted later well-being. Moreover, goal changes both during college and in young adulthood uniquely predicted adult well-being, controlling for goal levels entering college. These findings suggest that what matters for attaining adult well-being is both how you enter adulthood and how you change in response to it. PMID:23493639

  13. Functional Connectivity Changes in Second Language Vocabulary Learning

    ERIC Educational Resources Information Center

    Saidi, Ladan Ghazi; Perlbarg, Vincent; Marrelec, Guillaume; Pelegrini-Issac, Melani; Benali, Habib; Ansaldo, Ana-Ines

    2013-01-01

    Functional connectivity changes in the language network (Price, 2010), and in a control network involved in second language (L2) processing (Abutalebi & Green, 2007) were examined in a group of Persian (L1) speakers learning French (L2) words. Measures of network integration that characterize the global integrative state of a network (Marrelec,…

  14. TEMPORAL CHANGE IN GAP JUNCTION FUNCTION IN PRIMARY HEPATOCYTES

    EPA Science Inventory

    TEMPORAL CHANGES IN GAP JUNCTION FUNCTION IN PRIMARY *

    The objective of this study was to examine the reduction in gap junction communication (GJC) in primary hepatocytes due to coincident melatonin and magnetic field treatments to determine if these conditions could prov...

  15. Predicting change over time in career planning and career exploration for high school students.

    PubMed

    Creed, Peter A; Patton, Wendy; Prideaux, Lee-Ann

    2007-06-01

    This study assessed 166 high school students in Grade 8 and again in Grade 10. Four models were tested: (a) whether the T1 predictor variables (career knowledge, indecision, decision-making self efficacy, self-esteem, demographics) predicted the outcome variable (career planning/exploration) at T1; (b) whether the T1 predictor variables predicted the outcome variable at T2; (c) whether the T1 predictor variables predicted change in the outcome variable from T1-T2; and (d) whether changes in the predictor variables from T1-T2 predicted change in the outcome variable from T1-T2. Strong associations (R(2)=34%) were identified for the T1 analysis (confidence, ability and paid work experience were positively associated with career planning/exploration). T1 variables were less useful predictors of career planning/exploration at T2 (R(2)=9%; having more confidence at T1 was associated with more career planning/exploration at T2) and change in career planning/exploration from T1-T2 (R(2)=11%; less confidence and no work experience were associated with change in career planning/exploration from T1-T2). When testing effect of changes in predictor variables predicting changes in outcome variable (R(2)=22%), three important predictors, indecision, work experience and confidence, were identified. Overall, results indicated important roles for self-efficacy and early work experiences in current and future career planning/exploration of high school students.

  16. Modeling Spatial Recharge in the Arid Southern Okanagan Basin and Impacts of Future Predicted Climate Change

    NASA Astrophysics Data System (ADS)

    Allen, D. M.; Toews, M. W.

    2007-12-01

    Groundwater systems in arid regions will be particularly sensitive to climate change owing to the strong dependence of evapotranspiration rates on temperature, and potential shifts in the precipitation amounts and timing. In this study, future predicted climate change from three GCMs (CGCM1 GHG+A, CGCM3.1 A2, and HadCM3 A2) are used to evaluate the sensitivity of recharge in the Oliver region of the Okanagan Valley, south- central British Columbia, where annual precipitation is approximately 300~mm. Temperature data were downscaled using Statistical Downscaling Model (SDSM), while precipitation and solar radiation changes were estimated directly from the GCM data. Results for the region suggest that temperature will increase up to 4°C by the end of the century. Precipitation is expected to decrease in the spring, and increase in the fall. Solar radiation may decrease in the late summer. Shifts in climate, from present to future-predicted, were applied to the LARS-WG stochastic weather generator to generate daily stochastic weather series. Recharge was modeled spatially using output from the HELP hydrologic model applied to one-dimensional soil columns. An extensive valley-bottom soil database was used to determine both the spatial variation and vertical assemblage of soil horizons in the Oliver region. Soil hydraulic parameters were estimated from soil descriptions using pedotransfer functions through the ROSETTA program. Leaf area index (LAI) was estimated from ground-truthed Landsat 5 TM imagery, and surface slope was estimated from a digital elevation model. Irrigation application rates were modified for each climate scenario based on estimates of seasonal crop water demand. Daily irrigation was added to precipitation in irrigation districts using proportions of crop types along with daily climate and evapotranspiration data from LARS-WG. The two dominant crop classes are orchard (including peaches, cherries and apples) and vineyards (grapes). Recharge in

  17. A Heuristic Prediction of the Cosmic Evolution of the Co-luminosity Functions

    NASA Astrophysics Data System (ADS)

    Obreschkow, D.; Heywood, I.; Klöckner, H.-R.; Rawlings, S.

    2009-09-01

    We predict the emission line luminosity functions (LFs) of the first 10 rotational transitions of 12C16O in galaxies at redshift z = 0 to z = 10. This prediction relies on a recently presented simulation of the molecular cold gas content in ~3 × 107 evolving galaxies based on the Millennium Simulation. We combine this simulation with a model for the conversion between molecular mass and CO-line intensities, which incorporates the following mechanisms: (1) molecular gas is heated by the cosmic microwave background (CMB), starbursts (SBs), and active galactic nuclei (AGNs); (2) molecular clouds in dense or inclined galaxies can overlap; (3) compact gas can attain a smooth distribution in the densest part of disks; (4) CO luminosities scale with metallicity changes between galaxies; and (5) CO luminosities are always detected against the CMB. We analyze the relative importance of these effects and predict the cosmic evolution of the CO-LFs. The most notable conclusion is that the detection of regular galaxies (i.e., no AGN, no massive SB) at high z gsim 7 in CO emission will be dramatically hindered by the weak contrast against the CMB, in contradiction to earlier claims that CMB heating will ease the detection of high-redshift CO. The full simulation of extragalactic CO lines and the predicted CO-LFs at any redshift can be accessed online (http://s-cubed.physics.ox.ac.uk/, go to "S3-SAX") and they should be useful for the modeling of CO-line surveys with future telescopes, such as the Atacama Large Millimeter/submillimeter Array or the Square Kilometre Array.

  18. COMPASS: A computational model to predict changes in MMSE scores 24-months after initial assessment of Alzheimer’s disease

    PubMed Central

    Zhu, Fan; Panwar, Bharat; Dodge, Hiroko H.; Li, Hongdong; Hampstead, Benjamin M.; Albin, Roger L.; Paulson, Henry L.; Guan, Yuanfang

    2016-01-01

    We present COMPASS, a COmputational Model to Predict the development of Alzheimer’s diSease Spectrum, to model Alzheimer’s disease (AD) progression. This was the best-performing method in recent crowdsourcing benchmark study, DREAM Alzheimer’s Disease Big Data challenge to predict changes in Mini-Mental State Examination (MMSE) scores over 24-months using standardized data. In the present study, we conducted three additional analyses beyond the DREAM challenge question to improve the clinical contribution of our approach, including: (1) adding pre-validated baseline cognitive composite scores of ADNI-MEM and ADNI-EF, (2) identifying subjects with significant declines in MMSE scores, and (3) incorporating SNPs of top 10 genes connected to APOE identified from functional-relationship network. For (1) above, we significantly improved predictive accuracy, especially for the Mild Cognitive Impairment (MCI) group. For (2), we achieved an area under ROC of 0.814 in predicting significant MMSE decline: our model has 100% precision at 5% recall, and 91% accuracy at 10% recall. For (3), “genetic only” model has Pearson’s correlation of 0.15 to predict progression in the MCI group. Even though addition of this limited genetic model to COMPASS did not improve prediction of progression of MCI group, the predictive ability of SNP information extended beyond well-known APOE allele. PMID:27703197

  19. Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations

    PubMed Central

    Ou, Jian; Chen, Yongguang; Zhao, Feng; Liu, Jin; Xiao, Shunping

    2017-01-01

    The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity. PMID:28335492

  20. I-TASSER: a unified platform for automated protein structure and function prediction.

    PubMed

    Roy, Ambrish; Kucukural, Alper; Zhang, Yang

    2010-04-01

    The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional (3D) atomic models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission numbers and Gene Ontology terms. An estimate of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of online server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhanglab.ccmb.med.umich.edu/I-TASSER.

  1. Cross-modal prediction changes the timing of conscious access during the motion-induced blindness.

    PubMed

    Chang, Acer Y C; Kanai, Ryota; Seth, Anil K

    2015-01-01

    Despite accumulating evidence that perceptual predictions influence perceptual content, the relations between these predictions and conscious contents remain unclear, especially for cross-modal predictions. We examined whether predictions of visual events by auditory cues can facilitate conscious access to the visual stimuli. We trained participants to learn associations between auditory cues and colour changes. We then asked whether congruency between auditory cues and target colours would speed access to consciousness. We did this by rendering a visual target subjectively invisible using motion-induced blindness and then gradually changing its colour while presenting congruent or incongruent auditory cues. Results showed that the visual target gained access to consciousness faster in congruent than in incongruent trials; control experiments excluded potentially confounding effects of attention and motor response. The expectation effect was gradually established over blocks suggesting a role for extensive training. Overall, our findings show that predictions learned through cross-modal training can facilitate conscious access to visual stimuli.

  2. Cognitive Change Predicts Symptom Reduction With Cognitive Therapy for Posttraumatic Stress Disorder

    PubMed Central

    Kleim, Birgit; Grey, Nick; Wild, Jennifer; Nussbeck, Fridtjof W.; Stott, Richard; Hackmann, Ann; Clark, David M.; Ehlers, Anke

    2012-01-01

    Objective: There is a growing body of evidence for the effectiveness of trauma-focused cognitive behavior therapy (TF-CBT) for posttraumatic stress disorder (PTSD), but few studies to date have investigated the mechanisms by which TF-CBT leads to therapeutic change. Models of PTSD suggest that a core treatment mechanism is the change in dysfunctional appraisals of the trauma and its aftermath. If this is the case, then changes in appraisals should predict a change in symptoms. The present study investigated whether cognitive change precedes symptom change in Cognitive Therapy for PTSD, a version of TF-CBT. Method: The study analyzed weekly cognitive and symptom measures from 268 PTSD patients who received a course of Cognitive Therapy for PTSD, using bivariate latent growth modeling. Results: Results showed that (a) dysfunctional trauma-related appraisals and PTSD symptoms both decreased significantly over the course of treatment, (b) changes in appraisals and symptoms were correlated, and (c) weekly change in appraisals significantly predicted subsequent reduction in symptom scores (both corrected for the general decrease over the course of therapy). Changes in PTSD symptom severity did not predict subsequent changes in appraisals. Conclusions: The study provided preliminary evidence for the temporal precedence of a reduction in negative trauma-related appraisals in symptom reduction during trauma-focused CBT for PTSD. This supports the role of change in appraisals as an active therapeutic mechanism. PMID:23276122

  3. Predicting future changes in climate and its impact on change in land use: a case study of Cauvery Basin

    NASA Astrophysics Data System (ADS)

    Poyil, Rohith P.; Dhanalakshmi, S.; Goyal, Pramila

    2016-05-01

    The study involves the climate change prediction and its effects over a local sub grid scale of smaller area in Cauvery basin. The consequences of global warming due to anthropogenic activities are reflected in global as well as regional climate in terms of changes in key climatic variables such as temperature, precipitation, humidity and wind speed. The key objectives of the study are to define statistical relationships between different climate parameters, to estimate the sensitivities of climate variables to future climate scenarios by integrating with GIS and to predict the land use/ land cover change under the climate change scenarios. The historical data set was analyzed to predict the climate change and its impact on land use/land cover (LULC) is observed by correlating the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) values for two different times for the same area. It is so evident that due to the rise in temperature there is a considerable change in the land use affecting the vegetation index; increased temperature results in very low NDVI values or vegetation abundance.

  4. Does human presynaptic striatal dopamine function predict social conformity?

    PubMed

    Stokes, Paul R A; Benecke, Aaf; Puraite, Julita; Bloomfield, Michael A P; Shotbolt, Paul; Reeves, Suzanne J; Lingford-Hughes, Anne R; Howes, Oliver; Egerton, Alice

    2014-03-01

    Socially desirable responding (SDR) is a personality trait which reflects either a tendency to present oneself in an overly positive manner to others, consistent with social conformity (impression management (IM)), or the tendency to view one's own behaviour in an overly positive light (self-deceptive enhancement (SDE)). Neurochemical imaging studies report an inverse relationship between SDR and dorsal striatal dopamine D₂/₃ receptor availability. This may reflect an association between SDR and D₂/₃ receptor expression, synaptic dopamine levels or a combination of the two. In this study, we used a [¹⁸F]-DOPA positron emission tomography (PET) image database to investigate whether SDR is associated with presynaptic dopamine function. Striatal [¹⁸F]-DOPA uptake, (k(i)(cer), min⁻¹), was determined in two independent healthy participant cohorts (n=27 and 19), by Patlak analysis using a cerebellar reference region. SDR was assessed using the revised Eysenck Personality Questionnaire (EPQ-R) Lie scale, and IM and SDE were measured using the Paulhus Deception Scales. No significant associations were detected between Lie, SDE or IM scores and striatal [¹⁸F]-DOPA k(i)(cer). These results indicate that presynaptic striatal dopamine function is not associated with social conformity and suggests that social conformity may be associated with striatal D₂/₃ receptor expression rather than with synaptic dopamine levels.

  5. Comparative physiology: a "crystal ball" for predicting consequences of global change.

    PubMed

    Somero, George N

    2011-07-01

    Comparative physiology offers powerful approaches for developing causal, mechanistic explanations of shifts in biogeographic patterning occurring in concert with global change. These analyses can identify the cellular loci and intensities of stress-induced perturbation and generate predictions about ecosystem alterations in a changing world. Congeneric species adapted to different abiotic conditions offer excellent study systems for these purposes. Several findings have emerged from such comparative studies: 1) In aquatic and terrestrial habitats, the most heat-tolerant ectotherms may be most threatened by further increases in temperature, due to proximity of these species' thermal optima and tolerance limits to current maximal ambient temperatures and limited capacities for acclimatization to higher temperatures. 2) Cardiac function is a "weak link" in acute thermal tolerance. 3) Stress-induced changes in gene expression comprise a graded response involving genes linked to damage repair, lysis of irreversibly damaged molecules, and downregulation of cell proliferation. Transcriptomic and proteomic analyses provide "biomarkers" for diagnosing degrees of stress. 4) Different abiotic stresses may have synergistic or opposing effects on gene expression, a complexity needing consideration when developing integrated pictures of effects of global change. 5) Adaptation of proteins can result from one to a few amino acid substitutions, which can occur at many sites in a protein, a discovery with implications for rates of adaptive evolution. 6) Greater thermal tolerance of invasive species may favor their replacement of natives. 7) Losses of protein-coding genes and temperature-responsive gene regulatory abilities in stenothermal ectotherms of the Southern Ocean may lead to broad extinctions.

  6. Functional reorganization of the auditory pathways (or lack thereof) in callosal agenesis is predicted by monaural sound localization performance.

    PubMed

    Paiement, Philippe; Champoux, François; Bacon, Benoit A; Lassonde, Maryse; Mensour, Boualem; Leroux, Jean-Maxime; Lepore, Franco

    2010-01-01

    Neuroimaging studies show that permanent peripheral lesions such as unilateral deafness cause functional reorganization in the auditory pathways. However, functional reorganization of the auditory pathways as a result of higher-level damage or abnormalities remains poorly investigated. A relatively recent behavioural study points to functional changes in the auditory pathways in some, but interestingly not in all, of the acallosal individuals that were tested. The present study uses fMRI to investigate auditory activities in both cerebral hemispheres in those same acallosal subjects in order to directly investigate the contributions of ipsilateral and contralateral functional pathways reorganization. Predictions were made that functional reorganization could be predicted from behavioural performance. As reported previously in a number of neuroimaging studies, results showed that in neurologically intact subjects, binaural stimulation induced balanced activities between both hemispheres, while monaural stimulation induced strong contralateral activities and weak ipsilateral activities. In accordance with behavioural predictions, some acallosal subjects showed patterns of auditory cortical activities that were similar to those observed in neurologically intact subjects while others showed functional reorganization of the auditory pathways. Essentially they showed a significant increase and a significant decrease of neural activities in the contralateral and/or ipsilateral pathways, respectively. These findings indicate that at least in some acallosal subjects, functional reorganization inside the auditory pathways does contribute to compensate for the absence of the corpus callosum.

  7. A generalized activating function for predicting virtual electrodes in cardiac tissue.

    PubMed Central

    Sobie, E A; Susil, R C; Tung, L

    1997-01-01

    To fully understand the mechanisms of defibrillation, it is critical to know how a given electrical stimulus causes membrane polarizations in cardiac tissue. We have extended the concept of the activating function, originally used to describe neuronal stimulation, to derive a new expression that identifies the sources that drive changes in transmembrane potential. Source terms, or virtual electrodes, consist of either second derivatives of extracellular potential weighted by intracellular conductivity or extracellular potential gradients weighted by derivatives of intracellular conductivity. The full response of passive tissue can be considered, in simple cases, to be a convolution of this "generalized activating function" with the impulse response of the tissue. Computer simulations of a two-dimensional sheet of passive myocardium under steady-state conditions demonstrate that this source term is useful for estimating the effects of applied electrical stimuli. The generalized activating function predicts oppositely polarized regions of tissue when unequally anisotropic tissue is point stimulated and a monopolar response when a point stimulus is applied to isotropic tissue. In the bulk of the myocardium, this new expression is helpful for understanding mechanisms by which virtual electrodes can be produced, such as the hypothetical "sawtooth" pattern of polarization, as well as polarization owing to regions of depressed conductivity, missing cells or clefts, changes in fiber diameter, or fiber curvature. In comparing solutions obtained with an assumed extracellular potential distribution to those with fully coupled intra- and extracellular domains, we find that the former provides a reliable estimate of the total solution. Thus the generalized activating function that we have derived provides a useful way of understanding virtual electrode effects in cardiac tissue. Images FIGURE 2 FIGURE 4 FIGURE 5 FIGURE 6 PMID:9284308

  8. Amygdala functional connectivity as a longitudinal biomarker of symptom changes in generalized anxiety

    PubMed Central

    Makovac, Elena; Watson, David R.; Meeten, Frances; Garfinkel, Sarah N.; Cercignani, Mara; Critchley, Hugo D.

    2016-01-01

    Generalized anxiety disorder (GAD) is characterized by excessive worry, autonomic dysregulation and functional amygdala dysconnectivity, yet these illness markers have rarely been considered together, nor their interrelationship tested longitudinally. We hypothesized that an individual’s capacity for emotion regulation predicts longer-term changes in amygdala functional connectivity, supporting the modification of GAD core symptoms. Sixteen patients with GAD (14 women) and individually matched controls were studied at two time points separated by 1 year. Resting-state fMRI data and concurrent measurement of vagally mediated heart rate variability were obtained before and after the induction of perseverative cognition. A greater rise in levels of worry following the induction predicted a stronger reduction in connectivity between right amygdala and ventromedial prefrontal cortex, and enhanced coupling between left amygdala and ventral tegmental area at follow-up. Similarly, amplified physiological responses to the induction predicted increased connectivity between right amygdala and thalamus. Longitudinal shifts in a distinct set of functional connectivity scores were associated with concomitant changes in GAD symptomatology over the course of the year. Results highlight the prognostic value of indices of emotional dysregulation and emphasize the integral role of the amygdala as a critical hub in functional neural circuitry underlying the progression of GAD symptomatology. PMID:27369066

  9. PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

    PubMed

    Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

    2009-02-15

    Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http://dragon.bio.purdue.edu/pfp/.

  10. Is Personality Fixed? Personality Changes as Much as "Variable" Economic Factors and More Strongly Predicts Changes to Life Satisfaction

    ERIC Educational Resources Information Center

    Boyce, Christopher J.; Wood, Alex M.; Powdthavee, Nattavudh

    2013-01-01

    Personality is the strongest and most consistent cross-sectional predictor of high subjective well-being. Less predictive economic factors, such as higher income or improved job status, are often the focus of applied subjective well-being research due to a perception that they can change whereas personality cannot. As such there has been limited…

  11. Level and Change in Perceived Control Predict 19-Year Mortality: Findings from the Americans' Changing Lives Study

    ERIC Educational Resources Information Center

    Infurna, Frank J.; Ram, Nilam; Gerstorf, Denis

    2013-01-01

    Perceived control plays an important role for health across adulthood and old age. However, little is known about the factors that account for such associations and whether changes in control (or control trajectory) uniquely predict major health outcomes over and above mean levels of control. Using data from the nationwide Americans' Changing…

  12. Caregivers' Readiness for Change: Predictive Validity in a Child Welfare Sample

    ERIC Educational Resources Information Center

    Littell, J.H.; Girvin, H.

    2005-01-01

    Objective:: To assess the predictive validity of continuous measures of problem recognition (PR), intentions to change (ITC), and overall readiness for change (RFC) among primary caregivers who received in-home services following substantiated reports of child abuse or neglect. Method:: A modified version of the University of Rhode Island Change…

  13. Beyond body mass: how prey traits improve predictions of functional response parameters.

    PubMed

    Kalinoski, Ryan M; DeLong, John P

    2016-02-01

    Understanding the factors that determine the strength of predator-prey interactions is essential to understanding community structure and stability. Variation in the strength of predator-prey interactions often can be attributed to predator mass and prey mass, or abiotic factors like temperature. However, even when accounting for these factors, there remains a considerable amount of unexplained variation that may be attributed to other traits. We compiled functional response data from the literature to investigate how predator mass, prey mass, prey type (taxonomic identity), temperature, and prey defenses (hard vs soft integument) contributed to the variation found in the predator-prey interactions between freshwater cyclopoid copepods and their prey. Surprisingly, our results indicate that prey identity (taxonomic group) and defenses (hard vs soft integument) are more important for generating variation in interaction strengths than body mass and temperature. This suggests that allometric functions can only take us so far when attempting to better understand variation in individual predator prey interactions, and that we must evaluate how other traits influence interaction strengths. Identifying additional factors such as prey defenses may enable us to better predict potential changes in the structure and function of planktonic and other food webs by better accounting for the variation in the interactions between generalists and their many prey types.

  14. Structural and Functional Changes With the Aging Kidney.

    PubMed

    Denic, Aleksandar; Glassock, Richard J; Rule, Andrew D

    2016-01-01

    Senescence or normal physiologic aging portrays the expected age-related changes in the kidney as compared to a disease that occurs in some but not all individuals. The microanatomical structural changes of the kidney with older age include a decreased number of functional glomeruli from an increased prevalence of nephrosclerosis (arteriosclerosis, glomerulosclerosis, and tubular atrophy with interstitial fibrosis), and to some extent, compensatory hypertrophy of remaining nephrons. Among the macroanatomical structural changes, older age associates with smaller cortical volume, larger medullary volume until middle age, and larger and more numerous kidney cysts. Among carefully screened healthy kidney donors, glomerular filtration rate (GFR) declines at a rate of 6.3 mL/min/1.73 m(2) per decade. There is reason to be concerned that the elderly are being misdiagnosed with CKD. Besides this expected kidney function decline, the lowest risk of mortality is at a GFR of ≥75 mL/min/1.73 m(2) for age <55 years but at a lower GFR of 45 to 104 mL/min/1.73 m(2) for age ≥65 years. Changes with normal aging are still of clinical significance. The elderly have less kidney functional reserve when they do actually develop CKD, and they are at higher risk for acute kidney injury.

  15. Structural and functional changes in acute liver injury.

    PubMed Central

    Smuckler, E A

    1976-01-01

    Carbon tetrachloride produces liver cell injury in a variety of animal species. The first structurally recognizable changes occur in the endoplasmic reticulum, with alteration in ribosome-membrane interactions. Later there is an increase in intracellular fat, and the formation of tangled nets of the ergastoplasm. At no time are there changes in mitochondria or single membrane limited bodies in cells with intact plasmalemma, although a relative increase in cell sap may appear. In dead cells (those with plasmalemma discontinuties) crystalline deposits of calcium phosphatase may be noted. Functional changes are related to the endoplasmic reticulum and the plasma membrane. An early decrease in protein synthesis takes place; an accumulation of neutral lipid is related to this change. Later alterations in the ergastoplasmic functions (e.g., mixed function oxidation) occurs. Carbon tetrachloride is not the active agent; rather, a product of its metabolism, probably the CC1, free radical, is. The mechanisms of injury include macromolecular adduction and peroxide propagation. A third possibility includes a cascade effect with the production of secondary and tertiary products, also toxic in nature, with the ability to produce more widespread damage to intracellular structures. Images FIGURE 1. FIGURE 2. FIGURE 3. FIGURE 4. FIGURE 5. FIGURE 6. FIGURE 7. FIGURE 11. PMID:1001290

  16. Protein Function Prediction using Text-based Features extracted from the Biomedical Literature: The CAFA Challenge

    PubMed Central

    2013-01-01

    Background Advances in sequencing technology over the past decade have resulted in an abundance of sequenced proteins whose function is yet unknown. As such, computational systems that can automatically predict and annotate protein function are in demand. Most computational systems use features derived from protein sequence or protein structure to predict function. In an earlier work, we demonstrated the utility of biomedical literature as a source of text features for predicting protein subcellular location. We have also shown that the combination of text-based and sequence-based prediction improves the performance of location predictors. Following up on this work, for the Critical Assessment of Function Annotations (CAFA) Challenge, we developed a text-based system that aims to predict molecular function and biological process (using Gene Ontology terms) for unannotated proteins. In this paper, we present the preliminary work and evaluation that we performed for our system, as part of the CAFA challenge. Results We have developed a preliminary system that represents proteins using text-based features and predicts protein function using a k-nearest neighbour classifier (Text-KNN). We selected text features for our classifier by extracting key terms from biomedical abstracts based on their statistical properties. The system was trained and tested using 5-fold cross-validation over a dataset of 36,536 proteins. System performance was measured using the standard measures of precision, recall, F-measure and overall accuracy. The performance of our system was compared to two baseline classifiers: one that assigns function based solely on the prior distribution of protein function (Base-Prior) and one that assigns function based on sequence similarity (Base-Seq). The overall prediction accuracy of Text-KNN, Base-Prior, and Base-Seq for molecular function classes are 62%, 43%, and 58% while the overall accuracy for biological process classes are 17%, 11%, and 28

  17. Correlated Protein Function Prediction via Maximization of Data-Knowledge Consistency.

    PubMed

    Wang, Hua; Huang, Heng; Ding, Chris

    2015-06-01

    Conventional computational approaches for protein function prediction usually predict one function at a time, fundamentally. As a result, the protein functions are treated as separate target classes. However, biological processes are highly correlated in reality, which makes multiple functions assigned to a protein not independent. Therefore, it would be beneficial to make use of function category correlations when predicting protein functions. In this article, we propose a novel Maximization of Data-Knowledge Consistency (MDKC) approach to exploit function category correlations for protein function prediction. Our approach banks on the assumption that two proteins are likely to have large overlap in their annotated functions if they are highly similar according to certain experimental data. We first establish a new pairwise protein similarity using protein annotations from knowledge perspective. Then by maximizing the consistency between the established knowledge similarity upon annotations and the data similarity upon biological experiments, putative functions are assigned to unannotated proteins. Most importantly, function category correlations are gracefully incorporated into our learning objective through the knowledge similarity. Comprehensive experimental evaluations on the Saccharomyces cerevisiae species have demonstrated promising results that validate the performance of our methods.

  18. Predicting and correcting ataxia using a model of cerebellar function

    PubMed Central

    Bhanpuri, Nasir H.; Okamura, Allison M.

    2014-01-01

    Cerebellar damage results in uncoordinated, variable and dysmetric movements known as ataxia. Here we show that we can reliably model single-joint reaching trajectories of patients (n = 10), reproduce patient-like deficits in the behaviour of controls (n = 11), and apply patient-specific compensations that improve reaching accuracy (P < 0.02). Our approach was motivated by the theory that the cerebellum is essential for updating and/or storing an internal dynamic model that relates motor commands to changes in body state (e.g. arm position and velocity). We hypothesized that cerebellar damage causes a mismatch between the brain’s modelled dynamics and the actual body dynamics, resulting in ataxia. We used both behavioural and computational approaches to demonstrate that specific cerebellar patient deficits result from biased internal models. Our results strongly support the idea that an intact cerebellum is critical for maintaining accurate internal models of dynamics. Importantly, we demonstrate how subject-specific compensation can improve movement in cerebellar patients, who are notoriously unresponsive to treatment. PMID:24812203

  19. FINDSITE: a combined evolution/structure-based approach to protein function prediction

    PubMed Central

    Brylinski, Michal

    2009-01-01

    A key challenge of the post-genomic era is the identification of the function(s) of all the molecules in a given organism. Here, we review the status of sequence and structure-based approaches to protein function inference and ligand screening that can provide functional insights for a significant fraction of the ∼50% of ORFs of unassigned function in an average proteome. We then describe FINDSITE, a recently developed algorithm for ligand binding site prediction, ligand screening and molecular function prediction, which is based on binding site conservation across evolutionary distant proteins identified by threading. Importantly, FINDSITE gives comparable results when high-resolution experimental structures as well as predicted protein models are used. PMID:19324930

  20. Applications of Displacement Transfer Functions to Deformed Shape Predictions of the GIII Swept-Wing Structure

    NASA Technical Reports Server (NTRS)

    Lung, Shun-Fat; Ko, William L.

    2016-01-01

    The displacement transfer functions (DTFs) were applied to the GIII swept wing for the deformed shape prediction. The calculated deformed shapes are very close to the correlated finite element results as well as the measured data. The convergence study showed that using 17 strain stations, the wing-tip displacement prediction error was 1.6 percent, and that there is no need to use a large number of strain stations for G-III wing shape predictions.

  1. Functional Significance of Hormonal Changes in Mammalian Fathers

    PubMed Central

    Saltzman, Wendy; Ziegler, Toni E.

    2016-01-01

    In the 5–10% of mammals in which both parents routinely provide infant care, fathers as well as mothers undergo systematic endocrine changes as they transition into parenthood. Although fatherhood-associated changes in such hormones and neuropeptides as prolactin, testosterone, glucocorticoids, vasopressin, and oxytocin have been characterised in only a small number of biparental rodents and primates, they appear to be more variable than corresponding changes in mothers, and experimental studies typically have not provided strong or consistent evidence that these endocrine shifts play causal roles in the activation of paternal care. Consequently, their functional significance remains unclear. We propose that endocrine changes in mammalian fathers may enable males to meet the species-specific demands of fatherhood by influencing diverse aspects of their behaviour and physiology, similar to many effects of hormones and neuropeptides in mothers. We review the evidence for such effects, focusing on recent studies investigating whether mammalian fathers in biparental species undergo systematic changes in 1) energetics and body composition, 2) neural plasticity, cognition, and sensory physiology, and 3) stress responsiveness and emotionality, all of which may be mediated by endocrine changes. The few published studies, based on a small number of rodent and primate species, suggest that hormonal and neuropeptide alterations in mammalian fathers might mediate shifts in paternal energy balance, body composition, and neural plasticity, but do not appear to have major effects on stress responsiveness or emotionality. Further research is needed on a wider variety of biparental mammals, under more naturalistic conditions, to more fully elucidate the functional significance of hormone and neuropeptide profiles of mammalian fatherhood and to clarify how fatherhood may trade off with, or perhaps enhance, aspects of organismal function in biparental mammals. PMID:25039657

  2. Bioretention function under climate change scenarios in North Carolina, USA

    NASA Astrophysics Data System (ADS)

    Hathaway, J. M.; Brown, R. A.; Fu, J. S.; Hunt, W. F.

    2014-11-01

    The effect of climate change on stormwater controls is largely unknown. Evaluating such effects is important for understanding how well resiliency can be built into urban watersheds by implementing these systems. Bioretention areas with varied media depths, in situ soil types, drainage configurations, and surface infiltration capabilities have previously been monitored, modelled, and calibrated using the continuous simulation model, DRAINMOD. In this study, data from downscaled climate projections for 2055 through 2058 were utilized in these models to evaluate changes in system hydrologic function under two climate change scenarios (RCP 4.5 and 8.5). The results were compared to those generated using a “Base” scenario of observed data from 2001 to 2004. The results showed a modest change in the overall water balance of the system. In particular, the frequency and magnitude of overflow from the systems substantially increased under the climate change scenarios. As this represents an increase in the amount of uncontrolled, untreated runoff from the contributing watersheds, it is of particular concern. Further modelling showed that between 9.0 and 31.0 cm of additional storage would be required under the climate change scenarios to restrict annual overflow to that of the base scenario. Bioretention surface storage volume and infiltration rate appeared important in determining a system's ability to cope with increased yearly rainfall and higher rainfall magnitudes. As climate change effects vary based on location, similar studies should be performed in other locations to determine localized effects on stormwater controls.

  3. Comparison of Statistical and Clinical Predictions of Functional Outcome after Ischemic Stroke

    PubMed Central

    Thompson, Douglas D.; Murray, Gordon D.; Sudlow, Cathie L. M.; Dennis, Martin; Whiteley, William N.

    2014-01-01

    Background To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor’s clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs). Methods and Findings A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS). Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3) using five previously described CPMs. The specificity of a doctor’s informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97) and similar to CPMs (range 0.94 to 0.96); however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49) and clinical prediction models (range 0.38 to 0.45) was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76) and CPMs (range 0.69 to 0.75). No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients. Conclusions CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined. PMID:25299053

  4. Long-term cognitive function change among breast cancer survivors.

    PubMed

    Zheng, Ying; Luo, Jianfeng; Bao, Pingping; Cai, Hui; Hong, Zhen; Ding, Ding; Jackson, James C; Shu, Xiao-Ou; Dai, Qi

    2014-08-01

    Cognitive decline is a common health problem among breast cancer patients and understanding trajectories of cognitive change following among breast cancer survivors is an important public health goal. We conducted a longitudinal study to investigate the cognitive function changes from 18 month to 3 years after breast cancer diagnosis among participants of the Shanghai Breast cancer survivor study, a population-based cohort study of breast cancer survivors. In our study, we completed cognitive function evaluation for 1,300 breast cancer survivors at the 18th month's survey and 1,059 at 36th month's survey, respectively, using a battery of cognitive function measurements. We found the scores in attention and executive function, immediate memory and delayed memory significantly improved from 18 to 36 months after breast cancer diagnosis. The improvements appeared in breast cancer survivors receiving treatments (i.e., surgery, radiotherapy, tamoxifen, or chemotherapy combined with or without tamoxifen), but not in those who received neither chemotherapy nor tamoxifen treatment. The results indicate that cognitive functions, particularly immediate verbal episodic memory, and delayed memory significantly improved among breast cancer survivors from 18 to 36 months after cancer diagnosis. In general, comorbidity was inversely associated with the improvements.

  5. Effect of land use change on soil properties and functions

    NASA Astrophysics Data System (ADS)

    Tonutare, Tonu; Kõlli, Raimo; Köster, Tiina; Rannik, Kaire; Szajdak, Lech; Shanskiy, Merrit

    2014-05-01

    For good base of sustainable land management and ecologically sound protection of soils are researches on soil properties and functioning. Ecosystem approach to soil properties and functioning is equally important in both natural and cultivated land use conditions. Comparative analysis of natural and agro-ecosystems formed on similar soil types enables to elucidate principal changes caused by land use change (LUC) and to elaborate the best land use practices for local pedo-ecological conditions. Taken for actual analysis mineral soils' catena - rendzina → brown soils → pseudopodzolic soils → gley-podzols - represent ca 1/3 of total area of Estonian normal mineral soils. All soils of this catena differ substantially each from other by calcareousness, acidity, nutrition conditions, fabric and humus cover type. This catena (representative to Estonian pedo-ecological conditions) starts with drought-prone calcareous soils. Brown (distributed in northern and central Estonia) and pseudopodzolic soils (in southern Estonia) are the most broadly acknowledged for agricultural use medium-textured high-quality automorphic soils. Dispersedly distributed gley-podzols are permanently wet and strongly acid, low-productivity sandy soils. In presentation four complex functions of soils are treated: (1) being a suitable soil environment for plant cover productivity (expressed by annual increment, Mg ha-1 yr-1); (2) forming adequate conditions for decomposition, transformation and conversion of fresh falling litter (characterized by humus cover type); (3) deposition of humus, individual organic compounds, plant nutrition elements, air and water, and (4) forming (bio)chemically variegated active space for soil type specific edaphon. Capacity of soil cover as depositor (3) depends on it thickness, texture, calcareousness and moisture conditions. Biological activity of soil (4) is determined by fresh organic matter influx, quality and quantity of biochemical substances and humus

  6. Predicting maize phenology: Intercomparison of functions for developmental response to temperature

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate prediction of phenological development in maize is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were t...

  7. Predicting the biomechanical strength of proximal femur specimens with Minkowski functionals and support vector regression

    NASA Astrophysics Data System (ADS)

    Yang, Chien-Chun; Nagarajan, Mahesh B.; Huber, Markus B.; Carballido-Gamio, Julio; Bauer, Jan S.; Baum, Thomas; Eckstein, Felix; Lochmüller, Eva-Maria; Link, Thomas M.; Wismüller, Axel

    2014-03-01

    Regional trabecular bone quality estimation for purposes of femoral bone strength prediction is important for improving the clinical assessment of osteoporotic fracture risk. In this study, we explore the ability of 3D Minkowski Functionals derived from multi-detector computed tomography (MDCT) images of proximal femur specimens in predicting their corresponding biomechanical strength. MDCT scans were acquired for 50 proximal femur specimens harvested from human cadavers. An automated volume of interest (VOI)-fitting algorithm was used to define a consistent volume in the femoral head of each specimen. In these VOIs, the trabecular bone micro-architecture was characterized by statistical moments of its BMD distribution and by topological features derived from Minkowski Functionals. A linear multiregression analysis and a support vector regression (SVR) algorithm with a linear kernel were used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the true FL determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each feature set. The best prediction result was obtained from the Minkowski Functional surface used in combination with SVR, which had the lowest prediction error (RMSE = 0.939 ± 0.345) and which was significantly lower than mean BMD (RMSE = 1.075 ± 0.279, p<0.005). Our results indicate that the biomechanical strength prediction can be significantly improved in proximal femur specimens with Minkowski Functionals extracted from on MDCT images used in conjunction with support vector regression.

  8. Nurses' Assessment of Rehabilitation Potential and Prediction of Functional Status at Discharge from Inpatient Rehabilitation

    ERIC Educational Resources Information Center

    Myers, Jamie S.; Grigsby, Jim; Teel, Cynthia S.; Kramer, Andrew M.

    2009-01-01

    The goals of this study were to evaluate the accuracy of nurses' predictions of rehabilitation potential in older adults admitted to inpatient rehabilitation facilities and to ascertain whether the addition of a measure of executive cognitive function would enhance predictive accuracy. Secondary analysis was performed on prospective data collected…

  9. Predicting College Students' Positive Psychology Associated Traits with Executive Functioning Dimensions

    ERIC Educational Resources Information Center

    Marshall, Seth

    2016-01-01

    More research is needed that investigates how positive psychology-associated traits are predicted by neurocognitive processes. Correspondingly, the purpose of this study was to ascertain how, and to what extent, four traits, namely, grit, optimism, positive affect, and life satisfaction were predicted by the executive functioning (EF) dimensions…

  10. Factors Predicting Renal Function Outcome after Augmentation Cystoplasty

    PubMed Central

    Seyam, Raouf; Firdous, Sadia

    2017-01-01

    We determined the cause of renal deterioration after augmentation cystoplasty (AC). Twenty-nine adult patients with refractory bladder dysfunction and who underwent ileocystoplasty from 2004 to 2015 were studied. Patients with a decline in glomerular filtration rate (GFR) after augmentation were reviewed. The primary outcome was to determine the factors that might lead to deterioration of estimated GFR. Median follow-up was 7.0 ± 2.6 years. Significant bladder capacity, end filling pressure, and bladder compliance were achieved from median 114 ± 53.6 to 342.1 ± 68.3 ml (p = .0001), 68.5 ± 19.9 to 28.2 ± 6.9 cm H2O (p = .0001), and 3.0 ± 2.1 to 12.8 ± 3.9 (p = .0001), respectively. Renal function remained stable and improved in 22 (76%) patients from median eGFR 135 ± 81.98 to 142.82 ± 94.4 ml/min/1.73 m2 (p = .160). Significant deterioration was found in 7 (24%) patients from median eGFR 68.25 ± 42 to 36.57 ± 35.33 (p = .001). The causes of renal deterioration were noncompliance to self-catheterization (2 patients), posterior urethral valve/dysplastic kidneys (2 patients), and reflux/infection (2 patients). On multivariate analysis, recurrent pyelonephritis (OR 3.87, p = 0.0155) and noncompliance (OR 30.78, p = 0.0156) were significant. We concluded that AC is not the cause of progression to end-stage renal disease in patients with renal insufficiency. PMID:28367330

  11. Predictability of Social-anamnestic Variables on Receptive Vocabulary and Cognitive Functioning of the Elderly Population

    PubMed Central

    Ibrahimagic, Amela; Zunic, Lejla Junuzovic; Rasidovic, Mirsada; Radic, Bojan; Kantic, Ahmet

    2016-01-01

    Introduction: Aging, as an irrepressible biological process involves a series of physiological and pathological changes. The main aim of this study was to examine the correlation and predictability of receptive vocabulary and cognitive functioning of elderly people with anamnestic variables: chronological age, sex, level of formal education, marital status, years of work and retirement and years spent in an institution for the elderly. Material and Methods: The sample of participants consisted of 120 elderly people, average age was 78 years, placed in institutional care for elderly people in four cities in Bosnia and Herzegovina. It was three groups of variables: anamnestic, receptive vocabulary assessment, and cognitive assessments. A Montreal Cognitive Assessment Scale (MoCA) was used for the assessment of cognitive abilities. In order to estimate the receptive vocabulary Peabody Picture Vocabulary Test (PPVT-III-HR) was used. Results: Results of multiple regression analysis show that part of the variance of receptive language which is explained by the model (anamnestic variables) was 44.0% and of cognitive functioning was 33.7%. The biggest single contribution to explaining the development of receptive vocabulary was given by predictor variable of college education (β = 0.417) then variable university education (β = 0.293), while the smallest single contribution was given by variable secondary education (β = 0.167). The biggest single contribution to explaining the results of tests of cognitive function was given by predictor variable College education (β = 0.328) and variable unskilled (β = -0.229), which has a negative effect on the increase in recent cognitive functioning. Conclusion: Anamnestic variables were valid predictors of receptive vocabulary and cognitive functioning of elderly people. The highest individual contribution was given by variables describing the level of formal education of elderly. PMID:28144192

  12. Microbial response to simulated global change is phylogenetically conserved and linked with functional potential

    PubMed Central

    Amend, Anthony S; Martiny, Adam C; Allison, Steven D; Berlemont, Renaud; Goulden, Michael L; Lu, Ying; Treseder, Kathleen K; Weihe, Claudia; Martiny, Jennifer B H

    2016-01-01

    The high diversity of microbial communities hampers predictions about their responses to global change. Here we investigate the potential for using a phylogenetic, trait-based framework to capture the response of bacteria and fungi to global change manipulations. Replicated grassland plots were subjected to 3+ years of drought and nitrogen fertilization. The responses of leaf litter bacteria and fungi to these simulated changes were significantly phylogenetically conserved. Proportional changes in abundance were highly correlated among related organisms, such that relatives with approximately 5% ribosomal DNA genetic distance showed similar responses to the treatments. A microbe's change in relative abundance was significantly correlated between the treatments, suggesting a compromise between numerical abundance in undisturbed environments and resistance to change in general, independent of disturbance type. Lineages in which at least 90% of the microbes shared the same response were circumscribed at a modest phylogenetic depth (τD 0.014–0.021), but significantly larger than randomized simulations predict. In several clades, phylogenetic depth of trait consensus was higher. Fungal response to drought was more conserved than was response to nitrogen fertilization, whereas bacteria responded equally to both treatments. Finally, we show that a bacterium's response to the manipulations is correlated with its potential functional traits (measured here as the number of glycoside hydrolase genes encoding the capacity to degrade different types of carbohydrates). Together, these results suggest that a phylogenetic, trait-based framework may be useful for predicting shifts in microbial composition and functioning in the face of global change. PMID:26046258

  13. Predictive value and construct validity of the work functioning screener-healthcare (WFS-H)

    PubMed Central

    Boezeman, Edwin J.; Nieuwenhuijsen, Karen; Sluiter, Judith K.

    2016-01-01

    Objectives: To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Methods: Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. Results: The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (p<.001), associations with productivity (r=.51), mental health (r=.48), and distress (r=.47). Conclusions: The screener (WFS-H) had good predictive value and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers. PMID:27010085

  14. Reticulocyte hemoglobin content predicts functional iron deficiency in hemodialysis patients receiving rHuEPO.

    PubMed

    Mittman, N; Sreedhara, R; Mushnick, R; Chattopadhyay, J; Zelmanovic, D; Vaseghi, M; Avram, M M

    1997-12-01

    Early detection of iron sufficiency at the level of the erythropoietic cell is necessary to optimize management of uremic anemia with recombinant human erythropoietin (rHuEPO). "Absolute" and "functional" iron deficiency are the most important factors causing resistance to administered rHuEPO. Transferrin saturation and serum ferritin measurements have been noted to be insensitive and inaccurate measures to detect functional iron deficiency. Recently, the reticulocyte hemoglobin content (CHr) has been shown to be a sensitive and specific indicator of functional iron deficiency in nondialysis patients treated with rHuEPO. The purpose of this study is to compare CHr with currently used indices of iron sufficiency in rHuEPO-treated hemodialysis (HD) patients. In study 1, 364 stable HD patients were studied at two outpatient dialysis centers. CHr was normally distributed, with a mean value of 28.3 pg, and was consistent over two consecutive monthly samples in each center. CHr was weakly but consistently correlated with transferrin saturation and serum ferritin. CHr and reticulocyte number were inversely correlated with red blood cell (RBC) number, suggesting that the erythropoietic stimulus of routinely administered rHuEPO may have resulted in functional iron deficiency. Month-to-month changes in CHr correlated weakly with changes in serum iron and percent transferrin saturation, but not at all with changes in serum ferritin. When we analyzed those patients with baseline CHr less than 26 pg, a level strongly suggestive of functional iron deficiency, these correlations strengthened, and in addition, month-to-month changes in CHr correlated strongly and directly with concomitant changes in RBC count, hemoglobin, and hematocrit, suggesting that rising CHr was indicative of an erythropoietic response. In study 2, 79 patients received a single-dose infusion of 500 mg iron dextran. After intravenous iron, CHr rose within 48 hours, peaked at 96 hours, and then fell toward

  15. Which Moral Foundations Predict Willingness to Make Lifestyle Changes to Avert Climate Change in the USA?

    PubMed Central

    Dickinson, Janis L.; McLeod, Poppy; Bloomfield, Robert; Allred, Shorna

    2016-01-01

    Jonathan Haidt’s Moral Foundations Theory identifies five moral axes that can influence human motivation to take action on vital problems like climate change. The theory focuses on five moral foundations, including compassion, fairness, purity, authority, and ingroup loyalty; these have been found to differ between liberals and conservatives as well as Democrats and Republicans. Here we show, based on the Cornell National Social Survey (USA), that valuations of compassion and fairness were strong, positive predictors of willingness to act on climate change, whereas purity had a non-significant tendency in the positive direction (p = 0.07). Ingroup loyalty and authority were not supported as important predictor variables using model selection (ΔAICc__). Compassion and fairness were more highly valued by liberals, whereas purity, authority, and in-group loyalty were more highly valued by conservatives. As in previous studies, participants who were younger, more liberal, and reported greater belief in climate change, also showed increased willingness to act on climate change. Our research supports the potential importance of moral foundations as drivers of intentions with respect to climate change action, and suggests that compassion, fairness, and to a lesser extent, purity, are potential moral pathways for personal action on climate change in the USA. PMID:27760207

  16. Which Moral Foundations Predict Willingness to Make Lifestyle Changes to Avert Climate Change in the USA?

    PubMed

    Dickinson, Janis L; McLeod, Poppy; Bloomfield, Robert; Allred, Shorna

    2016-01-01

    Jonathan Haidt's Moral Foundations Theory identifies five moral axes that can influence human motivation to take action on vital problems like climate change. The theory focuses on five moral foundations, including compassion, fairness, purity, authority, and ingroup loyalty; these have been found to differ between liberals and conservatives as well as Democrats and Republicans. Here we show, based on the Cornell National Social Survey (USA), that valuations of compassion and fairness were strong, positive predictors of willingness to act on climate change, whereas purity had a non-significant tendency in the positive direction (p = 0.07). Ingroup loyalty and authority were not supported as important predictor variables using model selection ([Formula: see text]). Compassion and fairness were more highly valued by liberals, whereas purity, authority, and in-group loyalty were more highly valued by conservatives. As in previous studies, participants who were younger, more liberal, and reported greater belief in climate change, also showed increased willingness to act on climate change. Our research supports the potential importance of moral foundations as drivers of intentions with respect to climate change action, and suggests that compassion, fairness, and to a lesser extent, purity, are potential moral pathways for personal action on climate change in the USA.

  17. IMP: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks.

    PubMed

    Wong, Aaron K; Park, Christopher Y; Greene, Casey S; Bongo, Lars A; Guan, Yuanfang; Troyanskaya, Olga G

    2012-07-01

    Integrative multi-species prediction (IMP) is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides a framework for biologists to analyze their candidate gene sets in the context of functional networks, as they expand or focus these sets by mining functional relationships predicted from integrated high-throughput data. IMP integrates prior knowledge and data collections from multiple organisms in its analyses. Through flexible and interactive visualizations, researchers can compare functional contexts and interpret the behavior of their gene sets across organisms. Additionally, IMP identifies homologs with conserved functional roles for knowledge transfer, allowing for accurate function predictions even for biological processes that have very few experimental annotations in a given organism. IMP currently supports seven organisms (Homo sapiens, Mus musculus, Rattus novegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans and Saccharomyces cerevisiae), does not require any registration or installation and is freely available for use at http://imp.princeton.edu.

  18. FNTM: a server for predicting functional networks of tissues in mouse.

    PubMed

    Goya, Jonathan; Wong, Aaron K; Yao, Victoria; Krishnan, Arjun; Homilius, Max; Troyanskaya, Olga G

    2015-07-01

    Functional Networks of Tissues in Mouse (FNTM) provides biomedical researchers with tissue-specific predictions of functional relationships between proteins in the most widely used model organism for human disease, the laboratory mouse. Users can explore FNTM-predicted functional relationships for their tissues and genes of interest or examine gene function and interaction predictions across multiple tissues, all through an interactive, multi-tissue network browser. FNTM makes predictions based on integration of a variety of functional genomic data, including over 13 000 gene expression experiments, and prior knowledge of gene function. FNTM is an ideal starting point for clinical and translational researchers considering a mouse model for their disease of interest, researchers already working with mouse models who are interested in discovering new genes related to their pathways or phenotypes of interest, and biologists working with other organisms to explore the functional relationships of their genes of interest in specific mouse tissue contexts. FNTM predicts tissue-specific functional relationships in 200 tissues, does not require any registration or installation and is freely available for use at http://fntm.princeton.edu.

  19. Spatially distributed flame transfer functions for predicting combustion dynamics in lean premixed gas turbine combustors

    SciTech Connect

    Kim, K.T.; Lee, J.G.; Quay, B.D.; Santavicca, D.A.

    2010-09-15

    The present paper describes a methodology to improve the accuracy of prediction of the eigenfrequencies and growth rates of self-induced instabilities and demonstrates its application to a laboratory-scale, swirl-stabilized, lean-premixed, gas turbine combustor. The influence of the spatial heat release distribution is accounted for using local flame transfer function (FTF) measurements. The two-microphone technique and CH{sup *} chemiluminescence intensity measurements are used to determine the input (inlet velocity perturbation) and the output functions (heat release oscillation), respectively, for the local flame transfer functions. The experimentally determined local flame transfer functions are superposed using the flame transfer function superposition principle, and the result is incorporated into an analytic thermoacoustic model, in order to predict the linear stability characteristics of a given system. Results show that when the flame length is not acoustically compact the model prediction calculated using the local flame transfer functions is better than the prediction made using the global flame transfer function. In the case of a flame in the compact flame regime, accurate predictions of eigenfrequencies and growth rates can be obtained using the global flame transfer function. It was also found that the general response characteristics of the local FTF (gain and phase) are qualitatively the same as those of the global FTF. (author)

  20. Executive function in early childhood: longitudinal measurement invariance and developmental change.

    PubMed

    Willoughby, Michael T; Wirth, R J; Blair, Clancy B

    2012-06-01

    This study tested the longitudinal measurement invariance and developmental changes of a newly developed battery of executive function (EF) tasks for use in early childhood. The battery was administered in the Family Life Project-a prospective longitudinal study (N = 1,292) of families who were oversampled from low-income and African American families at the birth of a new child-at assessments conducted when the child was 3, 4, and 5 years old. All 6 individual EF tasks exhibited strong measurement invariance over time. The EF battery, which was derived from the 6 individual tasks, exhibited partial strong invariance over time. Second-order latent growth curve models revealed individual differences in the levels but not rates of change in latent EF ability. The functional form of change was nonlinear; 60% of the total change in EF ability that was observed between the 3- and 5-year assessments occurred between the Year 3 and Year 4 assessments. Results are discussed with respect to the importance of establishing scalable measures of EF ability prior to investigating experiences that predict or are predicted by changes in EF during early childhood.

  1. A new approach to assess and predict the functional roles of proteins across all known structures.

    PubMed

    Julfayev, Elchin S; McLaughlin, Ryan J; Tao, Yi-Ping; McLaughlin, William A

    2011-03-01

    The three dimensional atomic structures of proteins provide information regarding their function; and codified relationships between structure and function enable the assessment of function from structure. In the current study, a new data mining tool was implemented that checks current gene ontology (GO) annotations and predicts new ones across all the protein structures available in the Protein Data Bank (PDB). The tool overcomes some of the challenges of utilizing large amounts of protein annotation and measurement information to form correspondences between protein structure and function. Protein attributes were extracted from the Structural Biology Knowledgebase and open source biological databases. Based on the presence or absence of a given set of attributes, a given protein's functional annotations were inferred. The results show that attributes derived from the three dimensional structures of proteins enhanced predictions over that using attributes only derived from primary amino acid sequence. Some predictions reflected known but not completely documented GO annotations. For example, predictions for the GO term for copper ion binding reflected used information a copper ion was known to interact with the protein based on information in a ligand interaction database. Other predictions were novel and require further experimental validation. These include predictions for proteins labeled as unknown function in the PDB. Two examples are a role in the regulation of transcription for the protein AF1396 from Archaeoglobus fulgidus and a role in RNA metabolism for the protein psuG from Thermotoga maritima.

  2. EASE-MM: Sequence-Based Prediction of Mutation-Induced Stability Changes with Feature-Based Multiple Models.

    PubMed

    Folkman, Lukas; Stantic, Bela; Sattar, Abdul; Zhou, Yaoqi

    2016-03-27

    Protein engineering and characterisation of non-synonymous single nucleotide variants (SNVs) require accurate prediction of protein stability changes (ΔΔGu) induced by single amino acid substitutions. Here, we have developed a new prediction method called Evolutionary, Amino acid, and Structural Encodings with Multiple Models (EASE-MM), which comprises five specialised support vector machine (SVM) models and makes the final prediction from a consensus of two models selected based on the predicted secondary structure and accessible surface area of the mutated residue. The new method is applicable to single-domain monomeric proteins and can predict ΔΔGu with a protein sequence and mutation as the only inputs. EASE-MM yielded a Pearson correlation coefficient of 0.53-0.59 in 10-fold cross-validation and independent testing and was able to outperform other sequence-based methods. When compared to structure-based energy functions, EASE-MM achieved a comparable or better performance. The application to a large dataset of human germline non-synonymous SNVs showed that the disease-causing variants tend to be associated with larger magnitudes of ΔΔGu predicted with EASE-MM. The EASE-MM web-server is available at http://sparks-lab.org/server/ease.

  3. Functional Knowledge Transfer for High-accuracy Prediction of Under-studied Biological Processes

    PubMed Central

    Rowland, Jessica; Guan, Yuanfang; Bongo, Lars A.; Burdine, Rebecca D.; Troyanskaya, Olga G.

    2013-01-01

    A key challenge in genetics is identifying the functional roles of genes in pathways. Numerous functional genomics techniques (e.g. machine learning) that predict protein function have been developed to address this question. These methods generally build from existing annotations of genes to pathways and thus are often unable to identify additional genes participating in processes that are not already well studied. Many of these processes are well studied in some organism, but not necessarily in an investigator's organism of interest. Sequence-based search methods (e.g. BLAST) have been used to transfer such annotation information between organisms. We demonstrate that functional genomics can complement traditional sequence similarity to improve the transfer of gene annotations between organisms. Our method transfers annotations only when functionally appropriate as determined by genomic data and can be used with any prediction algorithm to combine transferred gene function knowledge with organism-specific high-throughput data to enable accurate function prediction. We show that diverse state-of-art machine learning algorithms leveraging functional knowledge transfer (FKT) dramatically improve their accuracy in predicting gene-pathway membership, particularly for processes with little experimental knowledge in an organism. We also show that our method compares favorably to annotation transfer by sequence similarity. Next, we deploy FKT with state-of-the-art SVM classifier to predict novel genes to 11,000 biological processes across six diverse organisms and expand the coverage of accurate function predictions to processes that are often ignored because of a dearth of annotated genes in an organism. Finally, we perform in vivo experimental investigation in Danio rerio and confirm the regulatory role of our top predicted novel gene, wnt5b, in leftward cell migration during heart development. FKT is immediately applicable to many bioinformatics techniques and will

  4. Improved prediction of accessible surface area results in efficient energy function ap