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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

    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.

  2. 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.

  3. Radionuclide renography predicts functional changes in patients with renal artery involvement by Takayasu's arteritis

    SciTech Connect

    Cuocolo, A.; McCarthy, K.E.; Sandrock, D.; Miller, D.L.; Neumann, R.D. )

    1989-01-01

    Renovascular hypertension is a major complication of Takayasu's arteritis, which contributes to the high mortality associated with the disease. We studied 5 patients affected by different degrees of Takayasu's arteritis to assess the usefulness of radionuclide renography in evaluating renal perfusion and function, and to predict changes induced by the disease before and after therapeutic interventions. Computer-assisted dynamic renal imaging with Tc-99m diethylenetriaminepentaacetic acid (DPTA) and I-131 orthoiodohippurate (OIH), and renal arteriography were concurrently performed in all patients. Two patients with hemodynamically insignificant renal artery stenosis showed normal perfusion and function by renography. Three patients had significant renal artery stenosis and functional changes on renography. Subsequently, two of these patients had successful therapy (one had bilateral renal artery bypass grafts, and the other had renal artery angioplasty), and both showed functional improvement at renography. Our results demonstrate that radionuclide renography is valuable in the assessment of functional changes induced by Takayasu's arteritis as well as for determining the response to therapeutic interventions.

  4. 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

  5. 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

  6. Initiating moderate to heavy alcohol use predicts changes in neuropsychological functioning for adolescent girls and boys.

    PubMed

    Squeglia, Lindsay M; Spadoni, Andrea D; Infante, M Alejandra; Myers, Mark G; Tapert, Susan F

    2009-12-01

    This study prospectively examines the influence of alcohol on neuropsychological functioning in boys and girls characterized prior to initiating drinking (N = 76, ages 12-14). Adolescents who transitioned into heavy (n = 25; 11 girls, 14 boys) or moderate (n = 11; 2 girls, 9 boys) drinking were compared with matched controls who remained nonusers throughout the approximately 3-year follow-up period (N = 40; 16 girls, 24 boys). For girls, more past year drinking days predicted a greater reduction in visuospatial task performance from baseline to follow-up, above and beyond performance on equivalent measures at baseline (R2Delta = 10%, p < .05), particularly on tests of visuospatial memory (R2Delta = 8%, p < .05). For boys, a tendency was seen for more past year hangover symptoms to predict worsened sustained attention (R2Delta = 7%, p < .05). These preliminary longitudinal findings suggest that initiating moderately heavy alcohol use and incurring hangover during adolescence may adversely influence neurocognitive functioning. Neurocognitive deficits linked to heavy drinking during this critical developmental period may lead to direct and indirect changes in neuromaturational course, with effects that would extend into adulthood.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Confirmation of linear system theory prediction: Changes in Herrnstein's k as a function of changes in reinforcer magnitude.

    PubMed

    McDowell, J J; Wood, H M

    1984-03-01

    Eight human subjects pressed a lever on a range of variable-interval schedules for 0.25 cent to 35.0 cent per reinforcement. Herrnstein's hyperbola described seven of the eight subjects' response-rate data well. For all subjects, the y-asymptote of the hyperbola increased with increasing reinforcer magnitude and its reciprocal was a linear function of the reciprocal of reinforcer magnitude. These results confirm predictions made by linear system theory; they contradict formal properties of Herrnstein's account and of six other mathematical accounts of single-alternative responding.

  14. Confirmation of linear system theory prediction: Changes in Herrnstein's k as a function of changes in reinforcer magnitude

    PubMed Central

    McDowell, J. J; Wood, Helena M.

    1984-01-01

    Eight human subjects pressed a lever on a range of variable-interval schedules for 0.25¢ to 35.0¢ per reinforcement. Herrnstein's hyperbola described seven of the eight subjects' response-rate data well. For all subjects, the y-asymptote of the hyperbola increased with increasing reinforcer magnitude and its reciprocal was a linear function of the reciprocal of reinforcer magnitude. These results confirm predictions made by linear system theory; they contradict formal properties of Herrnstein's account and of six other mathematical accounts of single-alternative responding. PMID:16812366

  15. 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.

  16. Treatment-related alteration of cortisol predicts change in neuropsychological function during acute treatment of late-life anxiety disorder

    PubMed Central

    Lenze, Eric J.; Dixon, David; Mantella, Rose C.; Dore, Peter M.; Andreescu, Carmen; Reynolds, Charles F.; Newcomer, John W.; Butters, Meryl A.

    2012-01-01

    Objective Older adults with anxiety disorders are burdened by impairment in neurocognition, which may be mediated by elevated circulating cortisol levels. In a randomized controlled trial of acute serotonin-reuptake inhibitor treatment for late-life anxiety disorder, we examined whether change in salivary cortisol concentrations during treatment predicted improvements in measures of memory and executive function. Methods We examined 60 adults aged 60 and older, who took part in a 12-week trial of escitalopram vs. placebo for Generalized Anxiety Disorder. All subjects had pre- and post-treatment assessments that included monitoring of peak and total daily cortisol and a comprehensive neuropsychological evaluation. Results Salivary cortisol changes during treatment showed significant associations with changes in immediate and delayed memory, but no association with executive tasks (measures of working memory and set-shifting). Analyses suggested that a decrease in cortisol due to serotonin-reuptake inhibitor treatment was responsible for the memory changes: memory improvement was seen with cortisol reduction among patients receiving escitalopram, but not among patients receiving placebo. Conclusion Serotonin-reuptake inhibitor-induced alteration in circulating cortisol during treatment of Generalized Anxiety Disorder predicted changes in immediate and delayed memory. This finding suggests a novel treatment strategy in late-life anxiety disorders: targeting HPA axis dysfunction to improve memory. PMID:21681817

  17. Detecting and predicting changes.

    PubMed

    Brown, Scott D; Steyvers, Mark

    2009-02-01

    When required to predict sequential events, such as random coin tosses or basketball free throws, people reliably use inappropriate strategies, such as inferring temporal structure when none is present. We investigate the ability of observers to predict sequential events in dynamically changing environments, where there is an opportunity to detect true temporal structure. In two experiments we demonstrate that participants often make correct statistical decisions when asked to infer the hidden state of the data generating process. However, when asked to make predictions about future outcomes, accuracy decreased even though normatively correct responses in the two tasks were identical. A particle filter model accounts for all data, describing performance in terms of a plausible psychological process. By varying the number of particles, and the prior belief about the probability of a change occurring in the data generating process, we were able to model most of the observed individual differences.

  18. Does Change in Cognitive Function Predict Change in Costs of Care for People With a Schizophrenia Diagnosis Following Cognitive Remediation Therapy?

    PubMed Central

    Reeder, Clare; Harris, Victoria; Pickles, Andrew; Patel, Anita; Cella, Matteo; Wykes, Til

    2014-01-01

    Background and Aims: Schizophrenia leads to significant personal costs matched by high economic costs. Cognitive function is a strong predictor of disabilities in schizophrenia, which underpin these costs. This study of cognitive remediation therapy (CRT), which has been shown to improve cognition and reduce disability in schizophrenia, aims to investigate associations between improvements in cognition and cost changes. Methods: Eighty-five participants with schizophrenia were randomized to receive CRT or treatment as usual and were assessed at baseline, posttherapy, and 6 month follow-up. Four structural equation models investigated associations between changes in cognitive function and costs of care. Results: All 4 models provided a good fit. Improvement in 3 individual cognitive variables did not predict total cost changes (model 1). But improvement in a single latent cognition factor was associated with a reduction in depression, which in turn was associated with reduced subsequent total costs (model 2). No significant associations with constituent daycare and special accommodation cost changes were apparent with 3 individual cognitive change variables (model 3). But improvement in a single latent cognitive change variable was associated with subsequent reductions in both daycare and special accommodation costs (model 4). Conclusion: This study exemplifies a method of using cost changes to investigate the effects and mechanisms of CRT and suggests that executive function change may be an important target if we are to reduce disability and resultant health and social care costs. PMID:24682210

  19. Longitudinal Changes in Functional Brain Connectivity Predicts Conversion to Alzheimer's Disease.

    PubMed

    Serra, Laura; Cercignani, Mara; Mastropasqua, Chiara; Torso, Mario; Spanò, Barbara; Makovac, Elena; Viola, Vanda; Giulietti, Giovanni; Marra, Camillo; Caltagirone, Carlo; Bozzali, Marco

    2016-01-01

    This longitudinal study investigates the modifications in structure and function occurring to typical Alzheimer's disease (AD) brains over a 2-year follow-up, from pre-dementia stages of disease, with the aim of identifying biomarkers of prognostic value. Thirty-one patients with amnestic mild cognitive impairment were recruited and followed-up with clinical, neuropsychological, and MRI assessments. Patients were retrospectively classified as AD Converters or Non-Converters, and the data compared between groups. Cross-sectional MRI data at baseline, assessing volume and functional connectivity abnormalities, confirmed previous findings, showing a more severe pattern of regional grey matter atrophy and default-mode network disconnection in Converters than in Non-Converters. Longitudinally, Converters showed more grey matter atrophy in the frontotemporal areas, accompanied by increased connectivity in the precuneus. Discriminant analysis revealed that functional connectivity of the precuneus within the default mode network at baseline is the parameter able to correctly classify patients in Converters and Non-Converters with high sensitivity, specificity, and accuracy.

  20. Confirmation of linear system theory prediction: Rate of change of Herrnstein's kappa as a function of response-force requirement.

    PubMed

    McDowell, J J; Wood, H M

    1985-01-01

    Four human subjects worked on all combinations of five variable-interval schedules and five reinforcer magnitudes ( cent/reinforcer) in each of two phases of the experiment. In one phase the force requirement on the operandum was low (1 or 11 N) and in the other it was high (25 or 146 N). Estimates of Herrnstein's kappa were obtained at each reinforcer magnitude. The results were: (1) response rate was more sensitive to changes in reinforcement rate at the high than at the low force requirement, (2) kappa increased from the beginning to the end of the magnitude range for all subjects at both force requirements, (3) the reciprocal of kappa was a linear function of the reciprocal of reinforcer magnitude for seven of the eight data sets, and (4) the rate of change of kappa was greater at the high than at the low force requirement by an order of magnitude or more. The second and third findings confirm predictions made by linear system theory, and replicate the results of an earlier experiment (McDowell & Wood, 1984). The fourth finding confirms a further prediction of the theory and supports the theory's interpretation of conflicting data on the constancy of Herrnstein's kappa.

  1. Confirmation of linear system theory prediction: Rate of change of Herrnstein's κ as a function of response-force requirement

    PubMed Central

    McDowell, J. J; Wood, Helena M.

    1985-01-01

    Four human subjects worked on all combinations of five variable-interval schedules and five reinforcer magnitudes (¢/reinforcer) in each of two phases of the experiment. In one phase the force requirement on the operandum was low (1 or 11 N) and in the other it was high (25 or 146 N). Estimates of Herrnstein's κ were obtained at each reinforcer magnitude. The results were: (1) response rate was more sensitive to changes in reinforcement rate at the high than at the low force requirement, (2) κ increased from the beginning to the end of the magnitude range for all subjects at both force requirements, (3) the reciprocal of κ was a linear function of the reciprocal of reinforcer magnitude for seven of the eight data sets, and (4) the rate of change of κ was greater at the high than at the low force requirement by an order of magnitude or more. The second and third findings confirm predictions made by linear system theory, and replicate the results of an earlier experiment (McDowell & Wood, 1984). The fourth finding confirms a further prediction of the theory and supports the theory's interpretation of conflicting data on the constancy of Herrnstein's κ. PMID:16812408

  2. 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.

  3. 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. PMID:27349456

  4. 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.

  5. 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

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

    PubMed

    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.

  7. Predicting communities from functional traits.

    PubMed

    Cadotte, Marc W; Arnillas, Carlos A; Livingstone, Stuart W; Yasui, Simone-Louise E

    2015-09-01

    Species traits influence where species live and how they interact. While there have been many advances in describing the functional composition and diversity of communities, only recently do researchers have the ability to predict community composition and diversity. This predictive ability can offer fundamental insights into ecosystem resilience and restoration. PMID:26190136

  8. 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

  9. Predicting cognitive change within domains

    PubMed Central

    Duff, Kevin; Beglinger, Leigh J.; Moser, David J.; Paulsen, Jane S.

    2010-01-01

    Standardized regression based (SRB) formulas, a method for predicting cognitive change across time, traditionally use baseline performance on a neuropsychological measure to predict future performance on that same measure. However, there are instances in which the same tests may not be given at follow-up assessments (e.g., lack of continuity of provider, avoiding practice effects). The current study sought to expand this methodology by developing SRBs to predict performance on different tests within the same cognitive domain. Using a sample of 127 non-demented community-dwelling older adults assessed at baseline and after one year, two sets of SRBs were developed: 1. those predicting performance on the same test, and 2. those predicting performance on a different test within the same cognitive domain. The domains examined were learning and memory, processing speed, and language. Across both sets of SRBs, one year scores were significantly predicted by baseline scores, especially for the learning and memory and processing speed measures. Although SRBs developed for the same test were comparable to those developed for different tests within the same domain, less variance was accounted for as tests became less similar. The current results lend preliminary support for additional development of SRBs, both for same- and different-tests, as well as beginning to examine domain-based SRBs. PMID:20358479

  10. 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.

  11. 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…

  12. Smoking Abstinence-Induced Changes in Resting State Functional Connectivity with Ventral Striatum Predict Lapse During a Quit Attempt.

    PubMed

    Sweitzer, Maggie M; Geier, Charles F; Addicott, Merideth A; Denlinger, Rachel; Raiff, Bethany R; Dallery, Jesse; McClernon, F Joseph; Donny, Eric C

    2016-09-01

    The ventral and dorsal striatum are critical substrates of reward processing and motivation and have been repeatedly linked to addictive disorders, including nicotine dependence. However, little is known about how functional connectivity between these and other brain regions is modulated by smoking withdrawal and may contribute to relapse vulnerability. In the present study, 37 smokers completed resting state fMRI scans during both satiated and 24-h abstinent conditions, prior to engaging in a 3-week quit attempt supported by contingency management. We examined the effects of abstinence condition and smoking outcome (lapse vs non-lapse) on whole-brain connectivity with ventral and dorsal striatum seed regions. Results indicated a significant condition by lapse outcome interaction for both right and left ventral striatum seeds. Robust abstinence-induced increases in connectivity with bilateral ventral striatum were observed across a network of regions implicated in addictive disorders, including insula, superior temporal gyrus, and anterior/mid-cingulate cortex among non-lapsers; the opposite pattern was observed for those who later lapsed. For dorsal striatum seeds, 24-h abstinence decreased connectivity across both groups with several regions, including medial prefrontal cortex, posterior cingulate cortex, hippocampus, and supplemental motor area. These findings suggest that modulation of striatal connectivity with the cingulo-insular network during early withdrawal may be associated with smoking cessation outcomes. PMID:27091382

  13. Prenatal arsenic exposure and the epigenome: identifying sites of 5-methylcytosine alterations that predict functional changes in gene expression in newborn cord blood and subsequent birth outcomes.

    PubMed

    Rojas, Daniel; Rager, Julia E; Smeester, Lisa; Bailey, Kathryn A; Drobná, Zuzana; Rubio-Andrade, Marisela; Stýblo, Miroslav; García-Vargas, Gonzalo; Fry, Rebecca C

    2015-01-01

    Prenatal exposure to inorganic arsenic (iAs) is detrimental to the health of newborns and increases the risk of disease development later in life. Here we examined a subset of newborn cord blood leukocyte samples collected from subjects enrolled in the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort in Gómez Palacio, Mexico, who were exposed to a range of drinking water arsenic concentrations (0.456-236 µg/l). Changes in iAs-associated DNA 5-methylcytosine methylation were assessed across 424,935 CpG sites representing 18,761 genes and compared with corresponding mRNA expression levels and birth outcomes. In the context of arsenic exposure, a total of 2919 genes were identified with iAs-associated differences in DNA methylation. Site-specific analyses identified DNA methylation changes that were most predictive of gene expression levels where CpG methylation within CpG islands positioned within the first exon, the 5' untranslated region and 200 bp upstream of the transcription start site yielded the most significant association with gene expression levels. A set of 16 genes was identified with correlated iAs-associated changes in DNA methylation and mRNA expression and all were highly enriched for binding sites of the early growth response (EGR) and CCCTC-binding factor (CTCF) transcription factors. Furthermore, DNA methylation levels of 7 of these genes were associated with differences in birth outcomes including gestational age and head circumference.These data highlight the complex interplay between DNA methylation, functional changes in gene expression and health outcomes and underscore the need for functional analyses coupled to epigenetic assessments.

  14. Prenatal arsenic exposure and the epigenome: identifying sites of 5-methylcytosine alterations that predict functional changes in gene expression in newborn cord blood and subsequent birth outcomes.

    PubMed

    Rojas, Daniel; Rager, Julia E; Smeester, Lisa; Bailey, Kathryn A; Drobná, Zuzana; Rubio-Andrade, Marisela; Stýblo, Miroslav; García-Vargas, Gonzalo; Fry, Rebecca C

    2015-01-01

    Prenatal exposure to inorganic arsenic (iAs) is detrimental to the health of newborns and increases the risk of disease development later in life. Here we examined a subset of newborn cord blood leukocyte samples collected from subjects enrolled in the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort in Gómez Palacio, Mexico, who were exposed to a range of drinking water arsenic concentrations (0.456-236 µg/l). Changes in iAs-associated DNA 5-methylcytosine methylation were assessed across 424,935 CpG sites representing 18,761 genes and compared with corresponding mRNA expression levels and birth outcomes. In the context of arsenic exposure, a total of 2919 genes were identified with iAs-associated differences in DNA methylation. Site-specific analyses identified DNA methylation changes that were most predictive of gene expression levels where CpG methylation within CpG islands positioned within the first exon, the 5' untranslated region and 200 bp upstream of the transcription start site yielded the most significant association with gene expression levels. A set of 16 genes was identified with correlated iAs-associated changes in DNA methylation and mRNA expression and all were highly enriched for binding sites of the early growth response (EGR) and CCCTC-binding factor (CTCF) transcription factors. Furthermore, DNA methylation levels of 7 of these genes were associated with differences in birth outcomes including gestational age and head circumference.These data highlight the complex interplay between DNA methylation, functional changes in gene expression and health outcomes and underscore the need for functional analyses coupled to epigenetic assessments. PMID:25304211

  15. Prenatal Arsenic Exposure and the Epigenome: Identifying Sites of 5-methylcytosine Alterations that Predict Functional Changes in Gene Expression in Newborn Cord Blood and Subsequent Birth Outcomes

    PubMed Central

    Rojas, Daniel; Rager, Julia E.; Smeester, Lisa; Bailey, Kathryn A.; Drobná, Zuzana; Rubio-Andrade, Marisela; Stýblo, Miroslav; García-Vargas, Gonzalo; Fry, Rebecca C.

    2015-01-01

    Prenatal exposure to inorganic arsenic (iAs) is detrimental to the health of newborns and increases the risk of disease development later in life. Here we examined a subset of newborn cord blood leukocyte samples collected from subjects enrolled in the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort in Gómez Palacio, Mexico, who were exposed to a range of drinking water arsenic concentrations (0.456–236 µg/l). Changes in iAs-associated DNA 5-methylcytosine methylation were assessed across 424 935 CpG sites representing 18 761 genes and compared with corresponding mRNA expression levels and birth outcomes. In the context of arsenic exposure, a total of 2919 genes were identified with iAs-associated differences in DNA methylation. Site-specific analyses identified DNA methylation changes that were most predictive of gene expression levels where CpG methylation within CpG islands positioned within the first exon, the 5′ untranslated region and 200 bp upstream of the transcription start site yielded the most significant association with gene expression levels. A set of 16 genes was identified with correlated iAs-associated changes in DNA methylation and mRNA expression and all were highly enriched for binding sites of the early growth response (EGR) and CCCTC-binding factor (CTCF) transcription factors. Furthermore, DNA methylation levels of 7 of these genes were associated with differences in birth outcomes including gestational age and head circumference.These data highlight the complex interplay between DNA methylation, functional changes in gene expression and health outcomes and underscore the need for functional analyses coupled to epigenetic assessments. PMID:25304211

  16. 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.

  17. Prediction and inter-dependence of stock and change of soil quality, function and diversity at a national scale and implications for ecosystem services

    NASA Astrophysics Data System (ADS)

    Reynolds, B.; Emmett, B.; Spurgeon, D.; Rowe, E. C.; Mills, R.; Griffiths, R.; Jones, D.; Simfukwe, P.

    2011-12-01

    A soils monitoring programme which uses an ecosystem approach has been in place in Great Britain for 30 years.The findings from the latest survey in 2007 has been interpreted within a natural capital and ecosystem services context to assess the outcome of a range of policies to protect the natural environment and increase sustainability. Issues of interest included the impacts of declines in atmospheric deposition of acidity, nitrogen and metals, the benefits of agri-environment schemes and climate change on carbon storage in soils and soil biodiversity, and reduced fertiliser applications on eutrophication of soils and waters. Topsoil samples (0-15cm) were taken within 600 1km squares across the country stratified to cover all major habitat types. At the same time botanical surveys in permanent vegetation plots were recorded together with change in land use and management and stream and pond water quality and ecology. These data are used together with satellite images, digital cartography, and ancillary datasets to assess change in landcover for all of GB and upscaling of change data from the samples squares. Changes in topsoil were assessed in 1978, 1998 and again in 2007. An increase in pH but no change in soil carbon was observed between 1978 and 2007. Additional measures added in 1998 enabled a decline in Olsen-P,increase in C:N, decline in soil mesofauna diversity and decline in many metal concentrations to be identified over the last 10 years. In 2007, futher measurements were added to include carbon substrate utilisation, nitrogen mineralisation and bacterial diversity (fungi is in progress)enabling national maps to be created for the first time for these important soil parameters. Multi-variate statistics were used to explore the relationship between the different soil measures, the predictive capability of soil and vegetation type, and drivers of change to be identified. In addition, assigning measurements to specific functions which underpinned

  18. Myeloperoxidase levels predict executive function.

    PubMed

    Haslacher, H; Perkmann, T; Lukas, I; Barth, A; Ponocny-Seliger, E; Michlmayr, M; Scheichenberger, V; Wagner, O; Winker, R

    2012-12-01

    The main purpose of the study was to investigate whether baseline myeloperoxidase (MPO) levels are associated with executive cognitive function in individuals with high physical activity. Baseline serum MPO levels of 56 elderly marathon runners and 58 controls were assessed by ELISA. Standardized tests were applied to survey domain-specific cognitive functions. Changes in brain morphology were visualized by magnetic resonance imaging (MRI). High baseline serum MPO levels correlated with worse outcome in tests assessing executive cognitive function in athletes but not in the control group (NAI maze test p<0.05, Trail Making Test ratio p<0.01). In control participants, subcortical white matter hyperintensities were associated with higher scores on the Geriatric Depression Scale (p<0.05), whereas athletes seem to be protected from this effect. During strenuous exercising, MPO as well as its educts may be elevated due to increased oxygen intake and excretion of pro-inflammatory mediators inducing host tissue damage via oxidative stress. This outweighs the potential benefits of physical activity on cognitive function.

  19. Myeloperoxidase levels predict executive function.

    PubMed

    Haslacher, H; Perkmann, T; Lukas, I; Barth, A; Ponocny-Seliger, E; Michlmayr, M; Scheichenberger, V; Wagner, O; Winker, R

    2012-12-01

    The main purpose of the study was to investigate whether baseline myeloperoxidase (MPO) levels are associated with executive cognitive function in individuals with high physical activity. Baseline serum MPO levels of 56 elderly marathon runners and 58 controls were assessed by ELISA. Standardized tests were applied to survey domain-specific cognitive functions. Changes in brain morphology were visualized by magnetic resonance imaging (MRI). High baseline serum MPO levels correlated with worse outcome in tests assessing executive cognitive function in athletes but not in the control group (NAI maze test p<0.05, Trail Making Test ratio p<0.01). In control participants, subcortical white matter hyperintensities were associated with higher scores on the Geriatric Depression Scale (p<0.05), whereas athletes seem to be protected from this effect. During strenuous exercising, MPO as well as its educts may be elevated due to increased oxygen intake and excretion of pro-inflammatory mediators inducing host tissue damage via oxidative stress. This outweighs the potential benefits of physical activity on cognitive function. PMID:22855218

  20. Predicting protein functions from PPI networks using functional aggregation.

    PubMed

    Hou, Jingyu; Chi, Xiaoxiao

    2012-11-01

    Predicting protein functions computationally from massive protein-protein interaction (PPI) data generated by high-throughput technology is one of the challenges and fundamental problems in the post-genomic era. Although there have been many approaches developed for computationally predicting protein functions, the mutual correlations among proteins in terms of protein functions have not been thoroughly investigated and incorporated into existing prediction methods, especially in voting based prediction methods. In this paper, we propose an innovative method to predict protein functions from PPI data by aggregating the functional correlations among relevant proteins using the Choquet-Integral in fuzzy theory. This functional aggregation measures the real impact of each relevant protein function on the final prediction results, and reduces the impact of repeated functional information on the prediction. Accordingly, a new protein similarity and a new iterative prediction algorithm are proposed in this paper. The experimental evaluations on real PPI datasets demonstrate the effectiveness of our method.

  1. Scoring function to predict solubility mutagenesis

    PubMed Central

    2010-01-01

    Background Mutagenesis is commonly used to engineer proteins with desirable properties not present in the wild type (WT) protein, such as increased or decreased stability, reactivity, or solubility. Experimentalists often have to choose a small subset of mutations from a large number of candidates to obtain the desired change, and computational techniques are invaluable to make the choices. While several such methods have been proposed to predict stability and reactivity mutagenesis, solubility has not received much attention. Results We use concepts from computational geometry to define a three body scoring function that predicts the change in protein solubility due to mutations. The scoring function captures both sequence and structure information. By exploring the literature, we have assembled a substantial database of 137 single- and multiple-point solubility mutations. Our database is the largest such collection with structural information known so far. We optimize the scoring function using linear programming (LP) methods to derive its weights based on training. Starting with default values of 1, we find weights in the range [0,2] so that predictions of increase or decrease in solubility are optimized. We compare the LP method to the standard machine learning techniques of support vector machines (SVM) and the Lasso. Using statistics for leave-one-out (LOO), 10-fold, and 3-fold cross validations (CV) for training and prediction, we demonstrate that the LP method performs the best overall. For the LOOCV, the LP method has an overall accuracy of 81%. Availability Executables of programs, tables of weights, and datasets of mutants are available from the following web page: http://www.wsu.edu/~kbala/OptSolMut.html. PMID:20929563

  2. Predicting Persuasion-Induced Behavior Change from the Brain

    PubMed Central

    Falk, Emily B.; Berkman, Elliot T.; Mann, Traci; Harrison, Brittany; Lieberman, Matthew D.

    2011-01-01

    Although persuasive messages often alter people’s self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p < 0.05). Additionally, an iterative cross-validation approach using activity in this MPFC ROI predicted an average 23% of the variance in behavior change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance. PMID:20573889

  3. 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. ...

  4. Protein Function Prediction: Problems and Pitfalls.

    PubMed

    Pearson, William R

    2015-01-01

    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. PMID:26334923

  5. Protein Function Prediction: Problems and Pitfalls.

    PubMed

    Pearson, William R

    2015-01-01

    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.

  6. 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…

  7. 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. PMID:26868584

  8. Integrating multiple networks for protein function prediction

    PubMed Central

    2015-01-01

    Background High throughput techniques produce multiple functional association networks. Integrating these networks can enhance the accuracy of protein function prediction. Many algorithms have been introduced to generate a composite network, which is obtained as a weighted sum of individual networks. The weight assigned to an individual network reflects its benefit towards the protein functional annotation inference. A classifier is then trained on the composite network for predicting protein functions. However, since these techniques model the optimization of the composite network and the prediction tasks as separate objectives, the resulting composite network is not necessarily optimal for the follow-up protein function prediction. Results We address this issue by modeling the optimization of the composite network and the prediction problems within a unified objective function. In particular, we use a kernel target alignment technique and the loss function of a network based classifier to jointly adjust the weights assigned to the individual networks. We show that the proposed method, called MNet, can achieve a performance that is superior (with respect to different evaluation criteria) to related techniques using the multiple networks of four example species (yeast, human, mouse, and fly) annotated with thousands (or hundreds) of GO terms. Conclusion MNet can effectively integrate multiple networks for protein function prediction and is robust to the input parameters. Supplementary data is available at https://sites.google.com/site/guoxian85/home/mnet. The Matlab code of MNet is available upon request. PMID:25707434

  9. 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

  10. Greater Sedentary Hours and Slower Walking Speed Outside the Home Predict Faster Declines in Functioning and Adverse Calf Muscle Changes in Peripheral Arterial Disease

    PubMed Central

    McDermott, Mary M.; Liu, Kiang; Ferrucci, Luigi; Tian, Lu; Guralnik, Jack M.; Liao, Yihua; Criqui, Michael H.

    2016-01-01

    Objectives In participants with peripheral arterial disease (PAD), we determined whether more sedentary behavior and slower outdoor walking speed were associated with faster functional decline and more adverse changes in calf muscle characteristics over time. Background Modifiable behaviors associated with faster functional decline in lower-extremity PAD are understudied. Methods Participants were 384 men and women with an ankle brachial index <0.90 followed for a median of 47 months. At baseline, participants reported the number of hours they spent sitting per day and their walking speeds outside their homes. Participants underwent baseline and annual measures of objective functional performance. Calf muscle characteristics were measured with computed tomography at baseline and every 2 years subsequently. Analyses were adjusted for age, sex, race, comorbidities, ankle brachial index, and other confounders. Results Slower walking speed outside the home was associated with faster annual decline in calf muscle density (brisk/ striding pace −0.32 g/cm3, average pace −0.46 g/cm3, casual strolling −1.03 g/cm3, no walking at all −1.43 g/cm3, p trend <0.001). Greater hours sitting per day were associated with faster decline in 6-min walk (<4 h: −35.8 feet/year; 4 to <7 h: −41.1 feet/year; 8 to <11 h: −68.7 feet; ≥12 h: −78.0 feet; p trend = 0.008). Similar associations were observed for greater hours sitting per day and faster declines in fast-paced (p trend = 0.018) and usual-paced (p trend < 0.001) 4-m walking velocity. Conclusions Greater sedentary hours per day and slower outdoor walking speed are modifiable behaviors that are associated with faster functional decline and greater decline in calf muscle density, respectively, in patients with PAD. PMID:21636037

  11. Biological cluster evaluation for gene function prediction.

    PubMed

    Klie, Sebastian; Nikoloski, Zoran; Selbig, Joachim

    2014-06-01

    Recent advances in high-throughput omics techniques render it possible to decode the function of genes by using the "guilt-by-association" principle on biologically meaningful clusters of gene expression data. However, the existing frameworks for biological evaluation of gene clusters are hindered by two bottleneck issues: (1) the choice for the number of clusters, and (2) the external measures which do not take in consideration the structure of the analyzed data and the ontology of the existing biological knowledge. Here, we address the identified bottlenecks by developing a novel framework that allows not only for biological evaluation of gene expression clusters based on existing structured knowledge, but also for prediction of putative gene functions. The proposed framework facilitates propagation of statistical significance at each of the following steps: (1) estimating the number of clusters, (2) evaluating the clusters in terms of novel external structural measures, (3) selecting an optimal clustering algorithm, and (4) predicting gene functions. The framework also includes a method for evaluation of gene clusters based on the structure of the employed ontology. Moreover, our method for obtaining a probabilistic range for the number of clusters is demonstrated valid on synthetic data and available gene expression profiles from Saccharomyces cerevisiae. Finally, we propose a network-based approach for gene function prediction which relies on the clustering of optimal score and the employed ontology. Our approach effectively predicts gene function on the Saccharomyces cerevisiae data set and is also employed to obtain putative gene functions for an Arabidopsis thaliana data set.

  12. 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.

  13. Quantitative assessment of protein function prediction programs.

    PubMed

    Rodrigues, B N; Steffens, M B R; Raittz, R T; Santos-Weiss, I C R; Marchaukoski, J N

    2015-12-21

    Fast prediction of protein function is essential for high-throughput sequencing analysis. Bioinformatic resources provide cheaper and faster techniques for function prediction and have helped to accelerate the process of protein sequence characterization. In this study, we assessed protein function prediction programs that accept amino acid sequences as input. We analyzed the classification, equality, and similarity between programs, and, additionally, compared program performance. The following programs were selected for our assessment: Blast2GO, InterProScan, PANTHER, Pfam, and ScanProsite. This selection was based on the high number of citations (over 500), fully automatic analysis, and the possibility of returning a single best classification per sequence. We tested these programs using 12 gold standard datasets from four different sources. The gold standard classification of the databases was based on expert analysis, the Protein Data Bank, or the Structure-Function Linkage Database. We found that the miss rate among the programs is globally over 50%. Furthermore, we observed little overlap in the correct predictions from each program. Therefore, a combination of multiple types of sources and methods, including experimental data, protein-protein interaction, and data mining, may be the best way to generate more reliable predictions and decrease the miss rate.

  14. Quantitative assessment of protein function prediction programs.

    PubMed

    Rodrigues, B N; Steffens, M B R; Raittz, R T; Santos-Weiss, I C R; Marchaukoski, J N

    2015-01-01

    Fast prediction of protein function is essential for high-throughput sequencing analysis. Bioinformatic resources provide cheaper and faster techniques for function prediction and have helped to accelerate the process of protein sequence characterization. In this study, we assessed protein function prediction programs that accept amino acid sequences as input. We analyzed the classification, equality, and similarity between programs, and, additionally, compared program performance. The following programs were selected for our assessment: Blast2GO, InterProScan, PANTHER, Pfam, and ScanProsite. This selection was based on the high number of citations (over 500), fully automatic analysis, and the possibility of returning a single best classification per sequence. We tested these programs using 12 gold standard datasets from four different sources. The gold standard classification of the databases was based on expert analysis, the Protein Data Bank, or the Structure-Function Linkage Database. We found that the miss rate among the programs is globally over 50%. Furthermore, we observed little overlap in the correct predictions from each program. Therefore, a combination of multiple types of sources and methods, including experimental data, protein-protein interaction, and data mining, may be the best way to generate more reliable predictions and decrease the miss rate. PMID:26782400

  15. Stock price change rate prediction by utilizing social network activities.

    PubMed

    Deng, Shangkun; 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.

  16. 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

  17. Stock price change rate prediction by utilizing social network activities.

    PubMed

    Deng, Shangkun; 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

  18. Enzyme function prediction with interpretable models.

    PubMed

    Syed, Umar; Yona, Golan

    2009-01-01

    Enzymes play central roles in metabolic pathways, and the prediction of metabolic pathways in newly sequenced genomes usually starts with the assignment of genes to enzymatic reactions. However, genes with similar catalytic activity are not necessarily similar in sequence, and therefore the traditional sequence similarity-based approach often fails to identify the relevant enzymes, thus hindering efforts to map the metabolome of an organism.Here we study the direct relationship between basic protein properties and their function. Our goal is to develop a new tool for functional prediction (e.g., prediction of Enzyme Commission number), which can be used to complement and support other techniques based on sequence or structure information. In order to define this mapping we collected a set of 453 features and properties that characterize proteins and are believed to be related to structural and functional aspects of proteins. We introduce a mixture model of stochastic decision trees to learn the set of potentially complex relationships between features and function. To study these correlations, trees are created and tested on the Pfam classification of proteins, which is based on sequence, and the EC classification, which is based on enzymatic function. The model is very effective in learning highly diverged protein families or families that are not defined on the basis of sequence. The resulting tree structures highlight the properties that are strongly correlated with structural and functional aspects of protein families, and can be used to suggest a concise definition of a protein family.

  19. 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. PMID:26869536

  20. Predicting Protein Function Using Multiple Kernels.

    PubMed

    Yu, Guoxian; Rangwala, Huzefa; Domeniconi, Carlotta; Zhang, Guoji; Zhang, Zili

    2015-01-01

    High-throughput experimental techniques provide a wide variety of heterogeneous proteomic data sources. To exploit the information spread across multiple sources for protein function prediction, these data sources are transformed into kernels and then integrated into a composite kernel. Several methods first optimize the weights on these kernels to produce a composite kernel, and then train a classifier on the composite kernel. As such, these approaches result in an optimal composite kernel, but not necessarily in an optimal classifier. On the other hand, some approaches optimize the loss of binary classifiers and learn weights for the different kernels iteratively. For multi-class or multi-label data, these methods have to solve the problem of optimizing weights on these kernels for each of the labels, which are computationally expensive and ignore the correlation among labels. In this paper, we propose a method called Predicting Protein Function using Multiple Kernels (ProMK). ProMK iteratively optimizes the phases of learning optimal weights and reduces the empirical loss of multi-label classifier for each of the labels simultaneously. ProMK can integrate kernels selectively and downgrade the weights on noisy kernels. We investigate the performance of ProMK on several publicly available protein function prediction benchmarks and synthetic datasets. We show that the proposed approach performs better than previously proposed protein function prediction approaches that integrate multiple data sources and multi-label multiple kernel learning methods. The codes of our proposed method are available at https://sites.google.com/site/guoxian85/promk.

  1. Parental Education Predicts Corticostriatal Functionality in Adulthood

    PubMed Central

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

    2011-01-01

    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. PMID:20810623

  2. A Prospective Longitudinal Study of Shyness from Infancy to Adolescence: Stability, Age-Related Changes, and Prediction of Socio-Emotional Functioning

    ERIC Educational Resources Information Center

    Karevold, Evalill; Ystrom, Eivind; Coplan, Robert J.; Sanson, Ann V.; Mathiesen, Kristin S.

    2012-01-01

    This longitudinal, population-based and prospective study investigated the stability, age-related changes, and socio-emotional outcomes of shyness from infancy to early adolescence. A sample of 921 children was followed from ages 1.5 to 12.5 years. Parent-reported shyness was assessed at five time points and maternal- and self-reported social…

  3. Consistent probabilistic outputs for protein function prediction

    PubMed Central

    Obozinski, Guillaume; Lanckriet, Gert; Grant, Charles; Jordan, Michael I; Noble, William Stafford

    2008-01-01

    In predicting hierarchical protein function annotations, such as terms in the Gene Ontology (GO), the simplest approach makes predictions for each term independently. However, this approach has the unfortunate consequence that the predictor may assign to a single protein a set of terms that are inconsistent with one another; for example, the predictor may assign a specific GO term to a given protein ('purine nucleotide binding') but not assign the parent term ('nucleotide binding'). Such predictions are difficult to interpret. In this work, we focus on methods for calibrating and combining independent predictions to obtain a set of probabilistic predictions that are consistent with the topology of the ontology. We call this procedure 'reconciliation'. We begin with a baseline method for predicting GO terms from a collection of data types using an ensemble of discriminative classifiers. We apply the method to a previously described benchmark data set, and we demonstrate that the resulting predictions are frequently inconsistent with the topology of the GO. We then consider 11 distinct reconciliation methods: three heuristic methods; four variants of a Bayesian network; an extension of logistic regression to the structured case; and three novel projection methods - isotonic regression and two variants of a Kullback-Leibler projection method. We evaluate each method in three different modes - per term, per protein and joint - corresponding to three types of prediction tasks. Although the principal goal of reconciliation is interpretability, it is important to assess whether interpretability comes at a cost in terms of precision and recall. Indeed, we find that many apparently reasonable reconciliation methods yield reconciled probabilities with significantly lower precision than the original, unreconciled estimates. On the other hand, we find that isotonic regression usually performs better than the underlying, unreconciled method, and almost never performs worse

  4. 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.

  5. Advection and diffusion in shoreline change prediction

    NASA Astrophysics Data System (ADS)

    Anderson, T. R.; Frazer, L. N.

    2010-12-01

    We added longshore advection and diffusion to the simple cross-shore rate calculation method, as used widely by the USGS and others, to model historic shorelines and to predict future shoreline positions; and applied this to Hawaiian Island beach data. Aerial photographs, sporadically taken throughout the past century, yield usable, albeit limited, historic shoreline data. These photographs provide excellent spatial coverage, but poor temporal resolution, of the shoreline. Due to the sparse historic shoreline data, and the many natural and anthropogenic events influencing coastlines, we constructed a simplistic shoreline change model that can identify long-term behavior of a beach. Our new, two-dimensional model combines the simple rate method to accommodate for cross-shore sediment transport with the classic Pelnard-Considère model for diffusion, as well as a longshore advection speed term. Inverse methods identify cross-shore rate, longshore advection speed, and longshore diffusivity down a sandy coastline. A spatial averaging technique then identifies shoreline segments where one parameter can reasonably account for the cross-shore and longshore transport rates in that area. This produces model results with spatial resolution more appropriate to the temporal spacing of the data. Because changes in historic data can be accounted for by varying degrees of cross-shore and longshore sediment transport - for example, beach erosion can equally be explained by sand moving either off-shore or laterally - we tested several different model scenarios on the data: allowing only cross-shore sediment movement, only longshore movement, and a combination of the two. We used statistical information criteria to determine both the optimal spatial resolution and best-fitting scenario. Finally, we employed a voting method predicting the relaxed shoreline position over time.

  6. Functional structure of biological communities predicts ecosystem multifunctionality.

    PubMed

    Mouillot, David; Villéger, Sébastien; Scherer-Lorenzen, Michael; Mason, Norman W H

    2011-01-01

    The accelerating rate of change in biodiversity patterns, mediated by ever increasing human pressures and global warming, demands a better understanding of the relationship between the structure of biological communities and ecosystem functioning (BEF). Recent investigations suggest that the functional structure of communities, i.e. the composition and diversity of functional traits, is the main driver of ecological processes. However, the predictive power of BEF research is still low, the integration of all components of functional community structure as predictors is still lacking, and the multifunctionality of ecosystems (i.e. rates of multiple processes) must be considered. Here, using a multiple-processes framework from grassland biodiversity experiments, we show that functional identity of species and functional divergence among species, rather than species diversity per se, together promote the level of ecosystem multifunctionality with a predictive power of 80%. Our results suggest that primary productivity and decomposition rates, two key ecosystem processes upon which the global carbon cycle depends, are primarily sustained by specialist species, i.e. those that hold specialized combinations of traits and perform particular functions. Contrary to studies focusing on single ecosystem functions and considering species richness as the sole measure of biodiversity, we found a linear and non-saturating effect of the functional structure of communities on ecosystem multifunctionality. Thus, sustaining multiple ecological processes would require focusing on trait dominance and on the degree of community specialization, even in species-rich assemblages.

  7. Sequence-only evolutionary and predicted structural features for the prediction of stability changes in protein mutants

    PubMed Central

    2013-01-01

    Background Even a single amino acid substitution in a protein sequence may result in significant changes in protein stability, structure, and therefore in protein function as well. In the post-genomic era, computational methods for predicting stability changes from only the sequence of a protein are of importance. While evolutionary relationships of protein mutations can be extracted from large protein databases holding millions of protein sequences, relevant evolutionary features for the prediction of stability changes have not been proposed. Also, the use of predicted structural features in situations when a protein structure is not available has not been explored. Results We proposed a number of evolutionary and predicted structural features for the prediction of stability changes and analysed which of them capture the determinants of protein stability the best. We trained and evaluated our machine learning method on a non-redundant data set of experimentally measured stability changes. When only the direction of the stability change was predicted, we found that the best performance improvement can be achieved by the combination of the evolutionary features mutation likelihood and SIFTscore in conjunction with the predicted structural feature secondary structure. The same two evolutionary features in the combination with the predicted structural feature accessible surface area achieved the lowest error when the prediction of actual values of stability changes was assessed. Compared to similar studies, our method achieved improvements in prediction performance. Conclusion Although the strongest feature for the prediction of stability changes appears to be the vector of amino acid identities in the sequential neighbourhood of the mutation, the most relevant combination of evolutionary and predicted structural features further improves prediction performance. Even the predicted structural features, which did not perform well on their own, turn out to be beneficial

  8. Predicting folding free energy changes upon single point mutations

    PubMed Central

    Zhang, Zhe; Wang, Lin; Gao, Yang; Zhang, Jie; Zhenirovskyy, Maxim; Alexov, Emil

    2012-01-01

    Motivation: The folding free energy is an important characteristic of proteins stability and is directly related to protein's wild-type function. The changes of protein's stability due to naturally occurring mutations, missense mutations, are typically causing diseases. Single point mutations made in vitro are frequently used to assess the contribution of given amino acid to the stability of the protein. In both cases, it is desirable to predict the change of the folding free energy upon single point mutations in order to either provide insights of the molecular mechanism of the change or to design new experimental studies. Results: We report an approach that predicts the free energy change upon single point mutation by utilizing the 3D structure of the wild-type protein. It is based on variation of the molecular mechanics Generalized Born (MMGB) method, scaled with optimized parameters (sMMGB) and utilizing specific model of unfolded state. The corresponding mutations are built in silico and the predictions are tested against large dataset of 1109 mutations with experimentally measured changes of the folding free energy. Benchmarking resulted in root mean square deviation = 1.78 kcal/mol and slope of the linear regression fit between the experimental data and the calculations was 1.04. The sMMGB is compared with other leading methods of predicting folding free energy changes upon single mutations and results discussed with respect to various parameters. Availability: All the pdb files we used in this article can be downloaded from http://compbio.clemson.edu/downloadDir/mentaldisorders/sMMGB_pdb.rar Contact: ealexov@clemson.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22238268

  9. The predictability of molecular evolution during functional innovation.

    PubMed

    Blank, Diana; Wolf, Luise; Ackermann, Martin; Silander, Olin K

    2014-02-25

    Determining the molecular changes that give rise to functional innovations is a major unresolved problem in biology. The paucity of examples has served as a significant hindrance in furthering our understanding of this process. Here we used experimental evolution with the bacterium Escherichia coli to quantify the molecular changes underlying functional innovation in 68 independent instances ranging over 22 different metabolic functions. Using whole-genome sequencing, we show that the relative contribution of regulatory and structural mutations depends on the cellular context of the metabolic function. In addition, we find that regulatory mutations affect genes that act in pathways relevant to the novel function, whereas structural mutations affect genes that act in unrelated pathways. Finally, we use population genetic modeling to show that the relative contributions of regulatory and structural mutations during functional innovation may be affected by population size. These results provide a predictive framework for the molecular basis of evolutionary innovation, which is essential for anticipating future evolutionary trajectories in the face of rapid environmental change.

  10. Spinal meningiomas: clinicoradiological factors predicting recurrence and functional outcome.

    PubMed

    Maiti, Tanmoy K; Bir, Shyamal C; Patra, Devi Prasad; Kalakoti, Piyush; Guthikonda, Bharat; Nanda, Anil

    2016-08-01

    OBJECTIVE Spinal meningiomas are benign tumors with a wide spectrum of clinical and radiological features at presentation. The authors analyzed multiple clinicoradiological factors to predict recurrence and functional outcome in a cohort with a mean follow-up of more than 4 years. The authors also discuss the results of clinical studies regarding spinal meningiomas in the last 15 years. METHODS The authors retrospectively reviewed the clinical and radiological details of patients who underwent surgery for spinal tumors between 2001 and 2015 that were histopathologically confirmed as meningiomas. Demographic parameters, such as age, sex, race, and association with neurofibromatosis Type 2, were considered. Radiological parameters, such as tumor size, signal changes of spinal cord, spinal level, number of levels, location of tumor attachment, shape of tumor, and presence of dural tail/calcification, were noted. These factors were analyzed to predict recurrence and functional outcome. Furthermore, a pooled analysis was performed from 13 reports of spinal meningiomas in the last 15 years. RESULTS A total of 38 patients were included in this study. Male sex and tumors with radiological evidence of a dural tail were associated with an increased risk of recurrence at a mean follow-up of 51.2 months. Ventral or ventrolateral location, large tumors, T2 cord signal changes, and poor preoperative functional status were associated with poor functional outcome at 1-year follow-up. CONCLUSIONS Spine surgeons must be aware of the natural history and risk factors of spinal meningiomas to establish a prognosis for their patients.

  11. 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;…

  12. Developmental Changes in Executive Functioning

    ERIC Educational Resources Information Center

    Lee, Kerry; Bull, Rebecca; Ho, Ringo M. H.

    2013-01-01

    Although early studies of executive functioning in children supported Miyake et al.'s (2000) three-factor model, more recent findings supported a variety of undifferentiated or two-factor structures. Using a cohort-sequential design, this study examined whether there were age-related differences in the structure of executive functioning among…

  13. Linking changes in community composition and function under climate change.

    PubMed

    Mokany, Karel; Thomson, Joshua J; Lynch, Jasmyn J; Jordan, Gregory J; Ferrier, Simon

    2015-12-01

    Climate change is expected to directly alter the composition of communities and the functioning of ecosystems across the globe. Improving our understanding of links between biodiversity and ecosystem functioning across large spatial scales and rapid global change is a major priority to help identify management responses that will retain diverse, functioning systems. Here we address this challenge by linking projected changes in plant community composition and functional attributes (height, leaf area, seed mass) under climate change across Tasmania, Australia. Using correlative community-level modeling, we found that projected changes in plant community composition were not consistently related to projected changes in community mean trait values. In contrast, we identified specific mechanisms through which alternative combinations of projected functional and compositional change across Tasmania could be realized, including loss/replacement of functionally similar species (lowland grasslands/grassy woodlands) and loss of a small number of functionally unique species (lowland forests). Importantly, we demonstrate how these linked projections of change in community composition and functional attributes can be utilized to inform specific management actions that may assist in maintaining diverse, functioning ecosystems under climate change.

  14. 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

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

    PubMed

    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

  16. 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.

  17. Predicting functional decline in behavioural variant frontotemporal dementia.

    PubMed

    Josephs, Keith A; Whitwell, Jennifer L; Weigand, Stephen D; Senjem, Matthew L; Boeve, Bradley F; Knopman, David S; Smith, Glenn E; Ivnik, Robert J; Jack, Clifford R; Petersen, Ronald C

    2011-02-01

    Behavioural variant frontotemporal dementia is characterized by a change in comportment. It is associated with considerable functional decline over the course of the illness albeit with sometimes dramatic variability among patients. It is unknown whether any baseline features, or combination of features, could predict rate of functional decline in behavioural variant frontotemporal dementia. The aim of this study was to investigate the effects of different baseline clinical, neuropsychological, neuropsychiatric, genetic and anatomic predictors on the rate of functional decline as measured by the Clinical Dementia Rating Sum of Boxes scale. We identified 86 subjects with behavioural variant frontotemporal dementia that had multiple serial Clinical Dementia Rating Sum of Boxes assessments (mean 4, range 2-18). Atlas-based parcellation was used to generate volumes for specific regions of interest at baseline. Volumes were utilized to classify subjects into different anatomical subtypes using the advanced statistical technique of cluster analysis and were assessed as predictor variables. Composite scores were generated for the neuropsychological domains of executive, language, memory and visuospatial function. Behaviours from the brief questionnaire form of the Neuropsychiatric Inventory were assessed. Linear mixed-effects regression modelling was used to determine which baseline features predict rate of future functional decline. Rates of functional decline differed across the anatomical subtypes of behavioural variant frontotemporal dementia, with faster rates observed in the frontal dominant and frontotemporal subtypes. In addition, subjects with poorer performance on neuropsychological tests of executive, language and visuospatial function, less disinhibition, agitation/aggression and night-time behaviours at presentation, and smaller medial, lateral and orbital frontal lobe volumes showed faster rates of decline. In many instances, the effect of the predictor

  18. 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

  19. Prediction uncertainty of environmental change effects on temperate European biodiversity.

    PubMed

    Dormann, Carsten F; Schweiger, Oliver; Arens, P; Augenstein, I; Aviron, St; Bailey, Debra; Baudry, J; Billeter, R; Bugter, R; Bukácek, R; Burel, F; Cerny, M; Cock, Raphaël De; De Blust, Geert; DeFilippi, R; Diekötter, Tim; Dirksen, J; Durka, W; Edwards, P J; Frenzel, M; Hamersky, R; Hendrickx, Frederik; Herzog, F; Klotz, St; Koolstra, B; Lausch, A; Le Coeur, D; Liira, J; Maelfait, J P; Opdam, P; Roubalova, M; Schermann-Legionnet, Agnes; Schermann, N; Schmidt, T; Smulders, M J M; Speelmans, M; Simova, P; Verboom, J; van Wingerden, Walter; Zobel, M

    2008-03-01

    Observed patterns of species richness at landscape scale (gamma diversity) cannot always be attributed to a specific set of explanatory variables, but rather different alternative explanatory statistical models of similar quality may exist. Therefore predictions of the effects of environmental change (such as in climate or land cover) on biodiversity may differ considerably, depending on the chosen set of explanatory variables. Here we use multimodel prediction to evaluate effects of climate, land-use intensity and landscape structure on species richness in each of seven groups of organisms (plants, birds, spiders, wild bees, ground beetles, true bugs and hoverflies) in temperate Europe. We contrast this approach with traditional best-model predictions, which we show, using cross-validation, to have inferior prediction accuracy. Multimodel inference changed the importance of some environmental variables in comparison with the best model, and accordingly gave deviating predictions for environmental change effects. Overall, prediction uncertainty for the multimodel approach was only slightly higher than that of the best model, and absolute changes in predicted species richness were also comparable. Richness predictions varied generally more for the impact of climate change than for land-use change at the coarse scale of our study. Overall, our study indicates that the uncertainty introduced to environmental change predictions through uncertainty in model selection both qualitatively and quantitatively affects species richness projections. PMID:18070098

  20. Ongoing dynamics in large-scale functional connectivity predict perception

    PubMed Central

    Sadaghiani, Sepideh; Poline, Jean-Baptiste; Kleinschmidt, Andreas; D’Esposito, Mark

    2015-01-01

    Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22–40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency. PMID:26106164

  1. Ongoing dynamics in large-scale functional connectivity predict perception.

    PubMed

    Sadaghiani, Sepideh; Poline, Jean-Baptiste; Kleinschmidt, Andreas; D'Esposito, Mark

    2015-07-01

    Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22-40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency. PMID:26106164

  2. Ongoing dynamics in large-scale functional connectivity predict perception.

    PubMed

    Sadaghiani, Sepideh; Poline, Jean-Baptiste; Kleinschmidt, Andreas; D'Esposito, Mark

    2015-07-01

    Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22-40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency.

  3. 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.

  4. 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. PMID:27151536

  5. Template-based prediction of protein function.

    PubMed

    Petrey, Donald; Chen, T Scott; Deng, Lei; Garzon, Jose Ignacio; Hwang, Howook; Lasso, Gorka; Lee, Hunjoong; Silkov, Antonina; Honig, Barry

    2015-06-01

    We discuss recent approaches for structure-based protein function annotation. We focus on template-based methods where the function of a query protein is deduced from that of a template for which both the structure and function are known. We describe the different ways of identifying a template. These are typically based on sequence analysis but new methods based on purely structural similarity are also being developed that allow function annotation based on structural relationships that cannot be recognized by sequence. The growing number of available structures of known function, improved homology modeling techniques and new developments in the use of structure allow template-based methods to be applied on a proteome-wide scale and in many different biological contexts. This progress significantly expands the range of applicability of structural information in function annotation to a level that previously was only achievable by sequence comparison.

  6. 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.

  7. 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…

  8. 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,…

  9. Past paleoclimatic changes, origin and prediction

    NASA Astrophysics Data System (ADS)

    Mörner, N.-A.; Nevanlinna, H.; Shumilov, O.

    2003-04-01

    In north-western to western Europe, short periods of cold climate are recorded in the decades of 1440-1460, 1687-1703 and 1808-1821. This fits reasonably well with periods of sunspot minima; viz. the Spörer (1420-1500), Maunder (1645-1705) and Dalton (1800-1820) Minima, and a causal connection has been advocated. During these minima, Earth’s rotation experienced a speeding-up leading to a changed ocean circulation pulling down cold Arctic water along the European coasts and concentrating the hot Gulf Stream to the south European region (Mörner, 1995). Via the recording of past changes in aurora frequency and the relation between sunspot activity and aurora frequency, the sunspot activity can be approximated for 1500-2000 years. Even for this period, there seems to be a reasonable correlation between sunspot activity and recorded changes in climate. The combined Schwabe-Gleisberg sunspot cycles provide good correlation with observed changes in climate for the last 300-400 years (Shumilov). The phase of the sunspot cycles and global climate for the period 1860 to 1985 fit exceptionally well (Friis-Christensen &Lassen, 1991). The aa-index and climate fit well for the last 150 years all the way up to 1985 (Pulkkinen et al., 2001). If we extrapolate the combined Schwabe-Gleisberg cycles or the aa-index curve, a new period of cold climate is to be expected in AD 2050-2100. This fact has not yet been included in the IPCC scenarios on future changes in climate, and is quite contrary to their main conclusions.

  10. Prediction of functional phosphorylation sites by incorporating evolutionary information.

    PubMed

    Niu, Shen; Wang, Zhen; Ge, Dongya; Zhang, Guoqing; Li, Yixue

    2012-09-01

    Protein phosphorylation is a ubiquitous protein post-translational modification, which plays an important role in cellular signaling systems underlying various physiological and pathological processes. Current in silico methods mainly focused on the prediction of phosphorylation sites, but rare methods considered whether a phosphorylation site is functional or not. Since functional phosphorylation sites are more valuable for further experimental research and a proportion of phosphorylation sites have no direct functional effects, the prediction of functional phosphorylation sites is quite necessary for this research area. Previous studies have shown that functional phosphorylation sites are more conserved than non-functional phosphorylation sites in evolution. Thus, in our method, we developed a web server by integrating existing phosphorylation site prediction methods, as well as both absolute and relative evolutionary conservation scores to predict the most likely functional phosphorylation sites. Using our method, we predicted the most likely functional sites of the human, rat and mouse proteomes and built a database for the predicted sites. By the analysis of overall prediction results, we demonstrated that protein phosphorylation plays an important role in all the enriched KEGG pathways. By the analysis of protein-specific prediction results, we demonstrated the usefulness of our method for individual protein studies. Our method would help to characterize the most likely functional phosphorylation sites for further studies in this research area.

  11. Predicting toxicity through computers: a changing world

    PubMed Central

    Benfenati, Emilio

    2007-01-01

    The computational approaches used to predict toxicity are evolving rapidly, a process hastened on by the emergence of new ways of describing chemical information. Although this trend offers many opportunities, new regulations, such as the European Community's 'Registration, Evaluation, Authorisation and Restriction of Chemicals' (REACH), demand that models be ever more robust. In this commentary, we outline the numerous factors involved in the evolution of quantitative structure-regulatory activity relationship (QSAR) models. Such models not only require powerful tools, but must also be adapted for their intended application, such as in using suitable input values and having an output that complies with legal requirements. In addition, transparency and model reproducibility are important factors. As more models become available, it is vital that new theoretical possibilities are embraced, and efforts are combined in order to promote new flexible, modular tools. PMID:18088418

  12. 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

  13. Commitment to Change Statements Can Predict Actual Change in Practice

    ERIC Educational Resources Information Center

    Wakefield, Jacqueline; Herbert, Carol P.; Maclure, Malcolm; Dormuth, Colin; Wright, James M.; Legare, Jeanne; Brett-MacLean, Pamela; Premi, John

    2003-01-01

    Introduction: Statements of commitment to change are advocated both to promote and to assess continuing education interventions. However, most studies of commitment to change have used self-reported outcomes, and self-reports may significantly overestimate actual performance. As part of an educational randomized controlled trial, this study…

  14. Confronting species distribution model predictions with species functional traits.

    PubMed

    Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

    2016-02-01

    Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

  15. 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. PMID:20453049

  16. MASS FUNCTION PREDICTIONS BEYOND {Lambda}CDM

    SciTech Connect

    Bhattacharya, Suman; Lukic, Zarija; Habib, Salman; Heitmann, Katrin; White, Martin; Wagner, Christian

    2011-05-10

    The statistics of dark matter halos is an essential component of precision cosmology. The mass distribution of halos, as specified by the halo mass function, is a key input for several cosmological probes. The sizes of N-body simulations are now such that, for the most part, results need no longer be statistics-limited, but are still subject to various systematic uncertainties. Discrepancies in the results of simulation campaigns for the halo mass function remain in excess of statistical uncertainties and of roughly the same size as the error limits set by near-future observations; we investigate and discuss some of the reasons for these differences. Quantifying error sources and compensating for them as appropriate, we carry out a high-statistics study of dark matter halos from 67 N-body simulations to investigate the mass function and its evolution for a reference {Lambda}CDM cosmology and for a set of wCDM cosmologies. For the reference {Lambda}CDM cosmology (close to WMAP5), we quantify the breaking of universality in the form of the mass function as a function of redshift, finding an evolution of as much as 10% away from the universal form between redshifts z = 0 and z = 2. For cosmologies very close to this reference we provide a fitting formula to our results for the (evolving) {Lambda}CDM mass function over a mass range of 6 x 10{sup 11}-3 x 10{sup 15} M{sub sun} to an estimated accuracy of about 2%. The set of wCDM cosmologies is taken from the Coyote Universe simulation suite. The mass functions from this suite (which includes a {Lambda}CDM cosmology and others with w {approx_equal} -1) are described by the fitting formula for the reference {Lambda}CDM case at an accuracy level of 10%, but with clear systematic deviations. We argue that, as a consequence, fitting formulae based on a universal form for the mass function may have limited utility in high-precision cosmological applications.

  17. Mass Function Predictions Beyond ΛCDM

    NASA Astrophysics Data System (ADS)

    Bhattacharya, Suman; Heitmann, Katrin; White, Martin; Lukić, Zarija; Wagner, Christian; Habib, Salman

    2011-05-01

    The statistics of dark matter halos is an essential component of precision cosmology. The mass distribution of halos, as specified by the halo mass function, is a key input for several cosmological probes. The sizes of N-body simulations are now such that, for the most part, results need no longer be statistics-limited, but are still subject to various systematic uncertainties. Discrepancies in the results of simulation campaigns for the halo mass function remain in excess of statistical uncertainties and of roughly the same size as the error limits set by near-future observations; we investigate and discuss some of the reasons for these differences. Quantifying error sources and compensating for them as appropriate, we carry out a high-statistics study of dark matter halos from 67 N-body simulations to investigate the mass function and its evolution for a reference ΛCDM cosmology and for a set of wCDM cosmologies. For the reference ΛCDM cosmology (close to WMAP5), we quantify the breaking of universality in the form of the mass function as a function of redshift, finding an evolution of as much as 10% away from the universal form between redshifts z = 0 and z = 2. For cosmologies very close to this reference we provide a fitting formula to our results for the (evolving) ΛCDM mass function over a mass range of 6 × 1011-3 × 1015 M sun to an estimated accuracy of about 2%. The set of wCDM cosmologies is taken from the Coyote Universe simulation suite. The mass functions from this suite (which includes a ΛCDM cosmology and others with w ~= -1) are described by the fitting formula for the reference ΛCDM case at an accuracy level of 10%, but with clear systematic deviations. We argue that, as a consequence, fitting formulae based on a universal form for the mass function may have limited utility in high-precision cosmological applications.

  18. Maintaining Change: The Maintenance Function and the Change Process.

    ERIC Educational Resources Information Center

    Cooke, Fang Lee

    2003-01-01

    Explores the organization of the maintenance function of five manufacturing and utility companies and the involvement of maintenance workers in plant improvement. Highlights the role of tacit skills of maintenance workers and of the maintenance function on technological change and organizational performance. (Contains 41 references.) (JOW)

  19. 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.

  20. Predicting change in fish mercury concentrations following reservoir impoundment.

    PubMed

    Therriault, T W; Schneider, D C

    1998-01-01

    Fish mercury concentrations frequently increase after impoundment of a reservoir. Soil flooding releases organic matter and nutrients, providing food to bacterial communities that methylate inorganic mercury. Methylation and bioaccumulation are the primary pathways for mercury accumulation in fish. We investigated if changes in fish mercury concentrations could be predicted from the change in reservoir size. Data for three fish species, northern pike (Esox lucius), walleye (Stizostedion vitreum), and lake whitefish (Coregonus clupeaformis) from reservoirs in northern Manitoba and northern Quebec were used to evaluate four simple models of change in mercury with change in flooded area. For three additional fish species, all primary carnivores, the preferred model consisted of a single exponential enrichment term. This model successfully predicted two cases not used in model development-one with a large change in area and one with a small change in area. Models with good predictive skill can be developed when the underlying dynamics are known. PMID:15093096

  1. Changes in gastrointestinal tract function and structure in functional dyspepsia.

    PubMed

    Vanheel, Hanne; Farré, Ricard

    2013-03-01

    Functional dyspepsia is an extremely common disorder of gastrointestinal function. The disorder is thought to be heterogeneous, with different pathophysiological mechanisms underlying varied symptom patterns. A diversity of changes in gastrointestinal tract function and structure has been described in functional dyspepsia. These involve alterations in the stomach, such as impaired accommodation, delayed gastric emptying and hypersensitivity, and alterations in the duodenum, such as increased sensitivity to duodenal acid and/or lipids and low-grade inflammation. In this Review, we summarize all these abnormalities in an attempt to provide an integrated overview of the pathophysiological mechanisms in functional dyspepsia. PMID:23318268

  2. Prospective evaluation of a Bayesian model to predict organizational change.

    PubMed

    Molfenter, Todd; Gustafson, Dave; Kilo, Chuck; Bhattacharya, Abhik; Olsson, Jesper

    2005-01-01

    This research examines a subjective Bayesian model's ability to predict organizational change outcomes and sustainability of those outcomes for project teams participating in a multi-organizational improvement collaborative. PMID:16093893

  3. 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

  4. Model of local temperature changes in brain upon functional activation.

    PubMed

    Collins, Christopher M; Smith, Michael B; Turner, Robert

    2004-12-01

    Experimental results for changes in brain temperature during functional activation show large variations. It is, therefore, desirable to develop a careful numerical model for such changes. Here, a three-dimensional model of temperature in the human head using the bioheat equation, which includes effects of metabolism, perfusion, and thermal conduction, is employed to examine potential temperature changes due to functional activation in brain. It is found that, depending on location in brain and corresponding baseline temperature relative to blood temperature, temperature may increase or decrease on activation and concomitant increases in perfusion and rate of metabolism. Changes in perfusion are generally seen to have a greater effect on temperature than are changes in metabolism, and hence active brain is predicted to approach blood temperature from its initial temperature. All calculated changes in temperature for reasonable physiological parameters have magnitudes <0.12 degrees C and are well within the range reported in recent experimental studies involving human subjects.

  5. Functional prediction of hypothetical proteins in human adenoviruses.

    PubMed

    Dorden, Shane; Mahadevan, Padmanabhan

    2015-01-01

    Assigning functional information to hypothetical proteins in virus genomes is crucial for gaining insight into their proteomes. Human adenoviruses are medium sized viruses that cause a range of diseases. Their genomes possess proteins with uncharacterized function known as hypothetical proteins. Using a wide range of protein function prediction servers, functional information was obtained about these hypothetical proteins. A comparison of functional information obtained from these servers revealed that some of them produced functional information, while others provided little functional information about these human adenovirus hypothetical proteins. The PFP, ESG, PSIPRED, 3d2GO, and ProtFun servers produced the most functional information regarding these hypothetical proteins. PMID:26664031

  6. A Simple Model Predicting Individual Weight Change in Humans

    PubMed Central

    Thomas, Diana M.; Martin, Corby K.; Heymsfield, Steven; Redman, Leanne M.; Schoeller, Dale A.; Levine, James A.

    2010-01-01

    Excessive weight in adults is a national concern with over 2/3 of the US population deemed overweight. Because being overweight has been correlated to numerous diseases such as heart disease and type 2 diabetes, there is a need to understand mechanisms and predict outcomes of weight change and weight maintenance. A simple mathematical model that accurately predicts individual weight change offers opportunities to understand how individuals lose and gain weight and can be used to foster patient adherence to diets in clinical settings. For this purpose, we developed a one dimensional differential equation model of weight change based on the energy balance equation is paired to an algebraic relationship between fat free mass and fat mass derived from a large nationally representative sample of recently released data collected by the Centers for Disease Control. We validate the model's ability to predict individual participants’ weight change by comparing model estimates of final weight data from two recent underfeeding studies and one overfeeding study. Mean absolute error and standard deviation between model predictions and observed measurements of final weights are less than 1.8 ± 1.3 kg for the underfeeding studies and 2.5 ± 1.6 kg for the overfeeding study. Comparison of the model predictions to other one dimensional models of weight change shows improvement in mean absolute error, standard deviation of mean absolute error, and group mean predictions. The maximum absolute individual error decreased by approximately 60% substantiating reliability in individual weight change predictions. The model provides a viable method for estimating individual weight change as a result of changes in intake and determining individual dietary adherence during weight change studies. PMID:24707319

  7. Functional brain changes in presymptomatic Huntington's disease.

    PubMed

    Reading, Sarah A J; Dziorny, Adam C; Peroutka, Laura A; Schreiber, Mathew; Gourley, Lisa M; Yallapragada, Venu; Rosenblatt, Adam; Margolis, Russell L; Pekar, James J; Pearlson, Godfrey D; Aylward, Elizabeth; Brandt, Jason; Bassett, Susan S; Ross, Christopher A

    2004-06-01

    Evidence suggests early structural brain changes in individuals with the Huntington's disease (HD) genetic mutation who are presymptomatic for the movement symptoms of the illness. The aim of this study was to investigate the presence of functional brain changes in this same population using functional magnetic resonance imaging. Subjects and matched controls underwent an functional magnetic resonance imaging "interference" protocol, a task known to be mediated in part by corticostriatal circuitry. In the setting of normal cognitive performance, presymptomatic HD subjects had significantly and specifically less activation in the left anterior cingulate cortex (BA 24, 32) compared with matched controls.

  8. Gesture Performance in Schizophrenia Predicts Functional Outcome After 6 Months

    PubMed Central

    Walther, Sebastian; Eisenhardt, Sarah; Bohlhalter, Stephan; Vanbellingen, Tim; Müri, René; Strik, Werner; Stegmayer, Katharina

    2016-01-01

    The functional outcome of schizophrenia is heterogeneous and markers of the course are missing. Functional outcome is associated with social cognition and negative symptoms. Gesture performance and nonverbal social perception are critically impaired in schizophrenia. Here, we tested whether gesture performance or nonverbal social perception could predict functional outcome and the ability to adequately perform relevant skills of everyday function (functional capacity) after 6 months. In a naturalistic longitudinal study, 28 patients with schizophrenia completed tests of nonverbal communication at baseline and follow-up. In addition, functional outcome, social and occupational functioning, as well as functional capacity at follow-up were assessed. Gesture performance and nonverbal social perception at baseline predicted negative symptoms, functional outcome, and functional capacity at 6-month follow-up. Gesture performance predicted functional outcome beyond the baseline measure of functioning. Patients with gesture deficits at baseline had stable negative symptoms and experienced a decline in social functioning. While in patients without gesture deficits, negative symptom severity decreased and social functioning remained stable. Thus, a simple test of hand gesture performance at baseline may indicate favorable outcomes in short-term follow-up. The results further support the importance of nonverbal communication skills in subjects with schizophrenia. PMID:27566843

  9. 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

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

    PubMed

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

    2016-03-01

    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 marked 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 were able to 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

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

    PubMed

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

    2016-03-01

    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 marked 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 were able to 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.

  12. 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…

  13. 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.

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

    PubMed Central

    Whitmal, Nathaniel A.; DeRoy, Kristina

    2011-01-01

    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. PMID:22225057

  15. A Survey of Computational Intelligence Techniques in Protein Function Prediction

    PubMed Central

    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. PMID:25574395

  16. 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…

  17. 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.

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

    PubMed

    Yang, Jianyi; Zhang, Yang

    2015-01-01

    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.

  19. Prospective prediction of functional difficulties among recently separated veterans.

    PubMed

    Larson, Gerald E; Norman, Sonya B

    2014-01-01

    Reports of functional problems are common among Veterans who served post-9/11 (more than 25% report functional difficulties in at least one domain). However, little prospective work has examined the risk and protective factors for functional difficulties among Veterans. In a sample of recently separated Marines, we used stepwise logistic and multiple regressions to identify predictors of functional impairment, including work-related problems, financial problems, unlawful behavior, activity limitations due to mental health symptoms, and perceived difficulty reintegrating into civilian life. Posttraumatic stress disorder symptoms assessed both before and after military separation significantly predicted functional difficulties across all domains except unlawful behavior. Certain outcomes, such as unlawful behavior and activity limitations due to mental health symptoms, were predicted by other or additional predictors. Although several forms of functioning were examined, the list was not exhaustive. The results highlight a number of areas where targeted interventions may facilitate the reintegration of military servicemembers into civilian life.

  20. 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

  1. 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.

  2. 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

  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. 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.

  5. 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 ...

  6. Decision support system for predicting color change after tooth whitening.

    PubMed

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

    Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ΔE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value=0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values. PMID:26657921

  7. Decision support system for predicting color change after tooth whitening.

    PubMed

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

    Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ΔE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value=0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values.

  8. PredictProtein—an open resource for online prediction of protein structural and functional features

    PubMed Central

    Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

    2014-01-01

    PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431

  9. 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.

  10. Prediction of Postchemotherapy Ovarian Function Using Markers of Ovarian Reserve

    PubMed Central

    Xia, Rong; Schott, Anne F.; McConnell, Daniel; Banerjee, Mousumi; Hayes, Daniel F.

    2014-01-01

    Background. Reproductive-aged women frequently receive both chemotherapy and endocrine therapy as part of their treatment regimen for early stage hormone receptor-positive breast cancer. Chemotherapy results in transient or permanent ovarian failure in the majority of women. The difficulty in determining which patients will recover ovarian function has implications for adjuvant endocrine therapy decision making. We hypothesized that pretreatment serum anti-Müllerian hormone (AMH) and inhibin B concentrations would predict for ovarian function following chemotherapy. Methods. Pre- and perimenopausal women aged 25–50 years with newly diagnosed breast cancer were enrolled. Subjects underwent phlebotomy for assessment of serum AMH, inhibin B, follicle-stimulating hormone, and estradiol prior to chemotherapy and 1 month and 1 year following completion of treatment. Associations among hormone concentrations, clinical factors, and biochemically assessed ovarian function were assessed. Results. Twenty-seven subjects were evaluable for the primary endpoint. Median age was 41. Twenty subjects (74.1%) experienced recovery of ovarian function within 18 months. Of the 26 evaluable subjects assessed prior to chemotherapy, 19 (73.1%) had detectable serum concentrations of AMH. The positive predictive value of a detectable baseline serum AMH concentration for recovery of ovarian function was 94.7%, and the negative predictive value was 85.7%. On univariate analysis, younger age and detectable serum AMH concentration at chemotherapy initiation were predictive of increased likelihood of recovery of ovarian function. Conclusion. Prechemotherapy assessment of serum AMH may be useful for predicting postchemotherapy ovarian function. This finding has implications for decision making about adjuvant endocrine therapy in premenopausal women treated with chemotherapy. PMID:24319018

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

    PubMed

    James, Logan S; Sakata, Jon T

    2015-10-01

    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

  12. 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

  13. Borderline personality traits and disorder: predicting prospective patient functioning

    PubMed Central

    Hopwood, Christopher J.; Zanarini, Mary C.

    2011-01-01

    Objective Decisions about the composition of personality assessment in DSM-V will be heavily influenced by the clinical utility of candidate constructs. This study addressed one aspect of clinical utility by testing the incremental validity of five-factor model personality traits and Borderline Personality Disorder (BPD) symptoms for predicting prospective patient functioning. Method Five-factor personality traits and BPD features were correlated with one another and predicted 2, 4, 6, 8, and 10-year psychosocial functioning scores for 362 personality-disordered patients. Results Traits and symptom domains related significantly and pervasively to one another and to prospective functioning. FFM extraversion and agreeableness tended to be most incrementally predictive of psychosocial functioning across all intervals; cognitive and impulse action features of BPD features incremented FFM traits in some models. Conclusions These data suggest that BPD symptoms and personality traits are important long-term indicators of clinical functioning that both overlap with and increment one another in clinical predictions. Results support the integration of personality traits and disorders in DSM-V. PMID:20658814

  14. 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.

  15. 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

  16. Predicting real-world functional milestones in schizophrenia.

    PubMed

    Olsson, Anna-Karin; Hjärthag, Fredrik; Helldin, Lars

    2016-08-30

    Schizophrenia is a severe disorder that often causes impairments in major areas of functioning, and most patients do not achieve expected real-world functional milestones. The aim of this study was to identify which variables of demography, illness activity, and functional capacity predict patients' ability to attain real-world functional milestones. Participants were 235 outpatients, 149 men and 86 women, diagnosed with schizophrenia spectrum disorder. Our results showed that younger patients managed to achieve a higher level of functioning in educational level, marital status, and social contacts. Patients' functional capacity was primarily associated with educational level and housing situation. We also found that women needed less support regarding housing and obtained a higher level of marital status as compared with men. Our findings demonstrate the importance of considering current symptoms, especially negative symptoms, and remission stability over time, together with age, duration of illness, gender, educational level, and current functional capacity, when predicting patients' future real-world functioning. We also conclude that there is an advantage in exploring symptoms divided into positive, negative, and general domains considering their probable impact on functional achievements.

  17. 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/.

  18. 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

  19. 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.

  20. A predictive framework to understand forest responses to global change.

    PubMed

    McMahon, Sean M; Dietze, Michael C; Hersh, Michelle H; Moran, Emily V; Clark, James S

    2009-04-01

    Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.

  1. Predicting Changes in the Radio Emission Fluxes of Extragalactic Sources

    NASA Astrophysics Data System (ADS)

    Sukharev, A. L.; Ryabov, M. I.; Donskikh, G. I.

    2016-06-01

    Data from long-term monitoring with the 26-m University of Michigan radio telescope at a frequency of 14.5 GHz (1974-2011) is used to predict changes in the radio emission fluxes from the extragalactic sources 3C273, 3C120, 3C345, 3C446, 3C454.3, OJ287, OT081, and BLLac. The predictions are based on data on the major periods of variability and their durations obtained by wavelet analysis. The radio emission fluxes from the sources 3C345, 3C446, and 3C454.3, which have complicated variabilities, are predicted using an autoregression linear prediction method. This yields a forecast of the flux variations extending up to 5 years. Harmonic prediction is used for another group of sources, BLLac, OJ287, and OT081, with rapid variability. This approach yielded forecasts extending 4-9 years. For the sources 3C273 and 3C120, which have stable long periods, the harmonic method was also used and yielded a forecast extending up to 16 years. The reliability of the prediction was confirmed by independent observational data from the MOJAVE program for 2011-2015.

  2. Protein side chain conformation predictions with an MMGBSA energy function.

    PubMed

    Gaillard, Thomas; Panel, Nicolas; Simonson, Thomas

    2016-06-01

    The prediction of protein side chain conformations from backbone coordinates is an important task in structural biology, with applications in structure prediction and protein design. It is a difficult problem due to its combinatorial nature. We study the performance of an "MMGBSA" energy function, implemented in our protein design program Proteus, which combines molecular mechanics terms, a Generalized Born and Surface Area (GBSA) solvent model, with approximations that make the model pairwise additive. Proteus is not a competitor to specialized side chain prediction programs due to its cost, but it allows protein design applications, where side chain prediction is an important step and MMGBSA an effective energy model. We predict the side chain conformations for 18 proteins. The side chains are first predicted individually, with the rest of the protein in its crystallographic conformation. Next, all side chains are predicted together. The contributions of individual energy terms are evaluated and various parameterizations are compared. We find that the GB and SA terms, with an appropriate choice of the dielectric constant and surface energy coefficients, are beneficial for single side chain predictions. For the prediction of all side chains, however, errors due to the pairwise additive approximation overcome the improvement brought by these terms. We also show the crucial contribution of side chain minimization to alleviate the rigid rotamer approximation. Even without GB and SA terms, we obtain accuracies comparable to SCWRL4, a specialized side chain prediction program. In particular, we obtain a better RMSD than SCWRL4 for core residues (at a higher cost), despite our simpler rotamer library. Proteins 2016; 84:803-819. © 2016 Wiley Periodicals, Inc.

  3. Predicting changes in the distribution and abundance of species under environmental change

    PubMed Central

    Ehrlén, Johan; Morris, William F

    2015-01-01

    Environmental changes are expected to alter both the distribution and the abundance of organisms. A disproportionate amount of past work has focused on distribution only, either documenting historical range shifts or predicting future occurrence patterns. However, simultaneous predictions of abundance and distribution across landscapes would be far more useful. To critically assess which approaches represent advances towards the goal of joint predictions of abundance and distribution, we review recent work on changing distributions and on effects of environmental drivers on single populations. Several methods have been used to predict changing distributions. Some of these can be easily modified to also predict abundance, but others cannot. In parallel, demographers have developed a much better understanding of how changing abiotic and biotic drivers will influence growth rate and abundance in single populations. However, this demographic work has rarely taken a landscape perspective and has largely ignored the effects of intraspecific density. We advocate a synthetic approach in which population models accounting for both density dependence and effects of environmental drivers are used to make integrated predictions of equilibrium abundance and distribution across entire landscapes. Such predictions would constitute an important step forward in assessing the ecological consequences of environmental changes. PMID:25611188

  4. Predicting changes in the distribution and abundance of species under environmental change.

    PubMed

    Ehrlén, Johan; Morris, William F

    2015-03-01

    Environmental changes are expected to alter both the distribution and the abundance of organisms. A disproportionate amount of past work has focused on distribution only, either documenting historical range shifts or predicting future occurrence patterns. However, simultaneous predictions of abundance and distribution across landscapes would be far more useful. To critically assess which approaches represent advances towards the goal of joint predictions of abundance and distribution, we review recent work on changing distributions and on effects of environmental drivers on single populations. Several methods have been used to predict changing distributions. Some of these can be easily modified to also predict abundance, but others cannot. In parallel, demographers have developed a much better understanding of how changing abiotic and biotic drivers will influence growth rate and abundance in single populations. However, this demographic work has rarely taken a landscape perspective and has largely ignored the effects of intraspecific density. We advocate a synthetic approach in which population models accounting for both density dependence and effects of environmental drivers are used to make integrated predictions of equilibrium abundance and distribution across entire landscapes. Such predictions would constitute an important step forward in assessing the ecological consequences of environmental changes.

  5. Predicting changes in the distribution and abundance of species under environmental change.

    PubMed

    Ehrlén, Johan; Morris, William F

    2015-03-01

    Environmental changes are expected to alter both the distribution and the abundance of organisms. A disproportionate amount of past work has focused on distribution only, either documenting historical range shifts or predicting future occurrence patterns. However, simultaneous predictions of abundance and distribution across landscapes would be far more useful. To critically assess which approaches represent advances towards the goal of joint predictions of abundance and distribution, we review recent work on changing distributions and on effects of environmental drivers on single populations. Several methods have been used to predict changing distributions. Some of these can be easily modified to also predict abundance, but others cannot. In parallel, demographers have developed a much better understanding of how changing abiotic and biotic drivers will influence growth rate and abundance in single populations. However, this demographic work has rarely taken a landscape perspective and has largely ignored the effects of intraspecific density. We advocate a synthetic approach in which population models accounting for both density dependence and effects of environmental drivers are used to make integrated predictions of equilibrium abundance and distribution across entire landscapes. Such predictions would constitute an important step forward in assessing the ecological consequences of environmental changes. PMID:25611188

  6. 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…

  7. Perinatal medical variables predict executive function within a sample of preschoolers born very low birth weight.

    PubMed

    Duvall, Susanne W; Erickson, Sarah J; MacLean, Peggy; Lowe, Jean R

    2015-05-01

    The goal was to identify perinatal predictors of early executive dysfunction in preschoolers born very low birth weight. Fifty-seven preschoolers completed 3 executive function tasks: Dimensional Change Card Sort-Separated (inhibition, working memory, and cognitive flexibility), Bear Dragon (inhibition and working memory), and Gift Delay Open (inhibition). Relationships between executive function and perinatal medical severity factors (gestational age, days on ventilation, size for gestational age, maternal steroids, and number of surgeries) and chronological age were investigated by multiple linear regression and logistic regression. Different perinatal medical severity factors were predictive of executive function tasks, with gestational age predicting Bear Dragon and Gift Open; and number of surgeries and maternal steroids predicting performance on Dimensional Change Card Sort-Separated. By understanding the relationship between perinatal medical severity factors and preschool executive outcomes, we can identify children at highest risk for future executive dysfunction, thereby focusing targeted early intervention services. PMID:25117418

  8. Predicting early clinical function after hip or knee arthroplasty

    PubMed Central

    Poitras, S.; Wood, K. S.; Savard, J.; Dervin, G. F.; Beaule, P. E.

    2015-01-01

    Objectives Patient function after arthroplasty should ideally quickly improve. It is not known which peri-operative function assessments predict length of stay (LOS) and short-term functional recovery. The objective of this study was to identify peri-operative functions assessments predictive of hospital LOS and short-term function after hospital discharge in hip or knee arthroplasty patients. Methods In total, 108 patients were assessed peri-operatively with the timed-up-and-go (TUG), Iowa level of assistance scale, post-operative quality of recovery scale, readiness for hospital discharge scale, and the Western Ontario and McMaster Osteoarthritis Index (WOMAC). The older Americans resources and services activities of daily living (ADL) questionnaire (OARS) was used to assess function two weeks after discharge. Results Following multiple regressions, the pre- and post-operative day two TUG was significantly associated with LOS and OARS score, while the pre-operative WOMAC function subscale was associated with the OARS score. Pre-operatively, a cut-off TUG time of 11.7 seconds for LOS and 10.3 seconds for short-term recovery yielded the highest sensitivity and specificity, while a cut-off WOMAC function score of 48.5/100 yielded the highest sensitivity and specificity. Post-operatively, a cut-off day two TUG time of 31.5 seconds for LOS and 30.9 seconds for short-term function yielded the highest sensitivity and specificity. Conclusions The pre- and post-operative day two TUG can indicate hospital LOS and short-term functional capacities, while the pre-operative WOMAC function subscale can indicate short-term functional capacities. Cite this article: Bone Joint Res 2015;4:145–151. PMID:26336897

  9. Changes in Reflective Functioning during Psychoanalytic Psychotherapies.

    PubMed

    Hörz-Sagstetter, Susanne; Mertens, Wolfgang; Isphording, Sybille; Buchheim, Anna; Taubner, Svenja

    2015-06-01

    This study examines how reflective functioning (RF) can be assessed in analytic sessions and throughout psychoanalytic psychotherapy. The goals are to replicate in part a study by Josephs and colleagues (2004) by applying the RF Scale to analytic sessions and to study fluctuations of RF within each session. Additionally, RF based on sessions was compared with the RF ratings based on the Adult Attachment Interview (AAI) during the course of two psychoanalytic psychotherapies with a duration of 240 hours. RF changes based on 10 sessions per patient, assessed at baseline and after 80, 160, and 240 hours of therapy, and RF changes based on AAI ratings measured at baseline and after 240 hours of therapy, and in one case at follow-up, were related to changes of symptoms and attachment classifications over time. Results showed that in both cases RF fluctuated within sessions. The average RF rating per session increased over the course of treatment, while the AAI-based RF rating needed longer to increase. Rather good correspondence was found between session-based RF ratings and independent AAI-based RF ratings. In both cases, changes in RF over time were compared to changes in attachment classification based on the AAI and to symptomatic change. Better correspondence between symptomatic and attachment changes was found with the AAI-based RF rating. It was tentatively interpreted that session-based RF ratings may represent a state of RF that is strongly influenced by the therapist-patient interaction, whereas AAI-based RF can be considered to have more trait characteristics. PMID:26185290

  10. 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.

  11. 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.

  12. Pattern recognition methods for protein functional site prediction.

    PubMed

    Yang, Zheng Rong; Wang, Lipo; Young, Natasha; Trudgian, Dave; Chou, Kuo-Chen

    2005-10-01

    Protein functional site prediction is closely related to drug design, hence to public health. In order to save the cost and the time spent on identifying the functional sites in sequenced proteins in biology laboratory, computer programs have been widely used for decades. Many of them are implemented using the state-of-the-art pattern recognition algorithms, including decision trees, neural networks and support vector machines. Although the success of this effort has been obvious, advanced and new algorithms are still under development for addressing some difficult issues. This review will go through the major stages in developing pattern recognition algorithms for protein functional site prediction and outline the future research directions in this important area. PMID:16248799

  13. Effects of changing illuminance on somatosensory function.

    PubMed

    Yoshinaga, Naoki; Fujita, Mizuho; Tanaka, Yuji L; Nemoto, Seiji

    2011-01-01

    Artificial sources of illumination can be easily used, regardless of the time and place, to improve visibility at night and in dark places. Illuminance and color temperature are particularly important factors since they are known to elicit physiological effects. However, the relationship between changes in illuminance and somatosensory function has not been sufficiently clarified. Thus, the purpose of this study was to construct a laboratorial model to examine the effects of lowering or raising illuminance on somatosensory function. Three illuminance levels (200 lx, 50 lx, and 0 lx), which were changed using all combinations, and an artificial sensory stimulus maintained at a constant intensity were presented to the subjects of this study. Objective sensory function in response to the sensory stimulus was investigated by somatosensory evoked potential (SEP), and subjective sensory evaluation in response to the stimulus was investigated using a visual analogue scale (VAS) and by interview. In many cases, the SEP amplitude and VAS value tended to decrease when illuminance was lowered and tended to increase when illuminance was raised. However, in a few cases, SEP amplitude and VAS value tended to increase in spite of the low illuminance. The occurrence of attention responses and unpleasant emotional responses caused by lowering the illuminance seems to be related to this study finding.

  14. Climate change and predicted trend of fungal keratitis in Egypt.

    PubMed

    Saad-Hussein, A; El-Mofty, H M; Hassanien, M A

    2011-06-01

    Rising rates of invasive fungal infections may be linked to global climate change. A study was made of the trend of ophthalmic fungal corneal keratitis in the greater Cairo area of Egypt and its association with climate records during the same period. Data on diagnosed cases of fungal keratitis were collected from records of ophthalmic departments of Cairo University hospital and atmospheric temperature and humidity for the greater Cairo area were obtained from online records. Statistical analysis showed a significant increase in the relative frequency of keratomycosis during 1997-2007. The rise correlated significantly with rises n min,mum temperature and the maximum atmospheric humidity in the greater Cairo area over the same period (after exclusion of the effect of the maximum atmos pheric temperature). The predicted increase in keratomycosis up to the year 2030 corresponds to predicted increases in CO2 emissions and surface temperature from climate change models for Egypt.

  15. Predicting Climate Change: Lessons From Reductionism, Emergence, and the Past

    NASA Astrophysics Data System (ADS)

    Harrison, Stephan; Stainforth, Dave

    2009-03-01

    Climate and Earth system models are the only tools used to make predictions of future climate change. Such predictions are subject to considerable uncertainties, and understanding these uncertainties has clear and important policy implications. This Forum highlights the concepts of reductionism and emergence, and past climate variability, to illuminate some of the uncertainties faced by those wishing to model the future evolution of global climate. General circulation models (GCMs) of the atmosphere-ocean system are scientists' principal tools for providing information about future climate. GCMs consequently have considerable influence on climate change-related policy questions. Over the past decade, there have been significant attempts, mainly by statisticians and mathematicians, to explore the uncertainties in model simulations of possible futures, accompanied by growing debate about the interpretation of these simulations as aids in societal decisions. In this Forum, we discuss atmosphere-ocean GCMs in the context of reductionist and emergent approaches to scientific study.

  16. Probabilistic Prediction in Scale-Free Networks: Diameter Changes

    NASA Astrophysics Data System (ADS)

    Kim, J.-H.; Goh, K.-I.; Kahng, B.; Kim, D.

    2003-08-01

    In complex systems, responses to small perturbations are too diverse to definitely predict how much they would be, and then such diverse responses can be predicted in a probabilistic way. Here we study such a problem in scale-free networks, for example, the diameter changes by the deletion of a single vertex for various in silico and real-world scale-free networks. We find that the diameter changes are indeed diverse and their distribution exhibits an algebraic decay with an exponent ζ asymptotically. Interestingly, the exponent ζ is robust as ζ≃2.2(1) for most scale-free networks and insensitive to the degree exponents γ as long as 2<γ≤3. However, there is another type with ζ≃1.7(1) and its examples include the Internet and its related in silico model.

  17. 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

  18. 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.

  19. Predicting biotic interactions and their variability in a changing environment.

    PubMed

    Kadowaki, Kohmei; Barbera, Claire G; Godsoe, William; Delsuc, Frédéric; Mouquet, Nicolas

    2016-05-01

    Global environmental change is altering the patterns of biodiversity worldwide. Observation and theory suggest that species' distributions and abundances depend on a suite of processes, notably abiotic filtering and biotic interactions, both of which are constrained by species' phylogenetic history. Models predicting species distribution have historically mostly considered abiotic filtering and are only starting to integrate biotic interaction. However, using information on present interactions to forecast the future of biodiversity supposes that biotic interactions will not change when species are confronted with new environments. Using bacterial microcosms, we illustrate how biotic interactions can vary along an environmental gradient and how this variability can depend on the phylogenetic distance between interacting species. PMID:27220858

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

    PubMed Central

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

    2008-01-01

    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. PMID:18195375

  1. 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…

  2. Structure activity relationships: their function in biological prediction

    SciTech Connect

    Schultz, T.W.

    1982-01-01

    Quantitative structure activity relationships provide a means of ranking or predicting biological effects based on chemical structure. For each compound used to formulate a structure activity model two kinds of quantitative information are required: (1) biological activity and (2) molecular properties. Molecular properties are of three types: (1) molecular shape, (2) physiochemical parameters, and (3) abstract quantitations of molecular structure. Currently the two best descriptors are the hydrophobic parameter, log 1-octanol/water partition coefficient (log P), and the /sup 1/X/sup v/(one-chi-v) molecular connectivity index. Biological responses can be divided into three main categories: (1) non-specific effects due to membrane perturbation, (2) non-specific effects due to interaction with functional groups of proteins, and (3) specific effects due to interaction with receptors. Twenty-six synthetic fossil fuel-related nitrogen-containing aromatic compounds were examined to determine the quantitative correlation between log P and /sup 1/X/sup v/ and population growth impairment of Tetrahymena pyriformis. Nitro-containing compounds are the most active, followed by amino-containing compounds and azaarenes. Within each analog series activity increases with alkyl substitution and ring addition. The planar model log BR = 0.5564 log P + 0.3000 /sup 1/X/sup v/ -2.0138 was determined using mono-nitrogen substituted compounds. Attempts to extrapolate this model to dinitrogen-containing molecules were, for the most part, unsuccessful because of a change in mode of action from membrane perturbation to uncoupling of oxidative phosphoralation.

  3. Towards computational prediction of microRNA function and activity

    PubMed Central

    Ulitsky, Igor; Laurent, Louise C.; Shamir, Ron

    2010-01-01

    While it has been established that microRNAs (miRNAs) play key roles throughout development and are dysregulated in many human pathologies, the specific processes and pathways regulated by individual miRNAs are mostly unknown. Here, we use computational target predictions in order to automatically infer the processes affected by human miRNAs. Our approach improves upon standard statistical tools by addressing specific characteristics of miRNA regulation. Our analysis is based on a novel compendium of experimentally verified miRNA-pathway and miRNA-process associations that we constructed, which can be a useful resource by itself. Our method also predicts novel miRNA-regulated pathways, refines the annotation of miRNAs for which only crude functions are known, and assigns differential functions to miRNAs with closely related sequences. Applying our approach to groups of co-expressed genes allows us to identify miRNAs and genomic miRNA clusters with functional importance in specific stages of early human development. A full list of the predicted mRNA functions is available at http://acgt.cs.tau.ac.il/fame/. PMID:20576699

  4. Plant functional group composition modifies the effects of precipitation change on grassland ecosystem function.

    PubMed

    Fry, Ellen L; Manning, Pete; Allen, David G P; Hurst, Alex; Everwand, Georg; Rimmler, Martin; Power, Sally A

    2013-01-01

    Temperate grassland ecosystems face a future of precipitation change, which can alter community composition and ecosystem functions through reduced soil moisture and waterlogging. There is evidence that functionally diverse plant communities contain a wider range of water use and resource capture strategies, resulting in greater resistance of ecosystem function to precipitation change. To investigate this interaction between composition and precipitation change we performed a field experiment for three years in successional grassland in southern England. This consisted of two treatments. The first, precipitation change, simulated end of century predictions, and consisted of a summer drought phase alongside winter rainfall addition. The second, functional group identity, divided the plant community into three groups based on their functional traits- broadly described as perennials, caespitose grasses and annuals- and removed these groups in a factorial design. Ecosystem functions related to C, N and water cycling were measured regularly. Effects of functional groupidentity were apparent, with the dominant trend being that process rates were higher under control conditions where a range of perennial species were present. E.g. litter decomposition rates were significantly higher in plots containing several perennial species, the group with the highest average leaf N content. Process rates were also very strongly affected by the precipitation change treatmentwhen perennial plant species were dominant, but not where the community contained a high abundance of annual species and caespitose grasses. This contrasting response could be attributable to differing rooting patterns (shallower structures under annual plants, and deeper roots under perennials) and faster nutrient uptake in annuals compared to perennials. Our results indicate that precipitation change will have a smaller effect on key process rates in grasslandscontaining a range of perennial and annual species

  5. Identifying functional sites based on prediction of charged group behavior.

    PubMed

    Ondrechen, Mary Jo

    2004-09-01

    This protocol describes the implementation and interpretation of THEMATICS, a simple computational predictor of functional information for proteins from the three-dimensional structure. This method is based on the computation of the electrical potential function for the protein and the calculation of the predicted titration curves for each of the titratable groups in the protein. While most of the titratable residues in a protein have predicted titration behavior that fits the Henderson-Hasselbalch equation, the ionizable residues in the active site generally deviate dramatically from the typical behavior. From the calculated titration curves, one identifies those residues that deviate significantly from Henderson-Hasselbalch behavior. A cluster of two or more of such deviant titratable residues in physical proximity is a reliable predictor of active-site location.

  6. 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.

  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. PMID:25599106

  8. 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.

  9. 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

  10. Implicit self-evaluations predict changes in implicit partner evaluations.

    PubMed

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

    2014-08-01

    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 evaluation. The current longitudinal study of newlywed couples used implicit measures of self- and partner evaluation, as well as explicit measures of self-, relationship, and partner evaluation, to examine the link between self-evaluations and changes in relationship evaluations over the first 3 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 adds to previous research by highlighting the importance of automatic processes and implicit measures in the study of close interpersonal relationships.

  11. Prediction of protein complexes using empirical free energy functions.

    PubMed Central

    Weng, Z.; Vajda, S.; Delisi, C.

    1996-01-01

    A long sought goal in the physical chemistry of macromolecular structure, and one directly relevant to understanding the molecular basis of biological recognition, is predicting the geometry of bimolecular complexes from the geometries of their free monomers. Even when the monomers remain relatively unchanged by complex formation, prediction has been difficult because the free energies of alternative conformations of the complex have been difficult to evaluate quickly and accurately. This has forced the use of incomplete target functions, which typically do no better than to provide tens of possible complexes with no way of choosing between them. Here we present a general framework for empirical free energy evaluation and report calculations, based on a relatively complete and easily executable free energy function, that indicate that the structures of complexes can be predicted accurately from the structures of monomers, including close sequence homologues. The calculations also suggest that the binding free energies themselves may be predicted with reasonable accuracy. The method is compared to an alternative formulation that has also been applied recently to the same data set. Both approaches promise to open new opportunities in macromolecular design and specificity modification. PMID:8845751

  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 predicting climate change impacts on pome fruit phenology.

    PubMed

    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.

  14. 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.

  15. Predictions of Geospace Drivers By the Probability Distribution Function Model

    NASA Astrophysics Data System (ADS)

    Bussy-Virat, C.; Ridley, A. J.

    2014-12-01

    Geospace drivers like the solar wind speed, interplanetary magnetic field (IMF), and solar irradiance have a strong influence on the density of the thermosphere and the near-Earth space environment. This has important consequences on the drag on satellites that are in low orbit and therefore on their position. One of the basic problems with space weather prediction is that these drivers can only be measured about one hour before they affect the environment. In order to allow for adequate planning for some members of the commercial, military, or civilian communities, reliable long-term space weather forecasts are needed. The study presents a model for predicting geospace drivers up to five days in advance. This model uses the same general technique to predict the solar wind speed, the three components of the IMF, and the solar irradiance F10.7. For instance, it uses Probability distribution functions (PDFs) to relate the current solar wind speed and slope to the future solar wind speed, as well as the solar wind speed to the solar wind speed one solar rotation in the future. The PDF Model has been compared to other models for predictions of the speed. It has been found that it is better than using the current solar wind speed (i.e., persistence), and better than the Wang-Sheeley-Arge Model for prediction horizons of 24 hours. Once the drivers are predicted, and the uncertainty on the drivers are specified, the density in the thermosphere can be derived using various models of the thermosphere, such as the Global Ionosphere Thermosphere Model. In addition, uncertainties on the densities can be estimated, based on ensembles of simulations. From the density and uncertainty predictions, satellite positions, as well as the uncertainty in those positions can be estimated. These can assist operators in determining the probability of collisions between objects in low Earth orbit.

  16. Density functional theory predictions of isotropic hyperfine coupling constants.

    PubMed

    Hermosilla, L; Calle, P; García de la Vega, J M; Sieiro, C

    2005-02-17

    The reliability of density functional theory (DFT) in the determination of the isotropic hyperfine coupling constants (hfccs) of the ground electronic states of organic and inorganic radicals is examined. Predictions using several DFT methods and 6-31G, TZVP, EPR-III and cc-pVQZ basis sets are made and compared to experimental values. The set of 75 radicals here studied was selected using a wide range of criteria. The systems studied are neutral, cationic, anionic; doublet, triplet, quartet; localized, and conjugated radicals, containing 1H, 9Be, 11B, 13C, 14N, 17O, 19F, 23Na, 25Mg, 27Al, 29Si, 31P, 33S, and 35Cl nuclei. The considered radicals provide 241 theoretical hfcc values, which are compared with 174 available experimental ones. The geometries of the studied systems are obtained by theoretical optimization using the same functional and basis set with which the hfccs were calculated. Regression analysis is used as a basic and appropriate methodology for this kind of comparative study. From this analysis, we conclude that DFT predictions of the hfccs are reliable for B3LYP/TZVP and B3LYP/EPR-III combinations. Both functional/basis set scheme are the more useful theoretical tools for predicting hfccs if compared to other much more expensive methods.

  17. 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.

  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. PMID:24119205

  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. 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. PMID:25212581

  1. Origin and Functional Prediction of Pollen Allergens in Plants.

    PubMed

    Chen, Miaolin; Xu, Jie; Devis, Deborah; Shi, Jianxin; Ren, Kang; Searle, Iain; Zhang, Dabing

    2016-09-01

    Pollen allergies have long been a major pandemic health problem for human. However, the evolutionary events and biological function of pollen allergens in plants remain largely unknown. Here, we report the genome-wide prediction of pollen allergens and their biological function in the dicotyledonous model plant Arabidopsis (Arabidopsis thaliana) and the monocotyledonous model plant rice (Oryza sativa). In total, 145 and 107 pollen allergens were predicted from rice and Arabidopsis, respectively. These pollen allergens are putatively involved in stress responses and metabolic processes such as cell wall metabolism during pollen development. Interestingly, these putative pollen allergen genes were derived from large gene families and became diversified during evolution. Sequence analysis across 25 plant species from green alga to angiosperms suggest that about 40% of putative pollen allergenic proteins existed in both lower and higher plants, while other allergens emerged during evolution. Although a high proportion of gene duplication has been observed among allergen-coding genes, our data show that these genes might have undergone purifying selection during evolution. We also observed that epitopes of an allergen might have a biological function, as revealed by comprehensive analysis of two known allergens, expansin and profilin. This implies a crucial role of conserved amino acid residues in both in planta biological function and allergenicity. Finally, a model explaining how pollen allergens were generated and maintained in plants is proposed. Prediction and systematic analysis of pollen allergens in model plants suggest that pollen allergens were evolved by gene duplication and then functional specification. This study provides insight into the phylogenetic and evolutionary scenario of pollen allergens that will be helpful to future characterization and epitope screening of pollen allergens. PMID:27436829

  2. 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.

  3. Temporal predictions based on a gradual change in tempo.

    PubMed

    Cope, Thomas E; Grube, Manon; Griffiths, Timothy D

    2012-05-01

    Previous studies investigating sensitivity to step changes in tempo and prediction of tone onset time have generally utilized isochronous sequences. This study investigates subjects' ability to detect deviations from a gradual change in the tempo of a tone sequence (experiment 1) and their judgment of the perceptually optimal timing of this tone (experiment 2). In experiment 1, inter-onset-intervals within pairs of eight-tone sequences followed a geometric progression to create a gradual tempo change. In one sequence, the final tone was presented either earlier or later than specified by the progression. Subjects performed well at detecting deviations that exaggerated the tempo progression but poorly when it was counteracted. Experiment 2 used similar pairs except that the final tone was always presented earlier in one sequence than the other. Final interval length was adaptively adjusted to subjects' judgments; it was adjudged in best agreement with the progression when its length was roughly half way between the mathematically correct value and the length of the penultimate interval. The data support "multiple-look" and entrainment models of tempo sensitivity and suggest that temporal prediction is based less on the tempo contour of a whole sequence than on the duration of the preceding interval.

  4. 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. PMID:27062059

  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. Remote sensing of vegetation ecophysiological function for improved hydrologic prediction

    NASA Astrophysics Data System (ADS)

    Drewry, D.; Ruddell, B. L.

    2014-12-01

    Land surface hydrology in vegetated landscapes is strongly controlled by ecophysiological function. The coupling between photosynthesis, stomatal dynamics and leaf energy balance fundamentally links the hydrologic and carbon cycles, and provides a basis for examining the utility of observations of functional plant traits for hydrologic prediction. Here we explore the potential of solar induced fluorescence (SIF) and thermal infrared (TIR) remote sensing observations to improve the accuracy and reduce the uncertainty in hydrologic prediction. While SIF represents an emission of radiation associated with photosynthesis, TIR provides information on foliage temperature and is related to stomatal function and water stress. A set of remote observing system simulation experiments are conducted to quantify the value of remotely sensed observations of SIF and TIR when assimilated into a detailed vegetation biophysical model. The MLCan model discretizes a dense plant canopy to resolve vertical variation in photosynthesis, water vapor and energy exchange. Here we present extensions to MLCan that allow for direct computation of the canopy emission of both SIF and TIR. The detailed representation of the physical environment and biological functioning of structurally complex canopies makes MLCan an ideal simulation tool for exploring the impact of these two unique, and potentially synergistic observables. This work specifically addresses remote sensing capabilities on both recently launched (OCO-2) and near-term (ECOSTRESS) satellite platforms. We contrast the information gained through the assimilation of SIF and TIR observations to that of the assimilation of data related to physical states such as soil moisture and leaf area index.

  7. 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. PMID:27070016

  8. 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

  9. 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

  10. 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.…

  11. 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

    2012-07-01

    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.

  12. Prediction of functional regulatory SNPs in monogenic and complex disease

    PubMed Central

    Zhao, Yiqiang; Clark, Wyatt T.; Mort, Matthew; Cooper, David N.; Radivojac, Predrag; Mooney, Sean D.

    2013-01-01

    Next-Generation Sequencing (NGS) technologies are yielding ever-higher volumes of human genome sequence data. Given this large amount of data, it has become both a possibility and a priority to determine how disease-causing single nucleotide polymorphisms (SNPs) detected within gene regulatory regions (rSNPs) exert their effects on gene expression. Recently, several studies have explored whether disease-causing polymorphisms have attributes that can distinguish them from those that are neutral, attaining moderate success at discriminating between functional and putatively neutral regulatory SNPs. Here, we have extended this work by assessing the utility of both SNP-based features (those associated only with the polymorphism site and the surrounding DNA) and Gene-based features (those derived from the associated gene in whose regulatory region the SNP lies) in the identification of functional regulatory polymorphisms involved in either monogenic or complex disease. Gene-based features were found to be capable of both augmenting and enhancing the utility of SNP-based features in the prediction of known regulatory mutations. Adopting this approach, we achieved an AUC of 0.903 for predicting regulatory SNPs. Finally, our tool predicted 225 new regulatory SNPs with a high degree of confidence, with 105 of the 225 falling into linkage disequilibrium blocks of reported disease-associated GWAS SNPs. PMID:21796725

  13. Change in BMI accurately predicted by social exposure to acquaintances.

    PubMed

    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 R(2). 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.

  14. Perlite exposure and 4-year change in lung function.

    PubMed

    Polatli, M; Erdinç, M; Erdinç, E; Okyay, E

    2001-07-01

    Perlite is a volcanic glass or amorphous aluminium silicate composed of 71-75% SiO(2). When heated to 800-1100 degrees C, it expands to form processed perlite, which has a low density, high surface area, and a low thermal conductivity. The objective was to determine the effect of perlite exposure on pulmonary function tests. Pulmonary function tests in conjunction with chest radiogram were carried out in 36 perlite-exposed workers and 22 unexposed office workers in 1992 and 1996. Respirable dust level exceeded permissible dust levels in work places in the 4 years under study. Transfer coefficient (K(CO)) decline was significant in nonsmoker perlite-exposed workers (n=9), and found to be 5.28+/-0.71 (predicted 4.32+/-0.11) and 3.84+/-0.96 (predicted 4.18+/-0.18) 1/min/mmHg, in 1992 and 1996, respectively (P<0.001). Both smoker perlite workers and office workers showed significant obstruction to airflow in small airways with respect to predicted values and 4-year change in transfer factor (T(L), CO) was significant. Although predicted, 12-year perlite exposure did not lead to a decrease in mean pulmonary function test parameters, there was a tendency to a decline in T(L), CO in the 4-year study period, which may be due to high perlite dust levels. As early effects of perlite dust exposure may not be detected by spirometric measurements alone, the transfer coefficient should be added to spirometry.

  15. Electrocortical indices of selective attention predict adolescent executive functioning.

    PubMed

    Lackner, Christine L; Santesso, Diane L; Dywan, Jane; Wade, Terrance J; Segalowitz, Sidney J

    2013-05-01

    Executive functioning is considered a powerful predictor of behavioral and mental health outcomes during adolescence. Our question was whether executive functioning skills, normally considered "top-down" processes, are related to automatic aspects of selective attention. Event-related potentials (ERPs) were recorded from typically-developing 12-14-year-old adolescents as they responded to tones presented in attended and unattended channels in an auditory selective attention task. Examining these ERPs in relation to parental reports on the Behavior Rating Inventory of Executive Function (BRIEF) revealed that an early frontal positivity (EFP) elicited by to-be-ignored/unattended tones was larger in those with poorer executive functions, driven by scores on the BRIEF Metacognition Index. As is traditionally found, N1 amplitudes were more negative for the to-be-attended rather than unattended tones. Additionally, N1 latencies to unattended tones correlated with parent-ratings on the BRIEF Behavior Regulation Index, where shorter latencies predicted better executive functions. Results suggest that the ability to disengage attention from distractor information in the early stages of stimulus processing is associated with adolescent executive functioning skills. PMID:23528784

  16. Electrocortical indices of selective attention predict adolescent executive functioning.

    PubMed

    Lackner, Christine L; Santesso, Diane L; Dywan, Jane; Wade, Terrance J; Segalowitz, Sidney J

    2013-05-01

    Executive functioning is considered a powerful predictor of behavioral and mental health outcomes during adolescence. Our question was whether executive functioning skills, normally considered "top-down" processes, are related to automatic aspects of selective attention. Event-related potentials (ERPs) were recorded from typically-developing 12-14-year-old adolescents as they responded to tones presented in attended and unattended channels in an auditory selective attention task. Examining these ERPs in relation to parental reports on the Behavior Rating Inventory of Executive Function (BRIEF) revealed that an early frontal positivity (EFP) elicited by to-be-ignored/unattended tones was larger in those with poorer executive functions, driven by scores on the BRIEF Metacognition Index. As is traditionally found, N1 amplitudes were more negative for the to-be-attended rather than unattended tones. Additionally, N1 latencies to unattended tones correlated with parent-ratings on the BRIEF Behavior Regulation Index, where shorter latencies predicted better executive functions. Results suggest that the ability to disengage attention from distractor information in the early stages of stimulus processing is associated with adolescent executive functioning skills.

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

    PubMed

    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

    2013-11-01

    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

  18. 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

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

    PubMed

    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

    2013-11-01

    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.

  20. 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

  1. Predictions of a Global Climate Change and Cycle on Jupiter

    NASA Astrophysics Data System (ADS)

    Marcus, P. S.

    2003-12-01

    We predict that most of Jupiter's large vortices, similar to (but not including) the Great Red Spot, will soon disappear due to vortex mergers. This will cause global temperature changes of ˜10oK. Within a decade, several of Jupiter's westward jet streams (there are 12) will form waves. They will grow, break, roll-up and re-populate Jupiter with new vortices. These dynamics should be visible from earth as the break-up of a circumferential band of clouds into ``spots''. The new vortices will be similar to those that were observed during most of the 20th century. For ˜60 years they will change only slowly, then abruptly bunch together. Shortly afterward, most will disappear by merging with other vortices. The cycle described above will repeat with a ˜70-year time scale, with many of the events detectable from earth or by satellite. The formation of the White Oval ``spots'' in 1939 began the current global climate cycle, and their mergers in 1997--2000 signaled the beginning of its end. Our predictions are based on fundamental vortex dynamics rather than global circulation models.

  2. 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.

  3. PSCL: predicting protein subcellular localization based on optimal functional domains.

    PubMed

    Wang, Kai; Hu, Le-Le; Shi, Xiao-He; Dong, Ying-Song; Li, Hai-Peng; Wen, Tie-Qiao

    2012-01-01

    It is well known that protein subcellular localizations are closely related to their functions. Although many computational methods and tools are available from Internet, it is still necessary to develop new algorithms in this filed to gain a better understanding of the complex mechanism of plant subcellular localization. Here, we provide a new web server named PSCL for plant protein subcellular localization prediction by employing optimized functional domains. After feature optimization, 848 optimal functional domains from InterPro were obtained to represent each protein. By calculating the distances to each of the seven categories, PSCL showing the possibilities of a protein located into each of those categories in ascending order. Toward our dataset, PSCL achieved a first-order predicted accuracy of 75.7% by jackknife test. Gene Ontology enrichment analysis showing that catalytic activity, cellular process and metabolic process are strongly correlated with the localization of plant proteins. Finally, PSCL, a Linux Operate System based web interface for the predictor was designed and is accessible for public use at http://pscl.biosino.org/.

  4. 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.

  5. Cardiorespiratory fitness predicts changes in adiposity in overweight Hispanic boys.

    PubMed

    Byrd-Williams, Courtney E; Shaibi, Gabriel Q; Sun, Ping; Lane, Christianne J; Ventura, Emily E; Davis, Jaimie N; Kelly, Louise A; Goran, Michael I

    2008-05-01

    We have previously shown that cardiorespiratory fitness predicts increasing fat mass during growth in white and African-American youth, but limited data are available examining this issue in Hispanic youth. Study participants were 160 (53% boys) overweight (BMI>or=85th percentile for age and gender) Hispanic children (mean+/-s.d. age at baseline=11.2+/-1.7 years). Cardiorespiratory fitness, assessed by VO2max, was measured through a maximal effort treadmill test at baseline. Body composition through dual-energy X-ray absorptiometry and Tanner stage through clinical exam were measured at baseline and annually thereafter for up to 4 years. Linear mixed models were used to examine the gender-specific relationship between VO2max and increases in adiposity (change in fat mass independent of change in lean tissue mass) over 4 years. The analysis was adjusted for changes in Tanner stage, age, and lean tissue mass. In boys, higher VO2max at baseline was inversely associated with the rate of increase in adiposity (beta=-0.001, P=0.03); this effect translates to a 15% higher VO2max at baseline resulting in a 1.38 kg lower fat mass gain over 4 years. However, VO2max was not significantly associated with changes in fat mass in girls (beta=0.0002, P=0.31). In overweight Hispanic boys, greater cardiorespiratory fitness at baseline was protective against increasing adiposity. In girls however initial cardiorespiratory fitness was not significantly associated with longitudinal changes in adiposity. These results suggest that cardiorespiratory fitness may be an important determinant of changes in adiposity in overweight Hispanic boys but not in girls.

  6. 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

  7. 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

  8. 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

  9. The Evolutionary Legacy of Diversification Predicts Ecosystem Function.

    PubMed

    Yguel, Benjamin; Jactel, Hervé; Pearse, Ian S; Moen, Daniel; Winter, Marten; Hortal, Joaquin; Helmus, Matthew R; Kühn, Ingolf; Pavoine, Sandrine; Purschke, Oliver; Weiher, Evan; Violle, Cyrille; Ozinga, Wim; Brändle, Martin; Bartish, Igor; Prinzing, Andreas

    2016-10-01

    Theory suggests that the structure of evolutionary history represented in a species community may affect its functioning, but phylogenetic diversity metrics do not allow for the identification of major differences in this structure. Here we propose a new metric, ELDERness (for Evolutionary Legacy of DivERsity) to estimate evolutionary branching patterns within communities by fitting a polynomial function to lineage-through-time (LTT) plots. We illustrate how real and simulated community branching patterns can be more correctly described by ELDERness and can successfully predict ecosystem functioning. In particular, the evolutionary history of branching patterns can be encapsulated by the parameters of third-order polynomial functions and further measured through only two parameters, the "ELDERness surfaces." These parameters captured variation in productivity of a grassland community better than existing phylogenetic diversity or diversification metrics and independent of species richness or presence of nitrogen fixers. Specifically, communities with small ELDERness surfaces (constant accumulation of lineages through time in LTT plots) were more productive, consistent with increased productivity resulting from complementary lineages combined with niche filling within lineages. Overall, while existing phylogenetic diversity metrics remain useful in many contexts, we suggest that our ELDERness approach better enables testing hypotheses that relate complex patterns of macroevolutionary history represented in local communities to ecosystem functioning.

  10. The Evolutionary Legacy of Diversification Predicts Ecosystem Function.

    PubMed

    Yguel, Benjamin; Jactel, Hervé; Pearse, Ian S; Moen, Daniel; Winter, Marten; Hortal, Joaquin; Helmus, Matthew R; Kühn, Ingolf; Pavoine, Sandrine; Purschke, Oliver; Weiher, Evan; Violle, Cyrille; Ozinga, Wim; Brändle, Martin; Bartish, Igor; Prinzing, Andreas

    2016-10-01

    Theory suggests that the structure of evolutionary history represented in a species community may affect its functioning, but phylogenetic diversity metrics do not allow for the identification of major differences in this structure. Here we propose a new metric, ELDERness (for Evolutionary Legacy of DivERsity) to estimate evolutionary branching patterns within communities by fitting a polynomial function to lineage-through-time (LTT) plots. We illustrate how real and simulated community branching patterns can be more correctly described by ELDERness and can successfully predict ecosystem functioning. In particular, the evolutionary history of branching patterns can be encapsulated by the parameters of third-order polynomial functions and further measured through only two parameters, the "ELDERness surfaces." These parameters captured variation in productivity of a grassland community better than existing phylogenetic diversity or diversification metrics and independent of species richness or presence of nitrogen fixers. Specifically, communities with small ELDERness surfaces (constant accumulation of lineages through time in LTT plots) were more productive, consistent with increased productivity resulting from complementary lineages combined with niche filling within lineages. Overall, while existing phylogenetic diversity metrics remain useful in many contexts, we suggest that our ELDERness approach better enables testing hypotheses that relate complex patterns of macroevolutionary history represented in local communities to ecosystem functioning. PMID:27622874

  11. 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

    2011-01-01

    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. PMID:21249228

  12. Prediction of climate variability and projection of climate change

    SciTech Connect

    Grassl, H.

    1996-12-31

    The years since 1985 have seen rapid progress in climate research. By the implementation of a new observing system in the Tropical Pacific Ocean combined with the development of adapted coupled ocean-atmosphere models the Tropical Ocean-Global Atmosphere (TOGA) project of the World Climate Research Programme (WCRP) led to the breakthrough to physically-based climate predictions. For most of the tropics and partly extending to mid-latitudes, climate anomalies can now be predicted for the next season and in some places even for the next year. On the other hand, global coupled ocean-atmosphere-land models have recently approached natural climate variability on time-scales to several decades to such an extent, that these models, partly validated with data from the past, became useful for answering the following two questions: Has mankind already changed global climate? Is anthropogenic global climate change, in the coming century, surmounting at least all variability observed during the last 10,000 years? Both questions are answered by yes. For the first question, the observed patterns of warming and cooling with respect to geographical, seasonal and vertical dependence can only be explained by a combined action of global greenhouse gas increase, regional sulfate aerosol load and stratospheric ozone depletion. For the second, even low climate sensitivity and low economic growth, will lead, if no measures are taken, to a mean global warming of 1.0 C, thus surmounting the warmest phase of the holocene. Implications of these findings for the implementation of the UN Framework Convention on Climate Change will also be discussed.

  13. Australian Tropical Cyclone Activity: Interannual Prediction and Climate Change

    NASA Astrophysics Data System (ADS)

    Nicholls, N.

    2014-12-01

    It is 35 years since it was first demonstrated that interannual variations in seasonal Australian region tropical cyclone (TC) activity could be predicted using simple indices of the El Niño - Southern Oscillation (ENSO). That demonstration (Nicholls, 1979), which was surprising and unexpected at the time, relied on only 25 years of data (1950-1975), but its later confirmation eventually led to the introduction of operational seasonal tropical cyclone activity. It is worth examining how well the ENSO-TC relationship has performed, over the period since 1975. Changes in observational technology, and even how a tropical cyclone is defined, have affected the empirical relationships between ENSO and seasonal activity, and ways to overcome this in forecasting seasonal activity will be discussed. Such changes also complicate the investigation of long-term trends in cyclone activity. The early work linked cyclone activity to local sea surface temperature thereby leading to the expectation that global warming would result in an increase in cyclone activity. But studies in the 1990s (eg., Nicholls et al., 1998) suggested that such an increase in activity was not occurring, neither in the Australian region nor elsewhere. Trends in Australian tropical cyclone activity will be discussed, and the confounding influence of factors such as changes in observational technologies will be examined. Nicholls, N. 1979. A possible method for predicting seasonal tropical cyclone activity in the Australian region. Mon. Weath. Rev., 107, 1221-1224 Nicholls, N., Landsea, C., and Gill, J., 1998. Recent trends in Australian region tropical cyclone activity. Meteorology and Atmospheric Physics, 65, 197-205.

  14. 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

  15. Defining Predictive Probability Functions for Species Sampling Models

    PubMed Central

    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. PMID:24368874

  16. 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.

  17. Predictions for the ARPES spectral function of kagome antiferromagnetic insulators

    NASA Astrophysics Data System (ADS)

    Pujari, Sumiran; Lawler, Michael J.

    2011-03-01

    There are now a number of spin liquid candidate materials possibly with exotic spin-1/2 ``spinon'' excitations. Motivation by these discoveries, we consider the scaling properties of the hole spectral function for the frustrated Kagome Heisenberg antiferromagnet assuming Dirac Spin Liquid(DSL) ground state proposed for Herbertsmithite [ 2 ] . We predict a sublinear in energy power law dependence of the ARPES spectral function at certain wave vectors. Using Renormalization group techniques, we show how (gauge) fluctuations of the DSL mean field give an anomalous exponent to spinons [ 2 ] and no anomalous exponent to holons thereby leading to the sublinear power law. If this behavior is observed in experiments, they would provide strong evidence for the existence of spinons in highly frustrated magnets. S.P. gratefully acknowledges support from NSF grant DMR-1005466.

  18. Utility functions predict variance and skewness risk preferences in monkeys.

    PubMed

    Genest, Wilfried; Stauffer, William R; Schultz, Wolfram

    2016-07-26

    Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals' preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals' preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys' choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences. PMID:27402743

  19. Utility functions predict variance and skewness risk preferences in monkeys

    PubMed Central

    Genest, Wilfried; Stauffer, William R.; Schultz, Wolfram

    2016-01-01

    Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals’ preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals’ preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys’ choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences. PMID:27402743

  20. Utility functions predict variance and skewness risk preferences in monkeys.

    PubMed

    Genest, Wilfried; Stauffer, William R; Schultz, Wolfram

    2016-07-26

    Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals' preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals' preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys' choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences.

  1. Predicting activity approach based on new atoms similarity kernel function.

    PubMed

    Abu El-Atta, Ahmed H; Moussa, M I; Hassanien, Aboul Ella

    2015-07-01

    Drug design is a high cost and long term process. To reduce time and costs for drugs discoveries, new techniques are needed. Chemoinformatics field implements the informational techniques and computer science like machine learning and graph theory to discover the chemical compounds properties, such as toxicity or biological activity. This is done through analyzing their molecular structure (molecular graph). To overcome this problem there is an increasing need for algorithms to analyze and classify graph data to predict the activity of molecules. Kernels methods provide a powerful framework which combines machine learning with graph theory techniques. These kernels methods have led to impressive performance results in many several chemoinformatics problems like biological activity prediction. This paper presents a new approach based on kernel functions to solve activity prediction problem for chemical compounds. First we encode all atoms depending on their neighbors then we use these codes to find a relationship between those atoms each other. Then we use relation between different atoms to find similarity between chemical compounds. The proposed approach was compared with many other classification methods and the results show competitive accuracy with these methods.

  2. Statistical Observations and Predictions of Time Changes in Electron Flux at Geosynchronous Orbit

    NASA Astrophysics Data System (ADS)

    Olson, D. K.; Larsen, B.; Friedel, R. H.; Geoffrey, R.

    2015-12-01

    A statistical survey of time changes in particle flux values (df/dt) at geosynchronous orbit reveals trends that are instructive to predictive magnetosphere models. A single spacecraft can provide short time scale df/dt measurements, while multiple spacecraft can provide values over periods comparable to the spacecraft separation. Using data from multiple LANL-GEO spacecraft provides a unique view of temporal and spatial variations that allow us to gauge time and length scales for changing particle fluxes at GEO. These scales provide a base ability to predict the plasma environment conditions for spacecraft crossing GEO. Probability distribution functions based on electron df/dt values are used to predict the electron flux at a given magnetic local time at GEO based on prior measurements. The predictions, when compared to new data taken in the same region, provide some measure of how the electron plasma environment at GEO has changed in the interim period. These predictions are compared to data from the Van Allen Probes as their orbits cross GEO to verify the validity of this technique.

  3. 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

  4. Testable Predictions for Large-Scale Coastline-Shape Change in Response to Changing Storm Climate

    NASA Astrophysics Data System (ADS)

    Murray, A. B.; Moore, L. J.; McNamara, D.; Brenner, O.; Slott, J.

    2008-12-01

    Recent modeling (Ashton et al. 2001; Ashton and Murray, 2006a) and observations (Ashton and Murray 2006b) suggest that sandy coastlines self-organize into large-scale, plan-view shapes that depend sensitively on the regional wave climate-the distribution of influences on alongshore sediment transport from different deep-water wave-approach angles. Subsequent modeling (Slott et al., 2007) shows that even moderate changes in wave climate, as are likely to arise as storm behaviors shift in the coming century, will cause coastlines to change shape rapidly, compared to a steady-wave-climate scenario. Such large-scale shape changes involve greatly accentuated rates of local erosion, and highly variable erosion/accretion rates. A recent analysis of wave records from the Southeastern US (Komar and Allen, 2007) indicates that wave climates have already been changing over the past three decades; the heights of waves attributable to tropical storms have been increasing, changing the angular distribution of wave influences. Modeling based on these observations leads to predictions of how coastlines in this region should already be changing shape (McNamara et al., in prep.). As a case study, we are examining historical shorelines for the Carolina coastline, to test whether the predicted alongshore patterns of shoreline change can already be detected.

  5. 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.

  6. 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

  7. Better prediction of functional effects for sequence variants

    PubMed Central

    2015-01-01

    Elucidating the effects of naturally occurring genetic variation is one of the major challenges for personalized health and personalized medicine. Here, we introduce SNAP2, a novel neural network based classifier that improves over the state-of-the-art in distinguishing between effect and neutral variants. Our method's improved performance results from screening many potentially relevant protein features and from refining our development data sets. Cross-validated on >100k experimentally annotated variants, SNAP2 significantly outperformed other methods, attaining a two-state accuracy (effect/neutral) of 83%. SNAP2 also outperformed combinations of other methods. Performance increased for human variants but much more so for other organisms. Our method's carefully calibrated reliability index informs selection of variants for experimental follow up, with the most strongly predicted half of all effect variants predicted at over 96% accuracy. As expected, the evolutionary information from automatically generated multiple sequence alignments gave the strongest signal for the prediction. However, we also optimized our new method to perform surprisingly well even without alignments. This feature reduces prediction runtime by over two orders of magnitude, enables cross-genome comparisons, and renders our new method as the best solution for the 10-20% of sequence orphans. SNAP2 is available at: https://rostlab.org/services/snap2web Definitions used Delta, input feature that results from computing the difference feature scores for native amino acid and feature scores for variant amino acid; nsSNP, non-synoymous SNP; PMD, Protein Mutant Database; SNAP, Screening for non-acceptable polymorphisms; SNP, single nucleotide polymorphism; variant, any amino acid changing sequence variant. PMID:26110438

  8. 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.

  9. Deterioration in Psychosocial Functioning Predicts Relapse/Recurrence After Cognitive Therapy for Depression

    PubMed Central

    Vittengl, Jeffrey R.; Clark, Lee Anna; Jarrett, Robin B.

    2008-01-01

    Background Associations between major depressive disorder (MDD) and psychosocial functioning are incompletely understood across time and during continuation phase cognitive therapy (C-CT). We examined the validity of the Range of Impaired Functioning Tool (RIFT; Leon et al., 1999) as a measure of psychosocial functioning and its relations to depressive symptoms in C-CT and assessment-only control conditions. Methods Outpatients with recurrent MDD who responded to acute-phase cognitive therapy (A-CT) were randomized to 8 months of C-CT (n = 41) or assessment only (n = 43) and followed 16 additional months (Jarrett et al., 2001). Interviewers rated depressive symptoms and psychosocial functioning monthly. Patients completed additional self-reports. Results The RIFT converged appropriately with other measures of psychosocial functioning, depressive symptoms, cognitive content, and personality. About half (55%) of patients were psychosocially “well” (RIFT ≤ 8) during the first month post-A-CT. C-CT improved psychosocial functioning only transiently compared to the assessment control. Examined prospectively, depressive symptom level did not predict monthly changes in psychosocial functioning significantly, whereas psychosocial dysfunction level predicted monthly changes in depressive symptoms and relapse/recurrence. Limitations Findings may not generalize to other patient populations, treatments, and assessment methods. The cross-lagged correlational data structure allows only tentative conclusions about the causal effect of psychosocial functioning on depressive symptoms. Conclusions The RIFT is a valid measure of psychosocial functioning among responders to A-CT for depression. After such response, deteriorations in psychosocial functioning may signal imminent major depressive relapse/recurrence and provide targets for change during treatments focused on relapse/recurrence prevention. PMID:18539337

  10. Selection, adaptation, and predictive information in changing environments

    NASA Astrophysics Data System (ADS)

    Feltgen, Quentin; Nemenman, Ilya

    2014-03-01

    Adaptation by means of natural selection is a key concept in evolutionary biology. Individuals better matched to the surrounding environment outcompete the others. This increases the fraction of the better adapted individuals in the population, and hence increases its collective fitness. Adaptation is also prominent on the physiological scale in neuroscience and cell biology. There each individual infers properties of the environment and changes to become individually better, improving the overall population as well. Traditionally, these two notions of adaption have been considered distinct. Here we argue that both types of adaptation result in the same population growth in a broad class of analytically tractable population dynamics models in temporally changing environments. In particular, both types of adaptation lead to subextensive corrections to the population growth rates. These corrections are nearly universal and are equal to the predictive information in the environment time series, which is also the characterization of the time series complexity. This work has been supported by the James S. McDonnell Foundation.

  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. Predicting Gene-Regulation Functions: Lessons from Temperate Bacteriophages

    PubMed Central

    Teif, Vladimir B.

    2010-01-01

    Gene-regulation functions (GRF) provide a unique characteristic of a cis-regulatory module (CRM), relating the concentrations of transcription factors (input) to the promoter activities (output). The challenge is to predict GRFs from the sequence. Here we systematically consider the lysogeny-lysis CRMs of different temperate bacteriophages such as the Lactobacillus casei phage A2, Escherichia coli phages λ, and 186 and Lactococcal phage TP901-1. This study allowed explaining a recent experimental puzzle on the role of Cro protein in the lambda switch. Several general conclusions have been drawn: 1), long-range interactions, multilayer assembly and DNA looping may lead to complex GRFs that cannot be described by linear functions of binding site occupancies; 2), in general, GRFs cannot be described by the Boolean logic, whereas a three-state non-Boolean logic suffices for the studied examples; 3), studied CRMs of the intact phages seemed to have a similar GRF topology (the number of plateaus and peaks corresponding to different expression regimes); we hypothesize that functionally equivalent CRMs might have topologically equivalent GRFs for a larger class of genetic systems; and 4) within a given GRF class, a set of mechanistic-to-mathematical transformations has been identified, which allows shaping the GRF before carrying out a system-level analysis. PMID:20371324

  13. 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

  14. 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.

  15. Imaging memory and predicting postoperative memory decline in temporal lobe epilepsy: Insights from functional imaging.

    PubMed

    Dupont, S

    2015-03-01

    After medial temporal lobe epilepsy (MTLE) surgery, there is considerable individual variation in the extent, nature and direction of postoperative memory change. Before surgery, epileptic patients who are surgery candidates need precise information about the potential cognitive after effects, and particularly in temporal lobe epilepsy, postoperative memory changes. Clinical and neuropsychological data may bring useful information to predict the postoperative memory outcome, but, these data are not always sufficient to replace the Wada test, considered for a long time, as the gold standard to predict postoperative decline following surgery. In any case, numerous studies demonstrate that the Wada procedure can be nowadays reliably replaced by functional MRI (fMRI) activation studies. A vast majority of fMRI studies suggest that it is the functional adequacy of the resected hippocampus rather than the functional reserve of the contralateral hippocampus that determines the extent of postoperative memory decline. In addition, new functional neuroimaging procedures that explore more widespread network disruptions commonly found in MTLE such as diffusion-tensor imaging (DTI) or connectivity studies could in the future constitute a reliable approach combined with fMRI activation studies to significantly improve the prediction of postsurgical memory decline.

  16. Sexual abuse predicts functional somatic symptoms: an adolescent population study.

    PubMed

    Bonvanie, Irma J; van Gils, Anne; Janssens, Karin A M; Rosmalen, Judith G M

    2015-08-01

    The main aim of this study was to investigate the effect of childhood sexual abuse on medically not well explained or functional somatic symptoms (FSSs) in adolescents. We hypothesized that sexual abuse predicts higher levels of FSSs and that anxiety and depression contribute to this relationship. In addition, we hypothesized that more severe abuse is associated with higher levels of FSSs and that sexual abuse is related to gastrointestinal FSSs in particular. This study was part of the Tracking Adolescents' Individual Lives Survey (TRAILS): a general population cohort which started in 2001 (N=2,230; 50.8% girls, mean age 11.1 years). The current study uses data of 1,680 participants over four assessment waves (75% of baseline, mean duration of follow-up: 8 years). FSSs were measured by the Somatic Complaints subscale of the Youth Self-Report at all waves. Sexual abuse before the age of sixteen was assessed retrospectively with a questionnaire at T4. To test the hypotheses linear mixed models were used adjusted for age, sex, socioeconomic status, anxiety and depression. Sexual abuse predicted higher levels of FSSs after adjustment for age sex and socioeconomic status (B=.06) and after additional adjustment for anxiety and depression (B=.03). While sexual abuse involving physical contact significantly predicted the level of FSSs (assault; B=.08, rape; B=.05), non-contact sexual abuse was not significantly associated with FSSs (B=.04). Sexual abuse was not a stronger predictor of gastrointestinal FSSs (B=.06) than of all FSSs. Further research is needed to clarify possible mechanisms underlying relationship between sexual abuse and FSSs. PMID:26142915

  17. 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.

  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

    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

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. Predicting biodiversity change and averting collapse in agricultural landscapes.

    PubMed

    Mendenhall, Chase D; Karp, Daniel S; Meyer, Christoph F J; Hadly, Elizabeth A; Daily, Gretchen C

    2014-05-01

    The equilibrium theory of island biogeography is the basis for estimating extinction rates and a pillar of conservation science. The default strategy for conserving biodiversity is the designation of nature reserves, treated as islands in an inhospitable sea of human activity. Despite the profound influence of islands on conservation theory and practice, their mainland analogues, forest fragments in human-dominated landscapes, consistently defy expected biodiversity patterns based on island biogeography theory. Countryside biogeography is an alternative framework, which recognizes that the fate of the world's wildlife will be decided largely by the hospitality of agricultural or countryside ecosystems. Here we directly test these biogeographic theories by comparing a Neotropical countryside ecosystem with a nearby island ecosystem, and show that each supports similar bat biodiversity in fundamentally different ways. The island ecosystem conforms to island biogeographic predictions of bat species loss, in which the water matrix is not habitat. In contrast, the countryside ecosystem has high species richness and evenness across forest reserves and smaller forest fragments. Relative to forest reserves and fragments, deforested countryside habitat supports a less species-rich, yet equally even, bat assemblage. Moreover, the bat assemblage associated with deforested habitat is compositionally novel because of predictable changes in abundances by many species using human-made habitat. Finally, we perform a global meta-analysis of bat biogeographic studies, spanning more than 700 species. It generalizes our findings, showing that separate biogeographic theories for countryside and island ecosystems are necessary. A theory of countryside biogeography is essential to conservation strategy in the agricultural ecosystems that comprise roughly half of the global land surface and are likely to increase even further.

  5. Extreme hydrometeorological events and climate change predictions in Europe

    NASA Astrophysics Data System (ADS)

    Millán, Millán M.

    2014-10-01

    Field meteorological data collected in several European Commission projects (from 1974 to 2011) were re-analysed in the context of a perceived reduction in summer storms around the Western Mediterranean Basin (WMB). The findings reveal some hitherto overlooked processes that raise questions about direct impacts on European hydrological cycles, e.g., extreme hydrometeorological events, and about the role of feedbacks on climate models and climate predictions. For instance, the summer storms are affected by land-use changes along the coasts and mountain slopes. Their loss triggers a chain of events that leads to an Accumulation Mode (AM) where water vapour and air pollutants (ozone) become stacked in layers, up to 4000(+) m, over the WMB. The AM cycle can last 3-5 consecutive days, and recur several times each month from mid May to late August. At the end of each cycle the accumulated water vapour can feed Vb track events and generate intense rainfall and summer floods in Central Europe. Venting out of the water vapour that should have precipitated within the WMB increases the salinity of the sea and affects the Atlantic-Mediterranean Salinity valve at Gibraltar. This, in turn, can alter the tracks of Atlantic Depressions and their frontal systems over Atlantic Europe. Another effect is the greenhouse heating by water vapour and photo-oxidants (e.g., O3) when layered over the Basin during the AM cycle. This increases the Sea Surface Temperature (SST), and the higher SST intensifies torrential rain events over the Mediterranean coasts in autumn. All these processes raise research questions that must be addressed to improve the meteorological forecasting of extreme events, as well as climate model predictions.

  6. 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

  7. Predicting biodiversity change and averting collapse in agricultural landscapes.

    PubMed

    Mendenhall, Chase D; Karp, Daniel S; Meyer, Christoph F J; Hadly, Elizabeth A; Daily, Gretchen C

    2014-05-01

    The equilibrium theory of island biogeography is the basis for estimating extinction rates and a pillar of conservation science. The default strategy for conserving biodiversity is the designation of nature reserves, treated as islands in an inhospitable sea of human activity. Despite the profound influence of islands on conservation theory and practice, their mainland analogues, forest fragments in human-dominated landscapes, consistently defy expected biodiversity patterns based on island biogeography theory. Countryside biogeography is an alternative framework, which recognizes that the fate of the world's wildlife will be decided largely by the hospitality of agricultural or countryside ecosystems. Here we directly test these biogeographic theories by comparing a Neotropical countryside ecosystem with a nearby island ecosystem, and show that each supports similar bat biodiversity in fundamentally different ways. The island ecosystem conforms to island biogeographic predictions of bat species loss, in which the water matrix is not habitat. In contrast, the countryside ecosystem has high species richness and evenness across forest reserves and smaller forest fragments. Relative to forest reserves and fragments, deforested countryside habitat supports a less species-rich, yet equally even, bat assemblage. Moreover, the bat assemblage associated with deforested habitat is compositionally novel because of predictable changes in abundances by many species using human-made habitat. Finally, we perform a global meta-analysis of bat biogeographic studies, spanning more than 700 species. It generalizes our findings, showing that separate biogeographic theories for countryside and island ecosystems are necessary. A theory of countryside biogeography is essential to conservation strategy in the agricultural ecosystems that comprise roughly half of the global land surface and are likely to increase even further. PMID:24739971

  8. The relationship between change in cognition and change in functional ability in schizophrenia during cognitive and psychosocial rehabilitation.

    PubMed

    Rispaud, Samuel G; Rose, Jennifer; Kurtz, Matthew M

    2016-10-30

    While a wealth of studies have evaluated cross-sectional links between cognition and functioning in schizophrenia, few have investigated the relationship between change in cognition and change in functioning in the context of treatment trials targeted at cognition. Identifying cognitive skills that, when improved, predict improvement in functioning will guide the development of more targeted rehabilitation for this population. The present study identifies the relationship between change in specific cognitive skills and change in functional ability during one year of cognitive rehabilitation. Ninety-six individuals with schizophrenia were assessed with a battery of cognitive measures and a measure of performance-based functioning before and after cognitive training consisting of either drill-and-practice cognitive remediation or computer skills training. Results revealed that while working and episodic memory, problem-solving, and processing speed skills all improved during the trial, only improved working memory and processing speed skills predicted improvement in functional ability. Secondary analyses revealed these relationships were driven by individuals who showed a moderate level (SD≥0.5) of cognitive improvement during the trial. These findings suggest that while a variety of cognitive skills may improve during training targeted at cognition, only improvements in a subset of cognitive functions may translate into functional gains.

  9. Balance assessments for predicting functional ankle instability and stable ankles.

    PubMed

    Ross, Scott E; Linens, Shelley W; Wright, Cynthia J; Arnold, Brent L

    2011-10-01

    A number of instrumented and non-instrumented measures are used to detect balance deficits associated with functional ankle instability (FAI). Determining outcome measures that detect balance deficits associated with FAI might assist clinicians in identifying impairments that may otherwise go undetected with less responsive balance measures. Thus, our objective was to determine the balance measure that best predicted ankle group membership (FAI or stable ankle). Participants included 17 subjects without a history of ankle sprains (168±9 cm, 66±14 kg, 24±5 yr) and 17 subjects with FAI (172±9 cm, 71±11 kg, 22±3 yr). Balance trials were performed without vision and subjects stood on a single leg as motionless as possible for 20s. Balance was quantified with center-of-pressure measures (velocity, area) and error score. Measures were positively correlated with each other (r range: 0.60-0.76). The multifactorial model with all three measures best predicted group membership (F((3,30))=7.20, P=0.001; R(2)=0.42; percent classified correctly=77%), and was followed by the multifactorial model with resultant center-of-pressure velocity and error score (F((2,31))=8.73, P=0.001; R(2)=0.36; percent classified correctly=74%). The resultant center-of-pressure velocity (F((1,32))=13.46, P=0.001; R(2)=0.30; percent classified correctly=74%; unique variance=12.7%) and error score (F((1,32))=12.51, P=0.001; R(2)=0.28; percent classified correctly=71%; unique variance=12.0%) predicted group membership; however, 95th percentile center-of-pressure area ellipse did not (F((1,32))=4.16, P=0.05; R(2)=0.12; percent classified correctly=65%; unique variance=5.8%). A multifactorial single leg balance assessment is best for predicting group membership. COPV is the best single predictor of group membership, but clinicians may use error score to identify deficits associated with FAI if force plates are not available. PMID:21868225

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

    PubMed

    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

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

    PubMed

    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.

  12. 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

  13. 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. PMID:27309309

  14. 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.

  15. 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.

  16. 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

  17. Uncertainty levels in predicted patterns of anthropogenic climate change

    NASA Astrophysics Data System (ADS)

    Barnett, Tim P.; Hegerl, Gabriele; Knutson, Tom; Tett, Simon

    2000-06-01

    This paper investigates the uncertainties in different model estimates of an expected anthropogenic signal in the near-surface air temperature field. We first consider nine coupled global climate models (CGCMs) forced by CO2 increasing at the rate of 1%/yr. Averaged over years 71-80 of their integrations, the approximate time of CO2 doubling, the models produce a global mean temperature change that agrees to within about 25% of the nine model average. However, the spatial patterns of change can be rather different. This is likely to be due to different representations of various physical processes in the respective models, especially those associated with land and sea ice processes. We next analyzed 11 different runs from three different CGCMs, each forced by observed/projected greenhouse gases (GHG) and estimated direct sulfate aerosol effects. Concentrating on the patterns of trend of near-surface air temperature change over the period 1945-1995, we found that the raw individual model simulations often bore little resemblance to each other or to the observations. This was due partially to large magnitude, small-scale spatial noise that characterized all the model runs, a feature resulting mainly from internal model variability. Heavy spatial smoothing and ensemble averaging improved the intermodel agreement. The existence of substantial differences between different realizations of an ensemble produced by identical forcing almost requires that detection and attribution work be done with ensembles of scenario runs, as single runs can be misleading. Application of recent detection and attribution methods, coupled with ensemble averaging, produced a reasonably consistent match between model predictions of expected patterns of temperature trends due to a combination of GHG and direct sulfate aerosols and those observed. This statement is provisional since the runs studied here did not include other anthropogenic pollutants thought to be important (e.g., indirect

  18. 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

  19. 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.

  20. 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.

  1. 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. PMID:25903243

  2. 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

  3. Impact of heterogeneous chemistry on model predictions of ozone changes

    SciTech Connect

    Granier, C.; Brasseur, G. )

    1992-11-20

    A two-dimensional chemical/transport model of the middle atmosphere is used to assess the importance of chemical heterogeneous processes in the polar regions (on polar stratospheric clouds (PSCs)) and at other latitudes (on sulfate aerosols). When conversion on type I and type II PSCs of N[sub 2]O[sub 5] into HNO[sub 3] and of CIONO[sub 2] into reactive forms of chlorine is taken into account, enhanced CIO concentrations lead to the formation of a springtime ozone hole over the Antarctic continent; no such major reduction in the ozone column is found in the Arctic region. When conversion of nitrogen and chlorine compounds is assumed to occur on sulfate particles in the lower stratosphere, significant perturbations in the chemistry are also found. For background aerosol conditions, the concentration of nitric acid is enhanced and agrees with observed values, while that of nitrogen oxides is reduced and agrees less than if heterogeneous processes are ignored in the calculations. The concentration of the OH radical is significantly increased. Ozone number density appears to become larger between 16 and 30 km but smaller below 16 km, especially at high latitudes. The ozone column is only slightly modified, except at high latitudes where it is substantially reduced if the CIONO[sub 2] conversion into reactive chlorine is considered. After a large volcanic eruption these changes are further exacerbated. The ozone budget in the lower stratrosphere becomes less affected by nitrogen oxides but is largely controlled by the CIO[sub x] and HO[sub x] chemistries. A substantial decrease in the ozone column is predicted as a result of the Pinatubo volcanic eruption, mostly in winter at middle and high latitudes. 62 refs., 18 figs., 3 tabs.

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

    PubMed Central

    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

    2015-01-01

    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. PMID:25567651

  6. Age Related Changes in Autonomic Functions

    PubMed Central

    Amir, Mohammed; Pakhare, Abhijit; Rathi, Preeti; Chaudhary, Lalita

    2016-01-01

    Introduction Autonomic Nervous System (ANS) imbalance may trigger or enhance pathology in different organ systems that varies in different age groups hence objective of present study was to evaluate association of different Age-groups with autonomic functions. Materials and Methods A cross-sectional study was conducted in 62 healthy volunteers in Department of Physiology LLRM Medical College Meerut, India. Volunteers were divided into three groups as younger (15-45 years), middle (45-60) and elder age (above 60), Autonomic functions were tested in three domains viz. Cardio-vagal, adrenergic and sudomotor functions. Numerical data was summarized as mean and standard deviation and categorical data as count and percentage. ANOVA and Chi-square test were used to find difference among groups, p<0.05 was considered statistically significant. Results Mean ± standard deviation OHT(Orthostatic Hypotension Test) among of younger, middle and elder age groups were 8.80±2.28, 13.40±4.64 and 21.82±6.04 respectively which represent decrease in sympathetic functions with age (p<0.001). Cardio-vagal or parasympathetic responses indicated by DBT (Deep Breathing Test) Valsalva and 30:15 ratio of HR response to standing tests has shown statistically significant (p<0.001) decrease in mean response with increasing age. Sudomotor response appeared normal in younger and middle group but was interrupted in more than half of elderly people (p<0.001). Conclusion Sympathetic responses & para-sympathetic responses have shown the significant decline with increasing age group. Sudomotor responses were partially interrupted in elderly age group. PMID:27134865

  7. Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure

    PubMed Central

    Nilmeier, Jerome P.; Kirshner, Daniel A.; Wong, Sergio E.; Lightstone, Felice C.

    2013-01-01

    We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues – The Catalytic Site Atlas (CSA). Two main processes are involved. The first process is a rapid protein-to-template matching algorithm that scales quadratically with target protein size and linearly with template size. The second process incorporates a number of physical descriptors, including binding site predictions, in a logistic scoring procedure to re-score matches found in Process 1. This approach shows very good performance overall, with a Receiver-Operator-Characteristic Area Under Curve (AUC) of 0.971 for the training set evaluated. The procedure is able to process cofactors, ions, nonstandard residues, and point substitutions for residues and ions in a robust and integrated fashion. Sites with only two critical (catalytic) residues are challenging cases, resulting in AUCs of 0.9411 and 0.5413 for the training and test sets, respectively. The remaining sites show excellent performance with AUCs greater than 0.90 for both the training and test data on templates of size greater than two critical (catalytic) residues. The procedure has considerable promise for larger scale searches. PMID:23675414

  8. Prediction of Functional Outcome in Axonal Guillain-Barre Syndrome

    PubMed Central

    2016-01-01

    Objective To identify the factors that could predict the functional outcome in patients with the axonal type of Guillain-Barre syndrome (GBS). Methods Two hundred and two GBS patients admitted to our university hospital between 2003 and 2014 were reviewed retrospectively. We defined a good outcome as being "able to walk independently at 1 month after onset" and a poor outcome as being "unable to walk independently at 1 month after onset". We evaluated the factors that differed between the good and poor outcome groups. Results Twenty-four patients were classified into the acute motor axonal neuropathy type. There was a statistically significant difference between the good and poor outcome groups in terms of the GBS disability score at admission, and GBS disability score and Medical Research Council sum score at 1 month after admission. In an electrophysiologic analysis, the good outcome group showed greater amplitude of median, ulnar, deep peroneal, and posterior tibial nerve compound muscle action potentials (CMAP) and greater amplitude of median, ulnar, and superficial peroneal sensory nerve action potentials (SNAP) than the poor outcome group. Conclusion A lower GBS disability score at admission, high amplitude of median, ulnar, deep peroneal, and posterior tibial CMAPs, and high amplitude of median, ulnar, and superficial peroneal SNAPs were associated with being able to walk at 1 month in patients with axonal GBS. PMID:27446785

  9. Anisotropic yield function capable of predicting eight ears

    NASA Astrophysics Data System (ADS)

    Yoon, J. H.; Cazacu, O.

    2011-08-01

    Deep drawing of a cylindrical cup from a rolled sheet is one of the typical forming operations where the effect of this anisotropy is most evident. Indeed, it is well documented in the literature that the number of ears and the shape of the earing pattern correlate with the r-values profile. For the strongly textured aluminum alloy AA 5042 (Numisheet Benchmark 2011), the experimental r-value distribution has two minima between the rolling and transverse direction data provided for this show that the r-value along the transverse direction (TD) is five times larger than the value corresponding to the rolling direction. Therefore, it is expected that there are more that the earing profile has more than four ears. The main objective of this paper is to assess whether a new form of CPB06ex2 yield function (Plunkett et al. (2008)) tailored for metals with no tension-compression asymmetry is capable of predicting more than four ears for this material.

  10. Rapid catalytic template searching as an enzyme function prediction procedure.

    PubMed

    Nilmeier, Jerome P; Kirshner, Daniel A; Wong, Sergio E; Lightstone, Felice C

    2013-01-01

    We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues--The Catalytic Site Atlas (CSA). Two main processes are involved. The first process is a rapid protein-to-template matching algorithm that scales quadratically with target protein size and linearly with template size. The second process incorporates a number of physical descriptors, including binding site predictions, in a logistic scoring procedure to re-score matches found in Process 1. This approach shows very good performance overall, with a Receiver-Operator-Characteristic Area Under Curve (AUC) of 0.971 for the training set evaluated. The procedure is able to process cofactors, ions, nonstandard residues, and point substitutions for residues and ions in a robust and integrated fashion. Sites with only two critical (catalytic) residues are challenging cases, resulting in AUCs of 0.9411 and 0.5413 for the training and test sets, respectively. The remaining sites show excellent performance with AUCs greater than 0.90 for both the training and test data on templates of size greater than two critical (catalytic) residues. The procedure has considerable promise for larger scale searches.

  11. Functional changes in littoral macroinvertebrate communities in response to watershed-level anthropogenic stress.

    PubMed

    Kovalenko, Katya E; Brady, Valerie J; Ciborowski, Jan J H; Ilyushkin, Sergey; Johnson, Lucinda B

    2014-01-01

    Watershed-scale anthropogenic stressors have profound effects on aquatic communities. Although several functional traits of stream macroinvertebrates change predictably in response to land development and urbanization, little is known about macroinvertebrate functional responses in lakes. We assessed functional community structure, functional diversity (Rao's quadratic entropy) and voltinism in macroinvertebrate communities sampled across the full gradient of anthropogenic stress in Laurentian Great Lakes coastal wetlands. Functional diversity and voltinism significantly decreased with increasing development, whereas agriculture had smaller or non-significant effects. Functional community structure was affected by watershed-scale development, as demonstrated by an ordination analysis followed by regression. Because functional community structure affects energy flow and ecosystem function, and functional diversity is known to have important implications for ecosystem resilience to further environmental change, these results highlight the necessity of finding ways to remediate or at least ameliorate these effects. PMID:25006811

  12. Functional Changes in Littoral Macroinvertebrate Communities in Response to Watershed-Level Anthropogenic Stress

    PubMed Central

    Kovalenko, Katya E.; Brady, Valerie J.; Ciborowski, Jan J. H.; Ilyushkin, Sergey; Johnson, Lucinda B.

    2014-01-01

    Watershed-scale anthropogenic stressors have profound effects on aquatic communities. Although several functional traits of stream macroinvertebrates change predictably in response to land development and urbanization, little is known about macroinvertebrate functional responses in lakes. We assessed functional community structure, functional diversity (Rao’s quadratic entropy) and voltinism in macroinvertebrate communities sampled across the full gradient of anthropogenic stress in Laurentian Great Lakes coastal wetlands. Functional diversity and voltinism significantly decreased with increasing development, whereas agriculture had smaller or non-significant effects. Functional community structure was affected by watershed-scale development, as demonstrated by an ordination analysis followed by regression. Because functional community structure affects energy flow and ecosystem function, and functional diversity is known to have important implications for ecosystem resilience to further environmental change, these results highlight the necessity of finding ways to remediate or at least ameliorate these effects. PMID:25006811

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

    PubMed

    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.

  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. 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.

  16. Investigating repetition and change in musical rhythm by functional MRI.

    PubMed

    Danielsen, A; Otnæss, M K; Jensen, J; Williams, S C R; Ostberg, B C

    2014-09-01

    Groove-based rhythm is a basic and much appreciated feature of Western popular music. It is commonly associated with dance, movement and pleasure and is characterized by the repetition of a basic rhythmic pattern. At various points in the musical course, drum breaks occur, representing a change compared to the repeated pattern of the groove. In the present experiment, we investigated the brain response to such drum breaks in a repetitive groove. Participants were scanned with functional magnetic resonance imaging (fMRI) while listening to a previously unheard naturalistic groove with drum breaks at uneven intervals. The rhythmic pattern and the timing of its different parts as performed were the only aspects that changed from the repetitive sections to the breaks. Differences in blood oxygen level-dependent activation were analyzed. In contrast to the repetitive parts, the drum breaks activated the left cerebellum, the right inferior frontal gyrus (RIFG), and the superior temporal gyri (STG) bilaterally. A tapping test using the same stimulus showed an increase in the standard deviation of inter-tap-intervals in the breaks versus the repetitive parts, indicating extra challenges for auditory-motor integration in the drum breaks. Both the RIFG and STG have been associated with structural irregularity and increase in musical-syntactical complexity in several earlier studies, whereas the left cerebellum is known to play a part in timing. Together these areas may be recruited in the breaks due to a prediction error process whereby the internal model is being updated. This concurs with previous research suggesting a network for predictive feed-forward control that comprises the cerebellum and the cortical areas that were activated in the breaks. PMID:24972303

  17. 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.

  18. Importance of atmospheric angular momentum function in non-linear prediction of length of day variation

    NASA Astrophysics Data System (ADS)

    Wang, Q. J.; Liao, D. C.; Zhou, Y. H.; Liao, X. H.

    2008-01-01

    Prediction of the variations of the length of day (LOD) is of great importance in both scientific issues and practical applications. However, due to the complex time-variable characteristics of the LOD variation, it's usually difficult to obtain satisfied prediction results by conventional linear time series analysis methods. The artificial neural networks (ANN) is a non-linear information processing system. This study employs the ANN to predict the LOD change. The topology of the ANN model is determined based on the criterion of minimization of the root mean square error (RMSE). For most of the studies that use ANN to predict the LOD, the influence of global atmospheric movements on the variations of the LOD hasn't been considered. Considering the close connection between the LOD variation and the atmospheric circulation movement, and the capability of simulating and forecasting the axial atmospheric angular momentum (AAM) function with global atmospheric circulation pattern, the axial AAM is added into the ANN model as an additional input parameter to predict the LOD variation. The daily LOD series in this study are from the C04 series of the International Earth rotation and reference systems service (IERS), spanning from 1962 to 2005. We first removed the contributions of the 62 zonal Earth tides from the LOD changes with periods from 5 days to 18.6 years according to IERS Convention 2003, and the effects that can be described by functional models, e.g. the annual and semi-annual oscillations, the terms whose periods are 1, 1/2, 1/3 of the length of the whole data set. Only the residuals between the modeled and the observed LODRs, are used for training. Likewise, the axial AAM series are also de-trended. The residuals of LODR and axial AAM series are used to train the networks. The trained networks are applied to predict the LODR variation for time interval of 1 to 40 days. For comparisons, we also use the LODR only to construct the ANN model and to predict the

  19. Changes in cardiopulmonary function induced by nanoparticles.

    PubMed

    Mann, Erin E; Thompson, Leslie C; Shannahan, Jonathan H; Wingard, Christopher J

    2012-01-01

    Nanoparticles (NP) are highly applicable in a variety of technological and biomedical fields because of their unique physicochemical properties. The increased development and utilization of NP has amplified human exposure and raised concerns regarding their potential to generate toxicity. The biological impacts of NP exposures have been shown to be dependent on aerodynamic size, chemical composition, and the route of exposure (oral, dermal, intravenous, and inhalation), while recent research has demonstrated the cardiovascular (CV) system as an important site of toxicity. Proposed mechanisms responsible for these effects include inflammation, oxidative stress, autonomic dysregulation, and direct interactions of NP with CV cells. Specifically, NP have been shown to impact vascular endothelial cell (EC) integrity, which may disrupt the dynamic endothelial regulation of vascular tone, possibly altering systemic vascular resistance and impairing the appropriate distribution of blood flow throughout the circulation. Cardiac consequences of NP-induced toxicity include disruption of heart rate and electrical activity via catecholamine release, increased susceptibility to ischemia/reperfusion injury, and modified baroreceptor control of cardiac function. These and other CV outcomes likely contribute to adverse health effects promoting myocardial infarction, hypertension, cardiac arrhythmias, and thrombosis. This review will assess the current knowledge regarding the principle sites of CV toxicity following NP exposure. Furthermore, we will propose mechanisms contributing to altered CV function and hypothesize possible outcomes resulting in decrements in human health.

  20. Functional identity and functional structure change through succession in a rocky intertidal marine herbivore assemblage.

    PubMed

    Aguilera, Moisés A; Navarrete, Sergio A

    2012-01-01

    Despite the great interest in characterizing the functional structure and resilience of functional groups in natural communities, few studies have examined in which way the roles and relationships of coexisting species change during community succession, a fundamental and natural process that follows the release of new resources in terrestrial and aquatic ecosystems. Variation in algal traits that characterize different phases and stages of community succession on rocky shores are likely to influence the magnitude, direction of effects, and the level of redundancy and complementarity in the diverse assemblage of herbivores. Two separate field experiments were conducted to quantify per capita and population effects and the functional relationship (i.e., redundancy or complementarity) of four herbivore species found in central Chile during early and late algal succession. The first experiment examined grazer effects on the colonization and establishment of early-succession algal species. The second experiment examined effects on the late-successional, dominant corticated alga Mazzaella laminarioides. Complementary laboratory experiments with all species and under natural environmental conditions allowed us to further characterize the collective effects of these species. We found that, during early community succession, all herbivore species had similar effects on the ephemeral algae, ulvoids, but only during the phase of colonization. Once these algae were established, only a subset of the species was able to control their abundance. During late succession, only the keyhole limpet Fissurella crassa could control corticated Mazzaella. The functional relationships among these species changed dramatically from redundant effects on ephemeral algae during early colonization, to a more complementary role on established early-successional algae, to a dominant (i.e., keystone) effect on late succession. This study highlights that functional relationship within consumer

  1. 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.

  2. 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. PMID:23129709

  3. 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.

  4. The conformational signature of β-arrestin2 predicts its trafficking and signalling functions.

    PubMed

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

    2016-03-31

    Arrestins are cytosolic proteins that regulate G-protein-coupled receptor (GPCR) desensitization, internalization, trafficking and signalling. Arrestin recruitment uncouples GPCRs from heterotrimeric G proteins, and targets the proteins for internalization via clathrin-coated pits. Arrestins also function as ligand-regulated scaffolds that recruit multiple non-G-protein effectors into GPCR-based 'signalsomes'. Although the dominant function(s) of arrestins vary between receptors, the mechanism whereby different GPCRs specify these divergent functions is unclear. Using a panel of intramolecular fluorescein arsenical hairpin (FlAsH) bioluminescence resonance energy transfer (BRET) reporters to monitor conformational changes in β-arrestin2, here we show that GPCRs impose distinctive arrestin 'conformational signatures' that reflect the stability of the receptor-arrestin complex and role of β-arrestin2 in activating or dampening downstream signalling 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 β-arrestin2 conformation. Our findings demonstrate that information about ligand-receptor conformation is encoded within the population average β-arrestin2 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 ligands and in identifying factors that dictate arrestin conformation and function. PMID:27007854

  5. 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

  6. The role of plant functional trade-offs for biodiversity changes and biome shifts under scenarios of global climatic change

    NASA Astrophysics Data System (ADS)

    Reu, B.; Zaehle, S.; Proulx, R.; Bohn, K.; Kleidon, A.; Pavlick, R.; Schmidtlein, S.

    2010-10-01

    The global geographic distribution of biodiversity and biomes is determined by species-specific physiological tolerances to climatic constraints. Current models implement empirical bioclimatic relationships to predict present-day vegetation patterns and to forecast biodiversity changes and biome shifts under climatic change. In this paper, we consider plant functional trade-offs and their interactions with climatic changes to forecast and explain biodiversity changes and biome shifts. The Jena Diversity model (JeDi) simulates plant survival according to essential plant functional trade-offs, including eco-physiological processes such as water uptake, photosynthesis, allocation, reproduction and phenology. We apply JeDi to quantify biodiversity changes and biome shifts between present-day and a range of possible future climates from two scenarios (A2 and B1) and seven global climate models using metrics of plant functional richness and functional identity. Our results show (i) a significant biodiversity loss in the tropics, (ii) an increase in biodiversity at mid and high latitudes, and (iii) a poleward shift of biomes. While these results are consistent with the findings of empirical approaches, we are able to explain them in terms of the plant functional trade-offs involved in the allocation, metabolic and reproduction strategies of plants. We conclude that general aspects of plant physiological tolerances can be derived from plant functional trade-offs, which may provide a useful process- and trait-based alternative to bioclimatic relationships in order to address questions about the causes of biodiversity changes and biome shifts.

  7. 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

  8. Stages of change or changes of stage? Predicting transitions in transtheoretical model stages in relation to healthy food choice.

    PubMed

    Armitage, Christopher J; Sheeran, Paschal; Conner, Mark; Arden, Madelynne A

    2004-06-01

    Relatively little research has examined factors that account for transitions between transtheoretical model (TTM) stages of change. The present study (N = 787) used sociodemographic, TTM, and theory of planned behavior (TPB) variables, as well as theory-driven interventions to predict changes in stage. Longitudinal analyses revealed that sociodemographic, TPB, and 1 of the interventions predicted transitions between most stages of change. In fact, only progression from the preparation stage was not predictable. However, given that this change of stage marks the transition between cognition and actual behavior, the identification of variables that bridge this gap is crucial for the development of interventions to promote stage transitions. PMID:15279532

  9. 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.

  10. 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. PMID:1958548

  11. 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.

  12. 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.

  13. 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…

  14. Gradient radial basis function networks for nonlinear and nonstationary time series prediction.

    PubMed

    Chng, E S; Chen, S; Mulgrew, B

    1996-01-01

    We present a method of modifying the structure of radial basis function (RBF) network to work with nonstationary series that exhibit homogeneous nonstationary behavior. In the original RBF network, the hidden node's function is to sense the trajectory of the time series and to respond when there is a strong correlation between the input pattern and the hidden node's center. This type of response, however, is highly sensitive to changes in the level and trend of the time series. To counter these effects, the hidden node's function is modified to one which detects and reacts to the gradient of the series. We call this new network the gradient RBF (GRBF) model. Single and multistep predictive performance for the Mackey-Glass chaotic time series were evaluated using the classical RBF and GRBF models. The simulation results for the series without and with a tine-varying mean confirm the superior performance of the GRBF predictor over the RBF predictor.

  15. 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.

  16. 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

  17. Changes in goal selection induced by cue conflicts are in register with predictions from changes in place cell field locations.

    PubMed

    Kubie, John L; Fenton, Andre; Novikov, Nicolay; Touretzky, David; Muller, Robert U

    2007-08-01

    In the cognitive mapping theory of hippocampal function, currently active place cells represent a rat's spatial location (J. O'Keefe & L. Nadel, 1978). A systematic shift of firing field locations should therefore produce a similar shift in a rat's judgment of its location. A. A. Fenton, G. Csizmadia, and R. U. Muller (2000a) recorded place cells in cylinders with 2 cue cards separated by 135 degrees . When the separation was changed, firing fields moved systematically, as described by a vector-field equation (A. A. Fenton, G. Csizmadia, & R. U. Muller, 2000b). Given this cohesive movement of firing fields, the mapping theory predicts that a rat's decisions about the location of an unmarked goal should move after card separation changes, as described by the vector-field equation. The authors tested this reasoning with a task in which the rat earned a food reward by pausing in a small, unmarked goal zone. When cues were shifted in the absence of reward, goal choice shifts were accurately predicted by the vector-field equation, providing strong support for the notion that a rat's judgment of its spatial location is intimately related to the across-cell discharge pattern of simultaneously active place cells.

  18. Predicting risk selection following major changes in Medicare.

    PubMed

    Pizer, Steven D; Frakt, Austin B; Feldman, Roger

    2008-04-01

    The Medicare Modernization Act of 2003 created several new types of private insurance plans within Medicare, starting in 2006. Some of these plan types previously did not exist in the commercial market and there was great uncertainty about their prospects. In this paper, we show that statistical models and historical data from the Medicare Current Beneficiary Survey can be used to predict the experience of new plan types with reasonable accuracy. This lays the foundation for the analysis of program modifications currently under consideration. We predict market share, risk selection, and stability for the most prominent new plan type, the stand-alone Medicare prescription drug plan (PDP). First, we estimate a model of consumer choice across Medicare insurance plans available in the data. Next, we modify the data to include PDPs and use the model to predict the probability of enrollment for each beneficiary in each plan type. Finally, we calculate mean-adjusted actual spending by plan type. We predict that adverse selection into PDPs will be substantial, but that enrollment and premiums will be stable. Our predictions correspond well to actual experience in 2006. PMID:17557273

  19. 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.

  20. Interdecadal change of interannual variability and predictability of two types of ENSO using a MME method

    NASA Astrophysics Data System (ADS)

    Jeong, H. I.; Ahn, J. B.; Lee, J. Y.; Alessandri, A.; Hendon, H.

    2014-12-01

    A significant interdecadal climate shift of interannual variability and predictability of two types of the El Nino-Southern Oscillation (ENSO), namely the canonical or eastern Pacific (EP)-type and Modoki or central Pacific (CP) type, are investigated. Using the retrospective forecasts of six-state-of-the-art coupled models and their multi-model ensemble (MME) for December-January-February during the period of 1972-2005 along with corresponding observed and reanalyzed data, we examine the climate regime shift that occurred in the winter of 1988/1989 and how the shift affected interannual variability and predictability of two types of ENSO for the two periods of 1972-1988 (hereafter PRE) and 1989-2005 (hereafter POST). The result first shows substantial interdecadal changes of observed sea surface temperature (SST) in mean state and variability over the western and central Pacific attributable to the significant warming trend in the POST period. In the POST period, the SST variability increased (decreased) significantly over the western (eastern) Pacific. The MME realistically reproduces the observed interdecadal changes with 1- and 4-month forecast lead time. It is found that the CP-type ENSO was more prominent and predictable during the POST than the PRE period while there was no apparent difference in the variability and predictability of the EP-type ENSO between two periods. Note that the second empirical orthogonal function mode of the Pacific SST during the POST period represents the CP-type ENSO but that during the PRE period captures the ENSO transition phase. The MME better predicts the former than the latter. We also investigate distinctive regional impacts associated with the two types of ENSO during the two periods.

  1. Interdecadal change of interannual variability and predictability of two types of ENSO

    NASA Astrophysics Data System (ADS)

    Jeong, Hye-In; Ahn, Joong-Bae; Lee, June-Yi; Alessandri, Andrea; Hendon, Harry H.

    2015-02-01

    A significant interdecadal climate shift of interannual variability and predictability of two types of the El Niño-Southern Oscillation (ENSO), namely the canonical or eastern Pacific (EP)-type and Modoki or central Pacific (CP) type, are investigated. Using the retrospective forecasts of six-state-of-the-art coupled models and their multi-model ensemble (MME) for December-January-February during the period of 1972-2005 along with corresponding observed and reanalyzed data, we examine the climate regime shift that occurred in the winter of 1988/1989 and how the shift affected interannual variability and predictability of two types of ENSO for the two periods of 1972-1988 (hereafter PRE) and 1989-2005 (hereafter POST). The result first shows substantial interdecadal changes of observed sea surface temperature (SST) in mean state and variability over the western and central Pacific attributable to the significant warming trend in the POST period. In the POST period, the SST variability increased (decreased) significantly over the western (eastern) Pacific. The MME realistically reproduces the observed interdecadal changes with 1- and 4-month forecast lead time. It is found that the CP-type ENSO was more prominent and predictable during the POST than the PRE period while there was no apparent difference in the variability and predictability of the EP-type ENSO between two periods. Note that the second empirical orthogonal function mode of the Pacific SST during the POST period represents the CP-type ENSO but that during the PRE period captures the ENSO transition phase. The MME better predicts the former than the latter. We also investigate distinctive regional impacts associated with the two types of ENSO during the two periods.

  2. Prediction of functional sites in proteins using conserved functional group analysis.

    PubMed

    Innis, C Axel; Anand, A Prem; Sowdhamini, R

    2004-04-01

    A detailed knowledge of a protein's functional site is an absolute prerequisite for understanding its mode of action at the molecular level. However, the rapid pace at which sequence and structural information is being accumulated for proteins greatly exceeds our ability to determine their biochemical roles experimentally. As a result, computational methods are required which allow for the efficient processing of the evolutionary information contained in this wealth of data, in particular that related to the nature and location of functionally important sites and residues. The method presented here, referred to as conserved functional group (CFG) analysis, relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. We show that CFG analysis can fully or partially predict the location of functional sites in approximately 96% of the 470 cases tested and that, unlike other methods available, it is able to tolerate wide variations in sequence identity. In addition, we discuss its potential in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function. This is exemplified by our analysis of the hypothetical protein Ydde_Ecoli, whose structure was recently solved by members of the North East Structural Genomics consortium. Although the proposed active site for this protein needs to be validated experimentally, this example illustrates the scope of CFG analysis as a general tool for the identification of residues likely to play an important role in a protein's biochemical function. Thus, our method offers a convenient solution to rapidly and automatically process the vast amounts of data that are beginning to emerge from structural genomics projects. PMID:15033369

  3. 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. PMID:26011750

  4. 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.

  5. 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.

  6. The role of plant functional trade-offs for biodiversity changes and biome shifts under scenarios of global climatic change

    NASA Astrophysics Data System (ADS)

    Reu, B.; Zaehle, S.; Proulx, R.; Bohn, K.; Kleidon, A.; Pavlick, R.; Schmidtlein, S.

    2011-05-01

    The global geographic distribution of biodiversity and biomes is determined by species-specific physiological tolerances to climatic constraints. Current vegetation models employ empirical bioclimatic relationships to predict present-day vegetation patterns and to forecast biodiversity changes and biome shifts under climatic change. In this paper, we consider trade-offs in plant functioning and their responses under climatic changes to forecast and explain changes in plant functional richness and shifts in biome geographic distributions. The Jena Diversity model (JeDi) simulates plant survival according to essential plant functional trade-offs, including ecophysiological processes such as water uptake, photosynthesis, allocation, reproduction and phenology. We use JeDi to quantify changes in plant functional richness and biome shifts between present-day and a range of possible future climates from two SRES emission scenarios (A2 and B1) and seven global climate models using metrics of plant functional richness and functional identity. Our results show (i) a significant loss of plant functional richness in the tropics, (ii) an increase in plant functional richness at mid and high latitudes, and (iii) a pole-ward shift of biomes. While these results are consistent with the findings of empirical approaches, we are able to explain them in terms of the plant functional trade-offs involved in the allocation, metabolic and reproduction strategies of plants. We conclude that general aspects of plant physiological tolerances can be derived from functional trade-offs, which may provide a useful process- and trait-based alternative to bioclimatic relationships. Such a mechanistic approach may be particularly relevant when addressing vegetation responses to climatic changes that encounter novel combinations of climate parameters that do not exist under contemporary climate.

  7. 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.

  8. Functional traits help predict post-disturbance demography of tropical trees.

    PubMed

    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.

  9. 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

  10. 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.

  11. Fluctuating Electrocardiographic Changes Predict Poor Outcomes After Acute Subarachnoid Hemorrhage

    PubMed Central

    Elsharkawy, Hesham; Abd-Elsayed, Alaa; El-Hadi, Sherif; Provencio, Javier; Tetzlaff, John

    2016-01-01

    Background: Electrocardiogram (ECG) abnormalities following aneurysmal subarachnoid hemorrhage (SAH) have been well documented. Evidence suggests that ECG changes and cardiac dysfunction worsen outcome. Determining which patients are at most risk is unclear but important to ascertain. Methods: We prospectively studied clinical markers, cardiac abnormalities, and clinical outcomes in 20 patients admitted within 48 hours of aneurysmal SAH. All patients had ECGs prior to surgical clipping, during the clipping surgery, and during the postoperative period. Results: The aneurysm was located in the anterior circulation in 17 patients (85%) and in the posterior circulation in 3 patients (15%). Abnormal ECG changes in patients with acute SAH were observed, with a total incidence rate of 65%. The incidence of T wave abnormalities was 53.8% among the patients with ECG changes, 46.2% had ST segment change, and 30.8% had QT interval prolongation. Of the 13 patients with ECG changes, 4 (30.8%) had fluctuating ECG abnormalities (an abnormality that presented and disappeared during the study period or changed in character). All 4 patients with fluctuating ECG changes had a poor outcome (100%) compared to 3 of the 9 patients (33.3%) patients with fixed abnormalities (P<0.05). Conclusion: The unique finding in this study that has not been reported previously in the literature is the contribution of dynamic ECG changes to the prognosis for good recovery from aneurysmal SAH. In our group, all the patients who had ECG changes that fluctuated from one abnormal change to another had a poor outcome. The etiology of this finding is not clear but may open the door to further study into the pathogenesis of cardiac changes in aneurysmal SAH. The clinical utility of the variability of ECG abnormalities needs to be validated in a larger cohort of patients with longer follow-up than was possible in this study. PMID:27660569

  12. Fluctuating Electrocardiographic Changes Predict Poor Outcomes After Acute Subarachnoid Hemorrhage

    PubMed Central

    Elsharkawy, Hesham; Abd-Elsayed, Alaa; El-Hadi, Sherif; Provencio, Javier; Tetzlaff, John

    2016-01-01

    Background: Electrocardiogram (ECG) abnormalities following aneurysmal subarachnoid hemorrhage (SAH) have been well documented. Evidence suggests that ECG changes and cardiac dysfunction worsen outcome. Determining which patients are at most risk is unclear but important to ascertain. Methods: We prospectively studied clinical markers, cardiac abnormalities, and clinical outcomes in 20 patients admitted within 48 hours of aneurysmal SAH. All patients had ECGs prior to surgical clipping, during the clipping surgery, and during the postoperative period. Results: The aneurysm was located in the anterior circulation in 17 patients (85%) and in the posterior circulation in 3 patients (15%). Abnormal ECG changes in patients with acute SAH were observed, with a total incidence rate of 65%. The incidence of T wave abnormalities was 53.8% among the patients with ECG changes, 46.2% had ST segment change, and 30.8% had QT interval prolongation. Of the 13 patients with ECG changes, 4 (30.8%) had fluctuating ECG abnormalities (an abnormality that presented and disappeared during the study period or changed in character). All 4 patients with fluctuating ECG changes had a poor outcome (100%) compared to 3 of the 9 patients (33.3%) patients with fixed abnormalities (P<0.05). Conclusion: The unique finding in this study that has not been reported previously in the literature is the contribution of dynamic ECG changes to the prognosis for good recovery from aneurysmal SAH. In our group, all the patients who had ECG changes that fluctuated from one abnormal change to another had a poor outcome. The etiology of this finding is not clear but may open the door to further study into the pathogenesis of cardiac changes in aneurysmal SAH. The clinical utility of the variability of ECG abnormalities needs to be validated in a larger cohort of patients with longer follow-up than was possible in this study.

  13. 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…

  14. 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.

  15. 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.

  16. 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. PMID:10677464

  17. 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.…

  18. Lung function changes in wildland firefighters working at prescribed burns.

    SciTech Connect

    Adetona, Olorunfemi; Hall, Daniel, B.; Naeher, L,P.

    2011-10-01

    Although decline in lung function across workshift has been observed in wildland firefighters, measurements have been restricted to days when they worked at fires. Consequently, such results could have been confounded by normal circadian variation associated with lung function. We investigated the across-shift changes in lung function of wildland firefighters, and the effect of cumulative exposure on lung function during the burn season.

  19. "They like Me, They like Me Not": Popularity and Adolescents' Perceptions of Acceptance Predicting Social Functioning Over Time

    ERIC Educational Resources Information Center

    McElhaney, Kathleen B.; Antonishak, Jill; Allen, Joseph P.

    2008-01-01

    This study examined the dual roles of adolescents' perceptions of social acceptance and sociometric popularity in predicting relative changes over time in adolescents' social functioning. Observational, self-report, and peer report data were obtained from 164 adolescents who were interviewed at age 13 years and then again at age 14 years, as well…

  20. Prediction of hospital mortality by changes in the estimated glomerular filtration rate (eGFR).

    PubMed

    Berzan, E; Mellotte, G; Silke, B

    2015-03-01

    Deterioration of physiological or laboratory variables may provide important prognostic information. We have studied whether a change in estimated glomerular filtration rate (eGFR) value calculated using the (Modification of Diet in Renal Disease (MDRD) formula) over the hospital admission, would have predictive value. An analysis was performed on all emergency medical hospital episodes (N = 61964) admitted between 1 January 2002 and 31 December 2011. A stepwise logistic regression model examined the relationship between mortality and change in renal function from admission to discharge. The fully adjusted Odds Ratios (OR) for 5 classes of GFR deterioration showed a stepwise increased risk of 30-day death with OR's of 1.42 (95% CI: 1.20, 1.68), 1.59 (1.27, 1.99), 2.71 (2.24, 3.27), 5.56 (4.54, 6.81) and 11.9 (9.0, 15.6) respectively. The change in eGFR during a clinical episode, following an emergency medical admission, powerfully predicts the outcome. PMID:25876302

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

    SciTech Connect

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

    2010-01-01

    impact of climate change on soil ecosystem functioning, and hence, these indirect effects should be taken into account when predicting how climate change will alter ecosystem functioning.

  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. 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

  4. 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.

  5. 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...

  6. Modelling snow cover duration improves predictions of functional and taxonomic diversity for alpine plant communities

    PubMed Central

    Carlson, Bradley Z.; Choler, Philippe; Renaud, Julien; Dedieu, Jean-Pierre; Thuiller, Wilfried

    2015-01-01

    Background and Aims Quantifying relationships between snow cover duration and plant community properties remains an important challenge in alpine ecology. This study develops a method to estimate spatial variation in energy availability in the context of a topographically complex, high-elevation watershed, which was used to test the explanatory power of environmental gradients both with and without snow cover in relation to taxonomic and functional plant diversity. Methods Snow cover in the French Alps was mapped at 15-m resolution using Landsat imagery for five recent years, and a generalized additive model (GAM) was fitted for each year linking snow to time and topography. Predicted snow cover maps were combined with air temperature and solar radiation data at daily resolution, summed for each year and averaged across years. Equivalent growing season energy gradients were also estimated without accounting for snow cover duration. Relationships were tested between environmental gradients and diversity metrics measured for 100 plots, including species richness, community-weighted mean traits, functional diversity and hyperspectral estimates of canopy chlorophyll content. Key Results Accounting for snow cover in environmental variables consistently led to improved predictive power as well as more ecologically meaningful characterizations of plant diversity. Model parameters differed significantly when fitted with and without snow cover. Filtering solar radiation with snow as compared without led to an average gain in R2 of 0·26 and reversed slope direction to more intuitive relationships for several diversity metrics. Conclusions The results show that in alpine environments high-resolution data on snow cover duration are pivotal for capturing the spatial heterogeneity of both taxonomic and functional diversity. The use of climate variables without consideration of snow cover can lead to erroneous predictions of plant diversity. The results further indicate that

  7. 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.

  8. Executive function and theory of mind: Predictive relations from ages 2 to 4.

    PubMed

    Hughes, Claire; Ensor, Rosie

    2007-11-01

    Despite robust associations between children's theory of mind (ToM) and executive function (EF) skills, longitudinal studies examining this association remain scarce. In a socially diverse sample of 122 children (seen at ages 2, 3, and 4), this study examined (a) developmental stability of associations between ToM, EF, verbal ability, and social disadvantage; (b) continuity and change in ToM and EF; and (c) predictive relations between ToM and EF. Verbal ability and social disadvantage independently predicted changes in EF (but not ToM). Task scores improved with age and showed stable individual differences. The authors examined predictive relations between ToM and EF using partial correlations (controlling for age and verbal ability) and hierarchical regressions (that also controlled for social disadvantage and initial ToM and EF). The findings provide only partial support for the view that ToM is a prerequisite for EF but stronger support for the proposal that EF facilitates children's performance on ToM tasks.

  9. Diversity experiences predict changes in attitudes toward affirmative action.

    PubMed

    Aberson, Christopher L

    2007-10-01

    The current study examined the role of diversity experiences in promoting changes in attitudes toward affirmative action (AA). Using longitudinal data from a survey of over 1000 college students at admission and in their fourth year, results demonstrated that participation in diversity-related campus activities related to positive changes in attitudes toward affirmative action. This result was consistent across samples of White, African American, and Asian American students. Positive changes in attitudes persisted despite statistical controls for established predictors of attitudes toward AA such as merit and prevalence of discrimination beliefs, and individual-level characteristics such as experiences of discrimination and political liberalism. I discuss the relevance of this finding to the AA literature and to changing attitudes toward AA. PMID:17967096

  10. Are Psychotherapeutic Changes Predictable? Comparison of a Chicago Counseling Center Project with a Penn Psychotherapy Project.

    ERIC Educational Resources Information Center

    Luborsky, Lester; And Others

    1979-01-01

    Compared studies predicting outcomes of psychotherapy. Level of prediction success in both projects was modest. Particularly for the rated benefits score, the profile of variables showed similar levels of success between the projects. Successful predictions were based on adequacy of personality functioning, match on marital status, and length of…

  11. 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.

  12. 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.

  13. 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. PMID:23036371

  14. 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

  15. What Predicts Changes in Useful Field of View Test Performance?

    PubMed Central

    Lunsman, Melissa; Edwards, Jerri D.; Andel, Ross; Small, Brent J.; Ball, Karlene K.; Roenker, Daniel L.

    2015-01-01

    The Useful Field of View Test (UFOV1) has been used to examine age-related changes in visual processing and cognition and as an indicator of everyday performance outcomes, particularly driving, for over 20 years. How UFOV performance changes with age and what may impact such changes have not previously been investigated longitudinally. Predictors of change in UFOV performance over a five-year period among control-group participants (n = 690) from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study were examined. Random effects models were estimated with four-subtest total UFOV as the outcome and baseline age, education, gender, race, visual acuity, depressive symptoms, mental status, and self-rated health, as well as attrition, as predictors. UFOV performance generally followed a curvilinear pattern, improving and then declining over time. Only increased age was consistently related to greater declines in UFOV performance over time. UFOV and WAIS-R Digit Symbol Substitution (DSS), a standard measure of cognitive speed, had similar trajectories of change. The implications of these results are discussed. PMID:19140660

  16. 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.

  17. 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

  18. Neuroendocrine control of photoperiodic changes in immune function.

    PubMed

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

    2015-04-01

    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.

  19. 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.

  20. 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.

  1. Western Mountain Initiative: predicting ecosystem responses to climate change

    USGS Publications Warehouse

    Baron, Jill S.; Peterson, David L.; Wilson, J.T.

    2008-01-01

    Mountain ecosystems of the western United States provide irreplaceable goods and services such as water, timber, biodiversity, and recreational opportunities, but their responses to climatic changes are complex and not well understood. The Western Mountain Initiative (WMI), a collaboration between USGS and U.S. Forest Service scientists, catalyzes assessment and synthesis of the effects of disturbance and climate change across western mountain areas, focusing on national parks and surrounding national forests. The WMI takes an ecosystem approach to science, integrating research across science disciplines at scales ranging from field studies to global trends.

  2. An Unsupervised Approach to Predict Functional Relations between Genes Based on Expression Data

    PubMed Central

    Altaf-Ul-Amin, Md.; Sato, Tetsuo; Ono, Naoaki; Kanaya, Shigehiko

    2014-01-01

    This work presents a novel approach to predict functional relations between genes using gene expression data. Genes may have various types of relations between them, for example, regulatory relations, or they may be concerned with the same protein complex or metabolic/signaling pathways and obviously gene expression data should contain some clues to such relations. The present approach first digitizes the log-ratio type gene expression data of S. cerevisiae to a matrix consisting of 1, 0, and −1 indicating highly expressed, no major change, and highly suppressed conditions for genes, respectively. For each gene pair, a probability density mass function table is constructed indicating nine joint probabilities. Then gene pairs were selected based on linear and probabilistic relation between their profiles indicated by the sum of probability density masses in selected points. The selected gene pairs share many Gene Ontology terms. Furthermore a network is constructed by selecting a large number of gene pairs based on FDR analysis and the clustering of the network generates many modules rich with similar function genes. Also, the promoters of the gene sets in many modules are rich with binding sites of known transcription factors indicating the effectiveness of the proposed approach in predicting regulatory relations. PMID:24800208

  3. 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…

  4. Short-Term Study Abroad: Predicting Changes in Oral Skills

    ERIC Educational Resources Information Center

    Martinsen, Rob A.

    2010-01-01

    Increasing numbers of students are opting for study abroad programs of 2 months or less while research on study abroad generally focuses on semester- or year-long programs. This study quantitatively examines changes in students' spoken Spanish after 6 weeks in Argentina using native speaker ratings of student speech. The researcher then uses…

  5. 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.

  6. Environmental change and hedonic cost functions for automobiles

    SciTech Connect

    Berry, S.; Pakes, A.; Kortum, S.

    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 {open_quotes}hedonic cost functions{close_quotes} 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. 19 refs., 2 figs., 6 tabs.

  7. Cognitive Declines Precede and Predict Functional Declines in Aging and Alzheimer’s Disease

    PubMed Central

    Zahodne, Laura B.; Manly, Jennifer J.; MacKay-Brandt, Anna; Stern, Yaakov

    2013-01-01

    Objective To investigate the temporal ordering of cognitive and functional declines separately in older adults with or without Alzheimer’s disease (AD). Design and Setting A community-based longitudinal study of aging and dementia in Northern Manhattan (Washington Heights/Hamilton Heights Inwood Columbia Aging Project) and a multicenter, clinic-based longitudinal study of prevalent AD at Columbia University Medical Center, Johns Hopkins School of Medicine, Massachusetts General Hospital, and the Hôpital de la Salpêtrière in Paris, France (the Predictors Study). Participants 3,443 initially non-demented older adults (612 with eventual incident dementia) and 517 patients with AD. Main Outcome Measures Cognitive measures included the modified Mini-Mental State Exam and composite scores of memory and language derived from a standardized neuropsychological battery. Function was measured with the Blessed Dementia Rating Scale, completed by the participant (in the sample of non-demented older adults) or an informant (in the sample of prevalent AD patients). Data were analyzed with autoregressive cross-lagged panel analysis. Results Cognitive scores more consistently predicted subsequent functional abilities than vice versa in non-demented older adults, participants with eventual incident dementia, and patients with prevalent AD. Conclusions Cognitive declines appear to precede and cause functional declines prior to and following dementia diagnosis. Standardized neuropsychological tests are valid predictors of later functional changes in both non-demented and demented older adults. PMID:24023894

  8. Can pre-implantation biopsies predict renal allograft function in pediatric renal transplant recipients?

    PubMed Central

    Kari, Jameela A.; Ma, Alison L.; Dufek, Stephanie; Mohamed, Ismail; Mamode, Nizam; Sebire, Neil J.; Marks, Stephen D.

    2015-01-01

    Objectives: To determine the utility of pre-implantation renal biopsy (PIB) to predict renal allograft outcomes. Methods: This is a retrospective review of all patients that underwent PIB from January 2003 to December 2011 at the Great Ormond Street Hospital for Children in London, United Kingdom. Thirty-two male patients (56%) aged 1.5-16 years (median: 10.2) at the time of transplantation were included in the study and followed-up for 33 (6-78) months. The results were compared with 33 controls. Results: The PIB showed normal histopathological findings in 13 patients (41%), mild chronic vascular changes in 8 (25%), focal tubular atrophy in one, moderate to severe chronic vascular change in 3, mild to moderate acute tubular damage in 6, and tissue was inadequate in one subject. Delayed graft function (DGF) was observed in 3 patients; 2 with vascular changes in PIB, and one with normal histopathological findings. Two subjects with PIB changes lost their grafts. The estimated glomerular filtration rate at 3-, and 6-months post-transplantation was lower in children with abnormal PIB changes compared with those with normal PIB. There was one case of DGF in the control group, and 4 children lost their grafts including the one with DGF. Conclusion: Pre-implantation renal biopsy can provide important baseline information of the graft with implications on subsequent medical treatment for pediatric renal transplant recipients. PMID:26593162

  9. Prediction of permeability change at high ambient stresses via the isotropic Skempton coefficient B

    NASA Astrophysics Data System (ADS)

    Zimmermann, G.; Bloecher, M. G.; Milsch, H.

    2006-12-01

    For gas, oil and water exploration reservoir permeability as a function of effective stress is one of the most important hydraulic parameters. Estimation of permeability, especially in deep reservoirs, is very difficult and time-consuming. Therefore, permeability is often estimated in laboratory experiments under simulated in-situ conditions. Under these experimental conditions with a flow across the sample, many effects lead to changes in permeability. Besides the flow paths reduction as a function of effective pressure, plugging of the sample and filters by fines migration or rust and a swelling of the clay content can occur, which results in a decrease in permeability. All these non-mechanical effects are time dependent and affect the permeability measurements, hence a separation of all these influences is hard to achieve. To avoid these problems we estimated the permeability pressure dependence with the isotropic Skempton coefficient. The Skempton coefficient is defined as undrained pore pressure change due to ambient stress changes B=dpu/dσm. We could show that a heterogeneous deformation of pore space geometry led to a decrease of the Skempton coefficient with increasing confining pressure. The mechanisms which influence the Skempton coefficient are similar to the behavior of the sandstone sample during the permeability measurements. In both cases we consider a change in pore pressure and an adjacent equalization across the flow channels at the micro-scale. These flow channels change their geometry depending on the applied stresses. Therefore, the reduction of the Skempton coefficient should be comparable to the reduction of permeability. To validate this assumption we present experiments on Lower Permian sandstone (Rotliegend) samples from the NE German Basin and compared Skempton coefficient and permeability measurements to find a coherence of both rock properties. Applying this relation of Skempton coefficient and permeability, we can predict rock

  10. 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.

  11. Unique sequences and predicted functions of myosins in Tetrahymena thermophila.

    PubMed

    Sugita, Maki; Iwataki, Yoshinori; Nakano, Kentaro; Numata, Osamu

    2011-07-01

    Myosins are eukaryotic actin-dependent molecular motors that play important roles in many cellular events. The function of each myosin is determined by a variety of functional domains in its tail region. In some major model organisms, the functions and properties of myosins have been investigated based on their amino acid sequences. However, in protists, myosins have been little studied beyond the level of genome sequences. We therefore investigated the mRNA expression levels and amino acid sequences of 13 myosin genes in the ciliate Tetrahymena thermophila. This study is an overview of myosins in T. thermophila, which has no typical myosins, such as class I, II, or V myosins. We showed that all 13 myosins were expressed in vegetative cells. Furthermore, these myosins could be divided into 3 subclasses based on four functional domains in their tail regions. Subclass 1 comprised of 8 myosins has both MyTH4 and FERM domains, and has a potential to function in vesicle transport or anchoring between membrane and actin filaments. Subclass 2 comprised of 4 myosins has RCC1 (regulator of chromosome condensation 1) domains, which are found only in some protists, and may have unconventional features. Subclass 3 is comprised of one myosin, which has a long coiled-coil domain like class II myosin. In addition, phylogenetic analysis on the basis of motor domains showed that T. thermophila myosins are separated into two clusters: one consists of subclasses 1 and 2, and the other consists of subclass 3.

  12. Predicted changes in interannual water-level fluctuations due to climate change and its implications for the vegetation of the Florida Everglades.

    PubMed

    van der Valk, Arnold G; Volin, John C; Wetzel, Paul R

    2015-04-01

    The number of dominant vegetation types (wet prairies, sawgrass flats, ridges and sloughs, sloughs, and tree islands) historically and currently found in the Everglades, FL, USA, as with other wetlands with standing water, appears to be primarily a function of the magnitude of interannual water-level fluctuations. Analyses of 40 years of water-depth data were used to estimate the magnitude of contemporary (baseline) water-level fluctuations in undisturbed ridge and slough landscapes. Baseline interannual water-level fluctuations above the soil surface were at least 1.5 m. Predicted changes in interannual water-level fluctuations in 2060 were examined for seven climate change scenarios. When rainfall is predicted to increase by 10 %, the wettest scenario, the interannual range of water-level fluctuation increases to 1.8 m above the soil surface in sloughs. When rainfall is predicted to decrease by 10 % and temperatures to increase by 1.5 °C, the driest scenario, the range of interannual range of water-level fluctuations is predicted to decrease to 1.2 m above the soil surface in sloughs. A change of 25-30 cm in interannual water-level fluctuations is needed to change the number of vegetation types in a wetland. This suggests that the two most extreme climate change scenarios could have a significant impact on the overall structure of wetland vegetation, i.e., the number of vegetation types or zones, found in the Everglades.

  13. Changes in Retinal Nerve Fiber Layer Reflectance Intensity as a Predictor of Functional Progression in Glaucoma

    PubMed Central

    Gardiner, Stuart K.; Demirel, Shaban; Reynaud, Juan; Fortune, Brad

    2016-01-01

    Purpose We determined whether longitudinal changes in retinal nerve fiber layer (RNFL) reflectance provide useful prognostic information about longitudinal changes in function in glaucoma. Methods The reflectance intensity of each pixel within spectral-domain optical coherence tomography (SD-OCT) circle scans was extracted by custom software. A repeatability cohort comprising 53 eyes of 27 participants (average visual field mean deviation [MD] −1.65 dB) was tested five times within a few weeks. To minimize test–retest variability in their data, a reflectance intensity ratio was defined as the mean reflectance intensity of pixels within the RNFL divided by the mean between the RNFL and RPE. This was measured in a separate longitudinal cohort comprising 310 eyes of 205 participants tested eight times at 6-month intervals (average MD, −0.99 dB; median rate of change, −0.09 dB/y). The rate of change of this ratio, together with the rate of RNFL thinning, and their interaction, were used to predict the rate of change of MD. Results In univariate analyses, the rate of RNFL thinning was predictive of the rate of MD change (P < 0.0001), but the rate of change of reflectance intensity ratio was not (P = 0.116). However, in a multivariable model, the interaction between these two rates significantly improved upon predictions of the rate of functional change made using RNFL thickness alone (P = 0.038). Conclusions For a given rate of RNFL thinning, a reduction in the RNFL reflectance intensity ratio is associated with more rapid functional deterioration. Incorporating SD-OCT reflectance information may improve the structure–function relation in glaucoma. PMID:26978028

  14. Stages of Change or Changes of Stage? Predicting Transitions in Transtheoretical Model Stages in Relation to Healthy Food Choice

    ERIC Educational Resources Information Center

    Armitage, Christopher J.; Sheeran, Paschal; Conner, Mark; Arden, Madelynne A.

    2004-01-01

    Relatively little research has examined factors that account for transitions between transtheoretical model (TTM) stages of change. The present study (N=787) used sociodemographic, TTM, and theory of planned behavior (TPB) variables, as well as theory-driven interventions to predict changes in stage. Longitudinal analyses revealed that…

  15. Functional prediction: identification of protein orthologs and paralogs.

    PubMed Central

    Chen, R.; Jeong, S. S.

    2000-01-01

    Orthologs typically retain the same function in the course of evolution. Using beta-decarboxylating dehydrogenase family as a model, we demonstrate that orthologs can be confidently identified. The strategy is based on our recent findings that substitutions of only a few amino acid residues in these enzymes are sufficient to exchange substrate and coenzyme specificities. Hence, the few major specificity determinants can serve as reliable markers for determining orthologous or paralogous relationships. The power of this approach has been demonstrated by correcting similarity-based functional misassignment and discovering new genes and related pathways, and should be broadly applicable to other enzyme families. PMID:11206056

  16. 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

  17. 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…

  18. 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.

  19. 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

  20. 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

    2016-01-01

    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

  1. 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.

  2. 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

    2015-11-01

    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.

  3. 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

  4. Treatment response in couple therapy: Relationship adjustment and individual functioning change processes.

    PubMed

    Knobloch-Fedders, Lynne M; Pinsof, William M; Haase, Claudia M

    2015-10-01

    This study, a naturalistic investigation of the process of change in relationship adjustment and individual functioning during conjoint therapy, examined the first 8 sessions of a multisystemic model of couple therapy, integrative problem-centered metaframeworks (Breunlin, Pinsof, Russell, & Lebow, 2011; Pinsof, Breunlin, Russell, & Lebow, 2011). The sample consisted of 125 heterosexual couples who reported on their relationship adjustment and individual functioning before every session using the Systemic Therapy Inventory of Change (Pinsof et al., 2009; Pinsof, Zinbarg, et al., in press). Data were analyzed using dyadic latent growth curve and cross-lagged models. For both men and women, relationship adjustment and individual functioning showed nonlinear change, increasing during Sessions 1-4 and stabilizing during Sessions 5-8. At pretreatment, women reported lower levels of relationship adjustment than men; no gender differences existed in initial levels of individual functioning or in the change trajectories of relationship adjustment or individual functioning. Higher relationship adjustment predicted positive change in individual functioning for men (but not for women). In contrast, there were no cross-lagged effects of individual functioning on relationship adjustment for men or women. The results demonstrate the importance of examining the processes by which relational and individual pathology respond to couple-based interventions. PMID:26376428

  5. Improvement in protein functional site prediction by distinguishing structural and functional constraints on protein family evolution using computational design.

    PubMed

    Cheng, Gong; Qian, Bin; Samudrala, Ram; Baker, David

    2005-01-01

    The prediction of functional sites in newly solved protein structures is a challenge for computational structural biology. Most methods for approaching this problem use evolutionary conservation as the primary indicator of the location of functional sites. However, sequence conservation reflects not only evolutionary selection at functional sites to maintain protein function, but also selection throughout the protein to maintain the stability of the folded state. To disentangle sequence conservation due to protein functional constraints from sequence conservation due to protein structural constraints, we use all atom computational protein design methodology to predict sequence profiles expected under solely structural constraints, and to compute the free energy difference between the naturally occurring amino acid and the lowest free energy amino acid at each position. We show that functional sites are more likely than non-functional sites to have computed sequence profiles which differ significantly from the naturally occurring sequence profiles and to have residues with sub-optimal free energies, and that incorporation of these two measures improves sequence based prediction of protein functional sites. The combined sequence and structure based functional site prediction method has been implemented in a publicly available web server.

  6. Functional brain network changes associated with maintenance of cognitive function in multiple sclerosis.

    PubMed

    Helekar, Santosh A; Shin, Jae C; Mattson, Brandi J; Bartley, Krystle; Stosic, Milena; Saldana-King, Toni; Montague, P Read; Hutton, George J

    2010-01-01

    In multiple sclerosis (MS) functional changes in connectivity due to cortical reorganization could lead to cognitive impairment (CI), or reflect a re-adjustment to reduce the clinical effects of widespread tissue damage. Such alterations in connectivity could result in changes in neural activation as assayed by executive function tasks. We examined cognitive function in MS patients with mild to moderate CI and age-matched controls. We evaluated brain activity using functional magnetic resonance imaging (fMRI) during the successful performance of the Wisconsin card sorting (WCS) task by MS patients, showing compensatory maintenance of normal function, as measured by response latency and error rate. To assess changes in functional connectivity throughout the brain, we performed a global functional brain network analysis by computing voxel-by-voxel correlations on the fMRI time series data and carrying out a hierarchical cluster analysis. We found that during the WCS task there is a significant reduction in the number of smaller size brain functional networks, and a change in the brain areas representing the nodes of these networks in MS patients compared to age-matched controls. There is also a concomitant increase in the strength of functional connections between brain loci separated at intermediate-scale distances in these patients. These functional alterations might reflect compensatory neuroplastic reorganization underlying maintenance of relatively normal cognitive function in the face of white matter lesions and cortical atrophy produced by MS.

  7. Low dose dobutamine stress echocardiography predicts the improvement of left ventricular systolic function in dilated cardiomyopathy

    PubMed Central

    Kitaoka, H; Takata, J; Yabe, T; Hitomi, N; Furuno, T; Doi, Y

    1999-01-01

    OBJECTIVE—To determine whether dobutamine stress echocardiography can predict the improvement of left ventricular systolic function in patients with dilated cardiomyopathy (DCM).
METHODS—Myocardial contractile reserve, as assessed by dobutamine stress echocardiography, was determined in 18 patients with DCM (mean (SD) age 53 (13) years, left ventricular ejection fraction (LVEF) 28 (10)%) and compared with changes in LVEF during a follow up period of 15 (8) months. The LVEF and regional left ventricular wall motion score (0, normal to 4, dyskinesis) of 12 segments in short axis and four chamber views were analysed before and after dobutamine infusion (5-20 µg/kg/min).
RESULTS—During a follow up period of 15 (8) months, a significant improvement in LVEF (> 20%) was found in seven patients but not in the remaining 11. Baseline haemodynamic findings were similar in both groups. Patients with an improvement in follow up LVEF showed a greater change in wall motion score from baseline during dobutamine infusion than patients with no improvement (at rest, 1.7 (0.4) v 1.9 (0.2), NS; dobutamine 10 µg/kg/min, 0.6 (0.4) v 1.2 (0.4), p < 0.05). The percentage change in LVEF during dobutamine infusion was also significantly greater in patients who showed improvement than in those who did not. The change in LVEF during the follow up period (follow up LVEF/baseline LVEF) correlated well with the change in LVEF during dobutamine stress (LVEF at rest/LVEF at dobutamine 10 µg/kg/min; r = 0.74, p < 0.001).
CONCLUSIONS—Changes in left ventricular systolic performance during low dose dobutamine stress echocardiography are a useful marker to predict the outcome of left ventricular systolic function in patients with DCM.


Keywords: dilated cardiomyopathy; dobutamine stress echocardiography; contractile reserve PMID:10212172

  8. The predictive value of self assessed general, physical, and mental health on functional decline and mortality in older adults

    PubMed Central

    Lee, Y.

    2000-01-01

    OBJECTIVE—To examine the extent to which older people's self assessments of general health, physical health, and mental health predict functional decline and mortality.
DESIGN—The study uses population-based secondary data from the US Longitudinal Study of Aging (LSOA).
PARTICIPANTS—A total of 7527 persons aged 70 years or above living in the community.
METHODS—Eight different measures on self reported general, physical, and mental health were used. Change in functional status was measured using a composite index of ADLs and IADLs over a period of six years. Duration of survival was calculated over a period of seven years. Adjusting for age and gender, multiple logistic regression was used in analysing functional decline, and Cox proportional hazard model, for mortality. Then all of the self assessed health measures were incorporated into the final model—controlling for baseline sociodemographic characteristics, functional status, disease/conditions, and use of health and social services—to assess the independent contribution of each measure in predicting future health outcomes.
MAIN RESULTS—Overall, older people's self assessed general, physical, and mental health were predictive of functional decline and mortality. In multivariate analyses, older people who assessed their global health, self care ability, and physical activity less favourably were more likely to experience poor health outcomes. Gender disparity, however, was observed with poor global health affecting functional decline in men only. Self care ability was predictive of functioning in women only, whereas it was predictive of mortality in men only.
CONCLUSIONS—Self assessed global health, as well as, specific dimensions of health act as significant, independent predictors of functioning and mortality in a community dwelling older people.


Keywords: age; self assessed health; functional status; mortality PMID:10715745

  9. Use of contiguity on the chromosome to predict functional coupling.

    SciTech Connect

    Overbeek, R.; Fonstein, M.; Souza, D'Souza, M.; Pusch, G. D.; Maltsev, N.; Mathematics and Computer Science; Univ. of Chicago

    1999-01-01

    The availability of a growing number of completely sequenced genomes opens new opportunities for understanding of complex biological systems. Success of genome-based biology will, to a large extent, depend on the development of new approaches and tools for efficient comparative analysis of the genomes and their organization. We have developed a technique for detecting possible functional coupling between genes based on detection of potential operons. The approach involves computation of 'pairs of close bidirectional best hits', which are pairs of genes that apparently occur within operons in multiple genomes. Using these pairs, one can compose evidence (based on the number of distinct genomes and the phylogenetic distance between the orthologous pairs) that a pair of genes is potentially functionally coupled. The technique has revealed a surprisingly rich and apparently accurate set of functionally coupled genes. The approach depends on the use of a relatively large number of genomes, and the amount of detected coupling grows dramatically as the number of genomes increases.

  10. The changing landscape in translocator protein (TSPO) function.

    PubMed

    Selvaraj, Vimal; Stocco, Douglas M

    2015-07-01

    Translocator protein (TSPO), previously known as the peripheral benzodiazepine receptor (PBR), is an outer mitochondrial membrane protein. TSPO has been shown to cooperate with steroidogenic acute regulatory protein (StAR) and function in the transport of cholesterol into mitochondria. TSPO has also been considered as a structural component of the mitochondrial permeability transition pore (MPTP). However, recent advances have changed these views of TSPO's functions and have prompted a re-evaluation of established concepts. This review summarizes the history of TSPO, key elements of the debate, and functional experiments that have changed our understanding. Moving forward, we examine how this fundamental change impacts our understanding of TSPO and affects the future of TSPO as a therapeutic and diagnostic target.

  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. PMID:27453156

  12. 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.

  13. SIFTER search: a web server for accurate phylogeny-based protein function prediction.

    PubMed

    Sahraeian, Sayed M; Luo, Kevin R; Brenner, Steven E

    2015-07-01

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. The SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.

  14. An integrated probabilistic approach for gene function prediction using multiple sources of high-throughput data.

    PubMed

    Zhang, Chao; Joshi, Trupti; Lin, Guan Ning; Xu, Dong

    2008-01-01

    Characterising gene function is one of the major challenging tasks in the post-genomic era. Various approaches have been developed to integrate multiple sources of high-throughput data to predict gene function. Most of those approaches are just used for research purpose and have not been implemented as publicly available tools. Even for those implemented applications, almost all of them are still web-based 'prediction servers' that have to be managed by specialists. This paper introduces a systematic method for integrating various sources of high-throughput data to predict gene function and analyse our prediction results and evaluates its performances based on the competition for mouse gene function prediction (MouseFunc). A stand-alone Java-based software package 'GeneFAS' is freely available at http://digbio. missouri.eduigenefas.

  15. 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

  16. Predicting order of conformational changes during protein conformational transitions using an interpolated elastic network model.

    PubMed

    Tekpinar, Mustafa; Zheng, Wenjun

    2010-08-15

    The decryption of sequence of structural events during protein conformational transitions is essential to a detailed understanding of molecular functions of various biological nanomachines. Coarse-grained models have proven useful by allowing highly efficient simulations of protein conformational dynamics. By combining two coarse-grained elastic network models constructed based on the beginning and end conformations of a transition, we have developed an interpolated elastic network model to generate a transition pathway between the two protein conformations. For validation, we have predicted the order of local and global conformational changes during key ATP-driven transitions in three important biological nanomachines (myosin, F(1) ATPase and chaperonin GroEL). We have found that the local conformational change associated with the closing of active site precedes the global conformational change leading to mechanical motions. Our finding is in good agreement with the distribution of intermediate experimental structures, and it supports the importance of local motions at active site to drive or gate various conformational transitions underlying the workings of a diverse range of biological nanomachines.

  17. Novel semantic similarity measure improves an integrative approach to predicting gene functional associations

    PubMed Central

    2013-01-01

    Background Elucidation of the direct/indirect protein interactions and gene associations is required to fully understand the workings of the cell. This can be achieved through the use of both low- and high-throughput biological experiments and in silico methods. We present GAP (Gene functional Association Predictor), an integrative method for predicting and characterizing gene functional associations. GAP integrates different biological features using a novel taxonomy-based semantic similarity measure in predicting and prioritizing high-quality putative gene associations. The proposed similarity measure increases information gain from the available gene annotations. The annotation information is incorporated from several public pathway databases, Gene Ontology annotations as well as drug and disease associations from the scientific literature. Results We evaluated GAP by comparing its prediction performance with several other well-known functional interaction prediction tools over a comprehensive dataset of known direct and indirect interactions, and observed significantly better prediction performance. We also selected a small set of GAP’s highly-scored novel predicted pairs (i.e., currently not found in any known database or dataset), and by manually searching the literature for experimental evidence accessible in the public domain, we confirmed different categories of predicted functional associations with available evidence of interaction. We also provided extra supporting evidence for subset of the predicted functionally-associated pairs using an expert curated database of genes associated to autism spectrum disorders. Conclusions GAP’s predictedfunctional interactome” contains ≈1M highly-scored predicted functional associations out of which about 90% are novel (i.e., not experimentally validated). GAP’s novel predictions connect disconnected components and singletons to the main connected component of the known interactome. It can, therefore, be

  18. 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

  19. Correlating CCM upper atmosphere parameters to surface observations for regional climate change predictions

    SciTech Connect

    Li, Xiangshang; Sailor, D.J.

    1997-11-01

    This paper explores the use of statistical downscaling of General Circulation Model (GCM) results for the purpose of regional climate change analysis. The strong correlation between surface observations and GCM upper air predictions is used in an approach very similar to the Model Output Statistics approach used in numerical weather prediction. The primary assumption in this analysis is that the statistical relationships remain unchanged under conditions of climatic change. These relations are applied to GCM upper atmosphere predictions for future (2*CO{sub 2}) climate predictions. The result is a set of regional climate change predictions conceptually valid at the scale of cities. The downscaling for specific cities within a GCM grid cell reveals some of the anticipated variability within the grid cell. In addition, multiple linear regression analysis may indicate warming that is significantly higher or lower for a particular region than the raw data from the GCM runs. 3 refs., 3 figs., 2 tabs.

  20. In silico predicted structural and functional robustness of piscine steroidogenesis.

    PubMed

    Hala, D; Huggett, D B

    2014-03-21

    Assessments of metabolic robustness or susceptibility are inherently dependent on quantitative descriptions of network structure and associated function. In this paper a stoichiometric model of piscine steroidogenesis was constructed and constrained with productions of selected steroid hormones. Structural and flux metrics of this in silico model were quantified by calculating extreme pathways and optimal flux distributions (using linear programming). Extreme pathway analysis showed progestin and corticosteroid synthesis reactions to be highly participant in extreme pathways. Furthermore, reaction participation in extreme pathways also fitted a power law distribution (degree exponent γ=2.3), which suggested that progestin and corticosteroid reactions act as 'hubs' capable of generating other functionally relevant pathways required to maintain steady-state functionality of the network. Analysis of cofactor usage (O2 and NADPH) showed progestin synthesis reactions to exhibit high robustness, whereas estrogen productions showed highest energetic demands with low associated robustness to maintain such demands. Linear programming calculated optimal flux distributions showed high heterogeneity of flux values with a near-random power law distribution (degree exponent γ≥2.7). Subsequently, network robustness was tested by assessing maintenance of metabolite flux-sum subject to targeted deletions of rank-ordered (low to high metric) extreme pathway participant and optimal flux reactions. Network robustness was susceptible to deletions of extreme pathway participant reactions, whereas minimal impact of high flux reaction deletion was observed. This analysis shows that the steroid network is susceptible to perturbation of structurally relevant (extreme pathway) reactions rather than those carrying high flux. PMID:24333207

  1. Fibrosis with Inflammation at One Year Predicts Transplant Functional Decline

    PubMed Central

    Park, Walter D.; Griffin, Matthew D.; Cornell, Lynn D.; Cosio, Fernando G.

    2010-01-01

    Lack of knowledge regarding specific causes for late loss of kidney transplants hampers improvements in long-term allograft survival. Kidney transplants with both interstitial fibrosis and subclinical inflammation but not fibrosis alone after 1 year have reduced survival. This study tested whether fibrosis with inflammation at 1 year associates with decline of renal function in a low-risk cohort and characterized the nature of the inflammation. We studied 151 living-donor, tacrolimus/mycophenolate-treated recipients without overt risk factors for reduced graft survival. Transplants with normal histology (n = 86) or fibrosis alone (n = 45) on 1-year protocol biopsy had stable renal function between 1 and 5 years, whereas those with both fibrosis and inflammation (n = 20) exhibited a decline in GFR and reduced graft survival. Immunohistochemistry confirmed increased interstitial T cells and macrophages/dendritic cells in the group with both fibrosis and inflammation, and there was increased expression of transcripts related to innate and cognate immunity. Pathway- and pathologic process–specific analyses of microarray profiles revealed that potentially damaging immunologic activities were enriched among the overexpressed transcripts (e.g., Toll-like receptor signaling, antigen presentation/dendritic cell maturation, IFN-γ–inducible response, cytotoxic T lymphocyte–associated and acute rejection–associated genes). Therefore, the combination of fibrosis and inflammation in 1-year protocol biopsies associates with reduced graft function and survival as well as a rejection-like gene expression signature, even among recipients with no clinical risk factors for poor outcomes. Early interventions aimed at altering rejection-like inflammation may improve long-term survival of kidney allografts. PMID:20813870

  2. In silico prediction of tumor antigens derived from functional missense mutations of the cancer gene census

    PubMed Central

    Khalili, Jahan S.; Hanson, Russell W.; Szallasi, Zoltan

    2012-01-01

    Antigen-specific immune responses against peptides derived from missense gene mutations have been identified in multiple cancers. The application of personalized peptide vaccines based on the tumor mutation repertoire of each cancer patient is a near-term clinical reality. These peptides can be identified for pre-validation by leveraging the results of massive gene sequencing efforts in cancer. In this study, we utilized NetMHC 3.2 to predict nanomolar peptide binding affinity to 57 human HLA-A and B alleles. All peptides were derived from 5,685 missense mutations in 312 genes annotated as functionally relevant in the Cancer Genome Project. Of the 26,672,189 potential 8–11 mer peptide-HLA pairs evaluated, 0.4% (127,800) display binding affinities < 50 nM, predicting high affinity interactions. These peptides can be segregated into two groups based on the binding affinity to HLA proteins relative to germline-encoded sequences: peptides for which both the mutant and wild-type forms are high affinity binders, and peptides for which only the mutant form is a high affinity binder. Current evidence directs the attention to mutations that increase HLA binding affinity, as compared with cognate wild-type peptide sequences, as these potentially are more relevant for vaccine development from a clinical perspective. Our analysis generated a database including all predicted HLA binding peptides and the corresponding change in binding affinity as a result of point mutations. Our study constitutes a broad foundation for the development of personalized peptide vaccines that hone-in on functionally relevant targets in multiple cancers in individuals with diverse HLA haplotypes. PMID:23243591

  3. 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.

  4. 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

  5. Stability of executive function and predictions to adaptive behavior from middle childhood to pre-adolescence

    PubMed Central

    Harms, Madeline B.; Zayas, Vivian; Meltzoff, Andrew N.; Carlson, Stephanie M.

    2014-01-01

    The shift from childhood to adolescence is characterized by rapid remodeling of the brain and increased risk-taking behaviors. Current theories hypothesize that developmental enhancements in sensitivity to affective environmental cues in adolescence may undermine executive function (EF) and increase the likelihood of problematic behaviors. In the current study, we examined the extent to which EF in childhood predicts EF in early adolescence. We also tested whether individual differences in neural responses to affective cues (rewards/punishments) in childhood serve as a biological marker for EF, sensation-seeking, academic performance, and social skills in early adolescence. At age 8, 84 children completed a gambling task while event-related potentials (ERPs) were recorded. We examined the extent to which selections resulting in rewards or losses in this task elicited (i) the P300, a post-stimulus waveform reflecting the allocation of attentional resources toward a stimulus, and (ii) the SPN, a pre-stimulus anticipatory waveform reflecting a neural representation of a “hunch” about an outcome that originates in insula and ventromedial PFC. Children also completed a Dimensional Change Card-Sort (DCCS) and Flanker task to measure EF. At age 12, 78 children repeated the DCCS and Flanker and completed a battery of questionnaires. Flanker and DCCS accuracy at age 8 predicted Flanker and DCCS performance at age 12, respectively. Individual differences in the magnitude of P300 (to losses vs. rewards) and SPN (preceding outcomes with a high probability of punishment) at age 8 predicted self-reported sensation seeking (lower) and teacher-rated academic performance (higher) at age 12. We suggest there is stability in EF from age 8 to 12, and that childhood neural sensitivity to reward and punishment predicts individual differences in sensation seeking and adaptive behaviors in children entering adolescence. PMID:24795680

  6. 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...

  7. Microbial functional diversity enhances predictive models linking environmental parameters to ecosystem properties.

    PubMed

    Powell, Jeff R; Welsh, Allana; Hallin, Sara

    2015-07-01

    Microorganisms drive biogeochemical processes, but linking these processes to real changes in microbial communities under field conditions is not trivial. Here, we present a model-based approach to estimate independent contributions of microbial community shifts to ecosystem properties. The approach was tested empirically, using denitrification potential as our model process, in a spatial survey of arable land encompassing a range of edaphic conditions and two agricultural production systems. Soil nitrate was the most important single predictor of denitrification potential (the change in Akaike's information criterion, corrected for sample size, ΔAIC(c) = 20.29); however, the inclusion of biotic variables (particularly the evenness and size of denitrifier communities [ΔAIC(c) = 12.02], and the abundance of one denitrifier genotype [ΔAIC(c) = 18.04]) had a substantial effect on model precision, comparable to the inclusion of abiotic variables (biotic R2 = 0.28, abiotic R2 = 0.50, biotic + abiotic R2 = 0.76). This approach provides a valuable tool for explicitly linking microbial communities to ecosystem functioning. By making this link, we have demonstrated that including aspects of microbial community structure and diversity in biogeochemical models can improve predictions of nutrient cycling in ecosystems and enhance our understanding of ecosystem functionality.

  8. 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

  9. 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.

  10. INTREPID: a web server for prediction of functionally important residues by evolutionary analysis.

    PubMed

    Sankararaman, Sriram; Kolaczkowski, Bryan; Sjölander, Kimmen

    2009-07-01

    We present the INTREPID web server for predicting functionally important residues in proteins. INTREPID has been shown to boost the recall and precision of catalytic residue prediction over other sequence-based methods and can be used to identify other types of functional residues. The web server takes an input protein sequence, gathers homologs, constructs a multiple sequence alignment and phylogenetic tree and finally runs the INTREPID method to assign a score to each position. Residues predicted to be functionally important are displayed on homologous 3D structures (where available), highlighting spatial patterns of conservation at various significance thresholds. The INTREPID web server is available at http://phylogenomics.berkeley.edu/intrepid.

  11. GO-At: in silico prediction of gene function in Arabidopsis thaliana by combining heterogeneous data.

    PubMed

    Bradford, James R; Needham, Chris J; Tedder, Philip; Care, Matthew A; Bulpitt, Andrew J; Westhead, David R

    2010-02-01

    Despite recent advances, accurate gene function prediction remains an elusive goal, with very few methods directly applicable to the plant Arabidopsis thaliana. In this study, we present GO-At (gene ontology prediction in A. thaliana), a method that combines five data types (co-expression, sequence, phylogenetic profile, interaction and gene neighbourhood) to predict gene function in Arabidopsis. Using a simple, yet powerful two-step approach, GO-At first generates a list of genes ranked in descending order of probability of functional association with the query gene. Next, a prediction score is automatically assigned to each function in this list based on the assumption that functions appearing most frequently at the top of the list are most likely to represent the function of the query gene. In this way, the second step provides an effective alternative to simply taking the 'best hit' from the first list, and achieves success rates of up to 79%. GO-At is applicable across all three GO categories: molecular function, biological process and cellular component, and can assign functions at multiple levels of annotation detail. Furthermore, we demonstrate GO-At's ability to predict functions of uncharacterized genes by identifying ten putative golgins/Golgi-associated proteins amongst 8219 genes of previously unknown cellular component and present independent evidence to support our predictions. A web-based implementation of GO-At (http://www.bioinformatics.leeds.ac.uk/goat) is available, providing a unique resource for plant researchers to make predictions for uncharacterized genes and predict novel functions in Arabidopsis.

  12. Sleep spindles predict neural and behavioral changes in motor sequence consolidation.

    PubMed

    Barakat, Marc; Carrier, Julie; Debas, Karen; Lungu, Ovidiu; Fogel, Stuart; Vandewalle, Gilles; Hoge, Richard D; Bellec, Pierre; Karni, Avi; Ungerleider, Leslie G; Benali, Habib; Doyon, Julien

    2013-11-01

    The purpose of this study was to investigate the predictive function of sleep spindles in motor sequence consolidation. BOLD responses were acquired in 10 young healthy subjects who were trained on an explicitly known 5-item sequence using their left nondominant hand, scanned at 9:00 pm while performing that same task and then were retested and scanned 12 h later after a night of sleep during which polysomnographic measures were recorded. An automatic algorithm was used to detect sleep spindles and to quantify their characteristics (i.e., density, amplitude, and duration). Analyses revealed significant positive correlations between gains in performance and the amplitude of spindles. Moreover, significant increases in BOLD signal were observed in several motor-related areas, most of which were localized in the right hemisphere, particularly in the right cortico-striatal system. Such increases in BOLD signal also correlated positively with the amplitude of spindles at several derivations. Taken together, our results show that sleep spindles predict neural and behavioral changes in overnight motor sequence consolidation.

  13. 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

  14. Modified estimators for the change point in hazard function

    NASA Astrophysics Data System (ADS)

    Karasoy, Durdu; Kadilar, Cem

    2009-07-01

    We propose the consistent estimators for the change point in hazard function by improving the estimators in [A.P. Basu, J.K. Ghosh, S.N. Joshi, On estimating change point in a failure rate, in: S.S. Gupta, J.O. Berger (Eds.), Statistical Decision Theory and Related Topics IV, vol. 2, Springer-Verlag, 1988, pp. 239-252] and [H.T. Nguyen, G.S. Rogers, E.A. Walker, Estimation in change point hazard rate model, Biometrika 71 (1984) 299-304]. By a simulation study, we show that the proposed estimators are more efficient than the original estimators in many cases.

  15. 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.

  16. Changes in brain functional network connectivity after stroke.

    PubMed

    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

  17. The relationship between change in self-perceptions of aging and physical functioning in older adults.

    PubMed

    Sargent-Cox, Kerry A; Anstey, Kaarin J; Luszcz, Mary A

    2012-09-01

    Negative self-perceptions of aging (SPA) have been linked to poor physical health and functioning outcomes in late life, yet the direction of this relationship remain unclear. Using data from the Australian Longitudinal Study of Aging, we investigated the directionality of the dynamic relationship between self-perceptions of aging and physical functioning in 1,212 adults 65 years and above (mean age = 76.89, SD = 6.12) over 5 waves (up to 16 years). Bivariate Dual Change Score Models (BDCSM) revealed that the best fitting model for the data was that which allowed SPA to predict change in physical functioning over time lags of 1 year. The direction of the relationship remained after controlling for age, gender, partner status, residential care, number of medical conditions, self-rated health, and psychological well-being. Findings suggest that more positive SPA may be protective of decline in physical functioning in late life. PMID:22390161

  18. Changes in the ecosystem structure of the Black Sea under predicted climatological and anthropogenic variations

    NASA Astrophysics Data System (ADS)

    Akoglu, Ekin; Salihoglu, Baris; Fach Salihoglu, Bettina; Libralato, Simone; Cannaby, Heather; Oguz, Temel; Solidoro, Cosimo

    2014-05-01

    A dynamic Ecopath with Ecosim higher-trophic-level (HTL) model representation of the Black Sea ecosystem was coupled to the physical (BIMS-CIR) and biogeochemical (BIMS-ECO) models of the Black Sea in order to investigate historical anthropogenic and climatological interactions and feedbacks in the ecosystem. Further, the coupled models were used to assess the likely consequences of these interactions on the ecosystem's structure and functioning under predicted future climate (IPCC A1B) and fishing variability. Therefore, two model scenarios were used; i) a hindcast scenario (1980-1999) to evaluate and understand the impacts of the short-term climate and physical variability and the introduction of invasive species on the Black Sea ecosystem, and ii) a forecast scenario (2080-2099) to investigate the potential implications of climate change and anthropogenic exploitation on living resources of the Black Sea ecosystem by the end of the 21st century. According to the outcomes of the hindcast simulation, fisheries were found to be the main driver in determining the structure and functioning of the Black Sea ecosystem under changing environmental conditions. The coupled physical-biogeochemical forecast simulations predicted a slight but statistically significant basin-wide increase in the Black Sea's primary productivity by the end of the century due to increased stratification induced by basin-wide temperature increase and reduced Cold Intermediate Layer (CIL) formation which increased the residence time of riverine nutrients within the euphotic zone. Despite this increased primary productivity, the HTL model forecast simulation predicted a significant decrease in the commercial fish stocks primarily due to fisheries exploitation if current catch rates are maintained into the future. Results further suggested that some economically important small pelagic fish species are likely to disappear from the ecosystem making the recovery of the already-collapsed piscivorous

  19. 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

  20. Positive Selection or Free to Vary? Assessing the Functional Significance of Sequence Change Using Molecular Dynamics.

    PubMed

    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

  1. [Change in pancreatic exocrine function in acute appendicitis].

    PubMed

    Ivanov, Iu A

    1979-10-01

    In order to study changes in the functional state of the pancreas 1572 investigations of the blood and urine amylase, atoxylresistant lipase of the blood serum before operation were performed in different postoperative periods in 131 patients with acute appendicitis. The enzyme activity was established to increase, especially in destructive forms of appendicitis and in elderly patients.

  2. [Changes in thyroid function in primary degenerative dementia processes].

    PubMed

    Bilikiewicz, A; Bidzan, L

    1989-01-01

    To overcome diagnostic uncertainties in early phases of Alzheimer's disease (pre-senile dementia), the analysis of T-3 and T-4 concentration can be usefully employed. Arising out of the localisation neuropathological findings in Alzheimer type dementia, it could be that hormonal findings perform a useful function as indicators of a change in neurotransmitter activity in this disease. PMID:2704767

  3. 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...

  4. 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,…

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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.

  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. 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

  14. Dynamic Change and Target Prediction of Axon-Specific MicroRNAs in Regenerating Sciatic Nerve

    PubMed Central

    Phay, Monichan; Kim, Hak Hee; Yoo, Soonmoon

    2015-01-01

    Injury to axons in the peripheral nervous system induces rapid and local regenerative responses to form a new growth cone, and to generate a retrogradely transporting injury signal. The evidence for essential roles of intra-axonal protein synthesis during regeneration is now compelling. MicroRNA (miRNA) has recently been recognized as a prominent player in post-transcriptional regulation of axonal protein synthesis. Here, we directly contrast temporal changes of miRNA levels in the sciatic nerve following injury, as compared to those in an uninjured nerve using deep sequencing. Small RNAs (<200 nucleotides in length) were fractionated from the proximal nerve stumps to improve the representation of differential miRNA levels. Of 141 axoplasmic miRNAs annotated, 63 rat miRNAs showed significantly differential levels at five time points following injury, compared to an uninjured nerve. The differential changes in miRNA levels responding to injury were processed for hierarchical clustering analyses, and used to predict target mRNAs by Targetscan and miRanda. By overlapping these predicted targets with 2,924 axonally localizing transcripts previously reported, the overlapping set of 214 transcripts was further analyzed by the Gene Ontology enrichment and Ingenuity Pathway Analyses. These results suggest the possibility that the potential targets for these miRNAs play key roles in numerous neurological functions involved in ER stress response, cytoskeleton dynamics, vesicle formation, and neuro-degeneration and-regeneration. Finally, our results suggest that miRNAs could play a direct role in regenerative response and may be manipulated to promote regenerative ability of injured nerves. PMID:26331719

  15. Neck circumference predicts renal function decline in overweight women

    PubMed Central

    Yoon, Chang-Yun; Park, Jung Tak; Jhee, Jong Hyun; Kee, Youn Kyung; Seo, Changhwan; Lee, Misol; Cha, Min-Uk; Jung, Su-Young; Park, Seohyun; Yun, Hae-Ryong; Kwon, Young Eun; Oh, Hyung Jung; Han, Seung Hyeok; Yoo, Tae-Hyun; Kang, Shin-Wook

    2016-01-01

    Abstract Chronic kidney disease (CKD) is characterized by increased risks of morbidity and mortality. Upper-body subcutaneous fat, which is commonly estimated from the neck circumference (NC), was revealed to be the main reservoir of circulating nonesterified fatty acids in overweight patients. Despite a close association between NC and metabolic complications, the relationship of NC with renal function has not been fully investigated. In this study, the impact of NC on the development of incident CKD was elucidated. The data were retrieved from the Korean Genome and Epidemiology Study cohort. The subjects were followed at 2-year intervals from 2003 to 2011. Overweight was defined as a body mass index of ≥23 kg/m2. A total of 4298 cohort subjects were screened. After exclusion, 2268 overweight subjects were included for the final analysis. The primary end point was incident CKD, which was defined as a composite of estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 or the development of proteinuria. The mean patient age was 36.3 ± 3.0 years, and 1285 (56.7%) were men. They were divided into 2 groups according to the median NC in male and female subjects, separately. In both sexes, hypertension (men, P < 0.001; women, P = 0.009) and diabetes (men, P = 0.002; women, P < 0.001) were significantly more prevalent in the big NC group than in the small NC group. In contrast, eGFR was significantly lower only in male subjects of the big NC group (P < 0.001), whereas it was comparable between the small and big NC groups (P = 0.167). In multivariate Cox proportional hazards regression analysis, NC values were independently associated with incident CKD development in female subjects after adjusting for multiple confounding factors (per 1 cm increase, hazard ratio [95% confidence interval] = 1.159 [1.024–1.310], P = 0.019) but not in male subjects. NC is independently associated with the development of CKD in overweight female

  16. 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.

  17. 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.

  18. 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…

  19. 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…

  20. 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...

  1. 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

  2. Structural–functional coupling changes in temporal lobe epilepsy

    PubMed Central

    Chiang, Sharon; Stern, John M.; Engel, Jerome; Haneef, Zulfi

    2016-01-01

    Alterations in both structural connectivity (SC) and functional connectivity (FC) have been reported in temporal lobe epilepsy (TLE). However, the relationship between FC and SC remains less understood. This study used functional connectivity MRI and diffusion tensor imaging to examine coupling of FC and SC within the limbic network of TLE, as well as its relation to epilepsy duration, regional changes, and disease laterality in 14 patients with left TLE, 10 with right TLE, and 11 healthy controls. Structural and functional networks were separately constructed and the correlation estimated between structural and functional connectivity. This measure of SC–FC coupling was compared between left/right TLE and controls, and correlated with epilepsy duration. Elastic net regression was used to investigate regional structural and functional changes associated with SC–FC coupling. SC–FC coupling was decreased in left TLE compared to controls, and accompanied by reductions in FC for left and right TLE and in SC for left TLE. When examined in relation to disease duration, an increase in SC–FC coupling with longer epilepsy duration was observed, associated predominantly with structural loss of the fusiform and frontal inferior orbital gyrus in left TLE and functional hub redistribution in right TLE. These results suggest that decoupling between structural and functional networks in TLE is modulated by several factors, including epilepsy duration and regional changes in the fusiform, frontal inferior orbital gyrus, posterior cingulate, and hippocampus. SC–FC coupling may provide a more sensitive biomarker of disease burden in TLE than biomarkers based on single imaging modalities. PMID:25960346

  3. 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)

  4. Health literacy predicts change in physical activity self-efficacy among sedentary Latinas.

    PubMed

    Dominick, Gregory M; Dunsiger, Shira I; Pekmezi, Dorothy W; Marcus, Bess H

    2013-06-01

    Health literacy (HL) is associated with preventive health behaviors. Self-efficacy is a predictor of health behavior, including physical activity (PA); however, causal pathways between HL and self-efficacy for PA are unknown, especially among Latinas who are at risk for chronic disease. To explore this potential relationship, secondary analyses were conducted on data [Shortened Test of Functional Health Literacy in Adults (STOFHLA), PA self-efficacy, and socio-demographics] from a 6-month, randomized controlled trial of a print-based PA intervention (n = 89 Spanish-speaking Latinas). Linear regression models revealed associations between HL and baseline self-efficacy in addition to changes in self-efficacy at 6-months. After controlling for significant covariates, higher HL scores were associated with lower baseline PA self-efficacy. Regardless of treatment assignment, higher HL scores at baseline predicted greater changes in PA self-efficacy at 6-months. HL may contribute to Latinas' improved PA self-efficacy, though further research is warranted.

  5. 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…

  6. Predicting Health Behavior Changes in Adolescents: A Tenth Grade Nutrition Curriculum.

    ERIC Educational Resources Information Center

    Loesch-Griffin, Deborah; And Others

    Two studies investigated the utility of a Cognitive-Behavior Change model in predicting adolescents' health behavior changes. The intervention specifically aimed at increasing students' knowledge of heart healthy habits, strengthening their beliefs, attitudes, and confidence regarding their ability to improve their health habits, and providing…

  7. 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…

  8. 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…

  9. 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

  10. Human Motor Cortex Functional Changes in Acute Stroke: Gender Effects

    PubMed Central

    Di Lazzaro, Vincenzo; Pellegrino, Giovanni; Di Pino, Giovanni; Ranieri, Federico; Lotti, Fiorenza; Florio, Lucia; Capone, Fioravante

    2016-01-01

    The acute phase of stroke is accompanied by functional changes in the activity and interplay of both hemispheres. In healthy subjects, gender is known to impact the functional brain organization. We investigated whether gender influences also acute stroke functional changes. In thirty-five ischemic stroke patients, we evaluated the excitability of the affected (AH) and unaffected hemisphere (UH) by measuring resting and active motor threshold (AMT) and motor-evoked potential amplitude under baseline conditions and after intermittent theta burst stimulation (iTBS) of AH. We also computed an index of the excitability balance between the hemispheres, laterality indexes (LI), to evidence hemispheric asymmetry. AMT differed significantly between AH and UH only in the male group (p = 0.004), not in females (p > 0.200), and both LIAMT and LIRMT were significantly higher in males than in females (respectively p = 0.033 and p = 0.042). LTP-like activity induced by iTBS in AH was more frequent in females. Gender influences the functional excitability changes that take place after human stroke and the level of LTP that can be induced by repetitive stimulation. This knowledge is of high value in the attempt of individualizing to different genders any non-invasive stimulation strategy designed to foster stroke recovery. PMID:26858590

  11. Emotion-Induced Topological Changes in Functional Brain Networks.

    PubMed

    Park, Chang-Hyun; Lee, Hae-Kook; Kweon, Yong-Sil; Lee, Chung Tai; Kim, Ki-Tae; Kim, Young-Joo; Lee, Kyoung-Uk

    2016-01-01

    In facial expression perception, a distributed network is activated according to stimulus context. We proposed that an interaction between brain activation and stimulus context in response to facial expressions could signify a pattern of interactivity across the whole brain network beyond the face processing network. Functional magnetic resonance imaging data were acquired for 19 young healthy subjects who were exposed to either emotionally neutral or negative facial expressions. We constructed group-wise functional brain networks for 12 face processing areas [bilateral inferior occipital gyri (IOG), fusiform gyri (FG), superior temporal sulci (STS), amygdalae (AMG), inferior frontal gyri (IFG), and orbitofrontal cortices (OFC)] and for 73 whole brain areas, based on partial correlation of mean activation across subjects. We compared the topological properties of the networks with respect to functional distance-based measures, global and local efficiency, between the two types of face stimulus. In both face processing and whole brain networks, global efficiency was lower and local efficiency was higher for negative faces relative to neutral faces, indicating that network topology differed according to stimulus context. Particularly in the face processing network, emotion-induced changes in network topology were attributable to interactions between core (bilateral IOG, FG, and STS) and extended (bilateral AMG, IFG, and OFC) systems. These results suggest that changes in brain activation patterns in response to emotional face stimuli could be revealed as changes in the topological properties of functional brain networks for the whole brain as well as for face processing areas.

  12. 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.

  13. Bayesian Markov Random Field analysis for protein function prediction based on network data.

    PubMed

    Kourmpetis, Yiannis A I; van Dijk, Aalt D J; Bink, Marco C A M; van Ham, Roeland C H J; ter Braak, Cajo J F

    2010-02-24

    Inference of protein functions is one of the most important aims of modern biology. To fully exploit the large volumes of genomic data typically produced in modern-day genomic experiments, automated computational methods for protein function prediction are urgently needed. Established methods use sequence or structure similarity to infer functions but those types of data do not suffice to determine the biological context in which proteins act. Current high-throughput biological experiments produce large amounts of data on the interactions between proteins. Such data can be used to infer interaction networks and to predict the biological process that the protein is involved in. Here, we develop a probabilistic approach for protein function prediction using network data, such as protein-protein interaction measurements. We take a Bayesian approach to an existing Markov Random Field method by performing simultaneous estimation of the model parameters and prediction of protein functions. We use an adaptive Markov Chain Monte Carlo algorithm that leads to more accurate parameter estimates and consequently to improved prediction performance compared to the standard Markov Random Fields method. We tested our method using a high quality S. cereviciae validation network with 1622 proteins against 90 Gene Ontology terms of different levels of abstraction. Compared to three other protein function prediction methods, our approach shows very good prediction performance. Our method can be directly applied to protein-protein interaction or coexpression networks, but also can be extended to use multiple data sources. We apply our method to physical protein interaction data from S. cerevisiae and provide novel predictions, using 340 Gene Ontology terms, for 1170 unannotated proteins and we evaluate the predictions using the available literature.

  14. 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

  15. 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.

  16. Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction

    PubMed Central

    2013-01-01

    Background Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers. Results This article demonstrates the benefits (in terms of predictive accuracy) of considering autocorrelation in multi-class gene function prediction. We develop a tree-based algorithm for considering network autocorrelation in the setting of Hierarchical Multi-label Classification (HMC). We empirically evaluate the proposed algorithm, called NHMC (Network Hierarchical Multi-label Classification), on 12 yeast datasets using each of the MIPS-FUN and GO annotation schemes and exploiting 2 different PPI networks. The results clearly show that taking autocorrelation into account improves the predictive performance of the learned models for predicting gene function. Conclusions Our newly developed method for HMC takes into account network information in the learning phase: When

  17. Improvements to executive function during exercise training predict maintenance of physical activity over the following year

    PubMed Central

    Best, John R.; Nagamatsu, Lindsay S.; Liu-Ambrose, Teresa

    2014-01-01

    Previous studies have shown that exercise training benefits cognitive, neural, and physical health markers in older adults. It is likely that these positive effects will diminish if participants return to sedentary lifestyles following training cessation. Theory posits that that the neurocognitive processes underlying self-regulation, namely executive function (EF), are important to maintaining positive health behaviors. Therefore, we examined whether better EF performance in older women would predict greater adherence to routine physical activity (PA) over 1 year following a 12-month resistance exercise training randomized controlled trial. The study sample consisted of 125 community-dwelling women aged 65–75 years old. Our primary outcome measure was self-reported PA, as measured by the Physical Activity Scale for the Elderly (PASE), assessed on a monthly basis from month 13 to month 25. Executive function was assessed using the Stroop Test at baseline (month 0) and post-training (month 12). Latent growth curve analyses showed that, on average, PA decreased during the follow-up period but at a decelerating rate. Women who made greater improvements to EF during the training period showed better adherence to PA during the 1-year follow-up period (β = −0.36, p < 0.05); this association was unmitigated by the addition of covariates (β = −0.44, p < 0.05). As expected, EF did not predict changes in PA during the training period (p > 0.10). Overall, these findings suggest that improving EF plays an important role in whether older women maintain higher levels of PA following exercise training and that this association is only apparent after training when environmental support for PA is low. PMID:24904387

  18. Predicting accurate fluorescent spectra for high molecular weight polycyclic aromatic hydrocarbons using density functional theory

    NASA Astrophysics Data System (ADS)

    Powell, Jacob; Heider, Emily C.; Campiglia, Andres; Harper, James K.

    2016-10-01

    The ability of density functional theory (DFT) methods to predict accurate fluorescence spectra for polycyclic aromatic hydrocarbons (PAHs) is explored. Two methods, PBE0 and CAM-B3LYP, are evaluated both in the gas phase and in solution. Spectra for several of the most toxic PAHs are predicted and compared to experiment, including three isomers of C24H14 and a PAH containing heteroatoms. Unusually high-resolution experimental spectra are obtained for comparison by analyzing each PAH at 4.2 K in an n-alkane matrix. All theoretical spectra visually conform to the profiles of the experimental data but are systematically offset by a small amount. Specifically, when solvent is included the PBE0 functional overestimates peaks by 16.1 ± 6.6 nm while CAM-B3LYP underestimates the same transitions by 14.5 ± 7.6 nm. These calculated spectra can be empirically corrected to decrease the uncertainties to 6.5 ± 5.1 and 5.7 ± 5.1 nm for the PBE0 and CAM-B3LYP methods, respectively. A comparison of computed spectra in the gas phase indicates that the inclusion of n-octane shifts peaks by +11 nm on average and this change is roughly equivalent for PBE0 and CAM-B3LYP. An automated approach for comparing spectra is also described that minimizes residuals between a given theoretical spectrum and all available experimental spectra. This approach identifies the correct spectrum in all cases and excludes approximately 80% of the incorrect spectra, demonstrating that an automated search of theoretical libraries of spectra may eventually become feasible.

  19. Drug-target interaction prediction by integrating chemical, genomic, functional and pharmacological data.

    PubMed

    Yang, Fan; Xu, Jinbo; Zeng, Jianyang

    2014-01-01

    In silico prediction of unknown drug-target interactions (DTIs) has become a popular tool for drug repositioning and drug development. A key challenge in DTI prediction lies in integrating multiple types of data for accurate DTI prediction. Although recent studies have demonstrated that genomic, chemical and pharmacological data can provide reliable information for DTI prediction, it remains unclear whether functional information on proteins can also contribute to this task. Little work has been developed to combine such information with other data to identify new interactions between drugs and targets. In this paper, we introduce functional data into DTI prediction and construct biological space for targets using the functional similarity measure. We present a probabilistic graphical model, called conditional random field (CRF), to systematically integrate genomic, chemical, functional and pharmacological data plus the topology of DTI networks into a unified framework to predict missing DTIs. Tests on two benchmark datasets show that our method can achieve excellent prediction performance with the area under the precision-recall curve (AUPR) up to 94.9. These results demonstrate that our CRF model can successfully exploit heterogeneous data to capture the latent correlations of DTIs, and thus will be practically useful for drug repositioning. Supplementary Material is available at http://iiis.tsinghua.edu.cn/~compbio/papers/psb2014/psb2014_sm.pdf. PMID:24297542

  20. Emotionally biased cognitive processes: the weakest link predicts prospective changes in depressive symptom severity.

    PubMed

    Everaert, Jonas; Duyck, Wouter; Koster, Ernst H W

    2015-01-01

    Emotional biases in attention, interpretation, and memory are predictive of future depressive symptoms. It remains unknown, however, how these biased cognitive processes interact to predict depressive symptom levels in the long-term. In the present study, we tested the predictive value of two integrative approaches to model relations between multiple biased cognitive processes, namely the additive (i.e., cognitive processes have a cumulative effect) vs. the weakest link (i.e., the dominant pathogenic process is important) model. We also tested whether these integrative models interacted with perceived stress to predict prospective changes in depressive symptom severity. At Time 1, participants completed measures of depressive symptom severity and emotional biases in attention, interpretation, and memory. At Time 2, one year later, participants were reassessed to determine depressive symptom levels and perceived stress. Results revealed that the weakest link model had incremental validity over the additive model in predicting prospective changes in depressive symptoms, though both models explained a significant proportion of variance in the change in depressive symptoms from Time 1 to Time 2. None of the integrative models interacted with perceived stress to predict changes in depressive symptomatology. These findings suggest that the best cognitive marker of the evolution in depressive symptoms is the cognitive process that is dominantly biased toward negative material, which operates independent from experienced stress. This highlights the importance of considering idiographic cognitive profiles with multiple cognitive processes for understanding and modifying effects of cognitive biases in depression.

  1. Gene-Specific Function Prediction for Non-Synonymous Mutations in Monogenic Diabetes Genes

    PubMed Central

    Li, Quan; Liu, Xiaoming; Gibbs, Richard A.; Boerwinkle, Eric; Polychronakos, Constantin; Qu, Hui-Qi

    2014-01-01

    The rapid progress of genomic technologies has been providing new opportunities to address the need of maturity-onset diabetes of the young (MODY) molecular diagnosis. However, whether a new mutation causes MODY can be questionable. A number of in silico methods have been developed to predict functional effects of rare human mutations. The purpose of this study is to compare the performance of different bioinformatics methods in the functional prediction of nonsynonymous mutations in each MODY gene, and provides reference matrices to assist the molecular diagnosis of MODY. Our study showed that the prediction scores by different methods of the diabetes mutations were highly correlated, but were more complimentary than replacement to each other. The available in silico methods for the prediction of diabetes mutations had varied performances across different genes. Applying gene-specific thresholds defined by this study may be able to increase the performance of in silico prediction of disease-causing mutations. PMID:25136813

  2. PHOENIX: A Scoring Function for Affinity Prediction Derived Using High-Resolution Crystal Structures and Calorimetry Measurements

    PubMed Central

    Tang, Yat T.; Marshall, Garland R.

    2011-01-01

    Binding affinity prediction is one of the most critical components to computer-aided structure-based drug design. Despite advances in first-principle methods for predicting binding affinity, empirical scoring functions that are fast and only relatively accurate are still widely used in structure-based drug design. With the increasing availability of X-ray crystallographic structures in the Protein Data Bank and continuing application of biophysical methods such as isothermal titration calorimetry to measure thermodynamic parameters contributing to binding free energy, sufficient experimental data exists that scoring functions can now be derived by separating enthalpic (ΔH) and entropic (TΔS) contributions to binding free energy (ΔG). PHOENIX, a scoring function to predict binding affinities of protein-ligand complexes, utilizes the increasing availability of experimental data to improve binding affinity predictions by the following: model training and testing using high-resolution crystallographic data to minimize structural noise, independent models of enthalpic and entropic contributions fitted to thermodynamic parameters assumed to be thermodynamically biased to calculate binding free energy, use of shape and volume descriptors to better capture entropic contributions. A set of 42 descriptors and 112 protein-ligand complexes were used to derive functions using partial least squares for change of enthalpy (ΔH) and change of entropy (TΔS) to calculate change of binding free energy (ΔG), resulting in a predictive r2 (r2pred) of 0.55 and a standard error (SE) of 1.34 kcal/mol. External validation using the 2009 version of the PDBbind “refined set” (n = 1612) resulted in a Pearson correlation coefficient (Rp) of 0.575 and a mean error (ME) of 1.41 pKd. Enthalpy and entropy predictions were of limited accuracy individually. However, their difference resulted in a relatively accurate binding free energy. While the development of an accurate and applicable

  3. A bridge-functional-based classical mapping method for predicting the correlation functions of uniform electron gases at finite temperature

    SciTech Connect

    Liu, Yu; Wu, Jianzhong

    2014-02-28

    Efficient and accurate prediction of the correlation functions of uniform electron gases is of great importance for both practical and theoretical applications. This paper presents a bridge-functional-based classical mapping method for calculating the correlation functions of uniform spin-unpolarized electron gases at finite temperature. The bridge functional is formulated by following Rosenfeld's universality ansatz in combination with the modified fundamental measure theory. The theoretical predictions are in good agreement with recent quantum Monte Carlo results but with negligible computational cost, and the accuracy is better than a previous attempt based on the hypernetted-chain approximation. We find that the classical mapping method is most accurate if the effective mass of electrons increases as the density falls.

  4. Enhancing protein function prediction with taxonomic constraints--The Argot2.5 web server.

    PubMed

    Lavezzo, Enrico; Falda, Marco; Fontana, Paolo; Bianco, Luca; Toppo, Stefano

    2016-01-15

    Argot2.5 (Annotation Retrieval of Gene Ontology Terms) is a web server designed to predict protein function. It is an updated version of the previous Argot2 enriched with new features in order to enhance its usability and its overall performance. The algorithmic strategy exploits the grouping of Gene Ontology terms by means of semantic similarity to infer protein function. The tool has been challenged over two independent benchmarks and compared to Argot2, PANNZER, and a baseline method relying on BLAST, proving to obtain a better performance thanks to the contribution of some key interventions in critical steps of the working pipeline. The most effective changes regard: (a) the selection of the input data from sequence similarity searches performed against a clustered version of UniProt databank and a remodeling of the weights given to Pfam hits, (b) the application of taxonomic constraints to filter out annotations that cannot be applied to proteins belonging to the species under investigation. The taxonomic rules are derived from our in-house developed tool, FunTaxIS, that extends those provided by the Gene Ontology consortium. The web server is free for academic users and is available online at http://www.medcomp.medicina.unipd.it/Argot2-5/.

  5. Gastric microbiota and predicted gene functions are altered after subtotal gastrectomy in patients with gastric cancer

    PubMed Central

    Tseng, Ching-Hung; Lin, Jaw-Town; Ho, Hsiu J.; Lai, Zi-Lun; Wang, Chang-Bi; Tang, Sen-Lin; Wu, Chun-Ying

    2016-01-01

    Subtotal gastrectomy (i.e., partial removal of the stomach), a surgical treatment for early-stage distal gastric cancer, is usually accompanied by highly selective vagotomy and Billroth II reconstruction, leading to dramatic changes in the gastric environment. Based on accumulating evidence of a strong link between human gut microbiota and host health, a 2-year follow-up study was conducted to characterize the effects of subtotal gastrectomy. Gastric microbiota and predicted gene functions inferred from 16S rRNA gene sequencing were analyzed before and after surgery. The results demonstrated that gastric microbiota is significantly more diverse after surgery. Ralstonia and Helicobacter were the top two genera of discriminant abundance in the cancerous stomach before surgery, while Streptococcus and Prevotella were the two most abundant genera after tumor excision. Furthermore, N-nitrosation genes were prevalent before surgery, whereas bile salt hydrolase, NO and N2O reductase were prevalent afterward. To our knowledge, this is the first report to document changes in gastric microbiota before and after surgical treatment of stomach cancer. PMID:26860194

  6. Optical spectroscopy approach for the predictive assessment of kidney functional recovery following ischemic injury

    NASA Astrophysics Data System (ADS)

    Raman, Rajesh N.; Pivetti, Christopher D.; Rubenchik, Alexander M.; Matthews, Dennis L.; Troppmann, Christoph; Demos, Stavros G.

    2010-02-01

    Tissue that has undergone significant yet unknown amount of ischemic injury is frequently encountered in organ transplantation and trauma clinics. With no reliable real-time method of assessing the degree of injury incurred in tissue, surgeons generally rely on visual observation which is subjective. In this work, we investigate the use of optical spectroscopy methods as a potentially more reliable approach. Previous work by various groups was strongly suggestive that tissue autofluorescence from NADH obtained under UV excitation is sensitive to metabolic response changes. To test and expand upon this concept, we monitored autofluorescence and light scattering intensities of injured vs. uninjured rat kidneys via multimodal imaging under 355 nm, 325 nm, and 266 nm excitation as well as scattering under 500 nm illumination. 355 nm excitation was used to probe mainly NADH, a metabolite, while 266 nm excitation was used to probe mainly tryptophan to correct for non-metabolic signal artifacts. The ratio of autofluorescence intensities derived under these two excitation wavelengths was calculated and its temporal profile was fit to a relaxation model. Time constants were extracted, and longer time constants were associated with kidney dysfunction. Analysis of both the autofluorescence and light scattering images suggests that changes in microstructure tissue morphology, blood absorption spectral characteristics, and pH contribute to the behavior of the observed signal which may be used to obtain tissue functional information and offer predictive capability.

  7. Optical Spectroscopy Approach for the Predictive Assessment of Kidney Functional Recovery Following Ischemic Injury

    SciTech Connect

    Raman, R N; Pivetti, C D; Rubenchik, A M; Matthews, D L; Troppmann, C; Demos, S G

    2010-02-11

    Tissue that has undergone significant yet unknown amount of ischemic injury is frequently encountered in organ transplantation and trauma clinics. With no reliable real-time method of assessing the degree of injury incurred in tissue, surgeons generally rely on visual observation which is subjective. In this work, we investigate the use of optical spectroscopy methods as a potentially more reliable approach. Previous work by various groups was strongly suggestive that tissue autofluorescence from NADH obtained under UV excitation is sensitive to metabolic response changes. To test and expand upon this concept, we monitored autofluorescence and light scattering intensities of injured vs. uninjured rat kidneys via multimodal imaging under 355 nm, 325 nm, and 266 nm excitation as well as scattering under 500 nm illumination. 355 nm excitation was used to probe mainly NADH, a metabolite, while 266 nm excitation was used to probe mainly tryptophan to correct for non-metabolic signal artifacts. The ratio of autofluorescence intensities derived under these two excitation wavelengths was calculated and its temporal profile was fit to a relaxation model. Time constants were extracted, and longer time constants were associated with kidney dysfunction. Analysis of both the autofluorescence and light scattering images suggests that changes in microstructure tissue morphology, blood absorption spectral characteristics, and pH contribute to the behavior of the observed signal which may be used to obtain tissue functional information and offer predictive capability.

  8. Genetic divergence does not predict change in ornament expression among populations of stalk-eyed flies.

    PubMed

    Swallow, John G; Wallace, Lisa E; Christianson, Sarah J; Johns, Philip M; Wilkinson, Gerald S

    2005-10-01

    Stalk-eyed flies (Diptera: Diopsidae) possess eyes at the ends of elongated peduncles, and exhibit dramatic variation in eye span, relative to body length, among species. In some sexually dimorphic species, evidence indicates that eye span is under both intra- and intersexual selection. Theory predicts that isolated populations should evolve differences in sexually selected traits due to drift. To determine if eye span changes as a function of divergence time, 1370 flies from 10 populations of the sexually dimorphic species, Cyrtodiopsis dalmanni and Cyrtodiopsis whitei, and one population of the sexually monomorphic congener, Cyrtodiopsis quinqueguttata, were collected from Southeast Asia and measured. Genetic differentiation was used to assess divergence time by comparing mitochondrial (cytochrome oxidase II and 16S ribosomal RNA gene fragments) and nuclear (wingless gene fragment) DNA sequences for c. five individuals per population. Phylogenetic analyses indicate that most populations cluster as monophyletic units with up to 9% nucleotide substitutions between populations within a species. Analyses of molecular variance suggest a high degree of genetic structure within and among the populations; > 97% of the genetic variance occurs between populations and species while < 3% is distributed within populations, indicating that most populations have been isolated for thousands of years. Nevertheless, significant change in the allometric slope of male eye span on body length was detected for only one population of either dimorphic species. These results are not consistent with genetic drift. Rather, relative eye span appears to be under net stabilizing selection in most populations of stalk-eyed flies. Given that one population exhibited dramatic evolutionary change, selection, rather than genetic variation, appears to constrain eye span evolution.

  9. 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

  10. Age-Related Changes in Predictive Capacity Versus Internal Model Adaptability: Electrophysiological Evidence that Individual Differences Outweigh Effects of Age.

    PubMed

    Bornkessel-Schlesewsky, Ina; Philipp, Markus; Alday, Phillip M; Kretzschmar, Franziska; Grewe, Tanja; Gumpert, Maike; Schumacher, Petra B; Schlesewsky, Matthias

    2015-01-01

    Hierarchical predictive coding has been identified as a possible unifying principle of brain function, and recent work in cognitive neuroscience has examined how it may be affected by age-related changes. Using language comprehension as a test case, the present study aimed to dissociate age-related changes in prediction generation versus internal model adaptation following a prediction error. Event-related brain potentials (ERPs) were measured in a group of older adults (60-81 years; n = 40) as they read sentences of the form "The opposite of black is white/yellow/nice." Replicating previous work in young adults, results showed a target-related P300 for the expected antonym ("white"; an effect assumed to reflect a prediction match), and a graded N400 effect for the two incongruous conditions (i.e. a larger N400 amplitude for the incongruous continuation not related to the expected antonym, "nice," versus the incongruous associated condition, "yellow"). These effects were followed by a late positivity, again with a larger amplitude in the incongruous non-associated versus incongruous associated condition. Analyses using linear mixed-effects models showed that the target-related P300 effect and the N400 effect for the incongruous non-associated condition were both modulated by age, thus suggesting that age-related changes affect both prediction generation and model adaptation. However, effects of age were outweighed by the interindividual variability of ERP responses, as reflected in the high proportion of variance captured by the inclusion of by-condition random slopes for participants and items. We thus argue that - at both a neurophysiological and a functional level - the notion of general differences between language processing in young and older adults may only be of limited use, and that future research should seek to better understand the causes of interindividual variability in the ERP responses of older adults and its relation to cognitive performance. PMID

  11. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

    EPA Science Inventory

    We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

  12. COMBREX-DB: an experiment centered database of protein function: knowledge, predictions and knowledge gaps.

    PubMed

    Chang, Yi-Chien; Hu, Zhenjun; Rachlin, John; Anton, Brian P; Kasif, Simon; Roberts, Richard J; Steffen, Martin

    2016-01-01

    The COMBREX database (COMBREX-DB; combrex.bu.edu) is an online repository of information related to (i) experimentally determined protein function, (ii) predicted protein function, (iii) relationships among proteins of unknown function and various types of experimental data, including molecular function, protein structure, and associated phenotypes. The database was created as part of the novel COMBREX (COMputational BRidges to EXperiments) effort aimed at accelerating the rate of gene function validation. It currently holds information on ∼ 3.3 million known and predicted proteins from over 1000 completely sequenced bacterial and archaeal genomes. The database also contains a prototype recommendation system for helping users identify those proteins whose experimental determination of function would be most informative for predicting function for other proteins within protein families. The emphasis on documenting experimental evidence for function predictions, and the prioritization of uncharacterized proteins for experimental testing distinguish COMBREX from other publicly available microbial genomics resources. This article describes updates to COMBREX-DB since an initial description in the 2011 NAR Database Issue.

  13. Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment.

    PubMed

    Shameer, Khader; Tripathi, Lokesh P; Kalari, Krishna R; Dudley, Joel T; Sowdhamini, Ramanathan

    2016-09-01

    Accurate assessment of genetic variation in human DNA sequencing studies remains a nontrivial challenge in clinical genomics and genome informatics. Ascribing functional roles and/or clinical significances to single nucleotide variants identified from a next-generation sequencing study is an important step in genome interpretation. Experimental characterization of all the observed functional variants is yet impractical; thus, the prediction of functional and/or regulatory impacts of the various mutations using in silico approaches is an important step toward the identification of functionally significant or clinically actionable variants. The relationships between genotypes and the expressed phenotypes are multilayered and biologically complex; such relationships present numerous challenges and at the same time offer various opportunities for the design of in silico variant assessment strategies. Over the past decade, many bioinformatics algorithms have been developed to predict functional consequences of single nucleotide variants in the protein coding regions. In this review, we provide an overview of the bioinformatics resources for the prediction, annotation and visualization of coding single nucleotide variants. We discuss the currently available approaches and major challenges from the perspective of protein sequence, structure, function and interactions that require consideration when interpreting the impact of putatively functional variants. We also discuss the relevance of incorporating integrated workflows for predicting the biomedical impact of the functionally important variations encoded in a genome, exome or transcriptome. Finally, we propose a framework to classify variant assessment approaches and strategies for incorporation of variant assessment within electronic health records.

  14. COMBREX-DB: an experiment centered database of protein function: knowledge, predictions and knowledge gaps.

    PubMed

    Chang, Yi-Chien; Hu, Zhenjun; Rachlin, John; Anton, Brian P; Kasif, Simon; Roberts, Richard J; Steffen, Martin

    2016-01-01

    The COMBREX database (COMBREX-DB; combrex.bu.edu) is an online repository of information related to (i) experimentally determined protein function, (ii) predicted protein function, (iii) relationships among proteins of unknown function and various types of experimental data, including molecular function, protein structure, and associated phenotypes. The database was created as part of the novel COMBREX (COMputational BRidges to EXperiments) effort aimed at accelerating the rate of gene function validation. It currently holds information on ∼ 3.3 million known and predicted proteins from over 1000 completely sequenced bacterial and archaeal genomes. The database also contains a prototype recommendation system for helping users identify those proteins whose experimental determination of function would be most informative for predicting function for other proteins within protein families. The emphasis on documenting experimental evidence for function predictions, and the prioritization of uncharacterized proteins for experimental testing distinguish COMBREX from other publicly available microbial genomics resources. This article describes updates to COMBREX-DB since an initial description in the 2011 NAR Database Issue. PMID:26635392

  15. COMBREX-DB: an experiment centered database of protein function: knowledge, predictions and knowledge gaps

    PubMed Central

    Chang, Yi-Chien; Hu, Zhenjun; Rachlin, John; Anton, Brian P.; Kasif, Simon; Roberts, Richard J.; Steffen, Martin

    2016-01-01

    The COMBREX database (COMBREX-DB; combrex.bu.edu) is an online repository of information related to (i) experimentally determined protein function, (ii) predicted protein function, (iii) relationships among proteins of unknown function and various types of experimental data, including molecular function, protein structure, and associated phenotypes. The database was created as part of the novel COMBREX (COMputational BRidges to EXperiments) effort aimed at accelerating the rate of gene function validation. It currently holds information on ∼3.3 million known and predicted proteins from over 1000 completely sequenced bacterial and archaeal genomes. The database also contains a prototype recommendation system for helping users identify those proteins whose experimental determination of function would be most informative for predicting function for other proteins within protein families. The emphasis on documenting experimental evidence for function predictions, and the prioritization of uncharacterized proteins for experimental testing distinguish COMBREX from other publicly available microbial genomics resources. This article describes updates to COMBREX-DB since an initial description in the 2011 NAR Database Issue. PMID:26635392

  16. 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. PMID:26804571

  17. Using the functional response of a consumer to predict biotic resistance to invasive prey.

    PubMed

    Twardochleb, Laura A; Novak, Mark; Moore, Jonathan W

    2012-06-01

    Predators sometimes provide biotic resistance against invasions by nonnative prey. Understanding and predicting the strength of biotic resistance remains a key challenge in invasion biology. A predator's functional response to nonnative prey may predict whether a predator can provide biotic resistance against nonnative prey at different prey densities. Surprisingly, functional responses have not been used to make quantitative predictions about biotic resistance. We parameterized the functional response of signal crayfish (Pacifastacus leniusculus) to invasive New Zealand mud snails (Potamopyrgus antipodarum; NZMS) and used this functional response and a simple model of NZMS population growth to predict the probability of biotic resistance at different predator and prey densities. Signal crayfish were effective predators of NZMS, consuming more than 900 NZMS per predator in a 12-h period, and Bayesian model fitting indicated their consumption rate followed a type 3 functional response to NZMS density. Based on this functional response and associated parameter uncertainty, we predict that NZMS will be able to invade new systems at low crayfish densities (< 0.2 crayfish/m2) regardless of NZMS density. At intermediate to high crayfish densities (> 0.2 crayfish/m2), we predict that low densities of NZMS will be able to establish in new communities; however, once NZMS reach a threshold density of -2000 NZMS/m2, predation by crayfish will drive negative NZMS population growth. Further, at very high densities, NZMS overwhelm predation by crayfish and invade. Thus, interacting thresholds of propagule pressure and predator densities define the probability of biotic resistance. Quantifying the shape and uncertainty of predator functional responses to nonnative prey may help predict the outcomes of invasions.

  18. Functional connectivity changes in second language vocabulary learning.

    PubMed

    Ghazi Saidi, Ladan; Perlbarg, Vincent; Marrelec, Guillaume; Pélégrini-Issac, Mélani; Benali, Habib; Ansaldo, Ana-Inés

    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, Bellec et al., 2008) were gathered, in the shallow and consolidation phases of L2 vocabulary learning. Functional connectivity remained unchanged across learning phases for L1, whereas total, between- and within-network integration levels decreased as proficiency for L2 increased. The results of this study provide the first functional connectivity evidence regarding the dynamic role of the language processing and cognitive control networks in L2 learning (Abutalebi, Cappa, & Perani, 2005; Altarriba & Heredia, 2008; Leonard et al., 2011; Parker-Jones et al., 2011). Thus, increased proficiency results in a higher degree of automaticity and lower cognitive effort (Segalowitz & Hulstijn, 2005).

  19. Functional and histopathologic changes in the liver during sepsis.

    PubMed

    Caruana, J A; Montes, M; Camara, D S; Ummer, A; Potmesil, S H; Gage, A A

    1982-05-01

    Although liver failure from sepsis is a frequent occurrence in serious ill, hospitalized patients, little information is available on the histologic changes of the liver. We examined the histopathology of the liver of 19 patients who died of clinical sepsis and attempted to relate certain features of the illness or treatment to the observed histopathologic changes. The most striking finding was midzonal and peripheral necrosis of a moderate to marked degree in 11 of 19 patients. Other important changes were acute inflammation and cholestasis. The severity of hepatocellular necrosis did not appear to be influenced by the premortem circulating pathogen, by the nutritional support administered or by the arterial blood pressure. It is suggested that hepatocellular necrosis is characteristic of sepsis and may be caused by loss of specific factors which normally maintain liver function and structure. PMID:6803371

  20. Pulmonary function parameters changes at different altitudes in healthy athletes.

    PubMed

    Ziaee, Vahid; Alizadeh, Reza; Movafegh, Al