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Sample records for jnk1 activation predicts

  1. Prolonged duration of isoflurane anesthesia impairs spatial recognition memory through the activation of JNK1/2 in the hippocampus of mice.

    Science.gov (United States)

    Jiang, Shan; Miao, Bei; Chen, Ying

    2017-05-03

    Postoperative cognitive dysfunction is a frequent complication with surgery and anesthesia, and the underlying mechanism is unclear. Our aim was to investigate the effect of different durations of isoflurane anesthesia on spatial recognition memory and activation of JNK1/2 in the hippocampus of mice. In the present study, adult male mice were anesthetized with isoflurane for different durations (1.5% isoflurane for 1, 2, and 4 h). Spatial recognition memory was determined using spontaneous alternation and two-trial recognition memory in Y-maze at 24 h after anesthesia. The activation of JNK1/2 in the hippocampus was tested using western blot. Mice treated with isoflurane for 4 h showed significantly decreased spontaneous alternations and decreased exploration parameters compared with the no anesthesia group, but this was not observed in mice treated with isoflurane for 1 or 2 h. The protein levels of p-JNK1/2 in the hippocampus were significantly increased at 10 min after isoflurane anesthesia for 1, 2, and 4 h compared with no anesthesia. However, only isoflurane anesthesia for 4 h still increased JNK1/2 and p-JNK1/2 levels at 24 h after anesthesia. We concluded that prolonged duration of isoflurane anesthesia maintained the activation of JNK1/2, which led to memory impairment at 24 h after anesthesia.

  2. Phosphorylation- and nucleotide-binding-induced changes to the stability and hydrogen exchange patterns of JNK1ß1 provide insight into its mechanisms of activation

    CSIR Research Space (South Africa)

    Owen, GR

    2014-10-01

    Full Text Available –deuterium exchange (HX) mass spectrometry were used to investigate the changes to the stability and conformation/conformational dynamics of JNK1ß1 induced by phosphorylative activation. Equivalent studies were also employed to determine the effects of nucleotide...

  3. MAPK/JNK1 activation protects cells against cadmium-induced autophagic cell death via differential regulation of catalase and heme oxygenase-1 in oral cancer cells.

    Science.gov (United States)

    So, Keum-Young; Kim, Sang-Hun; Jung, Ki-Tae; Lee, Hyun-Young; Oh, Seon-Hee

    2017-10-01

    Antioxidant enzymes are related to oral diseases. We investigated the roles of heme oxygenase-1 (HO-1) and catalase in cadmium (Cd)-induced oxidative stress and the underlying molecular mechanism in oral cancer cells. Exposing YD8 cells to Cd reduced the expression levels of catalase and superoxide dismutase 1/2 and induced the expression of HO-1 as well as autophagy and apoptosis, which were reversed by N-acetyl-l-cysteine (NAC). Cd-exposed YD10B cells exhibited milder effects than YD8 cells, indicating that Cd sensitivity is associated with antioxidant enzymes and autophagy. Autophagy inhibition via pharmacologic and genetic modulations enhanced Cd-induced HO-1 expression, caspase-3 cleavage, and the production of reactive oxygen species (ROS). Ho-1 knockdown increased autophagy and apoptosis. Hemin treatment partially suppressed Cd-induced ROS production and apoptosis, but enhanced autophagy and CHOP expression, indicating that autophagy induction is associated with cellular stress. Catalase inhibition by pharmacological and genetic modulations increased Cd-induced ROS production, autophagy, and apoptosis, but suppressed HO-1, indicating that catalase is required for HO-1 induction. p38 inhibition upregulated Cd-induced phospho-JNK and catalase, but suppressed HO-1, autophagy, apoptosis. JNK suppression exhibited contrary results, enhancing the expression of phospho-p38. Co-suppression of p38 and JNK1 failed to upregulate catalase and procaspase-3, which were upregulated by JNK1 overexpression. Overall, the balance between the responses of p38 and JNK activation to Cd appears to have an important role in maintaining cellular homeostasis via the regulation of antioxidant enzymes and autophagy induction. In addition, the upregulation of catalase by JNK1 activation can play a critical role in cell protection against Cd-induced oxidative stress. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. JNK1/2 Activation by an Extract from the Roots of Morus alba L. Reduces the Viability of Multidrug-Resistant MCF-7/Dox Cells by Inhibiting YB-1-Dependent MDR1 Expression

    Directory of Open Access Journals (Sweden)

    Youn Kyung Choi

    2013-01-01

    Full Text Available Cancer cells acquire anticancer drug resistance during chemotherapy, which aggravates cancer disease. MDR1 encoded from multidrug resistance gene 1 mainly causes multidrug resistance phenotypes of different cancer cells. In this study, we demonstrate that JNK1/2 activation by an extract from the root of Morus alba L. (White mulberry reduces doxorubicin-resistant MCF-7/Dox cell viability by inhibiting YB-1 regulation of MDR1 gene expression. When MCF-7 or MCF-7/Dox cells, where MDR1 is highly expressed were treated with an extract from roots or leaves of Morus alba L., respectively, the root extract from the mulberry (REM but not the leaf extract (LEM reduced cell viabilities of both MCF-7 and MCF-7/Dox cells, which was enhanced by cotreatment with doxorubicin. REM but not LEM further inhibited YB-1 nuclear translocation and its regulation of MDR1 gene expression. Moreover, REM promoted phosphorylation of c-Jun NH2-terminal kinase 1/2 (JNK1/2 and JNK1/2 inhibitor, SP600125 and rescued REM inhibition of both MDR1 expression and viabilities in MCF-7/Dox cells. Consistently, overexpression of JNK1, c-Jun, or c-Fos inhibited YB-1-dependent MDR1 expression and reduced viabilities in MCF-7/Dox cells. In conclusion, our data indicate that REM-activated JNK-cJun/c-Fos pathway decreases the viability of MCF-7/Dox cells by inhibiting YB-1-dependent MDR1 gene expression. Thus, we suggest that REM may be useful for treating multidrug-resistant cancer cells.

  5. JNK1 induces hedgehog signaling from stellate cells to accelerate liver regeneration in mice.

    Science.gov (United States)

    Langiewicz, Magda; Graf, Rolf; Humar, Bostjan; Clavien, Pierre A

    2018-04-27

    To improve outcomes of two-staged hepatectomies for large/multiple liver tumors, portal vein ligation (PVL) has been combined with parenchymal transection (coined ALPPS; Associated Liver Partition and Portal vein ligation for Staged hepatectomy) to greatly accelerate liver regeneration. In a novel ALPPS mouse model, we have reported paracrine Indian hedgehog (IHH) signaling from stellate cells as an early contributor to augmented regeneration. Here, we sought to identify upstream regulators of IHH. ALPPS in mice was compared against PVL and additional control surgeries. Potential IHH regulators were identified through in silico mining of transcriptomic data. JNK1 activity was reduced through SP600125 to evaluate its effects on IHH signaling. Recombinant IHH was injected after JNK diminution to substantiate their relationship during accelerated liver regeneration. Mining linked Ihh to Mapk8. JNK1 upregulation after ALPPS was validated and preceded the IHH peak. On immunofluorescence, JNK1 and IHH co-localized in ASMA-positive non-parenchymal cells. Inhibition of JNK1 prior to ALPPS surgery reduced liver weight gain to PVL levels and was accompanied by downregulation of hepatocellular proliferation and the IHH-GLI1-CCND1 axis. In JNK1-inhibited mice, recombinant IHH restored ALPPS-like acceleration of regeneration and re-elevated JNK1 activity, suggesting the presence of a positive IHH-JNK1 feedback loop. JNK1-mediated induction of IHH paracrine signaling from HSCs is essential for accelerated regeneration of parenchymal mass. The JNK1-IHH axis is a mechanism unique to ALPPS surgery and may point to therapeutic alternatives for patients with insufficient regenerative capacity. ALPPS, a novel two-staged hepatectomy, induces an unprecedented acceleration of liver regeneration to enable treatment of unresectable liver tumors. Here, we demonstrate JNK1-IHH signaling as a mechanism underlying the regenerative acceleration induced by ALPPS. Copyright © 2018 European

  6. JNK1ß1 is phosphorylated during expression in E. coli and in vitro by MKK4 at three identical novel sites

    CSIR Research Space (South Africa)

    Owen, GR

    2013-03-01

    Full Text Available JNK1 is activated by phosphorylation of the canonical T183 and Y185 residues, modifications that are catalysed typically by the upstream eukaryotic kinases MKK4 and MKK7. Nonetheless, the exact sites at which the most abundant JNK variant, JNK1ß1...

  7. JNK1 ablation in mice confers long-term metabolic protection from diet-induced obesity at the cost of moderate skin oxidative damage.

    Science.gov (United States)

    Becattini, Barbara; Zani, Fabio; Breasson, Ludovic; Sardi, Claudia; D'Agostino, Vito Giuseppe; Choo, Min-Kyung; Provenzani, Alessandro; Park, Jin Mo; Solinas, Giovanni

    2016-09-01

    Obesity and insulin resistance are associated with oxidative stress, which may be implicated in the progression of obesity-related diseases. The kinase JNK1 has emerged as a promising drug target for the treatment of obesity and type 2 diabetes. JNK1 is also a key mediator of the oxidative stress response, which can promote cell death or survival, depending on the magnitude and context of its activation. In this article, we describe a study in which the long-term effects of JNK1 inactivation on glucose homeostasis and oxidative stress in obese mice were investigated for the first time. Mice lacking JNK1 (JNK1(-/-)) were fed an obesogenic high-fat diet (HFD) for a long period. JNK1(-/-) mice fed an HFD for the long term had reduced expression of antioxidant genes in their skin, more skin oxidative damage, and increased epidermal thickness and inflammation compared with the effects in control wild-type mice. However, we also observed that the protection from obesity, adipose tissue inflammation, steatosis, and insulin resistance, conferred by JNK1 ablation, was sustained over a long period and was paralleled by decreased oxidative damage in fat and liver. We conclude that compounds targeting JNK1 activity in brain and adipose tissue, which do not accumulate in the skin, may be safer and most effective.-Becattini, B., Zani, F., Breasson, L., Sardi, C., D'Agostino, V. G., Choo, M.-K., Provenzani, A., Park, J. M., Solinas, G. JNK1 ablation in mice confers long-term metabolic protection from diet-induced obesity at the cost of moderate skin oxidative damage. © FASEB.

  8. JNK1 protects against glucolipotoxicity-mediated beta-cell apoptosis

    DEFF Research Database (Denmark)

    Prause, Michala; Christensen, Dan Ploug; Billestrup, Nils

    2014-01-01

    Pancreatic β-cell dysfunction is central to type 2 diabetes pathogenesis. Prolonged elevated levels of circulating free-fatty acids and hyperglycemia, also termed glucolipotoxicity, mediate β-cell dysfunction and apoptosis associated with increased c-Jun N-terminal Kinase (JNK) activity. Endoplas......Pancreatic β-cell dysfunction is central to type 2 diabetes pathogenesis. Prolonged elevated levels of circulating free-fatty acids and hyperglycemia, also termed glucolipotoxicity, mediate β-cell dysfunction and apoptosis associated with increased c-Jun N-terminal Kinase (JNK) activity....... Endoplasmic reticulum (ER) and oxidative stress are elicited by palmitate and high glucose concentrations further potentiating JNK activity. Our aim was to determine the role of the JNK subtypes JNK1, JNK2 and JNK3 in palmitate and high glucose-induced β-cell apoptosis. We established insulin-producing INS1...... INS1 cells showed increased apoptosis and cleaved caspase 9 and 3 compared to non-sense shRNA expressing control INS1 cells when exposed to palmitate and high glucose associated with increased CHOP expression, ROS formation and Puma mRNA expression. JNK2 shRNA expressing INS1 cells did not affect...

  9. Forgetting in C. elegans Is Accelerated by Neuronal Communication via the TIR-1/JNK-1 Pathway

    Directory of Open Access Journals (Sweden)

    Akitoshi Inoue

    2013-03-01

    Full Text Available The control of memory retention is important for proper responses to constantly changing environments, but the regulatory mechanisms underlying forgetting have not been fully elucidated. Our genetic analyses in C. elegans revealed that mutants of the TIR-1/JNK-1 pathway exhibited prolonged retention of olfactory adaptation and salt chemotaxis learning. In olfactory adaptation, conditioning induces attenuation of odor-evoked Ca2+ responses in olfactory neurons, and this attenuation is prolonged in the TIR-1/JNK-1-pathway mutant animals. We also found that a pair of neurons in which the pathway functions is required for the acceleration of forgetting, but not for sensation or adaptation, in wild-type animals. In addition, the neurosecretion from these cells is important for the acceleration of forgetting. Therefore, we propose that these neurons accelerate forgetting through the TIR-1/JNK-1 pathway by sending signals that directly or indirectly stimulate forgetting.

  10. The mechanism by which MEK/ERK regulates JNK and p38 activity in polyamine depleted IEC-6 cells during apoptosis

    Science.gov (United States)

    Bavaria, Mitul N.; Jin, Shi; Ray, Ramesh M.; Johnson, Leonard R.

    2014-01-01

    Polyamine-depletion inhibited apoptosis by activating ERK1/2, while, preventing JNK1/2 activation. MKP-1 knockdown by SiRNA increased ERK1/2, JNK1/2, and p38 phosphorylation and apoptosis. Therefore, we predicted that polyamines might regulate MKP1 via MEK/ERK and thereby apoptosis. We examined the role of MEK/ERK in the regulation of MKP1 and JNK, and p38 activities and apoptosis. Inhibition of MKP-1 activity with a pharmacological inhibitor, sanguinarine (SA), increased JNK1/2, p38, and ERK1/2 activities without causing apoptosis. However, pre-activation of these kinases by SA significantly increased camptothecin (CPT)-induced apoptosis suggesting different roles for MAPKs during survival and apoptosis. Inhibition of MEK1 activity prevented the expression of MKP-1 protein and augmented CPT-induced apoptosis, which correlated with increased activities of JNK1/2, caspases, and DNA fragmentation. Polyamine depleted cells had higher levels of MKP-1 protein and decreased JNK1/2 activity and apoptosis. Inhibition of MEK1 prevented MKP-1 expression and increased JNK1/2 and apoptosis. Phospho-JNK1/2, phospho-ERK2, MKP-1, and the catalytic subunit of protein phosphatase 2A (PP2Ac) formed a complex in response to TNF/CPT. Inactivation of PP2Ac had no effect on the association of MKP-1 and JNK1. However, inhibition of MKP-1 activity decreased the formation of the MKP-1, PP2Ac and JNK complex. Following inhibition by SA, MKP-1 localized in the cytoplasm, while basal and CPT-induced MKP-1 remained in the nuclear fraction. These results suggest that nuclear MKP-1 translocates to the cytoplasm, binds phosphorylated JNK and p38 resulting in dephosphorylation and decreased activity. Thus, MEK/ERK activity controls the levels of MKP-1 and, thereby, regulates JNK activity in polyamine-depleted cells. PMID:24253595

  11. JNK1 Controls Dendritic Field Size in L2/3 and L5 of the Motor Cortex, Constrains Soma Size and Influences Fine Motor Coordination

    Directory of Open Access Journals (Sweden)

    Emilia eKomulainen

    2014-09-01

    Full Text Available Genetic anomalies on the JNK pathway confer susceptibility to autism spectrum disorders, schizophrenia and intellectual disability. The mechanism whereby a gain or loss of function in JNK signaling predisposes to these prevalent dendrite disorders, with associated motor dysfunction, remains unclear. Here we find that JNK1 regulates the dendritic field of L2/3 and L5 pyramidal neurons of the mouse motor cortex (M1, the main excitatory pathway controlling voluntary movement. In Jnk1-/- mice, basal dendrite branching of L5 pyramidal neurons is increased in M1, as is cell soma size, whereas in L2/3, dendritic arborization is decreased. We show that JNK1 phosphorylates rat HMW-MAP2 on T1619, T1622 and T1625 (Uniprot P15146 corresponding to mouse T1617, T1620, T1623, to create a binding motif, that is critical for MAP2 interaction with and stabilization of microtubules, and dendrite growth control. Targeted expression in M1 of GFP-HMW-MAP2 that is pseudo-phosphorylated on T1619, T1622 and T1625 increases dendrite complexity in L2/3 indicating that JNK1 phosphorylation of HMW-MAP2 regulates the dendritic field. Consistent with the morphological changes observed in L2/3 and L5, Jnk1-/- mice exhibit deficits in limb placement and motor coordination, while stride length is reduced in older animals. In summary, JNK1 phosphorylates HMW-MAP2 to increase its stabilization of microtubules while at the same time controlling dendritic fields in the main excitatory pathway of M1. Moreover, JNK1 contributes to normal functioning of fine motor coordination. We report for the first time, a quantitative sholl analysis of dendrite architecture, and of motor behavior in Jnk1-/- mice. Our results illustrate the molecular and behavioral consequences of interrupted JNK1 signaling and provide new ground for mechanistic understanding of those prevalent neuropyschiatric disorders where genetic disruption of the JNK pathway is central.

  12. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Data.gov (United States)

    U.S. Environmental Protection Agency — Data from a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating using predictive computational...

  13. Hypothalamic AMPK-ER Stress-JNK1 Axis Mediates the Central Actions of Thyroid Hormones on Energy Balance.

    Science.gov (United States)

    Martínez-Sánchez, Noelia; Seoane-Collazo, Patricia; Contreras, Cristina; Varela, Luis; Villarroya, Joan; Rial-Pensado, Eva; Buqué, Xabier; Aurrekoetxea, Igor; Delgado, Teresa C; Vázquez-Martínez, Rafael; González-García, Ismael; Roa, Juan; Whittle, Andrew J; Gomez-Santos, Beatriz; Velagapudi, Vidya; Tung, Y C Loraine; Morgan, Donald A; Voshol, Peter J; Martínez de Morentin, Pablo B; López-González, Tania; Liñares-Pose, Laura; Gonzalez, Francisco; Chatterjee, Krishna; Sobrino, Tomás; Medina-Gómez, Gema; Davis, Roger J; Casals, Núria; Orešič, Matej; Coll, Anthony P; Vidal-Puig, Antonio; Mittag, Jens; Tena-Sempere, Manuel; Malagón, María M; Diéguez, Carlos; Martínez-Chantar, María Luz; Aspichueta, Patricia; Rahmouni, Kamal; Nogueiras, Rubén; Sabio, Guadalupe; Villarroya, Francesc; López, Miguel

    2017-07-05

    Thyroid hormones (THs) act in the brain to modulate energy balance. We show that central triiodothyronine (T3) regulates de novo lipogenesis in liver and lipid oxidation in brown adipose tissue (BAT) through the parasympathetic (PSNS) and sympathetic nervous system (SNS), respectively. Central T3 promotes hepatic lipogenesis with parallel stimulation of the thermogenic program in BAT. The action of T3 depends on AMP-activated protein kinase (AMPK)-induced regulation of two signaling pathways in the ventromedial nucleus of the hypothalamus (VMH): decreased ceramide-induced endoplasmic reticulum (ER) stress, which promotes BAT thermogenesis, and increased c-Jun N-terminal kinase (JNK) activation, which controls hepatic lipid metabolism. Of note, ablation of AMPKα1 in steroidogenic factor 1 (SF1) neurons of the VMH fully recapitulated the effect of central T3, pointing to this population in mediating the effect of central THs on metabolism. Overall, these findings uncover the underlying pathways through which central T3 modulates peripheral metabolism. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  14. Human activity recognition and prediction

    CERN Document Server

    2016-01-01

    This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques. .

  15. CERAPP: Collaborative estrogen receptor activity prediction project

    DEFF Research Database (Denmark)

    Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra

    2016-01-01

    ). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. oBjectives: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project...... States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical......: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing. conclusion: This project demonstrated...

  16. Predicting environmental restoration activities through static simulation

    International Nuclear Information System (INIS)

    Ross, T.L.; King, D.A.; Wilkins, M.L.; Forward, M.F.

    1994-12-01

    This paper discusses a static simulation model that predicts several performance measures of environmental restoration activities over different remedial strategies. Basic model operation consists of manipulating and processing waste streams via selecting and applying remedial technologies according to the strategy. Performance measure prediction is possible for contaminated soil, solid waste, surface water, groundwater, storage tank, and facility sites. Simulations are performed for the U.S. Department of Energy in support of its Programmatic Environmental Impact Statement

  17. Prediction of Human Activity by Discovering Temporal Sequence Patterns.

    Science.gov (United States)

    Li, Kang; Fu, Yun

    2014-08-01

    Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

  18. Central melanin-concentrating hormone influences liver and adipose metabolism via specific hypothalamic nuclei and efferent autonomic/JNK1 pathways.

    Science.gov (United States)

    Imbernon, Monica; Beiroa, Daniel; Vázquez, María J; Morgan, Donald A; Veyrat-Durebex, Christelle; Porteiro, Begoña; Díaz-Arteaga, Adenis; Senra, Ana; Busquets, Silvia; Velásquez, Douglas A; Al-Massadi, Omar; Varela, Luis; Gándara, Marina; López-Soriano, Francisco-Javier; Gallego, Rosalía; Seoane, Luisa M; Argiles, Josep M; López, Miguel; Davis, Roger J; Sabio, Guadalupe; Rohner-Jeanrenaud, Françoise; Rahmouni, Kamal; Dieguez, Carlos; Nogueiras, Ruben

    2013-03-01

    Specific neuronal circuits modulate autonomic outflow to liver and white adipose tissue. Melanin-concentrating hormone (MCH)-deficient mice are hypophagic, lean, and do not develop hepatosteatosis when fed a high-fat diet. Herein, we sought to investigate the role of MCH, an orexigenic neuropeptide specifically expressed in the lateral hypothalamic area, on hepatic and adipocyte metabolism. Chronic central administration of MCH and adenoviral vectors increasing MCH signaling were performed in rats and mice. Vagal denervation was performed to assess its effect on liver metabolism. The peripheral effects on lipid metabolism were assessed by real-time polymerase chain reaction and Western blot. We showed that the activation of MCH receptors promotes nonalcoholic fatty liver disease through the parasympathetic nervous system, whereas it increases fat deposition in white adipose tissue via the suppression of sympathetic traffic. These metabolic actions are independent of parallel changes in food intake and energy expenditure. In the liver, MCH triggers lipid accumulation and lipid uptake, with c-Jun N-terminal kinase being an essential player, whereas in adipocytes MCH induces metabolic pathways that promote lipid storage and decreases lipid mobilization. Genetic activation of MCH receptors or infusion of MCH specifically in the lateral hypothalamic area modulated hepatic lipid metabolism, whereas the specific activation of this receptor in the arcuate nucleus affected adipocyte metabolism. Our findings show that central MCH directly controls hepatic and adipocyte metabolism through different pathways. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.

  19. Activities: Plotting and Predicting from Pairs.

    Science.gov (United States)

    Shulte, Albert P.; Swift, Jim

    1984-01-01

    This teacher's guide provides objectives, procedures, and list of materials needed for activities which center around the use of a scatter plot to examine relationships shown by bivariate data. The activities are suitable for grades 7 to 12. Four student worksheets are included. (JN)

  20. Activity, exposure rate and spectrum prediction with Java programming

    International Nuclear Information System (INIS)

    Sahin, D.; Uenlue, K.

    2009-01-01

    In order to envision the radiation exposure during Neutron Activation Analysis (NAA) experiments, a software called Activity Predictor is developed using Java TM programming language. The Activity Predictor calculates activities, exposure rates and gamma spectra of activated samples for NAA experiments performed at Radiation Science and Engineering Center (RSEC), Penn State Breazeale Reactor (PSBR). The calculation procedure for predictions involves both analytical and Monte Carlo methods. The Activity Predictor software is validated with a series of activation experiments. It has been found that Activity Predictor software calculates the activities and exposure rates precisely. The software also predicts gamma spectrum for each measurement. The predicted spectra agreed partially with measured spectra. The error in net photo peak areas varied from 4.8 to 51.29%, which is considered to be due to simplistic modeling, statistical fluctuations and unknown contaminants in the samples. (author)

  1. Predicting mining activity with parallel genetic algorithms

    Science.gov (United States)

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.; Beyer, H.G.; O'Reilly, U.M.; Banzhaf, Arnold D.; Blum, W.; Bonabeau, C.; Cantu-Paz, E.W.; ,; ,

    2005-01-01

    We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

  2. Prediction of iodine activity peak during refuelling

    International Nuclear Information System (INIS)

    Hozer, Z.; Vajda, N.

    2001-01-01

    The increase of fission product activities in the primary circuit of a nuclear power plant indicates the existence of defects in some fuel rods. The power change leads to the cooling down of the fuel and results in the fragmentation of the UO 2 pellets, which facilitates the release of fission products from the intergranular regions. Furthermore the injection of boric acid after shutdown will increase the primary activity, due to the solution of deposited fission products from the surface of the core components. The calculation of these phenomena usually is based on the evaluation of activity measurements and power plant data. The estimation of iodine spiking peak during reactor transients is based on correlation with operating parameters, such as reactor power and primary pressure. The approach used in the present method was applied for CANDU reactors. The VVER-440 specific correlations were determined using the activity measurements of the Paks NPP and the data provided by the Russian fuel supplier. The present method is used for the evaluation of the iodine isotopes, as well as the noble gases. A numerical model has been developed for iodine spiking simulation and has been validated against several shutdown transients, measured at Paks NPP. (R.P.)

  3. Predicting the degradability of waste activated sludge.

    Science.gov (United States)

    Jones, Richard; Parker, Wayne; Zhu, Henry; Houweling, Dwight; Murthy, Sudhir

    2009-08-01

    The objective of this study was to identify methods for estimating anaerobic digestibility of waste activated sludge (WAS). The WAS streams were generated in three sequencing batch reactors (SBRs) treating municipal wastewater. The wastewater and WAS properties were initially determined through simulation of SBR operation with BioWin (EnviroSim Associates Ltd., Flamborough, Ontario, Canada). Samples of WAS from the SBRs were subsequently characterized through respirometry and batch anaerobic digestion. Respirometry was an effective tool for characterizing the active fraction of WAS and could be a suitable technique for determining sludge composition for input to anaerobic models. Anaerobic digestion of the WAS revealed decreasing methane production and lower chemical oxygen demand removals as the SRT of the sludge increased. BioWin was capable of accurately describing the digestion of the WAS samples for typical digester SRTs. For extended digestion times (i.e., greater than 30 days), some degradation of the endogenous decay products was assumed to achieve accurate simulations for all sludge SRTs.

  4. Nonlinear Predictive Sliding Mode Control for Active Suspension System

    Directory of Open Access Journals (Sweden)

    Dazhuang Wang

    2018-01-01

    Full Text Available An active suspension system is important in meeting the requirements of the ride comfort and handling stability for vehicles. In this work, a nonlinear model of active suspension system and a corresponding nonlinear robust predictive sliding mode control are established for the control problem of active suspension. Firstly, a seven-degree-of-freedom active suspension model is established considering the nonlinear effects of springs and dampers; and secondly, the dynamic model is expanded in the time domain, and the corresponding predictive sliding mode control is established. The uncertainties in the controller are approximated by the fuzzy logic system, and the adaptive controller reduces the approximation error to increase the robustness of the control system. Finally, the simulation results show that the ride comfort and handling stability performance of the active suspension system is better than that of the passive suspension system and the Skyhook active suspension. Thus, the system can obviously improve the shock absorption performance of vehicles.

  5. Features and prospects of juridical predicting of entrepreneurial activity

    Directory of Open Access Journals (Sweden)

    Natalya V. Rubtsova

    2017-03-01

    Full Text Available Objective to identify characteristics and prospects of predicting the business activity. Methods historical sociological logical systematicstructural formallegal comparativelegal legal modeling method. Results in article suggests the legal definition of prediction of business activity as a scientific and practical study aimed at the determination of the future state and prospects of development of business activity consisting of the evaluation of legal regulation and analysis of the prospectsof further socioeconomic development which aims to select the optimal solution for the further development of entrepreneurship through legal regulators. The work proves the necessity of achieving a balanced legal regulation of social relations by changing the legislation in the field of business agreements investment and innovation. Scientific novelty the article for the first time formulates the concept characteristics and features of legal prediction of business activity substantiates the impact of predicting on the development of legal regulation of social relations. Practical significance the main provisions and conclusions of the article can be used in research and teaching while considering the issues of predicting both the socioeconomic processes in general and business activity in particular.

  6. Human medial frontal cortex activity predicts learning from errors.

    Science.gov (United States)

    Hester, Robert; Barre, Natalie; Murphy, Kevin; Silk, Tim J; Mattingley, Jason B

    2008-08-01

    Learning from errors is a critical feature of human cognition. It underlies our ability to adapt to changing environmental demands and to tune behavior for optimal performance. The posterior medial frontal cortex (pMFC) has been implicated in the evaluation of errors to control behavior, although it has not previously been shown that activity in this region predicts learning from errors. Using functional magnetic resonance imaging, we examined activity in the pMFC during an associative learning task in which participants had to recall the spatial locations of 2-digit targets and were provided with immediate feedback regarding accuracy. Activity within the pMFC was significantly greater for errors that were subsequently corrected than for errors that were repeated. Moreover, pMFC activity during recall errors predicted future responses (correct vs. incorrect), despite a sizeable interval (on average 70 s) between an error and the next presentation of the same recall probe. Activity within the hippocampus also predicted future performance and correlated with error-feedback-related pMFC activity. A relationship between performance expectations and pMFC activity, in the absence of differing reinforcement value for errors, is consistent with the idea that error-related pMFC activity reflects the extent to which an outcome is "worse than expected."

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Shangkun Deng

    2014-01-01

    Full Text Available 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.

  9. Predicting Solar Activity Using Machine-Learning Methods

    Science.gov (United States)

    Bobra, M.

    2017-12-01

    Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections. However, we do not, as of yet, fully understand the physical mechanism that triggers solar eruptions. A machine-learning algorithm, which is favorable in cases where the amount of data is large, is one way to [1] empirically determine the signatures of this mechanism in solar image data and [2] use them to predict solar activity. In this talk, we discuss the application of various machine learning algorithms - specifically, a Support Vector Machine, a sparse linear regression (Lasso), and Convolutional Neural Network - to image data from the photosphere, chromosphere, transition region, and corona taken by instruments aboard the Solar Dynamics Observatory in order to predict solar activity on a variety of time scales. Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We discuss our results (Bobra and Couvidat, 2015; Bobra and Ilonidis, 2016; Jonas et al., 2017) as well as other attempts to predict flares using machine-learning (e.g. Ahmed et al., 2013; Nishizuka et al. 2017) and compare these results with the more traditional techniques used by the NOAA Space Weather Prediction Center (Crown, 2012). We also discuss some of the challenges in using machine-learning algorithms for space science applications.

  10. Striatal Activation Predicts Differential Therapeutic Responses to Methylphenidate and Atomoxetine.

    Science.gov (United States)

    Schulz, Kurt P; Bédard, Anne-Claude V; Fan, Jin; Hildebrandt, Thomas B; Stein, Mark A; Ivanov, Iliyan; Halperin, Jeffrey M; Newcorn, Jeffrey H

    2017-07-01

    Methylphenidate has prominent effects in the dopamine-rich striatum that are absent for the selective norepinephrine transporter inhibitor atomoxetine. This study tested whether baseline striatal activation would predict differential response to the two medications in youth with attention-deficit/hyperactivity disorder (ADHD). A total of 36 youth with ADHD performed a Go/No-Go test during functional magnetic resonance imaging at baseline and were treated with methylphenidate and atomoxetine using a randomized cross-over design. Whole-brain task-related activation was regressed on clinical response. Task-related activation in right caudate nucleus was predicted by an interaction of clinical responses to methylphenidate and atomoxetine (F 1,30  = 17.00; p atomoxetine. The rate of robust response was higher for methylphenidate than for atomoxetine in youth with high (94.4% vs. 38.8%; p = .003; number needed to treat = 2, 95% CI = 1.31-3.73) but not low (33.3% vs. 50.0%; p = .375) caudate activation. Furthermore, response to atomoxetine predicted motor cortex activation (F 1,30  = 14.99; p atomoxetine in youth with ADHD, purportedly reflecting the dopaminergic effects of methylphenidate but not atomoxetine in the striatum, whereas motor cortex activation may predict response to atomoxetine. These data do not yet translate directly to the clinical setting, but the approach is potentially important for informing future research and illustrates that it may be possible to predict differential treatment response using a biomarker-driven approach. Stimulant Versus Nonstimulant Medication for Attention Deficit Hyperactivity Disorder in Children; https://clinicaltrials.gov/; NCT00183391. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

  11. Predicting activities after stroke : what is clinically relevant?

    NARCIS (Netherlands)

    Kwakkel, G.; Kollen, B. J.

    Knowledge about factors that determine the final outcome after stroke is important for early stroke management, rehabilitation goals, and discharge planning. This narrative review provides an overview of current knowledge about the prediction of activities after stroke. We reviewed the pattern of

  12. Merlin : microsimulation system for predicting leisure activity-travel patterns

    NARCIS (Netherlands)

    Middelkoop, van M.; Borgers, A.W.J.; Timmermans, H.J.P.

    2004-01-01

    Development of a model of annual activity-travel patterns of leisure and vacation travel is reported. The simulation system, called Merlin, is a hybrid model system consisting of discrete choice models and rule-based models. It predicts the annual number of day trips and vacations, and the profile

  13. Application of Avco data analysis and prediction techniques (ADAPT) to prediction of sunspot activity

    Science.gov (United States)

    Hunter, H. E.; Amato, R. A.

    1972-01-01

    The results are presented of the application of Avco Data Analysis and Prediction Techniques (ADAPT) to derivation of new algorithms for the prediction of future sunspot activity. The ADAPT derived algorithms show a factor of 2 to 3 reduction in the expected 2-sigma errors in the estimates of the 81-day running average of the Zurich sunspot numbers. The report presents: (1) the best estimates for sunspot cycles 20 and 21, (2) a comparison of the ADAPT performance with conventional techniques, and (3) specific approaches to further reduction in the errors of estimated sunspot activity and to recovery of earlier sunspot historical data. The ADAPT programs are used both to derive regression algorithm for prediction of the entire 11-year sunspot cycle from the preceding two cycles and to derive extrapolation algorithms for extrapolating a given sunspot cycle based on any available portion of the cycle.

  14. Prediction of adolescents doing physical activity after completing secondary education.

    Science.gov (United States)

    Moreno-Murcia, Juan Antonio; Huéscar, Elisa; Cervelló, Eduardo

    2012-03-01

    The purpose of this study, based on the self-determination theory (Ryan & Deci, 2000) was to test the prediction power of student's responsibility, psychological mediators, intrinsic motivation and the importance attached to physical education in the intention to continue to practice some form of physical activity and/or sport, and the possible relationships that exist between these variables. We used a sample of 482 adolescent students in physical education classes, with a mean age of 14.3 years, which were measured for responsibility, psychological mediators, sports motivation, the importance of physical education and intention to be physically active. We completed an analysis of structural equations modelling. The results showed that the responsibility positively predicted psychological mediators, and this predicted intrinsic motivation, which positively predicted the importance students attach to physical education, and this, finally, positively predicted the intention of the student to continue doing sport. Results are discussed in relation to the promotion of student's responsibility towards a greater commitment to the practice of physical exercise.

  15. Resting alpha activity predicts learning ability in alpha neurofeedback

    Directory of Open Access Journals (Sweden)

    Wenya eNan

    2014-07-01

    Full Text Available Individuals differ in their ability to learn how to regulate the alpha activity by neurofeedback. This study aimed to investigate whether the resting alpha activity is related to the learning ability of alpha enhancement in neurofeedback and could be used as a predictor. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback in order to learn how to enhance activity in the alpha frequency band. The learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback.

  16. Prediction of flare activity of stellar aggregates. I. Theoretical part

    International Nuclear Information System (INIS)

    Mnatsakanyan, M.A.; Mirzoyan, A.L.

    1989-01-01

    The problem is posed of predicting the number n k (t) of flare stars that have exhibited precisely k flares by the time t on the basis of data on these quantities known during the total time T of observations of the aggregate. The problem posed by Ambartsumyan of determining the distribution function f(ν) of the true frequency of stellar flares from known chronology of these data is equivalent to the limiting form of their formulation - prediction in the future over an infinitely long time. An exact analytic solution of the problem obtained without any assumption about the function f(ν) is given. It permits prediction of the steady flare activity of the aggregate into both the future and the (known) past. It follows from this solution that prediction into the future is in principle impossible to times that exceed the doubled time 2T of the available observations (this means that the problem of determining of the function f(ν) cannot be solved). Moreover, because of the unavoidable fluctuations in the observational data n k (T), such prediction is limited to even shorter times, and these are shorter the larger the value of k. Prediction into the past and into the future on the basis of the data n k (T) at the present time and its possible errors due to small fluctuations in these data are illustrated for the examples of the Pleiades and the Orion aggregate

  17. Predicting forest insect flight activity: A Bayesian network approach.

    Directory of Open Access Journals (Sweden)

    Stephen M Pawson

    Full Text Available Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model's predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways.

  18. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and fault...... can be used as a test signal for sanity check at the commissioning or for detection of faults hidden by regulatory actions of the controller. The method is tested on the two tank benchmark example. ©2009 IEEE....

  19. Uncertainty in Predicting CCN Activity of Aged and Primary Aerosols

    Science.gov (United States)

    Zhang, Fang; Wang, Yuying; Peng, Jianfei; Ren, Jingye; Collins, Don; Zhang, Renyi; Sun, Yele; Yang, Xin; Li, Zhanqing

    2017-11-01

    Understanding particle CCN activity in diverse atmospheres is crucial when evaluating aerosol indirect effects. Here aerosols measured at three sites in China were categorized as different types for attributing uncertainties in CCN prediction in terms of a comprehensive data set including size-resolved CCN activity, size-resolved hygroscopic growth factor, and chemical composition. We show that CCN activity for aged aerosols is unexpectedly underestimated 22% at a supersaturation (S) of 0.2% when using κ-Kohler theory with an assumption of an internal mixture with measured bulk composition that has typically resulted in an overestimate of the CCN activity in previous studies. We conclude that the underestimation stems from neglect of the effect of aging/coating on particle hygroscopicity, which is not considered properly in most current models. This effect enhanced the hygroscopicity parameter (κ) by between 11% (polluted conditions) and 30% (clean days), as indicated in diurnal cycles of κ based on measurements by different instruments. In the urban Beijing atmosphere heavily influenced by fresh emissions, the CCN activity was overestimated by 45% at S = 0.2%, likely because of inaccurate assumptions of particle mixing state and because of variability of chemical composition over the particle size range. For both fresh and aged aerosols, CCN prediction exhibits very limited sensitivity to κSOA, implying a critical role of other factors like mixing of aerosol components within and between particles in regulating CCN activity. Our findings could help improving CCN parameterization in climate models.

  20. Finite element predictions of active buckling control of stiffened panels

    Science.gov (United States)

    Thompson, Danniella M.; Griffin, O. H., Jr.

    1993-04-01

    Materials systems and structures that can respond 'intelligently' to their environment are currently being proposed and investigated. A series of finite element analyses was performed to investigate the potential for active buckling control of two different stiffened panels by embedded shape memory alloy (SMA) rods. Changes in the predicted buckling load increased with the magnitude of the actuation level for a given structural concept. Increasing the number of actuators for a given concept yielded greater predicted increases in buckling load. Considerable control authority was generated with a small number of actuators, with greater authority demonstrated for those structural concepts where the activated SMA rods could develop greater forces and moments on the structure. Relatively simple and inexpensive analyses were performed with standard finite elements to determine such information, indicating the viability of these types of models for design purposes.

  1. Preparatory neural activity predicts performance on a conflict task.

    Science.gov (United States)

    Stern, Emily R; Wager, Tor D; Egner, Tobias; Hirsch, Joy; Mangels, Jennifer A

    2007-10-24

    Advance preparation has been shown to improve the efficiency of conflict resolution. Yet, with little empirical work directly linking preparatory neural activity to the performance benefits of advance cueing, it is not clear whether this relationship results from preparatory activation of task-specific networks, or from activity associated with general alerting processes. Here, fMRI data were acquired during a spatial Stroop task in which advance cues either informed subjects of the upcoming relevant feature of conflict stimuli (spatial or semantic) or were neutral. Informative cues decreased reaction time (RT) relative to neutral cues, and cues indicating that spatial information would be task-relevant elicited greater activity than neutral cues in multiple areas, including right anterior prefrontal and bilateral parietal cortex. Additionally, preparatory activation in bilateral parietal cortex and right dorsolateral prefrontal cortex predicted faster RT when subjects responded to spatial location. No regions were found to be specific to semantic cues at conventional thresholds, and lowering the threshold further revealed little overlap between activity associated with spatial and semantic cueing effects, thereby demonstrating a single dissociation between activations related to preparing a spatial versus semantic task-set. This relationship between preparatory activation of spatial processing networks and efficient conflict resolution suggests that advance information can benefit performance by leading to domain-specific biasing of task-relevant information.

  2. Planning for subacute care: predicting demand using acute activity data.

    Science.gov (United States)

    Green, Janette P; McNamee, Jennifer P; Kobel, Conrad; Seraji, Md Habibur R; Lawrence, Suanne J

    2016-01-01

    Objective The aim of the present study was to develop a robust model that uses the concept of 'rehabilitation-sensitive' Diagnosis Related Groups (DRGs) in predicting demand for rehabilitation and geriatric evaluation and management (GEM) care following acute in-patient episodes provided in Australian hospitals. Methods The model was developed using statistical analyses of national datasets, informed by a panel of expert clinicians and jurisdictional advice. Logistic regression analysis was undertaken using acute in-patient data, published national hospital statistics and data from the Australasian Rehabilitation Outcomes Centre. Results The predictive model comprises tables of probabilities that patients will require rehabilitation or GEM care after an acute episode, with columns defined by age group and rows defined by grouped Australian Refined (AR)-DRGs. Conclusions The existing concept of rehabilitation-sensitive DRGs was revised and extended. When applied to national data, the model provided a conservative estimate of 83% of the activity actually provided. An example demonstrates the application of the model for service planning. What is known about the topic? Health service planning is core business for jurisdictions and local areas. With populations ageing and an acknowledgement of the underservicing of subacute care, it is timely to find improved methods of estimating demand for this type of care. Traditionally, age-sex standardised utilisation rates for individual DRGs have been applied to Australian Bureau of Statistics (ABS) population projections to predict the future need for subacute services. Improved predictions became possible when some AR-DRGs were designated 'rehabilitation-sensitive'. This improved methodology has been used in several Australian jurisdictions. What does this paper add? This paper presents a new tool, or model, to predict demand for rehabilitation and GEM services based on in-patient acute activity. In this model, the

  3. Spontaneous brain activity predicts learning ability of foreign sounds.

    Science.gov (United States)

    Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

    2013-05-29

    Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

  4. Neural activity predicts attitude change in cognitive dissonance.

    Science.gov (United States)

    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. Do Urinary Cystine Parameters Predict Clinical Stone Activity?

    Science.gov (United States)

    Friedlander, Justin I; Antonelli, Jodi A; Canvasser, Noah E; Morgan, Monica S C; Mollengarden, Daniel; Best, Sara; Pearle, Margaret S

    2018-02-01

    An accurate urinary predictor of stone recurrence would be clinically advantageous for patients with cystinuria. A proprietary assay (Litholink, Chicago, Illinois) measures cystine capacity as a potentially more reliable estimate of stone forming propensity. The recommended capacity level to prevent stone formation, which is greater than 150 mg/l, has not been directly correlated with clinical stone activity. We investigated the relationship between urinary cystine parameters and clinical stone activity. We prospectively followed 48 patients with cystinuria using 24-hour urine collections and serial imaging, and recorded stone activity. We compared cystine urinary parameters at times of stone activity with those obtained during periods of stone quiescence. We then performed correlation and ROC analysis to evaluate the performance of cystine parameters to predict stone activity. During a median followup of 70.6 months (range 2.2 to 274.6) 85 stone events occurred which could be linked to a recent urine collection. Cystine capacity was significantly greater for quiescent urine than for stone event urine (mean ± SD 48 ± 107 vs -38 ± 163 mg/l, p stone activity (r = -0.29, p r = -0.88, p r = -0.87, p stone quiescence. Decreasing the cutoff to 90 mg/l or greater improved sensitivity to 25.2% while maintaining specificity at 90.9%. Our results suggest that the target for capacity should be lower than previously advised. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  6. Predicting flow at work: investigating the activities and job characteristics that predict flow states at work.

    Science.gov (United States)

    Nielsen, Karina; Cleal, Bryan

    2010-04-01

    Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work. Copyright 2010 APA, all rights reserved.

  7. Interferon-β-induced activation of c-Jun NH2-terminal kinase mediates apoptosis through up-regulation of CD95 in CH31 B lymphoma cells

    International Nuclear Information System (INIS)

    Takada, Eiko; Shimo, Kuniaki; Hata, Kikumi; Abiake, Maira; Mukai, Yasuo; Moriyama, Masami; Heasley, Lynn; Mizuguchi, Junichiro

    2005-01-01

    Type I interferon (IFN)-induced antitumor action is due in part to apoptosis, but the molecular mechanisms underlying IFN-induced apoptosis remain largely unresolved. In the present study, we demonstrate that IFN-β induced apoptosis and the loss of mitochondrial membrane potential (ΔΨm) in the murine CH31 B lymphoma cell line, and this was accompanied by the up-regulation of CD95, but not CD95-ligand (CD95-L), tumor necrosis factor (TNF), or TNF-related apoptosis-inducing ligand (TRAIL). Pretreatment with anti-CD95-L mAb partially prevented the IFN-β-induced loss of ΔΨm, suggesting that the interaction of IFN-β-up-regulated CD95 with CD95-L plays a crucial role in the induction of fratricide. IFN-β induced a sustained activation of c-Jun NH 2 -terminal kinase 1 (JNK1), but not extracellular signal-regulated kinases (ERKs). The IFN-β-induced apoptosis and loss of ΔΨm were substantially compromised in cells overexpressing a dominant-negative form of JNK1 (dnJNK1), and it was slightly enhanced in cells carrying a constitutively active JNK construct, MKK7-JNK1 fusion protein. The IFN-β-induced up-regulation of CD95 together with caspase-8 activation was also abrogated in the dnJNK1 cells while it was further enhanced in the MKK7-JNK1 cells. The levels of cellular FLIP (c-FLIP), competitively interacting with caspase-8, were down-regulated by stimulation with IFN-β but were reversed by the proteasome inhibitor lactacystin. Collectively, the IFN-β-induced sustained activation of JNK mediates apoptosis, at least in part, through up-regulation of CD95 protein in combination with down-regulation of c-FLIP protein

  8. Nonlinear dynamical modeling and prediction of the terrestrial magnetospheric activity

    International Nuclear Information System (INIS)

    Vassiliadis, D.

    1992-01-01

    The irregular activity of the magnetosphere results from its complex internal dynamics as well as the external influence of the solar wind. The dominating self-organization of the magnetospheric plasma gives rise to repetitive, large-scale coherent behavior manifested in phenomena such as the magnetic substorm. Based on the nonlinearity of the global dynamics this dissertation examines the magnetosphere as a nonlinear dynamical system using time series analysis techniques. Initially the magnetospheric activity is modeled in terms of an autonomous system. A dimension study shows that its observed time series is self-similar, but the correlation dimension is high. The implication of a large number of degrees of freedom is confirmed by other state space techniques such as Poincare sections and search for unstable periodic orbits. At the same time a stability study of the time series in terms of Lyapunov exponents suggests that the series is not chaotic. The absence of deterministic chaos is supported by the low predictive capability of the autonomous model. Rather than chaos, it is an external input which is largely responsible for the irregularity of the magnetospheric activity. In fact, the external driving is so strong that the above state space techniques give results for magnetospheric and solar wind time series that are at least qualitatively similar. Therefore the solar wind input has to be included in a low-dimensional nonautonomous model. Indeed it is shown that such a model can reproduce the observed magnetospheric behavior up to 80-90 percent. The characteristic coefficients of the model show little variation depending on the external disturbance. The impulse response is consistent with earlier results of linear prediction filters. The model can be easily extended to contain nonlinear features of the magnetospheric activity and in particular the loading-unloading behavior of substorms

  9. Recent and Past Musical Activity Predicts Cognitive Aging Variability: Direct Comparison with Leisure Activities

    Directory of Open Access Journals (Sweden)

    Brenda eHanna-Pladdy

    2012-07-01

    Full Text Available Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years on preserved cognitive functioning in advanced age . These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to nonmusical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study examined the type of leisure activity (musical versus other as well as the timing of engagement (age of acquisition, past versus recent in predictive models of successful cognitive aging. Seventy age and education matched older musicians (> 10 years and nonmusicians (ages 59-80 were evaluated on neuropsychological tests and life-style activities (AAP. Partition analyses were conducted on significant cognitive measures to explain performance variance in musicians. Musicians scored higher on tests of phonemic fluency, verbal immediate recall, judgment of line orientation (JLO, and Letter Number Sequencing (LNS, but not the AAP. The first partition analysis revealed education best predicted JLO in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (< 9 years predicted enhanced LNS in musicians, while analyses for AAP, verbal recall and fluency were not predictive. Recent and past musical activity, but not leisure activity, predicted variability across verbal and visuospatial domains in aging. Early musical acquisition predicted auditory

  10. Prediction of antibacterial activity from physicochemical properties of antimicrobial peptides.

    Directory of Open Access Journals (Sweden)

    Manuel N Melo

    Full Text Available Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM, which conciliates the two types of observations.

  11. The sequential structure of brain activation predicts skill.

    Science.gov (United States)

    Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

    2016-01-29

    In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Recent and past musical activity predicts cognitive aging variability: direct comparison with general lifestyle activities.

    Science.gov (United States)

    Hanna-Pladdy, Brenda; Gajewski, Byron

    2012-01-01

    Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years) on preserved cognitive functioning in advanced age. These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to non-musical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in general lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study controlled for general activity level in evaluating cognition between musicians and nomusicians. Also, the timing of engagement (age of acquisition, past versus recent) was assessed in predictive models of successful cognitive aging. Seventy age and education matched older musicians (>10 years) and non-musicians (ages 59-80) were evaluated on neuropsychological tests and general lifestyle activities. Musicians scored higher on tests of phonemic fluency, verbal working memory, verbal immediate recall, visuospatial judgment, and motor dexterity, but did not differ in other general leisure activities. Partition analyses were conducted on significant cognitive measures to determine aspects of musical training predictive of enhanced cognition. The first partition analysis revealed education best predicted visuospatial functions in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (memory in musicians, while analyses for other measures were not predictive. Recent and past musical activity, but not general lifestyle activities, predicted variability

  13. Decreased dopamine activity predicts relapse in methamphetamine abusers

    Energy Technology Data Exchange (ETDEWEB)

    Wang G. J.; Wang, G.-J.; Smith, L.; Volkow, N.D.; Telang, F.; Logan, J.; Tomasi, D.; Wong, C.T.; Hoffman, W.; Jayne, M.; Alia-Klein, N.; Thanos, P.; Fowler, J.S.

    2011-01-20

    Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and [{sup 11}C]raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes.

  14. Decreased dopamine activity predicts relapse in methamphetamine abusers

    International Nuclear Information System (INIS)

    Wang, G.J.; Smith, L.; Volkow, N.D.; Telang, F.; Logan, J.; Tomasi, D.; Wong, C.T.; Hoffman, W.; Jayne, M.; Alia-Klein, N.; Thanos, P.; Fowler, J.S.

    2011-01-01

    Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and ( 11 C)raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes.

  15. Predicting the unpredictable: Critical analysis and practical implications of predictive anticipatory activity

    Directory of Open Access Journals (Sweden)

    Julia eMossbridge

    2014-03-01

    Full Text Available A recent meta-analysis of experiments from seven independent laboratories (n=26 published since 1978 indicates that the human body can apparently detect randomly delivered stimuli occurring 1-10 seconds in the future (Mossbridge, Tressoldi, & Utts, 2012. The key observation in these studies is that human physiology appears to be able to distinguish between unpredictable dichotomous future stimuli, such as emotional vs. neutral images or sound vs. silence. This phenomenon has been called presentiment (as in feeling the future. In this paper we call it predictive anticipatory activity or PAA. The phenomenon is predictive because it can distinguish between upcoming stimuli; it is anticipatory because the physiological changes occur before a future event; and it is an activity because it involves changes in the cardiopulmonary, skin, and/or nervous systems. PAA is an unconscious phenomenon that seems to be a time-reversed reflection of the usual physiological response to a stimulus. It appears to resemble precognition (consciously knowing something is going to happen before it does, but PAA specifically refers to unconscious physiological reactions as opposed to conscious premonitions. Though it is possible that PAA underlies the conscious experience of precognition, experiments testing this idea have not produced clear results. The first part of this paper reviews the evidence for PAA and examines the two most difficult challenges for obtaining valid evidence for it: expectation bias and multiple analyses. The second part speculates on possible mechanisms and the theoretical implications of PAA for understanding physiology and consciousness. The third part examines potential practical applications.

  16. Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.

    Science.gov (United States)

    Zou, Qihong; Ross, Thomas J; Gu, Hong; Geng, Xiujuan; Zuo, Xi-Nian; Hong, L Elliot; Gao, Jia-Hong; Stein, Elliot A; Zang, Yu-Feng; Yang, Yihong

    2013-12-01

    Although resting-state brain activity has been demonstrated to correspond with task-evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task-evoked deactivation and whether the rest-task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting-state and task-driven [N-back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low-frequency fluctuation (ALFF) as an index of intrinsic resting-state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task-evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task-evoked deactivation. Further, the relationship between the intrinsic resting-state activity and task-evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting-state activity and the task-evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting-state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task-evoked brain responses and behavioral performance. Copyright © 2012 Wiley Periodicals, Inc.

  17. Cortical activity patterns predict robust speech discrimination ability in noise

    Science.gov (United States)

    Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

    2012-01-01

    The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

  18. Bi-directional SIFT predicts a subset of activating mutations.

    Directory of Open Access Journals (Sweden)

    William Lee

    Full Text Available Advancements in sequencing technologies have empowered recent efforts to identify polymorphisms and mutations on a global scale. The large number of variations and mutations found in these projects requires high-throughput tools to identify those that are most likely to have an impact on function. Numerous computational tools exist for predicting which mutations are likely to be functional, but none that specifically attempt to identify mutations that result in hyperactivation or gain-of-function. Here we present a modified version of the SIFT (Sorting Intolerant from Tolerant algorithm that utilizes protein sequence alignments with homologous sequences to identify functional mutations based on evolutionary fitness. We show that this bi-directional SIFT (B-SIFT is capable of identifying experimentally verified activating mutants from multiple datasets. B-SIFT analysis of large-scale cancer genotyping data identified potential activating mutations, some of which we have provided detailed structural evidence to support. B-SIFT could prove to be a valuable tool for efforts in protein engineering as well as in identification of functional mutations in cancer.

  19. Seismic activity prediction using computational intelligence techniques in northern Pakistan

    Science.gov (United States)

    Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

    2017-10-01

    Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

  20. Prediction of Active Site and Distal Residues in E. coli DNA Polymerase III alpha Polymerase Activity.

    Science.gov (United States)

    Parasuram, Ramya; Coulther, Timothy A; Hollander, Judith M; Keston-Smith, Elise; Ondrechen, Mary Jo; Beuning, Penny J

    2018-02-20

    The process of DNA replication is carried out with high efficiency and accuracy by DNA polymerases. The replicative polymerase in E. coli is DNA Pol III, which is a complex of 10 different subunits that coordinates simultaneous replication on the leading and lagging strands. The 1160-residue Pol III alpha subunit is responsible for the polymerase activity and copies DNA accurately, making one error per 10 5 nucleotide incorporations. The goal of this research is to determine the residues that contribute to the activity of the polymerase subunit. Homology modeling and the computational methods of THEMATICS and POOL were used to predict functionally important amino acid residues through their computed chemical properties. Site-directed mutagenesis and biochemical assays were used to validate these predictions. Primer extension, steady-state single-nucleotide incorporation kinetics, and thermal denaturation assays were performed to understand the contribution of these residues to the function of the polymerase. This work shows that the top 15 residues predicted by POOL, a set that includes the three previously known catalytic aspartate residues, seven remote residues, plus five previously unexplored first-layer residues, are important for function. Six previously unidentified residues, R362, D405, K553, Y686, E688, and H760, are each essential to Pol III activity; three additional residues, Y340, R390, and K758, play important roles in activity.

  1. Development of METAL-ACTIVE SITE and ZINCCLUSTER tool to predict active site pockets.

    Science.gov (United States)

    Ajitha, M; Sundar, K; Arul Mugilan, S; Arumugam, S

    2018-03-01

    The advent of whole genome sequencing leads to increasing number of proteins with known amino acid sequences. Despite many efforts, the number of proteins with resolved three dimensional structures is still low. One of the challenging tasks the structural biologists face is the prediction of the interaction of metal ion with any protein for which the structure is unknown. Based on the information available in Protein Data Bank, a site (METALACTIVE INTERACTION) has been generated which displays information for significant high preferential and low-preferential combination of endogenous ligands for 49 metal ions. User can also gain information about the residues present in the first and second coordination sphere as it plays a major role in maintaining the structure and function of metalloproteins in biological system. In this paper, a novel computational tool (ZINCCLUSTER) is developed, which can predict the zinc metal binding sites of proteins even if only the primary sequence is known. The purpose of this tool is to predict the active site cluster of an uncharacterized protein based on its primary sequence or a 3D structure. The tool can predict amino acids interacting with a metal or vice versa. This tool is based on the occurrence of significant triplets and it is tested to have higher prediction accuracy when compared to that of other available techniques. © 2017 Wiley Periodicals, Inc.

  2. Extremely Randomized Machine Learning Methods for Compound Activity Prediction

    Directory of Open Access Journals (Sweden)

    Wojciech M. Czarnecki

    2015-11-01

    Full Text Available Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called ‘extremely randomized methods’—Extreme Entropy Machine and Extremely Randomized Trees—for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their ‘non-extreme’ competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

  3. Electrophysiological correlates of competitor activation predict retrieval-induced forgetting.

    Science.gov (United States)

    Hellerstedt, Robin; Johansson, Mikael

    2014-06-01

    The very act of retrieval modifies the accessibility of memory for knowledge and past events and can also cause forgetting. A prominent theory of such retrieval-induced forgetting (RIF) holds that retrieval recruits inhibition to overcome interference from competing memories, rendering these memories inaccessible. The present study tested a fundamental tenet of the inhibitory-control account: The competition-dependence assumption. Event-related potentials (ERPs) were recorded while participants engaged in a competitive retrieval task. Competition levels were manipulated within the retrieval task by varying the cue-item associative strength of competing items. In order to temporally separate ERP correlates of competitor activation and target retrieval, memory was probed with the sequential presentation of 2 cues: A category cue, to reactivate competitors, and a target cue. As predicted by the inhibitory-control account, competitors with strong compared with weak cue-competitor association were more susceptible to forgetting. Furthermore, competition-sensitive ERP modulations, elicited by the category cue, were observed over anterior regions and reflected individual differences in ensuing forgetting. The present study demonstrates ERP correlates of the reactivation of tightly bound associated memories (the competitors) and provides support for the inhibitory-control account of RIF.

  4. Temperature modelling and prediction for activated sludge systems.

    Science.gov (United States)

    Lippi, S; Rosso, D; Lubello, C; Canziani, R; Stenstrom, M K

    2009-01-01

    Temperature is an important factor affecting biomass activity, which is critical to maintain efficient biological wastewater treatment, and also physiochemical properties of mixed liquor as dissolved oxygen saturation and settling velocity. Controlling temperature is not normally possible for treatment systems but incorporating factors impacting temperature in the design process, such as aeration system, surface to volume ratio, and tank geometry can reduce the range of temperature extremes and improve the overall process performance. Determining how much these design or up-grade options affect the tank temperature requires a temperature model that can be used with existing design methodologies. This paper presents a new steady state temperature model developed by incorporating the best aspects of previously published models, introducing new functions for selected heat exchange paths and improving the method for predicting the effects of covering aeration tanks. Numerical improvements with embedded reference data provide simpler formulation, faster execution, easier sensitivity analyses, using an ordinary spreadsheet. The paper presents several cases to validate the model.

  5. Validation of Quantitative Structure-Activity Relationship (QSAR Model for Photosensitizer Activity Prediction

    Directory of Open Access Journals (Sweden)

    Sharifuddin M. Zain

    2011-11-01

    Full Text Available Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA method. Based on the method, r2 value, r2 (CV value and r2 prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC50 values ranging from 0.39 µM to 7.04 µM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r2 prediction for external test set of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set.

  6. Traction force dynamics predict gap formation in activated endothelium

    Energy Technology Data Exchange (ETDEWEB)

    Valent, Erik T.; Nieuw Amerongen, Geerten P. van; Hinsbergh, Victor W.M. van; Hordijk, Peter L., E-mail: p.hordijk@vumc.nl

    2016-09-10

    In many pathological conditions the endothelium becomes activated and dysfunctional, resulting in hyperpermeability and plasma leakage. No specific therapies are available yet to control endothelial barrier function, which is regulated by inter-endothelial junctions and the generation of acto-myosin-based contractile forces in the context of cell-cell and cell-matrix interactions. However, the spatiotemporal distribution and stimulus-induced reorganization of these integral forces remain largely unknown. Traction force microscopy of human endothelial monolayers was used to visualize contractile forces in resting cells and during thrombin-induced hyperpermeability. Simultaneously, information about endothelial monolayer integrity, adherens junctions and cytoskeletal proteins (F-actin) were captured. This revealed a heterogeneous distribution of traction forces, with nuclear areas showing lower and cell-cell junctions higher traction forces than the whole-monolayer average. Moreover, junctional forces were asymmetrically distributed among neighboring cells. Force vector orientation analysis showed a good correlation with the alignment of F-actin and revealed contractile forces in newly formed filopodia and lamellipodia-like protrusions within the monolayer. Finally, unstable areas, showing high force fluctuations within the monolayer were prone to form inter-endothelial gaps upon stimulation with thrombin. To conclude, contractile traction forces are heterogeneously distributed within endothelial monolayers and force instability, rather than force magnitude, predicts the stimulus-induced formation of intercellular gaps. - Highlights: • Endothelial monolayers exert dynamic- and heterogeneous traction forces. • High traction forces correlate with junctional areas and the F-actin cytoskeleton. • Newly formed inter-endothelial gaps are characterized by opposing traction forces. • Force stability is a key feature controlling endothelial permeability.

  7. Traction force dynamics predict gap formation in activated endothelium

    International Nuclear Information System (INIS)

    Valent, Erik T.; Nieuw Amerongen, Geerten P. van; Hinsbergh, Victor W.M. van; Hordijk, Peter L.

    2016-01-01

    In many pathological conditions the endothelium becomes activated and dysfunctional, resulting in hyperpermeability and plasma leakage. No specific therapies are available yet to control endothelial barrier function, which is regulated by inter-endothelial junctions and the generation of acto-myosin-based contractile forces in the context of cell-cell and cell-matrix interactions. However, the spatiotemporal distribution and stimulus-induced reorganization of these integral forces remain largely unknown. Traction force microscopy of human endothelial monolayers was used to visualize contractile forces in resting cells and during thrombin-induced hyperpermeability. Simultaneously, information about endothelial monolayer integrity, adherens junctions and cytoskeletal proteins (F-actin) were captured. This revealed a heterogeneous distribution of traction forces, with nuclear areas showing lower and cell-cell junctions higher traction forces than the whole-monolayer average. Moreover, junctional forces were asymmetrically distributed among neighboring cells. Force vector orientation analysis showed a good correlation with the alignment of F-actin and revealed contractile forces in newly formed filopodia and lamellipodia-like protrusions within the monolayer. Finally, unstable areas, showing high force fluctuations within the monolayer were prone to form inter-endothelial gaps upon stimulation with thrombin. To conclude, contractile traction forces are heterogeneously distributed within endothelial monolayers and force instability, rather than force magnitude, predicts the stimulus-induced formation of intercellular gaps. - Highlights: • Endothelial monolayers exert dynamic- and heterogeneous traction forces. • High traction forces correlate with junctional areas and the F-actin cytoskeleton. • Newly formed inter-endothelial gaps are characterized by opposing traction forces. • Force stability is a key feature controlling endothelial permeability.

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  9. Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

    Science.gov (United States)

    Naik, P K; Singh, T; Singh, H

    2009-07-01

    Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

  10. Phenyl Saligenin Phosphate Induced Caspase-3 and c-Jun N-Terminal Kinase Activation in Cardiomyocyte-Like Cells.

    Science.gov (United States)

    Felemban, Shatha G; Garner, A Christopher; Smida, Fathi A; Boocock, David J; Hargreaves, Alan J; Dickenson, John M

    2015-11-16

    At present, little is known about the effect(s) of organophosphorous compounds (OPs) on cardiomyocytes. In this study, we have investigated the effects of phenyl saligenin phosphate (PSP), two organophosphorothioate insecticides (diazinon and chlorpyrifos), and their acutely toxic metabolites (diazoxon and chlorpyrifos oxon) on mitotic and differentiated H9c2 cardiomyoblasts. OP-induced cytotoxicity was assessed by monitoring MTT reduction, LDH release, and caspase-3 activity. Cytotoxicity was not observed with diazinon, diazoxon, or chlorpyrifos oxon (48 h exposure; 200 μM). Chlorpyrifos-induced cytotoxicity was only evident at concentrations >100 μM. In marked contrast, PSP displayed pronounced cytotoxicity toward mitotic and differentiated H9c2 cells. PSP triggered the activation of JNK1/2 but not ERK1/2, p38 MAPK, or PKB, suggesting a role for this pro-apoptotic protein kinase in PSP-induced cell death. The JNK1/2 inhibitor SP 600125 attenuated PSP-induced caspase-3 and JNK1/2 activation, confirming the role of JNK1/2 in PSP-induced cytotoxicity. Fluorescently labeled PSP (dansylated PSP) was used to identify novel PSP binding proteins. Dansylated PSP displayed cytotoxicity toward differentiated H9c2 cells. 2D-gel electrophoresis profiles of cells treated with dansylated PSP (25 μM) were used to identify proteins fluorescently labeled with dansylated PSP. Proteomic analysis identified tropomyosin, heat shock protein β-1, and nucleolar protein 58 as novel protein targets for PSP. In summary, PSP triggers cytotoxicity in differentiated H9c2 cardiomyoblasts via JNK1/2-mediated activation of caspase-3. Further studies are required to investigate whether the identified novel protein targets of PSP play a role in the cytotoxicity of this OP, which is usually associated with the development of OP-induced delayed neuropathy.

  11. Predicting daily physical activity in a lifestyle intervention program

    NARCIS (Netherlands)

    Long, Xi; Pauws, S.C.; Pijl, M.; Lacroix, J.; Goris, A.H.C.; Aarts, R.M.; Gottfried, B.; Aghajan, H.

    2011-01-01

    The growing number of people adopting a sedentary lifestyle these days creates a serious need for effective physical activity promotion programs. Often, these programs monitor activity, provide feedback about activity and offer coaching to increase activity. Some programs rely on a human coach who

  12. Time and activity sequence prediction of business process instances

    DEFF Research Database (Denmark)

    Polato, Mirko; Sperduti, Alessandro; Burattin, Andrea

    2018-01-01

    The ability to know in advance the trend of running process instances, with respect to different features, such as the expected completion time, would allow business managers to timely counteract to undesired situations, in order to prevent losses. Therefore, the ability to accurately predict...... future features of running business process instances would be a very helpful aid when managing processes, especially under service level agreement constraints. However, making such accurate forecasts is not easy: many factors may influence the predicted features. Many approaches have been proposed...

  13. Predicting enhancer activity and variant impact using gkm-SVM.

    Science.gov (United States)

    Beer, Michael A

    2017-09-01

    We participated in the Critical Assessment of Genome Interpretation eQTL challenge to further test computational models of regulatory variant impact and their association with human disease. Our prediction model is based on a discriminative gapped-kmer SVM (gkm-SVM) trained on genome-wide chromatin accessibility data in the cell type of interest. The comparisons with massively parallel reporter assays (MPRA) in lymphoblasts show that gkm-SVM is among the most accurate prediction models even though all other models used the MPRA data for model training, and gkm-SVM did not. In addition, we compare gkm-SVM with other MPRA datasets and show that gkm-SVM is a reliable predictor of expression and that deltaSVM is a reliable predictor of variant impact in K562 cells and mouse retina. We further show that DHS (DNase-I hypersensitive sites) and ATAC-seq (assay for transposase-accessible chromatin using sequencing) data are equally predictive substrates for training gkm-SVM, and that DHS regions flanked by H3K27Ac and H3K4me1 marks are more predictive than DHS regions alone. © 2017 Wiley Periodicals, Inc.

  14. Factors predicting physical activity among children with special needs.

    Science.gov (United States)

    Yazdani, Shahram; Yee, Chu Tang; Chung, Paul J

    2013-07-18

    Obesity is especially prevalent among children with special needs. Both lack of physical activity and unhealthful eating are major contributing factors. The objective of our study was to investigate barriers to physical activity among these children. We surveyed parents of the 171 children attending Vista Del Mar School in Los Angeles, a nonprofit school serving a socioeconomically diverse group of children with special needs from kindergarten through 12th grade. Parents were asked about their child's and their own physical activity habits, barriers to their child's exercise, and demographics. The response rate was 67%. Multivariate logistic regression was used to examine predictors of children being physically active at least 3 hours per week. Parents reported that 45% of the children were diagnosed with attention deficit hyperactivity disorder, 38% with autism, and 34% with learning disabilities; 47% of children and 56% of parents were physically active less than 3 hours per week. The top barriers to physical activity were reported as child's lack of interest (43%), lack of developmentally appropriate programs (33%), too many behavioral problems (32%), and parents' lack of time (29%). However, child's lack of interest was the only parent-reported barrier independently associated with children's physical activity. Meanwhile, children whose parents were physically active at least 3 hours per week were 4.2 times as likely to be physically active as children whose parents were less physically active (P = .01). In this group of students with special needs, children's physical activity was strongly associated with parental physical activity; parent-reported barriers may have had less direct effect. Further studies should examine the importance of parental physical activity among children with special needs.

  15. Predicting human activities in sequences of actions in RGB-D videos

    Science.gov (United States)

    Jardim, David; Nunes, Luís.; Dias, Miguel

    2017-03-01

    In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.

  16. Predictive Active Set Selection Methods for Gaussian Processes

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2012-01-01

    We propose an active set selection framework for Gaussian process classification for cases when the dataset is large enough to render its inference prohibitive. Our scheme consists of a two step alternating procedure of active set update rules and hyperparameter optimization based upon marginal...... high impact to the classifier decision process while removing those that are less relevant. We introduce two active set rules based on different criteria, the first one prefers a model with interpretable active set parameters whereas the second puts computational complexity first, thus a model...... with active set parameters that directly control its complexity. We also provide both theoretical and empirical support for our active set selection strategy being a good approximation of a full Gaussian process classifier. Our extensive experiments show that our approach can compete with state...

  17. Ventromedial Prefrontal Cortex Activation Is Associated with Memory Formation for Predictable Rewards

    Science.gov (United States)

    Bialleck, Katharina A.; Schaal, Hans-Peter; Kranz, Thorsten A.; Fell, Juergen; Elger, Christian E.; Axmacher, Nikolai

    2011-01-01

    During reinforcement learning, dopamine release shifts from the moment of reward consumption to the time point when the reward can be predicted. Previous studies provide consistent evidence that reward-predicting cues enhance long-term memory (LTM) formation of these items via dopaminergic projections to the ventral striatum. However, it is less clear whether memory for items that do not precede a reward but are directly associated with reward consumption is also facilitated. Here, we investigated this question in an fMRI paradigm in which LTM for reward-predicting and neutral cues was compared to LTM for items presented during consumption of reliably predictable as compared to less predictable rewards. We observed activation of the ventral striatum and enhanced memory formation during reward anticipation. During processing of less predictable as compared to reliably predictable rewards, the ventral striatum was activated as well, but items associated with less predictable outcomes were remembered worse than items associated with reliably predictable outcomes. Processing of reliably predictable rewards activated the ventromedial prefrontal cortex (vmPFC), and vmPFC BOLD responses were associated with successful memory formation of these items. Taken together, these findings show that consumption of reliably predictable rewards facilitates LTM formation and is associated with activation of the vmPFC. PMID:21326612

  18. Nonlinear Economic Model Predictive Control Strategy for Active Smart Buildings

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm ...... controller is shown very reliable keeping the comfort levels in the two considered seasons and shifting the load away from peak hours in order to achieve the desired flexible electricity consumption.......Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm...

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

    Science.gov (United States)

    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. © 2016 Wiley Periodicals, Inc.

  20. Prediction of active control of subsonic centrifugal compressor rotating stall

    Science.gov (United States)

    Lawless, Patrick B.; Fleeter, Sanford

    1993-01-01

    A mathematical model is developed to predict the suppression of rotating stall in a centrifugal compressor with a vaned diffuser. This model is based on the employment of a control vortical waveform generated upstream of the impeller inlet to damp weak potential disturbances that are the early stages of rotating stall. The control system is analyzed by matching the perturbation pressure in the compressor inlet and exit flow fields with a model for the unsteady behavior of the compressor. The model was effective at predicting the stalling behavior of the Purdue Low Speed Centrifugal Compressor for two distinctly different stall patterns. Predictions made for the effect of a controlled inlet vorticity wave on the stability of the compressor show that for minimum control wave magnitudes, on the order of the total inlet disturbance magnitude, significant damping of the instability can be achieved. For control waves of sufficient amplitude, the control phase angle appears to be the most important factor in maintaining a stable condition in the compressor.

  1. Prediction of anticancer activity of aliphatic nitrosoureas using ...

    African Journals Online (AJOL)

    Design and development of new anticancer drugs with low toxicity is a very challenging task and computer aided methods are being increasingly used to solve this problem. In this study, we investigated the anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) ...

  2. PASS-GP: Predictive active set selection for Gaussian processes

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2010-01-01

    available in GPs to make a common ranking for both active and inactive points, allowing points to be removed again from the active set. This is important for keeping the complexity down and at the same time focusing on points close to the decision boundary. We lend both theoretical and empirical support...

  3. Adults' future time perspective predicts engagement in physical activity.

    Science.gov (United States)

    Stahl, Sarah T; Patrick, Julie Hicks

    2012-07-01

    Our aim was to examine how the relations among known predictors of physical activity, such as age, sex, and body mass index, interact with future time perspective (FTP) and perceived functional limitation to explain adults' engagement in physical activity. Self-report data from 226 adults (range 20-88 years) were collected to examine the hypothesis that a more expansive FTP is associated with engagement in physical activity. Results indicated a good fit of the data to the model χ(2) (4, N = 226) = 7.457, p = .14 and accounted for a moderate amount of variance in adults' physical activity (R(2) = 15.7). Specifically, results indicated that perceived functional limitation (β = -.140) and FTP (β = .162) were directly associated with physical activity. Age was indirectly associated with physical activity through its association with perceived functional limitation (β = -.264) and FTP (β = .541). Results indicate that FTP may play an important role in explaining engagement in health promoting behaviors across the life span. Researchers should consider additional constructs and perhaps adopt socioemotional selectivity theory when explaining adults' engagement in physical activity.

  4. A rapid method of predicting radiocaesium concentrations in sheep from activity levels in faeces

    International Nuclear Information System (INIS)

    McGee, E.J.; Synnott, H.J.; Colgan, P.A.; Keatinge, M.J.

    1994-01-01

    The use of faecal samples taken from sheep flocks as a means of predicting radiocaesium concentrations in live animals was studied. Radiocaesium levels in 1726 sheep from 29 flocks were measured using in vivo techniques and a single faecal sample taken from each flock was also analysed. A highly significant relationship was found to exist between mean flock activity and activity in the corresponding faecal samples. Least-square regression yielded a simple model for predicting mean flock radiocaesium concentrations based on activity levels in faecal samples. A similar analysis of flock maxima and activity levels in faeces provides an alternative model for predicting the expected within-flock maximum radiocaesium concentration. (Author)

  5. Visual short term memory related brain activity predicts mathematical abilities.

    Science.gov (United States)

    Boulet-Craig, Aubrée; Robaey, Philippe; Lacourse, Karine; Jerbi, Karim; Oswald, Victor; Krajinovic, Maja; Laverdière, Caroline; Sinnett, Daniel; Jolicoeur, Pierre; Lippé, Sarah

    2017-07-01

    Previous research suggests visual short-term memory (VSTM) capacity and mathematical abilities are significantly related. Moreover, both processes activate similar brain regions within the parietal cortex, in particular, the intraparietal sulcus; however, it is still unclear whether the neuronal underpinnings of VSTM directly correlate with mathematical operation and reasoning abilities. The main objective was to investigate the association between parieto-occipital brain activity during the retention period of a VSTM task and performance in mathematics. The authors measured mathematical abilities and VSTM capacity as well as brain activity during memory maintenance using magnetoencephalography (MEG) in 19 healthy adult participants. Event-related magnetic fields (ERFs) were computed on the MEG data. Linear regressions were used to estimate the strength of the relation between VSTM related brain activity and mathematical abilities. The amplitude of parieto-occipital cerebral activity during the retention of visual information was related to performance in 2 standardized mathematical tasks: mathematical reasoning and calculation fluency. The findings show that brain activity during retention period of a VSTM task is associated with mathematical abilities. Contributions of VSTM processes to numerical cognition should be considered in cognitive interventions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  6. Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

    Science.gov (United States)

    Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

    2014-08-01

    Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Prediction of BMI by impulsivity, eating behavior and activity level

    Directory of Open Access Journals (Sweden)

    Jiang Xiaxia

    2016-01-01

    Full Text Available Objective: Discuss the relationship between the impulsivity, eating behavior and activity level and the body mass index (BMI. Method: Test 147 female college students with the impulsivity questionnaire (BIS-11 and BIS/BAS, Dutch Eating Behavior Questionnaire (DBEQ, Sitting Time Scale (STS and Exercising Time Scale (ETS. Results: (1 The correlation analysis indicates that BMI and impulsivity (r = 0.43 and 0.52 have a significant positive correlation with the sitting time (r = 0.61 and a significant negative correlation with the activity level (r= −0.49. (2 The path analysis indicates that the reward sensitivity directly affects BMI and indirectly affects BMI through the activity level as well; the eating behavior has an insignificantly direct impact on BMI, because its impact is generated by the intermediary role of induced diet. Conclusion: (1 The impulsivity, eating behavior and activity level are closely related to BMI; (2 the activity level, sitting time and induced diet play an intermediary role between the impulsivity and BMI.

  8. Physical activity and epilepsy: proven and predicted benefits.

    Science.gov (United States)

    Arida, Ricardo M; Cavalheiro, Esper A; da Silva, Antonio C; Scorza, Fulvio A

    2008-01-01

    Epilepsy is a common disease found in 2% of the population, affecting people from all ages. Unfortunately, persons with epilepsy have previously been discouraged from participation in physical activity and sports for fear of inducing seizures or increasing seizure frequency. Despite a shift in medical recommendations toward encouraging rather than restricting participation, the stigma remains and persons with epilepsy continue to be less active than the general population. For this purpose, clinical and experimental studies have analysed the effect of physical exercise on epilepsy. Although there are rare cases of exercise-induced seizures, studies have shown that physical activity can decrease seizure frequency, as well as lead to improved cardiovascular and psychological health in people with epilepsy. The majority of physical activities or sports are safe for people with epilepsy to participate in with special attention to adequate seizure control, close monitoring of medications, and preparation of family or trainers. The evidence shows that patients with good seizure control can participate in both contact and non-contact sports without harmfully affecting seizure frequency. This article reviews the risks and benefits of physical activity in people with epilepsy, discusses sports in which persons with epilepsy may participate, and describes the positive effect of physical exercise in experimental models of epilepsy.

  9. Biological Activity Predictions and Hydrogen Bonding Analysis in Quinolines

    Science.gov (United States)

    Gupta, Palvi; Kamni

    The paper has been designed to make a comprehensive review of a particular series of organic molecular assembly in the form of compendium. An overview of general description of fifteen quinoline derivatives has been given. The biological activity spectra of quinoline derivatives have been correlated on structure activity relationships base which provides the different Pa (possibility of activity) and Pi (possibility of inactivity) values. Expositions of the role of intermolecular interactions in the identified derivatives have been discussed with the standard distance and angle cut-off criteria criteria as proposed by Desiraju and Steiner (1999) in an International monogram on crystallography. Distance-angle scatter plots for intermolecular interactions are presented for a better understanding of the packing interactions which exist in quinoline derivatives.

  10. Predicting Child Physical Activity and Screen Time: Parental Support for Physical Activity and General Parenting Styles

    Science.gov (United States)

    Crain, A. Lauren; Senso, Meghan M.; Levy, Rona L.; Sherwood, Nancy E.

    2014-01-01

    Objective: To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Methods: Participants were children (6.9 ± 1.8 years) with a body mass index in the 70–95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Results: Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Conclusions: Parenting practices and styles should be considered jointly, offering implications for tailored interventions. PMID:24812256

  11. Predicting child physical activity and screen time: parental support for physical activity and general parenting styles.

    Science.gov (United States)

    Langer, Shelby L; Crain, A Lauren; Senso, Meghan M; Levy, Rona L; Sherwood, Nancy E

    2014-07-01

    To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Participants were children (6.9 ± 1.8 years) with a body mass index in the 70-95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Parenting practices and styles should be considered jointly, offering implications for tailored interventions. © The Author 2014. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. Predicting and preventing the future: actively managing multiple sclerosis.

    LENUS (Irish Health Repository)

    Hutchinson, Michael

    2012-02-01

    Relapsing-remitting multiple sclerosis (MS) has a highly variable clinical course but a number of demographic, clinical and MRI features can guide the clinician in the assessment of disease activity and likely disability outcome. It is also clear that the inflammatory activity in the first five years of relapsing-remitting MS results in the neurodegenerative changes seen in secondary progressive MS 10-15 years later. While conventional first-line disease modifying therapy has an effect on relapses, about one third of patients have a suboptimal response to treatment. With the advent of highly active second-line therapies with their evident marked suppression of inflammation, the clinician now has the tools to manage the course of relapsing-remitting MS more effectively. The development of treatment optimisation recommendations based on the clinical response to first-line therapies can guide the neurologist in more active management of the early course of relapsing-remitting MS, with the aim of preventing both acute inflammatory axonal injury and the neurodegenerative process which leads to secondary progressive MS.

  13. Prediction of Positions of Active Compounds Makes It Possible To Increase Activity in Fragment-Based Drug Development

    Directory of Open Access Journals (Sweden)

    Yoshifumi Fukunishi

    2011-05-01

    Full Text Available We have developed a computational method that predicts the positions of active compounds, making it possible to increase activity as a fragment evolution strategy. We refer to the positions of these compounds as the active position. When an active fragment compound is found, the following lead generation process is performed, primarily to increase activity. In the current method, to predict the location of the active position, hydrogen atoms are replaced by small side chains, generating virtual compounds. These virtual compounds are docked to a target protein, and the docking scores (affinities are examined. The hydrogen atom that gives the virtual compound with good affinity should correspond to the active position and it should be replaced to generate a lead compound. This method was found to work well, with the prediction of the active position being 2 times more efficient than random synthesis. In the current study, 15 examples of lead generation were examined. The probability of finding active positions among all hydrogen atoms was 26%, and the current method accurately predicted 60% of the active positions.

  14. Analysis and prediction of daily physical activity level data using autoregressive integrated moving average models

    NARCIS (Netherlands)

    Long, Xi; Pauws, S.C.; Pijl, M.; Lacroix, J.; Goris, A.H.C.; Aarts, R.M.

    2009-01-01

    Results are provided on predicting daily physical activity level (PAL) data from past data of participants of a physical activity lifestyle program aimed at promoting a healthier lifestyle consisting of more physical exercise. The PAL data quantifies the level of a person’s daily physical activity

  15. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    Energy Technology Data Exchange (ETDEWEB)

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A [Duke University Medical Center, Durham, NC (United States); Ge, Y [University of North Carolina at Charlotte, Charlotte, NC (United States)

    2014-06-15

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

  16. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    International Nuclear Information System (INIS)

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A; Ge, Y

    2014-01-01

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

  17. Early prediction of outcome of activities of daily living after stroke: a systematic review

    OpenAIRE

    Veerbeek, J.M.; Kwakkel, G.; Wegen, van, E.E.H.; Ket, J.C.F.; Heijmans, M.W.

    2011-01-01

    BACKGROUND AND PURPOSE-Knowledge about robust and unbiased factors that predict outcome of activities of daily living (ADL) is paramount in stroke management. This review investigates the methodological quality of prognostic studies in the early poststroke phase for final ADL to identify variables that are predictive or not predictive for outcome of ADL after stroke. METHODS-PubMed, Ebsco/Cinahl and Embase were systematically searched for prognostic studies in which stroke patients were inclu...

  18. Triptolide, a diterpenoid triepoxide, induces antitumor proliferation via activation of c-Jun NH2-terminal kinase 1 by decreasing phosphatidylinositol 3-kinase activity in human tumor cells

    International Nuclear Information System (INIS)

    Miyata, Yoshiki; Sato, Takashi; Ito, Akira

    2005-01-01

    Triptolide, a diterpenoid triepoxide extracted from the Chinese herb Tripterygium wilfordii Hook f., exerts antitumorigenic actions against several tumor cells, but the intracellular target signal molecule(s) for this antitumorigenesis activity of triptolide remains to be identified. In the present study, we demonstrated that triptolide, in a dose-dependent manner, inhibited the proliferation of human fibrosarcoma HT-1080, human squamous carcinoma SAS, and human uterine cervical carcinoma SKG-II cells. In addition, triptolide was found to decrease phosphatidylinositol 3-kinase (PI3K) activity. A PI3K inhibitor, LY-294002, mimicked the triptolide-induced antiproliferative activity in HT-1080, SAS, and SKG-II cells. There was no change in the activity of Akt or protein kinase C (PKC), both of which are downstream effectors in the PI3K pathway. Furthermore, the phosphorylation of Ras, Raf, and mitogen-activated protein/extracellular signal-regulated kinase 1/2 was not modified in HT-1080 cells treated with triptolide. However, the phosphorylation of c-Jun NH 2 -terminal kinase 1 (JNK1) was found to increase in both triptolide- and LY-294002-treated cells. Furthermore, the triptolide-induced inhibition of HT-1080 cell proliferation was not observed by JNK1 siRNA-treatment. These results provide novel evidence that PI3K is a crucial target molecule in the antitumorigenic action of triptolide. They further suggest a possible triptolide-induced inhibitory signal for tumor cell proliferation that is initiated by the decrease in PI3K activity, which in turn leads to the augmentation of JNK1 phosphorylation via the Akt and/or PKC-independent pathway(s). Moreover, it is likely that the activation of JNK1 is required for the triptolide-induced inhibition of tumor proliferation

  19. Predicting the initial freezing point and water activity of meat products from composition data

    NARCIS (Netherlands)

    Sman, van der R.G.M.; Boer, E.P.J.

    2005-01-01

    In this paper we predict the water activity and initial freezing point of food products (meat and fish) based on their composition. The prediction is based on thermodynamics (the Clausius-Clapeyron equation, the Ross equation and an approximation of the Pitzer equation). Furthermore, we have taken

  20. Using Social Cognitive Theory to Predict Physical Activity and Fitness in Underserved Middle School Children

    Science.gov (United States)

    Martin, Jeffrey J.; McCaughtry, Nate; Flory, Sara; Murphy, Anne; Wisdom, Kimberlydawn

    2011-01-01

    Few researchers have used social cognitive theory and environment-based constructs to predict physical activity (PA) and fitness in underserved middle-school children. Hence, we evaluated social cognitive variables and perceptions of the school environment to predict PA and fitness in middle school children (N = 506, ages 10-14 years). Using…

  1. Diverse models for the prediction of CDK4 inhibitory activity of ...

    Indian Academy of Sciences (India)

    employed for development of models for the prediction of CDK4 inhibitory activity using a dataset comprising of 52 analogues of ... index; molecular connectivity index; connective eccentricity topochemical index. 1. ... 80% of human cancers.

  2. Optimism predicts sustained vigorous physical activity in postmenopausal women

    Directory of Open Access Journals (Sweden)

    Ana M. Progovac

    2017-12-01

    Full Text Available Optimism and cynical hostility are associated with health behaviors and health outcomes, including morbidity and mortality. This analysis assesses their association with longitudinal vigorous physical activity (PA in postmenopausal women of the Women's Health Initiative (WHI. Subjects include 73,485 women nationwide without history of cancer or cardiovascular disease (CVD, and no missing baseline optimism, cynical hostility, or PA data. The Life Orientation Test-Revised Scale measured optimism. A Cook Medley questionnaire subscale measured cynical hostility. Scale scores were divided into quartiles. Vigorous PA three times or more per week was assessed via self-report at study baseline (1994–1998 and through follow-up year 6. Descriptive analysis mapped lifetime trajectories of vigorous PA (recalled at ages 18, 25, 50; prospectively assessed at baseline, and 3 and 6years later. Hierarchical generalized linear mixed models examined the prospective association between optimism, cynical hostility, and vigorous PA over 6years. Models adjusted for baseline sociodemographic variables, psychosocial characteristics, and health conditions and behaviors. Vigorous PA rates were highest for most optimistic women, but fell for all women by approximately 60% between age 50 and study baseline. In adjusted models from baseline through year 6, most vs. least optimistic women were 15% more likely to exercise vigorously (p<0.001. Cynical hostility was not associated with lower odds of longitudinal vigorous PA after adjustment. Results did not differ by race/ethnicity or socioeconomic status. Higher optimism is associated with maintaining vigorous PA over time in post-menopausal women, and may protect women's health over the lifespan. Keywords: Physical activity, Aging, Optimism, Cynical hostility, women's health

  3. Predicting earthquakes by analyzing accelerating precursory seismic activity

    Science.gov (United States)

    Varnes, D.J.

    1989-01-01

    During 11 sequences of earthquakes that in retrospect can be classed as foreshocks, the accelerating rate at which seismic moment is released follows, at least in part, a simple equation. This equation (1) is {Mathematical expression},where {Mathematical expression} is the cumulative sum until time, t, of the square roots of seismic moments of individual foreshocks computed from reported magnitudes;C and n are constants; and tfis a limiting time at which the rate of seismic moment accumulation becomes infinite. The possible time of a major foreshock or main shock, tf,is found by the best fit of equation (1), or its integral, to step-like plots of {Mathematical expression} versus time using successive estimates of tfin linearized regressions until the maximum coefficient of determination, r2,is obtained. Analyzed examples include sequences preceding earthquakes at Cremasta, Greece, 2/5/66; Haicheng, China 2/4/75; Oaxaca, Mexico, 11/29/78; Petatlan, Mexico, 3/14/79; and Central Chile, 3/3/85. In 29 estimates of main-shock time, made as the sequences developed, the errors in 20 were less than one-half and in 9 less than one tenth the time remaining between the time of the last data used and the main shock. Some precursory sequences, or parts of them, yield no solution. Two sequences appear to include in their first parts the aftershocks of a previous event; plots using the integral of equation (1) show that the sequences are easily separable into aftershock and foreshock segments. Synthetic seismic sequences of shocks at equal time intervals were constructed to follow equation (1), using four values of n. In each series the resulting distributions of magnitudes closely follow the linear Gutenberg-Richter relation log N=a-bM, and the product n times b for each series is the same constant. In various forms and for decades, equation (1) has been used successfully to predict failure times of stressed metals and ceramics, landslides in soil and rock slopes, and volcanic

  4. Online communication predicts Belgian adolescents' initiation of romantic and sexual activity.

    Science.gov (United States)

    Vandenbosch, Laura; Beyens, Ine; Vangeel, Laurens; Eggermont, Steven

    2016-04-01

    Online communication is associated with offline romantic and sexual activity among college students. Yet, it is unknown whether online communication is associated with the initiation of romantic and sexual activity among adolescents. This two-wave panel study investigated whether chatting, visiting dating websites, and visiting erotic contact websites predicted adolescents' initiation of romantic and sexual activity. We analyzed two-wave panel data from 1163 Belgian adolescents who participated in the MORES Study. We investigated the longitudinal impact of online communication on the initiation of romantic relationships and sexual intercourse using logistic regression analyses. The odds ratios of initiating a romantic relationship among romantically inexperienced adolescents who frequently used chat rooms, dating websites, or erotic contact websites were two to three times larger than those of non-users. Among sexually inexperienced adolescents who frequently used chat rooms, dating websites, or erotic contact websites, the odds ratios of initiating sexual intercourse were two to five times larger than that among non-users, even after a number of other relevant factors were introduced. This is the first study to demonstrate that online communication predicts the initiation of offline sexual and romantic activity as early as adolescence. Practitioners and parents need to consider the role of online communication in adolescents' developing sexuality. • Adolescents increasingly communicate online with peers. • Online communication predicts romantic and sexual activity among college students. What is New: • Online communication predicts adolescents' offline romantic activity over time. • Online communication predicts adolescents' offline sexual activity over time.

  5. Cognitive emotion regulation enhances aversive prediction error activity while reducing emotional responses.

    Science.gov (United States)

    Mulej Bratec, Satja; Xie, Xiyao; Schmid, Gabriele; Doll, Anselm; Schilbach, Leonhard; Zimmer, Claus; Wohlschläger, Afra; Riedl, Valentin; Sorg, Christian

    2015-12-01

    Cognitive emotion regulation is a powerful way of modulating emotional responses. However, despite the vital role of emotions in learning, it is unknown whether the effect of cognitive emotion regulation also extends to the modulation of learning. Computational models indicate prediction error activity, typically observed in the striatum and ventral tegmental area, as a critical neural mechanism involved in associative learning. We used model-based fMRI during aversive conditioning with and without cognitive emotion regulation to test the hypothesis that emotion regulation would affect prediction error-related neural activity in the striatum and ventral tegmental area, reflecting an emotion regulation-related modulation of learning. Our results show that cognitive emotion regulation reduced emotion-related brain activity, but increased prediction error-related activity in a network involving ventral tegmental area, hippocampus, insula and ventral striatum. While the reduction of response activity was related to behavioral measures of emotion regulation success, the enhancement of prediction error-related neural activity was related to learning performance. Furthermore, functional connectivity between the ventral tegmental area and ventrolateral prefrontal cortex, an area involved in regulation, was specifically increased during emotion regulation and likewise related to learning performance. Our data, therefore, provide first-time evidence that beyond reducing emotional responses, cognitive emotion regulation affects learning by enhancing prediction error-related activity, potentially via tegmental dopaminergic pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Predictive capabilities of the specific activity hypothesis for Cs and Zn in freshwater systems

    International Nuclear Information System (INIS)

    Seelye, J.G.

    1975-01-01

    Predictions of radioisotope concentrations in components of aquatic systems have been attempted using the specific activity concept, an approach that seems theoretically sound. A comprehensive examination of the specific activities of 134 Cs and 65 Zn in the components of a freshwater system, over a 10 month period, was conducted to evaluate the specific activity hypothesis under applied conditions. This study was designed to provide comparisons of predicted and observed specific activities and to test the equivalence of specific activities between all components of the system. One dose of radioisotopes was added to the system in this study and even after 10 months these radioisotopes were not distributed similarly to the stable isotopes. This suggests that the time necessary to reach a specific activity equilibrium might be a matter of years rather than months. More importantly, in natural systems, where the radioisotope addition is continuous a specific activity equilibrium may never be achieved. These things plus the non-conservative nature of the 134 Cs and 65 Zn predicted concentrations indicates that the use of the specific activity concept for predicting radioisotope concentrations of Cs and Zn in freshwater systems is questionable. A more rigorous approach must be used, considering isotope transfer rates between components and the complexity of the system. Problems with statistical comparisons of derived variables, such as specific activities, are discussed and were considered in interpreting the results of this study

  7. Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

    Science.gov (United States)

    Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

    2017-09-01

    We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  8. Vigorous physical activity predicts higher heart rate variability among younger adults.

    Science.gov (United States)

    May, Richard; McBerty, Victoria; Zaky, Adam; Gianotti, Melino

    2017-06-14

    Baseline heart rate variability (HRV) is linked to prospective cardiovascular health. We tested intensity and duration of weekly physical activity as predictors of heart rate variability in young adults. Time and frequency domain indices of HRV were calculated based on 5-min resting electrocardiograms collected from 82 undergraduate students. Hours per week of both moderate and vigorous activity were estimated using the International Physical Activity Questionnaire. In regression analyses, hours of vigorous physical activity, but not moderate activity, significantly predicted greater time domain and frequency domain indices of heart rate variability. Adjusted for weekly frequency, greater daily duration of vigorous activity failed to predict HRV indices. Future studies should test direct measurements of vigorous activity patterns as predictors of autonomic function in young adulthood.

  9. A Trap Motion in Validating Muscle Activity Prediction from Musculoskeletal Model using EMG

    NARCIS (Netherlands)

    Wibawa, A. D.; Verdonschot, N.; Halbertsma, J.P.K.; Burgerhof, J.G.M.; Diercks, R.L.; Verkerke, G. J.

    2016-01-01

    Musculoskeletal modeling nowadays is becoming the most common tool for studying and analyzing human motion. Besides its potential in predicting muscle activity and muscle force during active motion, musculoskeletal modeling can also calculate many important kinetic data that are difficult to measure

  10. Predictive factors of unfavorable prostate cancer in patients who underwent prostatectomy but eligible for active surveillance

    Directory of Open Access Journals (Sweden)

    Seol Ho Choo

    2014-06-01

    Conclusions: A significant proportion of patients who were candidates for active surveillance had unfavorable prostate cancer. Age, PSA density, and two positive cores were independent significant predictive factors for unfavorable prostate cancer. These factors should be considered when performing active surveillance.

  11. New active drugs against liver stages of Plasmodium predicted by molecular topology.

    NARCIS (Netherlands)

    Mahmoudi, N.; Garcia-Domenech, R.; Galvez, J.; Farhati, K.; Franetich, J.F.; Sauerwein, R.W.; Hannoun, L.; Derouin, F.; Danis, M.; Mazier, D.

    2008-01-01

    We conducted a quantitative structure-activity relationship (QSAR) study based on a database of 127 compounds previously tested against the liver stage of Plasmodium yoelii in order to develop a model capable of predicting the in vitro antimalarial activities of new compounds. Topological indices

  12. Predicting Antitumor Activity of Peptides by Consensus of Regression Models Trained on a Small Data Sample

    Directory of Open Access Journals (Sweden)

    Ivanka Jerić

    2011-11-01

    Full Text Available Predicting antitumor activity of compounds using regression models trained on a small number of compounds with measured biological activity is an ill-posed inverse problem. Yet, it occurs very often within the academic community. To counteract, up to some extent, overfitting problems caused by a small training data, we propose to use consensus of six regression models for prediction of biological activity of virtual library of compounds. The QSAR descriptors of 22 compounds related to the opioid growth factor (OGF, Tyr-Gly-Gly-Phe-Met with known antitumor activity were used to train regression models: the feed-forward artificial neural network, the k-nearest neighbor, sparseness constrained linear regression, the linear and nonlinear (with polynomial and Gaussian kernel support vector machine. Regression models were applied on a virtual library of 429 compounds that resulted in six lists with candidate compounds ranked by predicted antitumor activity. The highly ranked candidate compounds were synthesized, characterized and tested for an antiproliferative activity. Some of prepared peptides showed more pronounced activity compared with the native OGF; however, they were less active than highly ranked compounds selected previously by the radial basis function support vector machine (RBF SVM regression model. The ill-posedness of the related inverse problem causes unstable behavior of trained regression models on test data. These results point to high complexity of prediction based on the regression models trained on a small data sample.

  13. M-ficolin levels reflect disease activity and predict remission in early rheumatoid arthritis

    DEFF Research Database (Denmark)

    Ammitzbøll, Christian Gytz; Thiel, Steffen; Jensenius, Jens Christian

    2013-01-01

    To assess plasma M-ficolin concentrations in disease-modifying antirheumatic drug (DMARD)-naive patients with early rheumatoid arthritis (RA), to investigate the correlation of M-ficolin concentrations with disease activity markers, and to determine the predictive value of M-ficolin with respect...... to the Disease Activity Score in 28 joints (DAS28)....

  14. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

    Science.gov (United States)

    In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

  15. High serum ACE activity predicts severe hypoglycaemia over time in patients with type 1 diabetes

    DEFF Research Database (Denmark)

    Færch, Louise; Pedersen-Bjergaard, Ulrik; Thorsteinsson, Birger

    2011-01-01

    High serum angiotensin-converting enzyme (ACE) activity is associated with increased risk of severe hypoglycaemia (SH) within 1 year in type 1 diabetes. We wanted to find out whether ACE activity is stable over time and predicts SH beyond 1 year, and if gender differences exist in the association...

  16. Design and implementation of predictive filtering system for current reference generation of active power filter

    Energy Technology Data Exchange (ETDEWEB)

    Kilic, Tomislav; Milun, Stanko; Petrovic, Goran [FESB University of Split, Faculty of Electrical Engineering, Machine Engineering and Naval Architecture, R. Boskovica bb, 21000, Split (Croatia)

    2007-02-15

    The shunt active power filters are used to attenuate the harmonic currents in power systems by injecting equal but opposite compensating currents. Successful control of the active filters requires an accurate current reference. In this paper the current reference determination based on predictive filtering structure is presented. Current reference was obtained by taking the difference of load current and its fundamental harmonic. For fundamental harmonic determination with no time delay a combination of digital predictive filter and low pass filter is used. The proposed method was implemented on a laboratory prototype of a three-phase active power filter. The algorithm for current reference determination was adapted and implemented on DSP controller. Simulation and experimental results show that the active power filter with implemented predictive filtering structure gives satisfactory performance in power system harmonic attenuation. (author)

  17. Activity Prediction of Schiff Base Compounds using Improved QSAR Models of Cinnamaldehyde Analogues and Derivatives

    Directory of Open Access Journals (Sweden)

    Hui Wang

    2015-10-01

    Full Text Available In past work, QSAR (quantitative structure-activity relationship models of cinnamaldehyde analogues and derivatives (CADs have been used to predict the activities of new chemicals based on their mass concentrations, but these approaches are not without shortcomings. Therefore, molar concentrations were used instead of mass concentrations to determine antifungal activity. New QSAR models of CADs against Aspergillus niger and Penicillium citrinum were established, and the molecular design of new CADs was performed. The antifungal properties of the designed CADs were tested, and the experimental Log AR values were in agreement with the predicted Log AR values. The results indicate that the improved QSAR models are more reliable and can be effectively used for CADs molecular design and prediction of the activity of CADs. These findings provide new insight into the development and utilization of cinnamaldehyde compounds.

  18. Fluoride-induced IL-8 release in human epithelial lung cells: Relationship to EGF-receptor-, SRC- and MAP-kinase activation

    International Nuclear Information System (INIS)

    Refsnes, Magne; Skuland, Tonje; Schwarze, Per E.; Ovrevik, Johan; Lag, Marit

    2008-01-01

    Exposure of human epithelial lung cells to fluorides is known to induce a marked increase in the release of interleukin (IL)-8, a chemokine involved in neutrophil recruitment. In the present study, the involvement of mitogen-activating protein kinases (MAPKs), the role of upstream activation of Src family kinases (SFKs), epidermal growth factor receptor (EGFR) activation and the interrelationships between these pathways in fluoride-induced IL-8 were examined in a human epithelial lung cell line (A549). Sodium fluoride strongly activated MAPK, in particular JNK1/2 and p38. The ERK1/2-inhibitor PD98059, the p38-inhibitor SB202190 and the JNK1/2-inhibitor SP600125 partially inhibited the fluoride-induced IL-8 response. Combinations of these inhibitors reduced the responses nearly to basal levels. Treatment with siRNA against JNK2 also reduced the IL-8 response to fluoride. Furthermore, fluoride activated SFKs, which was abolished by the SFK-inhibitor PP2. PP2 substantially inhibited the increased levels of IL-8, and partially reduced the fluoride-induced activation of ERK1/2, p38 and JNK1/2. Fluoride exposure also led to a phosphorylation of the EGFR, that was partially inhibited by PP2. AG1478, an EGFR-inhibitor, partially reduced the fluoride-induced IL-8 response and the phosphorylation of JNK1/2 and ERK1/2, but less the phosphorylation of p38. The effects of AG1478 were less than that of PP2. In conclusion, our findings suggest that the fluoride-induced IL-8 release involves the combined activation of ERK1/2, JNK1/2 and p38, and that the phosphorylation of these kinases, and in particular JNK1/2 and ERK1/2, partly, is mediated via a SFK-dependent EGFR-linked pathway. SFK-dependent, but EGFR-independent mechanisms seem important, and especially for phosphorylation of p38

  19. Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis.

    Science.gov (United States)

    Cheval, Boris; Sarrazin, Philippe; Pelletier, Luc

    2014-01-01

    Understanding the determinants of non-exercise activity thermogenesis (NEAT) is crucial, given its extensive health benefits. Some scholars have assumed that a proneness to react differently to environmental cues promoting sedentary versus active behaviors could be responsible for inter-individual differences in NEAT. In line with this reflection and grounded on the Reflective-Impulsive Model, we test the assumption that impulsive processes related to sedentary and physical activity behaviors can prospectively predict NEAT, operationalized as spontaneous effort exerted to maintain low intensity muscle contractions within the release phases of an intermittent maximal isometric contraction task. Participants (n = 91) completed a questionnaire assessing their intentions to adopt physical activity behaviors and a manikin task to assess impulsive approach tendencies towards physical activity behaviors (IAPA) and sedentary behaviors (IASB). Participants were then instructed to perform a maximal handgrip strength task and an intermittent maximal isometric contraction task. As hypothesized, multilevel regression analyses revealed that spontaneous effort was (a) positively predicted by IAPA, (b) negatively predicted by IASB, and (c) was not predicted by physical activity intentions, after controlling for some confounding variables such as age, sex, usual PA level and average force provided during the maximal-contraction phases of the task. These effects remained constant throughout all the phases of the task. This study demonstrated that impulsive processes may play a unique role in predicting spontaneous physical activity behaviors. Theoretically, this finding reinforces the utility of a motivational approach based on dual-process models to explain inter-individual differences in NEAT. Implications for health behavior theories and behavior change interventions are outlined.

  20. Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis.

    Directory of Open Access Journals (Sweden)

    Boris Cheval

    Full Text Available Understanding the determinants of non-exercise activity thermogenesis (NEAT is crucial, given its extensive health benefits. Some scholars have assumed that a proneness to react differently to environmental cues promoting sedentary versus active behaviors could be responsible for inter-individual differences in NEAT. In line with this reflection and grounded on the Reflective-Impulsive Model, we test the assumption that impulsive processes related to sedentary and physical activity behaviors can prospectively predict NEAT, operationalized as spontaneous effort exerted to maintain low intensity muscle contractions within the release phases of an intermittent maximal isometric contraction task. Participants (n = 91 completed a questionnaire assessing their intentions to adopt physical activity behaviors and a manikin task to assess impulsive approach tendencies towards physical activity behaviors (IAPA and sedentary behaviors (IASB. Participants were then instructed to perform a maximal handgrip strength task and an intermittent maximal isometric contraction task. As hypothesized, multilevel regression analyses revealed that spontaneous effort was (a positively predicted by IAPA, (b negatively predicted by IASB, and (c was not predicted by physical activity intentions, after controlling for some confounding variables such as age, sex, usual PA level and average force provided during the maximal-contraction phases of the task. These effects remained constant throughout all the phases of the task. This study demonstrated that impulsive processes may play a unique role in predicting spontaneous physical activity behaviors. Theoretically, this finding reinforces the utility of a motivational approach based on dual-process models to explain inter-individual differences in NEAT. Implications for health behavior theories and behavior change interventions are outlined.

  1. Application of Artificial Intelligence to the Prediction of the Antimicrobial Activity of Essential Oils.

    Science.gov (United States)

    Daynac, Mathieu; Cortes-Cabrera, Alvaro; Prieto, Jose M

    2015-01-01

    Essential oils (EOs) are vastly used as natural antibiotics in Complementary and Alternative Medicine (CAM). Their intrinsic chemical variability and synergisms/antagonisms between its components make difficult to ensure consistent effects through different batches. Our aim is to evaluate the use of artificial neural networks (ANNs) for the prediction of their antimicrobial activity. Methods. The chemical composition and antimicrobial activity of 49 EOs, extracts, and/or fractions was extracted from NCCLS compliant works. The fast artificial neural networks (FANN) software was used and the output data reflected the antimicrobial activity of these EOs against four common pathogens: Staphylococcus aureus, Escherichia coli, Candida albicans, and Clostridium perfringens as measured by standardised disk diffusion assays. Results. ANNs were able to predict >70% of the antimicrobial activities within a 10 mm maximum error range. Similarly, ANNs were able to predict 2 or 3 different bioactivities at the same time. The accuracy of the prediction was only limited by the inherent errors of the popular antimicrobial disk susceptibility test and the nature of the pathogens. Conclusions. ANNs can be reliable, fast, and cheap tools for the prediction of the antimicrobial activity of EOs thus improving their use in CAM.

  2. Model predictive control for a dual active bridge inverter with a floating bridge

    OpenAIRE

    Chowdhury, Shajjad; Wheeler, Patrick W.; Gerada, C.; Patel, Chintan

    2016-01-01

    This paper presents a Model Predictive Control technique applied to a dual active bridge inverter where one of the bridges is floating. The proposed floating bridge topology eliminates the need for isolation transformer in a dual inverter system and therefore reduces the size, weight and losses in the system. To achieve multilevel output voltage waveforms the floating inverter DC link capacitor is charged to the half of the main DC link voltage. A finite-set Model Predictive Control technique...

  3. Autonomous Motivation Predicts 7-Day Physical Activity in Hong Kong Students.

    Science.gov (United States)

    Ha, Amy S; Ng, Johan Y Y

    2015-07-01

    Autonomous motivation predicts positive health behaviors such as physical activity. However, few studies have examined the relation between motivational regulations and objectively measured physical activity and sedentary behaviors. Thus, we investigated whether different motivational regulations (autonomous motivation, controlled motivation, and amotivation) predicted 7-day physical activity, sedentary behaviors, and health-related quality of life (HRQoL) of students. A total of 115 students (mean age = 11.6 years, 55.7% female) self-reported their motivational regulations and health-related quality of life. Physical activity and sedentary behaviors were measured using accelerometers for seven days. Using multilevel modeling, we found that autonomous motivation predicted higher levels of moderate-to-vigorous physical activity, less sedentary behaviors, and better HRQoL. Controlled motivation and amotivation each only negatively predicted one facet of HRQoL. Results suggested that autonomous motivation could be an important predictor of physical activity behaviors in Hong Kong students. Promotion of this form of motivational regulation may also increase HRQoL. © 2015 The International Association of Applied Psychology.

  4. NESmapper: accurate prediction of leucine-rich nuclear export signals using activity-based profiles.

    Directory of Open Access Journals (Sweden)

    Shunichi Kosugi

    2014-09-01

    Full Text Available The nuclear export of proteins is regulated largely through the exportin/CRM1 pathway, which involves the specific recognition of leucine-rich nuclear export signals (NESs in the cargo proteins, and modulates nuclear-cytoplasmic protein shuttling by antagonizing the nuclear import activity mediated by importins and the nuclear import signal (NLS. Although the prediction of NESs can help to define proteins that undergo regulated nuclear export, current methods of predicting NESs, including computational tools and consensus-sequence-based searches, have limited accuracy, especially in terms of their specificity. We found that each residue within an NES largely contributes independently and additively to the entire nuclear export activity. We created activity-based profiles of all classes of NESs with a comprehensive mutational analysis in mammalian cells. The profiles highlight a number of specific activity-affecting residues not only at the conserved hydrophobic positions but also in the linker and flanking regions. We then developed a computational tool, NESmapper, to predict NESs by using profiles that had been further optimized by training and combining the amino acid properties of the NES-flanking regions. This tool successfully reduced the considerable number of false positives, and the overall prediction accuracy was higher than that of other methods, including NESsential and Wregex. This profile-based prediction strategy is a reliable way to identify functional protein motifs. NESmapper is available at http://sourceforge.net/projects/nesmapper.

  5. PASS assisted prediction and pharmacological evaluation of novel nicotinic analogs for nootropic activity in mice.

    Science.gov (United States)

    Khurana, Navneet; Ishar, Mohan Pal Singh; Gajbhiye, Asmita; Goel, Rajesh Kumar

    2011-07-15

    The aim of present study is to predict the probable nootropic activity of novel nicotine analogues with the help of computer program, PASS (prediction of activity spectra for substances) and evaluate the same. Two compounds from differently substituted pyridines were selected for synthesis and evaluation of nootropic activity based on their high probable activity (Pa) value predicted by PASS computer program. Evaluation of nootropic activity of compounds after acute and chronic treatment was done with transfer latency (TL) and step down latency (SDL) methods which showed significant nootropic activity. The effect on scopolamine induced amnesia was also observed along with their acetylcholine esterase inhibitory activity which also showed positive results which strengthened their efficacy as nootropic agents through involvement of cholinergic system. This nootropic effect was similar to the effect of nicotine and donepezil used as standard drugs. Muscle coordination and locomotor activity along with their addiction liability, safety and tolerability studies were also evaluated. These studies showed that these compounds are well tolerable and safe over a wide range of doses tested along with the absence of withdrawal effect which is present in nicotine due to its addiction liability. The study showed that these compounds are true nicotine analogs with desirable efficacy and safety profile for their use as effective nootropic agents. Copyright © 2011 Elsevier B.V. All rights reserved.

  6. Motor Skill Competence and Perceived Motor Competence: Which Best Predicts Physical Activity among Girls?

    Science.gov (United States)

    Khodaverdi, Zeinab; Bahram, Abbas; Khalaji, Hassan; Kazemnejad, Anoshirvan

    2013-10-01

    The main purpose of this study was to determine which correlate, perceived motor competence or motor skill competence, best predicts girls' physical activity behavior. A sample of 352 girls (mean age=8.7, SD=0.3 yr) participated in this study. To assess motor skill competence and perceived motor competence, each child completed the Test of Gross Motor Development-2 and Physical Ability sub-scale of Marsh's Self-Description Questionnaire. Children's physical activity was assessed by the Physical Activity Questionnaire for Older Children. Multiple linear regression model was used to determine whether perceived motor competence or motor skill competence best predicts moderate-to-vigorous self-report physical activity. Multiple regression analysis indicated that motor skill competence and perceived motor competence predicted 21% variance in physical activity (R(2)=0.21, F=48.9, P=0.001), and motor skill competence (R(2)=0.15, ᵝ=0.33, P= 0.001) resulted in more variance than perceived motor competence (R(2)=0.06, ᵝ=0.25, P=0.001) in physical activity. Results revealed motor skill competence had more influence in comparison with perceived motor competence on physical activity level. We suggest interventional programs based on motor skill competence and perceived motor competence should be administered or implemented to promote physical activity in young girls.

  7. Prediction of objectively measured physical activity and sedentariness among blue-collar workers using survey questionnaires

    DEFF Research Database (Denmark)

    Gupta, Nidhi; Heiden, Marina; Mathiassen, Svend Erik

    2016-01-01

    responded to a questionnaire containing information about personal and work related variables, available in most large epidemiological studies and surveys. Workers also wore accelerometers for 1-4 days measuring time spent sedentary and in physical activity, defined as non-sedentary time. Least......-squares linear regression models were developed, predicting objectively measured exposures from selected predictors in the questionnaire. RESULTS: A full prediction model based on age, gender, body mass index, job group, self-reported occupational physical activity (OPA), and self-reported occupational sedentary...

  8. Prediction signatures in the brain: Semantic pre-activation during language comprehension

    Directory of Open Access Journals (Sweden)

    Burkhard Maess

    2016-11-01

    Full Text Available There is broad agreement that context-based predictions facilitate lexical-semantic processing. A robust index of semantic prediction during language comprehension is an evoked response, known as the N400, whose amplitude is modulated as a function of semantic context. However, the underlying neural mechanisms that utilize relations of the prior context and the embedded word within it are largely unknown. We measured magnetoencephalography (MEG data while participants were listening to simple German sentences in which the verbs were either highly predictive for the occurrence of a particular noun (i.e., provided context or not. The identical set of nouns was presented in both conditions. Hence, differences for the evoked responses of the nouns can only be due to differences in the earlier context. We observed a reduction of the N400 response for highly predicted nouns. Interestingly, the opposite pattern was observed for the preceding verbs: Highly predictive (that is more informative verbs yielded stronger neural magnitude compared to less predictive verbs. A negative correlation between the N400 effect of the verb and that of the noun was found in a distributed brain network, indicating an integral relation between the predictive power of the verb and the processing of the subsequent noun. This network consisted of left hemispheric superior and middle temporal areas and a subcortical area; the parahippocampus. Enhanced activity for highly predictive relative to less predictive verbs, likely reflects establishing semantic features associated with the expected nouns, that is a pre-activation of the expected nouns.

  9. Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.

    Science.gov (United States)

    Du, Juan; Yang, Fang; Zhang, Zhiqiang; Hu, Jingze; Xu, Qiang; Hu, Jianping; Zeng, Fanyong; Lu, Guangming; Liu, Xinfeng

    2018-05-15

    An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.

  10. A time series based sequence prediction algorithm to detect activities of daily living in smart home.

    Science.gov (United States)

    Marufuzzaman, M; Reaz, M B I; Ali, M A M; Rahman, L F

    2015-01-01

    The goal of smart homes is to create an intelligent environment adapting the inhabitants need and assisting the person who needs special care and safety in their daily life. This can be reached by collecting the ADL (activities of daily living) data and further analysis within existing computing elements. In this research, a very recent algorithm named sequence prediction via enhanced episode discovery (SPEED) is modified and in order to improve accuracy time component is included. The modified SPEED or M-SPEED is a sequence prediction algorithm, which modified the previous SPEED algorithm by using time duration of appliance's ON-OFF states to decide the next state. M-SPEED discovered periodic episodes of inhabitant behavior, trained it with learned episodes, and made decisions based on the obtained knowledge. The results showed that M-SPEED achieves 96.8% prediction accuracy, which is better than other time prediction algorithms like PUBS, ALZ with temporal rules and the previous SPEED. Since human behavior shows natural temporal patterns, duration times can be used to predict future events more accurately. This inhabitant activity prediction system will certainly improve the smart homes by ensuring safety and better care for elderly and handicapped people.

  11. Music-induced emotions can be predicted from a combination of brain activity and acoustic features.

    Science.gov (United States)

    Daly, Ian; Williams, Duncan; Hallowell, James; Hwang, Faustina; Kirke, Alexis; Malik, Asad; Weaver, James; Miranda, Eduardo; Nasuto, Slawomir J

    2015-12-01

    It is widely acknowledged that music can communicate and induce a wide range of emotions in the listener. However, music is a highly-complex audio signal composed of a wide range of complex time- and frequency-varying components. Additionally, music-induced emotions are known to differ greatly between listeners. Therefore, it is not immediately clear what emotions will be induced in a given individual by a piece of music. We attempt to predict the music-induced emotional response in a listener by measuring the activity in the listeners electroencephalogram (EEG). We combine these measures with acoustic descriptors of the music, an approach that allows us to consider music as a complex set of time-varying acoustic features, independently of any specific music theory. Regression models are found which allow us to predict the music-induced emotions of our participants with a correlation between the actual and predicted responses of up to r=0.234,pmusic induced emotions can be predicted by their neural activity and the properties of the music. Given the large amount of noise, non-stationarity, and non-linearity in both EEG and music, this is an encouraging result. Additionally, the combination of measures of brain activity and acoustic features describing the music played to our participants allows us to predict music-induced emotions with significantly higher accuracies than either feature type alone (p<0.01). Copyright © 2015 Elsevier Inc. All rights reserved.

  12. A balance of activity in brain control and reward systems predicts self-regulatory outcomes

    OpenAIRE

    Lopez, Richard B.; Chen, Pin-Hao A.; Huckins, Jeremy F.; Hofmann, Wilhelm; Kelley, William M.; Heatherton, Todd F.

    2017-01-01

    Abstract Previous neuroimaging work has shown that increased reward-related activity following exposure to food cues is predictive of self-control failure. The balance model suggests that self-regulation failures result from an imbalance in reward and executive control mechanisms. However, an open question is whether the relative balance of activity in brain systems associated with executive control (vs reward) supports self-regulatory outcomes when people encounter tempting cues in daily lif...

  13. Structural maturation and brain activity predict future working memory capacity during childhood development.

    Science.gov (United States)

    Ullman, Henrik; Almeida, Rita; Klingberg, Torkel

    2014-01-29

    Human working memory capacity develops during childhood and is a strong predictor of future academic performance, in particular, achievements in mathematics and reading. Predicting working memory development is important for the early identification of children at risk for poor cognitive and academic development. Here we show that structural and functional magnetic resonance imaging data explain variance in children's working memory capacity 2 years later, which was unique variance in addition to that predicted using cognitive tests. While current working memory capacity correlated with frontoparietal cortical activity, the future capacity could be inferred from structure and activity in basal ganglia and thalamus. This gives a novel insight into the neural mechanisms of childhood development and supports the idea that neuroimaging can have a unique role in predicting children's cognitive development.

  14. Predicting active school travel: The role of planned behavior and habit strength

    Science.gov (United States)

    2012-01-01

    Background Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model’s predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children’s active school travel. Method Participants (N = 126 children aged 8–9 years; 59 % males) were sampled from five elementary schools in the west of Scotland and completed questionnaire measures of all TPB constructs in relation to walking to school and both walking and car/bus use habit. Over the subsequent week, commuting steps on school journeys were measured objectively using an accelerometer. Hierarchical multiple regressions were used to test the predictive utility of the TPB and habit strength in relation to both intention and subsequent behavior. Results The TPB accounted for 41 % and 10 % of the variance in intention and objectively measured behavior, respectively. Together, walking habit and car/bus habit significantly increased the proportion of explained variance in both intention and behavior by 6 %. Perceived behavioral control and both walking and car/bus habit independently predicted intention. Intention and car/bus habit independently predicted behavior. Conclusions The TPB significantly predicts children’s active school travel. However, habit strength augments the predictive validity of the model. The results indicate that school travel is controlled by both intentional and habitual processes. In practice, interventions could usefully decrease the habitual use of motorized transport for travel to school and increase children’s intention to walk (via increases in perceived behavioral control and walking habit, and decreases in car/bus habit). Further research is needed to identify effective strategies for changing these

  15. Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products

    Directory of Open Access Journals (Sweden)

    Huixiao Hong

    2016-09-01

    Full Text Available Sunscreen products are predominantly regulated as over-the-counter (OTC drugs by the US FDA. The “active” ingredients function as ultraviolet filters. Once a sunscreen product is generally recognized as safe and effective (GRASE via an OTC drug review process, new formulations using these ingredients do not require FDA review and approval, however, the majority of ingredients have never been tested to uncover any potential endocrine activity and their ability to interact with the estrogen receptor (ER is unknown, despite the fact that this is a very extensively studied target related to endocrine activity. Consequently, we have developed an in silico model to prioritize single ingredient estrogen receptor activity for use when actual animal data are inadequate, equivocal, or absent. It relies on consensus modeling to qualitatively and quantitatively predict ER binding activity. As proof of concept, the model was applied to ingredients commonly used in sunscreen products worldwide and a few reference chemicals. Of the 32 chemicals with unknown ER binding activity that were evaluated, seven were predicted to be active estrogenic compounds. Five of the seven were confirmed by the published data. Further experimental data is needed to confirm the other two predictions.

  16. Predicting Social Responsibility and Belonging in Urban After-School Physical Activity Programs with Underserved Children

    Science.gov (United States)

    Martin, Jeffrey J.; Byrd, Brigid; Garn, Alex; McCaughtry, Nate; Kulik, Noel; Centeio, Erin

    2016-01-01

    The purpose of this cross sectional study was to predict feelings of belonging and social responsibility based on the motivational climate perceptions and contingent self-worth of children participating in urban after-school physical activity programs. Three-hundred and four elementary school students from a major Midwestern city participated.…

  17. Predictive Duty Cycle Control of Three-Phase Active-Front-End Rectifiers

    DEFF Research Database (Denmark)

    Song, Zhanfeng; Tian, Yanjun; Chen, Wei

    2016-01-01

    This paper proposed an on-line optimizing duty cycle control approach for three-phase active-front-end rectifiers, aiming to obtain the optimal control actions under different operating conditions. Similar to finite control set model predictive control strategy, a cost function previously...

  18. QSAR classification models for the prediction of endocrine disrupting activity of brominated flame retardants.

    Science.gov (United States)

    Kovarich, Simona; Papa, Ester; Gramatica, Paola

    2011-06-15

    The identification of potential endocrine disrupting (ED) chemicals is an important task for the scientific community due to their diffusion in the environment; the production and use of such compounds will be strictly regulated through the authorization process of the REACH regulation. To overcome the problem of insufficient experimental data, the quantitative structure-activity relationship (QSAR) approach is applied to predict the ED activity of new chemicals. In the present study QSAR classification models are developed, according to the OECD principles, to predict the ED potency for a class of emerging ubiquitary pollutants, viz. brominated flame retardants (BFRs). Different endpoints related to ED activity (i.e. aryl hydrocarbon receptor agonism and antagonism, estrogen receptor agonism and antagonism, androgen and progesterone receptor antagonism, T4-TTR competition, E2SULT inhibition) are modeled using the k-NN classification method. The best models are selected by maximizing the sensitivity and external predictive ability. We propose simple QSARs (based on few descriptors) characterized by internal stability, good predictive power and with a verified applicability domain. These models are simple tools that are applicable to screen BFRs in relation to their ED activity, and also to design safer alternatives, in agreement with the requirements of REACH regulation at the authorization step. Copyright © 2011 Elsevier B.V. All rights reserved.

  19. Extracurricular Activity and Parental Involvement Predict Positive Outcomes in Elementary School Children

    Science.gov (United States)

    Lagace-Seguin, Daniel G.; Case, Emily

    2010-01-01

    The main goal of this study was to explore if parental involvement and extracurricular activity participation could predict well-being and academic competence in elementary school children. Seventy-two children (mean age = 10.9 years, SD = 0.85) and their parents participated. Results revealed that parental pressure and support, when paired with…

  20. Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities

    Science.gov (United States)

    Schemm, J. E.; Long, L.; Baxter, S.

    2013-12-01

    Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities Jae-Kyung E. Schemm, Lindsey Long and Stephen Baxter Climate Prediction Center, NCEP/NWS/NOAA Predictability of intraseasonal tropical storm (TS) activities is assessed using the 1999-2010 CFSv2 hindcast suite. Weekly TS activities in the CFSv2 45-day forecasts were determined using the TS detection and tracking method devised by Carmago and Zebiak (2002). The forecast periods are divided into weekly intervals for Week 1 through Week 6, and also the 30-day mean. The TS activities in those intervals are compared to the observed activities based on the NHC HURDAT and JTWC Best Track datasets. The CFSv2 45-day hindcast suite is made of forecast runs initialized at 00, 06, 12 and 18Z every day during the 1999 - 2010 period. For predictability evaluation, forecast TS activities are analyzed based on 20-member ensemble forecasts comprised of 45-day runs made during the most recent 5 days prior to the verification period. The forecast TS activities are evaluated in terms of the number of storms, genesis locations and storm tracks during the weekly periods. The CFSv2 forecasts are shown to have a fair level of skill in predicting the number of storms over the Atlantic Basin with the temporal correlation scores ranging from 0.73 for Week 1 forecasts to 0.63 for Week 6, and the average RMS errors ranging from 0.86 to 1.07 during the 1999-2010 hurricane season. Also, the forecast track density distribution and false alarm statistics are compiled using the hindcast analyses. In real-time applications of the intraseasonal TS activity forecasts, the climatological TS forecast statistics will be used to make the model bias corrections in terms of the storm counts, track distribution and removal of false alarms. An operational implementation of the weekly TS activity prediction is planned for early 2014 to provide an objective input for the CPC's Global Tropical Hazards

  1. Neural activity to a partner's facial expression predicts self-regulation after conflict

    Science.gov (United States)

    Hooker, Christine I.; Gyurak, Anett; Verosky, Sara; Miyakawa, Asako; Ayduk, Özlem

    2009-01-01

    Introduction Failure to self-regulate after an interpersonal conflict can result in persistent negative mood and maladaptive behaviors. Research indicates that lateral prefrontal cortex (LPFC) activity is related to the regulation of emotional experience in response to lab-based affective challenges, such as viewing emotional pictures. This suggests that compromised LPFC function may be a risk-factor for mood and behavior problems after an interpersonal stressor. However, it remains unclear whether LPFC activity to a lab-based affective challenge predicts self-regulation in real-life. Method We investigated whether LPFC activity to a lab-based affective challenge (negative facial expressions of a partner) predicts self-regulation after a real-life affective challenge (interpersonal conflict). During an fMRI scan, healthy, adult participants in committed, dating relationships (N = 27) viewed positive, negative, and neutral facial expressions of their partners. In an online daily-diary, participants reported conflict occurrence, level of negative mood, rumination, and substance-use. Results LPFC activity in response to the lab-based affective challenge predicted self-regulation after an interpersonal conflict in daily life. When there was no interpersonal conflict, LPFC activity was not related to the change in mood or behavior the next day. However, when an interpersonal conflict did occur, ventral LPFC (VLPFC) activity predicted the change in mood and behavior the next day, such that lower VLPFC activity was related to higher levels of negative mood, rumination, and substance-use. Conclusions Low LPFC function may be a vulnerability and high LPFC function may be a protective factor for the development of mood and behavior problems after an interpersonal stressor. PMID:20004365

  2. Neural activity to a partner's facial expression predicts self-regulation after conflict.

    Science.gov (United States)

    Hooker, Christine I; Gyurak, Anett; Verosky, Sara C; Miyakawa, Asako; Ayduk, Ozlem

    2010-03-01

    Failure to self-regulate after an interpersonal conflict can result in persistent negative mood and maladaptive behaviors. Research indicates that lateral prefrontal cortex (LPFC) activity is related to emotion regulation in response to laboratory-based affective challenges, such as viewing emotional pictures. This suggests that compromised LPFC function may be a risk factor for mood and behavior problems after an interpersonal conflict. However, it remains unclear whether LPFC activity to a laboratory-based affective challenge predicts self-regulation in real life. We investigated whether LPFC activity to a laboratory-based affective challenge (negative facial expressions of a partner) predicts self-regulation after a real-life affective challenge (interpersonal conflict). During a functional magnetic resonance imaging scan, healthy, adult participants in committed relationships (n = 27) viewed positive, negative, and neutral facial expressions of their partners. In a three-week online daily diary, participants reported conflict occurrence, level of negative mood, rumination, and substance use. LPFC activity in response to the laboratory-based affective challenge predicted self-regulation after an interpersonal conflict in daily life. When there was no interpersonal conflict, LPFC activity was not related to mood or behavior the next day. However, when an interpersonal conflict did occur, ventral LPFC (VLPFC) activity predicted mood and behavior the next day, such that lower VLPFC activity was related to higher levels of negative mood, rumination, and substance use. Low LPFC function may be a vulnerability and high LPFC function may be a protective factor for the development of mood and behavior problems after an interpersonal stressor. Copyright 2010 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  3. Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

    Science.gov (United States)

    Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

    2017-08-03

    Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

  4. Factors Predicting the Physical Activity Behavior of Female Adolescents: A Test of the Health Promotion Model

    Directory of Open Access Journals (Sweden)

    Hashem Mohamadian

    2014-01-01

    Full Text Available ObjectivesPhysical activity behavior begins to decline during adolescence and continues to decrease throughout young adulthood. This study aims to explain factors that influence physical activity behavior in a sample of female adolescents using a health promotion model framework.MethodsThis cross-sectional survey was used to explore physical activity behavior among a sample of female adolescents. Participants completed measures of physical activity, perceived self-efficacy, self-esteem, social support, perceived barriers, and perceived affect. Interactions among the variables were examined using path analysis within a covariance modeling framework.ResultsThe final model accounted for an R2 value of 0.52 for physical activity and offered a good model-data fit. The results indicated that physical activity was predicted by self-esteem (β=0.46, p<0.001, perceived self-efficacy (β=0.40, p<0.001, social support (β=0.24, p<0.001, perceived barriers (β=-0.19, p<0.001, and perceived affect (β=0.17, p<0.001.ConclusionsThe findings of this study showed that the health promotion model was useful to predict physical activity behavior among the Iranian female adolescents. Information related to the predictors of physical activity behavior will help researchers plan more tailored culturally relevant health promotion interventions for this population.

  5. Using quantitative structure-activity relationships (QSAR) to predict toxic endpoints for polycyclic aromatic hydrocarbons (PAH).

    Science.gov (United States)

    Bruce, Erica D; Autenrieth, Robin L; Burghardt, Robert C; Donnelly, K C; McDonald, Thomas J

    2008-01-01

    Quantitative structure-activity relationships (QSAR) offer a reliable, cost-effective alternative to the time, money, and animal lives necessary to determine chemical toxicity by traditional methods. Additionally, humans are exposed to tens of thousands of chemicals in their lifetimes, necessitating the determination of chemical toxicity and screening for those posing the greatest risk to human health. This study developed models to predict toxic endpoints for three bioassays specific to several stages of carcinogenesis. The ethoxyresorufin O-deethylase assay (EROD), the Salmonella/microsome assay, and a gap junction intercellular communication (GJIC) assay were chosen for their ability to measure toxic endpoints specific to activation-, induction-, and promotion-related effects of polycyclic aromatic hydrocarbons (PAH). Shape-electronic, spatial, information content, and topological descriptors proved to be important descriptors in predicting the toxicity of PAH in these bioassays. Bioassay-based toxic equivalency factors (TEF(B)) were developed for several PAH using the quantitative structure-toxicity relationships (QSTR) developed. Predicting toxicity for a specific PAH compound, such as a bioassay-based potential potency (PP(B)) or a TEF(B), is possible by combining the predicted behavior from the QSTR models. These toxicity estimates may then be incorporated into a risk assessment for compounds that lack toxicity data. Accurate toxicity predictions are made by examining each type of endpoint important to the process of carcinogenicity, and a clearer understanding between composition and toxicity can be obtained.

  6. PASS-Predicted Hepatoprotective Activity of Caesalpinia sappan in Thioacetamide-Induced Liver Fibrosis in Rats

    Directory of Open Access Journals (Sweden)

    Farkaad A. Kadir

    2014-01-01

    Full Text Available The antifibrotic effects of traditional medicinal herb Caesalpinia sappan (CS extract on liver fibrosis induced by thioacetamide (TAA and the expression of transforming growth factor β1 (TGF-β1, α-smooth muscle actin (αSMA, and proliferating cell nuclear antigen (PCNA in rats were studied. A computer-aided prediction of antioxidant and hepatoprotective activities was primarily performed with the Prediction Activity Spectra of the Substance (PASS Program. Liver fibrosis was induced in male Sprague Dawley rats by TAA administration (0.03% w/v in drinking water for a period of 12 weeks. Rats were divided into seven groups: control, TAA, Silymarin (SY, and CS 300 mg/kg body weight and 100 mg/kg groups. The effect of CS on liver fibrogenesis was determined by Masson’s trichrome staining, immunohistochemical analysis, and western blotting. In vivo determination of hepatic antioxidant activities, cytochrome P450 2E1 (CYP2E1, and matrix metalloproteinases (MPPS was employed. CS treatment had significantly increased hepatic antioxidant enzymes activity in the TAA-treated rats. Liver fibrosis was greatly alleviated in rats when treated with CS extract. CS treatment was noted to normalize the expression of TGF-β1, αSMA, PCNA, MMPs, and TIMP1 proteins. PASS-predicted plant activity could efficiently guide in selecting a promising pharmaceutical lead with high accuracy and required antioxidant and hepatoprotective properties.

  7. Parietal operculum and motor cortex activities predict motor recovery in moderate to severe stroke

    Directory of Open Access Journals (Sweden)

    Firdaus Fabrice Hannanu

    2017-01-01

    In subacute stroke, fMRI brain activity related to passive movement measured in a sensorimotor network defined by activity during voluntary movement predicted motor recovery better than baseline motor-FMS alone. Furthermore, fMRI sensorimotor network activity measures considered alone allowed excellent clinical recovery prediction and may provide reliable biomarkers for assessing new therapies in clinical trial contexts. Our findings suggest that neural reorganization related to motor recovery from moderate to severe stroke results from balanced changes in ipsilesional MI (BA4a and a set of phylogenetically more archaic sensorimotor regions in the ventral sensorimotor trend, in which OP1 and OP4 processes may complement the ipsilesional dorsal motor cortex in achieving compensatory sensorimotor recovery.

  8. Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors

    Directory of Open Access Journals (Sweden)

    Avval Zhila Mohajeri

    2015-01-01

    Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.

  9. Sound induced activity in voice sensitive cortex predicts voice memory ability

    Directory of Open Access Journals (Sweden)

    Rebecca eWatson

    2012-04-01

    Full Text Available The ‘temporal voice areas’ (TVAs (Belin et al., 2000 of the human brain show greater neuronal activity in response to human voices than to other categories of nonvocal sounds. However, a direct link between TVA activity and voice perceptionbehaviour has not yet been established. Here we show that a functional magnetic resonance imaging (fMRI measure of activity in the TVAs predicts individual performance at a separately administered voice memory test. This relation holds whengeneral sound memory ability is taken into account. These findings provide the first evidence that the TVAs are specifically involved in voice cognition.

  10. Can the theory of planned behaviour predict the physical activity behaviour of individuals?

    Science.gov (United States)

    Hobbs, Nicola; Dixon, Diane; Johnston, Marie; Howie, Kate

    2013-01-01

    The theory of planned behaviour (TPB) can identify cognitions that predict differences in behaviour between individuals. However, it is not clear whether the TPB can predict the behaviour of an individual person. This study employs a series of n-of-1 studies and time series analyses to examine the ability of the TPB to predict physical activity (PA) behaviours of six individuals. Six n-of-1 studies were conducted, in which TPB cognitions and up to three PA behaviours (walking, gym workout and a personally defined PA) were measured twice daily for six weeks. Walking was measured by pedometer step count, gym attendance by self-report with objective validation of gym entry and the personally defined PA behaviour by self-report. Intra-individual variability in TPB cognitions and PA behaviour was observed in all participants. The TPB showed variable predictive utility within individuals and across behaviours. The TPB predicted at least one PA behaviour for five participants but had no predictive utility for one participant. Thus, n-of-1 designs and time series analyses can be used to test theory in an individual.

  11. Anthropometry and physical activity level in the prediction of metabolic syndrome in children.

    Science.gov (United States)

    Andaki, Alynne Christian Ribeiro; Tinôco, Adelson Luiz Araújo; Mendes, Edmar Lacerda; Andaki Júnior, Roberto; Hills, Andrew P; Amorim, Paulo Roberto S

    2014-10-01

    To evaluate the effectiveness of anthropometric measures and physical activity level in the prediction of metabolic syndrome (MetS) in children. Cross-sectional study with children from public and private schools. Children underwent an anthropometric assessment, blood pressure measurement and biochemical evaluation of serum for determination of TAG, HDL-cholesterol and glucose. Physical activity level was calculated and number of steps per day obtained using a pedometer for seven consecutive days. Viçosa, south-eastern Brazil. Boys and girls (n 187), mean age 9·90 (SD 0·7) years. Conicity index, sum of four skinfolds, physical activity level and number of steps per day were accurate in predicting MetS in boys. Anthropometric indicators were accurate in predicting MetS for girls, specifically BMI, waist circumference measured at the narrowest point and at the level of the umbilicus, four skinfold thickness measures evaluated separately, the sum of subscapular and triceps skinfold thickness, the sum of four skinfolds and body fat percentage. The sum of four skinfolds was the most accurate method in predicting MetS in both genders.

  12. The ICAP Active Learning Framework Predicts the Learning Gains Observed in Intensely Active Classroom Experiences

    Directory of Open Access Journals (Sweden)

    Benjamin L. Wiggins

    2017-05-01

    Full Text Available STEM classrooms (science, technology, engineering, and mathematics in postsecondary education are rapidly improved by the proper use of active learning techniques. These techniques occupy a descriptive spectrum that transcends passive teaching toward active, constructive, and, finally, interactive methods. While aspects of this framework have been examined, no large-scale or actual classroom-based data exist to inform postsecondary education STEM instructors about possible learning gains. We describe the results of a quasi-experimental study to test the apex of the ICAP framework (interactive, constructive, active, and passive in this ecological classroom environment. Students in interactive classrooms demonstrate significantly improved learning outcomes relative to students in constructive classrooms. This improvement in learning is relatively subtle; similar experimental designs without repeated measures would be unlikely to have the power to observe this significance. We discuss the importance of seemingly small learning gains that might propagate throughout a course or departmental curriculum, as well as improvements with the necessity for faculty to develop and implement similar activities.

  13. Adaptability and Prediction of Anticipatory Muscular Activity Parameters to Different Movements in the Sitting Position.

    Science.gov (United States)

    Chikh, Soufien; Watelain, Eric; Faupin, Arnaud; Pinti, Antonio; Jarraya, Mohamed; Garnier, Cyril

    2016-08-01

    Voluntary movement often causes postural perturbation that requires an anticipatory postural adjustment to minimize perturbation and increase the efficiency and coordination during execution. This systematic review focuses specifically on the relationship between the parameters of anticipatory muscular activities and movement finality in sitting position among adults, to study the adaptability and predictability of anticipatory muscular activities parameters to different movements and conditions in sitting position in adults. A systematic literature search was performed using PubMed, Science Direct, Web of Science, Springer-Link, Engineering Village, and EbscoHost. Inclusion and exclusion criteria were applied to retain the most rigorous and specific studies, yielding 76 articles, Seventeen articles were excluded at first reading, and after the application of inclusion and exclusion criteria, 23 were retained. In a sitting position, central nervous system activity precedes movement by diverse anticipatory muscular activities and shows the ability to adapt anticipatory muscular activity parameters to the movement direction, postural stability, or charge weight. In addition, these parameters could be adapted to the speed of execution, as found for the standing position. Parameters of anticipatory muscular activities (duration, order, and amplitude of muscle contractions constituting the anticipatory muscular activity) could be used as a predictive indicator of forthcoming movement. In addition, this systematic review may improve methodology in empirical studies and assistive technology for people with disabilities. © The Author(s) 2016.

  14. Self-reported Physical Activity Predicts Pain Inhibitory and Facilitatory Function

    Science.gov (United States)

    Naugle, Kelly M.; Riley, Joseph L.

    2013-01-01

    Considerable evidence suggests regular physical activity can reduce chronic pain symptoms. Dysfunction of endogenous facilitatory and inhibitory systems has been implicated in multiple chronic pain conditions. However, few studies have investigated the relationship between levels of physical activity and descending pain modulatory function. Purpose This study’s purpose was to determine whether self-reported levels of physical activity in healthy adults predicted 1) pain sensitivity to heat and cold stimuli, 2) pain facilitatory function as tested by temporal summation of pain (TS), and 3) pain inhibitory function as tested by conditioned pain modulation (CPM) and offset analgesia. Methods Forty-eight healthy adults (age range 18–76) completed the International Physical Activity Questionnaire (IPAQ) and the following pain tests: heat pain thresholds (HPT), heat pain suprathresholds, cold pressor pain (CPP), temporal summation of heat pain, conditioned pain modulation, and offset analgesia. The IPAQ measured levels of walking, moderate, vigorous and total physical activity over the past seven days. Hierarchical linear regressions were conducted to determine the relationship between each pain test and self-reported levels of physical activity, while controlling for age, sex and psychological variables. Results Self-reported total and vigorous physical activity predicted TS and CPM (p’s pain and greater CPM. The IPAQ measures did not predict any of the other pain measures. Conclusion Thus, these results suggest that healthy older and younger adults who self-report greater levels of vigorous and total physical activity exhibit enhanced descending pain modulatory function. Improved descending pain modulation may be a mechanism through which exercise reduces or prevents chronic pain symptoms. PMID:23899890

  15. Which nerve conduction parameters can predict spontaneous electromyographic activity in carpal tunnel syndrome?

    Science.gov (United States)

    Chang, Chia-Wei; Lee, Wei-Ju; Liao, Yi-Chu; Chang, Ming-Hong

    2013-11-01

    We investigate electrodiagnostic markers to determine which parameters are the best predictors of spontaneous electromyographic (EMG) activity in carpal tunnel syndrome (CTS). We enrolled 229 patients with clinically proven and nerve conduction study (NCS)-proven CTS, as well as 100 normal control subjects. All subjects were evaluated using electrodiagnostic techniques, including median distal sensory latencies (DSLs), sensory nerve action potentials (SNAPs), distal motor latencies (DMLs), compound muscle action potentials (CMAPs), forearm median nerve conduction velocities (FMCVs) and wrist-palm motor conduction velocities (W-P MCVs). All CTS patients underwent EMG examination of the abductor pollicis brevis (APB) muscle, and the presence or absence of spontaneous EMG activities was recorded. Normal limits were determined by calculating the means ± 2 standard deviations from the control data. Associations between parameters from the NCS and EMG findings were investigated. In patients with clinically diagnosed CTS, abnormal median CMAP amplitudes were the best predictors of spontaneous activity during EMG examination (p95% (positive predictive rate >95%). If the median CMAP amplitude was higher than the normal limit (>4.9 mV), the rate of no spontaneous EMG activity was >94% (negative predictive rate >94%). An abnormal SNAP amplitude was the second best predictor of spontaneous EMG activity (p<0.001; OR 4.13; 95% CI 2.16-7.90), and an abnormal FMCV was the third best predictor (p=0.01; OR 2.10; 95% CI 1.20-3.67). No other nerve conduction parameters had significant power to predict spontaneous activity upon EMG examination. The CMAP amplitudes of the APB are the most powerful predictors of the occurrence of spontaneous EMG activity. Low CMAP amplitudes are strongly associated with spontaneous activity, whereas high CMAP amplitude are less associated with spontaneous activity, implying that needle EMG examination should be recommended for the detection of

  16. From Structure to Activity: Using Centrality Measures to Predict Neuronal Activity.

    Science.gov (United States)

    Fletcher, Jack McKay; Wennekers, Thomas

    2018-03-01

    It is clear that the topological structure of a neural network somehow determines the activity of the neurons within it. In the present work, we ask to what extent it is possible to examine the structural features of a network and learn something about its activity? Specifically, we consider how the centrality (the importance of a node in a network) of a neuron correlates with its firing rate. To investigate, we apply an array of centrality measures, including In-Degree, Closeness, Betweenness, Eigenvector, Katz, PageRank, Hyperlink-Induced Topic Search (HITS) and NeuronRank to Leaky-Integrate and Fire neural networks with different connectivity schemes. We find that Katz centrality is the best predictor of firing rate given the network structure, with almost perfect correlation in all cases studied, which include purely excitatory and excitatory-inhibitory networks, with either homogeneous connections or a small-world structure. We identify the properties of a network which will cause this correlation to hold. We argue that the reason Katz centrality correlates so highly with neuronal activity compared to other centrality measures is because it nicely captures disinhibition in neural networks. In addition, we argue that these theoretical findings are applicable to neuroscientists who apply centrality measures to functional brain networks, as well as offer a neurophysiological justification to high level cognitive models which use certain centrality measures.

  17. Development of a predictive model to determine micropollutant removal using granular activated carbon

    Directory of Open Access Journals (Sweden)

    D. J. de Ridder

    2009-12-01

    Full Text Available The occurrence of organic micropollutants in drinking water and its sources has opened up a field of study related to monitoring concentration levels in water sources, evaluating their toxicity and estimating their removal in drinking water treatment processes. Because a large number of organic micropollutants is currently present (although in relatively low concentrations in drinking water sources, a method should be developed to select which micropollutants has to be evaluated with priority. In this paper, a screening model is presented that can predict solute removal by activated carbon, in ultrapure water and in natural water. Solute removal prediction is based on a combination of solute hydrophobicity (expressed as log D, the pH corrected log Kow, solute charge and the carbon dose. Solute molecular weight was also considered as model input parameter, but this solute property appeared to relate insufficiently to solute removal.

    Removal of negatively charged solutes by preloaded activated carbon was reduced while the removal of positively charged solutes was increased, compared with freshly regenerated activated carbon. Differences in charged solute removal by freshly regenerated activated carbon were small, indicating that charge interactions are an important mechanism in adsorption onto preloaded carbon. The predicted solute removal was within 20 removal-% deviation of experimentally measured values for most solutes.

  18. Resting lateralized activity predicts the cortical response and appraisal of emotions: an fNIRS study.

    Science.gov (United States)

    Balconi, Michela; Grippa, Elisabetta; Vanutelli, Maria Elide

    2015-12-01

    This study explored the effect of lateralized left-right resting brain activity on prefrontal cortical responsiveness to emotional cues and on the explicit appraisal (stimulus evaluation) of emotions based on their valence. Indeed subjective responses to different emotional stimuli should be predicted by brain resting activity and should be lateralized and valence-related (positive vs negative valence). A hemodynamic measure was considered (functional near-infrared spectroscopy). Indeed hemodynamic resting activity and brain response to emotional cues were registered when subjects (N = 19) viewed emotional positive vs negative stimuli (IAPS). Lateralized index response during resting state, LI (lateralized index) during emotional processing and self-assessment manikin rating were considered. Regression analysis showed the significant predictive effect of resting activity (more left or right lateralized) on both brain response and appraisal of emotional cues based on stimuli valence. Moreover, significant effects were found as a function of valence (more right response to negative stimuli; more left response to positive stimuli) during emotion processing. Therefore, resting state may be considered a predictive marker of the successive cortical responsiveness to emotions. The significance of resting condition for emotional behavior was discussed. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  19. Lateral prefrontal cortex activity during cognitive control of emotion predicts response to social stress in schizophrenia

    Directory of Open Access Journals (Sweden)

    Laura M. Tully, PhD

    2014-01-01

    Full Text Available LPFC dysfunction is a well-established neural impairment in schizophrenia and is associated with worse symptoms. However, how LPFC activation influences symptoms is unclear. Previous findings in healthy individuals demonstrate that lateral prefrontal cortex (LPFC activation during cognitive control of emotional information predicts mood and behavior in response to interpersonal conflict, thus impairments in these processes may contribute to symptom exacerbation in schizophrenia. We investigated whether schizophrenia participants show LPFC deficits during cognitive control of emotional information, and whether these LPFC deficits prospectively predict changes in mood and symptoms following real-world interpersonal conflict. During fMRI, 23 individuals with schizophrenia or schizoaffective disorder and 24 healthy controls completed the Multi-Source Interference Task superimposed on neutral and negative pictures. Afterwards, schizophrenia participants completed a 21-day online daily-diary in which they rated the extent to which they experienced mood and schizophrenia-spectrum symptoms, as well as the occurrence and response to interpersonal conflict. Schizophrenia participants had lower dorsal LPFC activity (BA9 during cognitive control of task-irrelevant negative emotional information. Within schizophrenia participants, DLPFC activity during cognitive control of emotional information predicted changes in positive and negative mood on days following highly distressing interpersonal conflicts. Results have implications for understanding the specific role of LPFC in response to social stress in schizophrenia, and suggest that treatments targeting LPFC-mediated cognitive control of emotion could promote adaptive response to social stress in schizophrenia.

  20. A community computational challenge to predict the activity of pairs of compounds.

    Science.gov (United States)

    Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

    2014-12-01

    Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

  1. Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design.

    Science.gov (United States)

    Spreco, Armin; Eriksson, Olle; Dahlström, Örjan; Cowling, Benjamin John; Timpka, Toomas

    2017-06-15

    Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic "big data" from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning

  2. Predicting physical activity and outcome expectations in cancer survivors: an application of Self-Determination Theory.

    Science.gov (United States)

    Wilson, Philip M; Blanchard, Chris M; Nehl, Eric; Baker, Frank

    2006-07-01

    The purpose of this study was to examine the contributions of autonomous and controlled motives drawn from Self-Determination Theory (SDT; Intrinsic Motivation and Self-determination in Human Behavior. Plenum Press: New York, 1985; Handbook of Self-determination Research. University of Rochester Press: New York, 2002) towards predicting physical activity behaviours and outcome expectations in adult cancer survivors. Participants were cancer-survivors (N=220) and a non-cancer comparison cohort (N=220) who completed an adapted version of the Treatment Self-Regulation Questionnaire modified for physical activity behaviour (TSRQ-PA), an assessment of the number of minutes engaged in moderate-to-vigorous physical activity (MVPA) weekly, and the anticipated outcomes expected from regular physical activity (OE). Simultaneous multiple regression analyses indicated that autonomous motives was the dominant predictor of OEs across both cancer and non-cancer cohorts (R(2adj)=0.29-0.43), while MVPA was predicted by autonomous (beta's ranged from 0.21 to 0.34) and controlled (beta's ranged from -0.04 to -0.23) motives after controlling for demographic considerations. Cancer status (cancer versus no cancer) did not moderate the motivation-physical activity relationship. Collectively, these findings suggest that the distinction between autonomous and controlled motives is useful and compliments a growing body of evidence supporting SDT as a framework for understanding motivational processes in physical activity contexts with cancer survivors.

  3. Role of spontaneous physical activity in prediction of susceptibility to activity based anorexia in male and female rats.

    Science.gov (United States)

    Perez-Leighton, Claudio E; Grace, Martha; Billington, Charles J; Kotz, Catherine M

    2014-08-01

    Anorexia nervosa (AN) is a chronic eating disorder affecting females and males, defined by body weight loss, higher physical activity levels and restricted food intake. Currently, the commonalities and differences between genders in etiology of AN are not well understood. Animal models of AN, such as activity-based anorexia (ABA), can be helpful in identifying factors determining individual susceptibility to AN. In ABA, rodents are given an access to a running wheel while food restricted, resulting in paradoxical increased physical activity levels and weight loss. Recent studies suggest that different behavioral traits, including voluntary exercise, can predict individual weight loss in ABA. A higher inherent drive for movement may promote development and severity of AN, but this hypothesis remains untested. In rodents and humans, drive for movement is defined as spontaneous physical activity (SPA), which is time spent in low-intensity, non-volitional movements. In this paper, we show that a profile of body weight history and behavioral traits, including SPA, can predict individual weight loss caused by ABA in male and female rats with high accuracy. Analysis of the influence of SPA on ABA susceptibility in males and females rats suggests that either high or low levels of SPA increase the probability of high weight loss in ABA, but with larger effects in males compared to females. These results suggest that the same behavioral profile can identify individuals at-risk of AN for both male and female populations and that SPA has predictive value for susceptibility to AN. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. Predictive Factors of Clinical Response of Infliximab Therapy in Active Nonradiographic Axial Spondyloarthritis Patients

    Directory of Open Access Journals (Sweden)

    Zhiming Lin

    2015-01-01

    Full Text Available Objectives. To evaluate the efficiency and the predictive factors of clinical response of infliximab in active nonradiographic axial spondyloarthritis patients. Methods. Active nonradiographic patients fulfilling ESSG criteria for SpA but not fulfilling modified New York criteria were included. All patients received infliximab treatment for 24 weeks. The primary endpoint was ASAS20 response at weeks 12 and 24. The abilities of baseline parameters and response at week 2 to predict ASAS20 response at weeks 12 and 24 were assessed using ROC curve and logistic regression analysis, respectively. Results. Of 70 axial SpA patients included, the proportions of patients achieving an ASAS20 response at weeks 2, 6, 12, and 24 were 85.7%, 88.6%, 87.1%, and 84.3%, respectively. Baseline MRI sacroiliitis score (AUC = 0.791; P=0.005, CRP (AUC = 0.75; P=0.017, and ASDAS (AUC = 0.778, P=0.007 significantly predicted ASAS20 response at week 12. However, only ASDAS (AUC = 0.696, P=0.040 significantly predicted ASAS20 response at week 24. Achievement of ASAS20 response after the first infliximab infusion was a significant predictor of subsequent ASAS20 response at weeks 12 and 24 (wald χ2=6.87, P=0.009, and wald χ2=5.171, P=0.023. Conclusions. Infliximab shows efficiency in active nonradiographic axial spondyloarthritis patients. ASDAS score and first-dose response could help predicting clinical efficacy of infliximab therapy in these patients.

  5. Linear filters as a method of real-time prediction of geomagnetic activity

    International Nuclear Information System (INIS)

    McPherron, R.L.; Baker, D.N.; Bargatze, L.F.

    1985-01-01

    Important factors controlling geomagnetic activity include the solar wind velocity, the strength of the interplanetary magnetic field (IMF), and the field orientation. Because these quantities change so much in transit through the solar wind, real-time monitoring immediately upstream of the earth provides the best input for any technique of real-time prediction. One such technique is linear prediction filtering which utilizes past histories of the input and output of a linear system to create a time-invariant filter characterizing the system. Problems of nonlinearity or temporal changes of the system can be handled by appropriate choice of input parameters and piecewise approximation in various ranges of the input. We have created prediction filters for all the standard magnetic indices and tested their efficiency. The filters show that the initial response of the magnetosphere to a southward turning of the IMF peaks in 20 minutes and then again in 55 minutes. After a northward turning, auroral zone indices and the midlatitude ASYM index return to background within 2 hours, while Dst decays exponentially with a time constant of about 8 hours. This paper describes a simple, real-time system utilizing these filters which could predict a substantial fraction of the variation in magnetic activity indices 20 to 50 minutes in advance

  6. Restraint status improves the predictive value of motor vehicle crash criteria for pediatric trauma team activation.

    Science.gov (United States)

    Bozeman, Andrew P; Dassinger, Melvin S; Recicar, John F; Smith, Samuel D; Rettiganti, Mallikarjuna R; Nick, Todd G; Maxson, Robert T

    2012-12-01

    Most trauma centers incorporate mechanistic criteria (MC) into their algorithm for trauma team activation (TTA). We hypothesized that characteristics of the crash are less reliable than restraint status in predicting significant injury and the need for TTA. We identified 271 patients (age, <15 y) admitted with a diagnosis of motor vehicle crash. Mechanistic criteria and restraint status of each patient were recorded. Both MC and MC plus restraint status were evaluated as separate measures for appropriately predicting TTA based on treatment outcomes and injury scores. Improper restraint alone predicted a need for TTA with an odds ratios of 2.69 (P = .002). MC plus improper restraint predicted the need for TTA with an odds ratio of 2.52 (P = .002). In contrast, the odds ratio when using MC alone was 1.65 (P = .16). When the 5 MC were evaluated individually as predictive of TTA, ejection, death of occupant, and intrusion more than 18 inches were statistically significant. Improper restraint is an independent predictor of necessitating TTA in this single-institution study. Copyright © 2012 Elsevier Inc. All rights reserved.

  7. New mechanistically based model for predicting reduction of biosolids waste by ozonation of return activated sludge.

    Science.gov (United States)

    Isazadeh, Siavash; Feng, Min; Urbina Rivas, Luis Enrique; Frigon, Dominic

    2014-04-15

    Two pilot-scale activated sludge reactors were operated for 98 days to provide the necessary data to develop and validate a new mathematical model predicting the reduction of biosolids production by ozonation of the return activated sludge (RAS). Three ozone doses were tested during the study. In addition to the pilot-scale study, laboratory-scale experiments were conducted with mixed liquor suspended solids and with pure cultures to parameterize the biomass inactivation process during exposure to ozone. The experiments revealed that biomass inactivation occurred even at the lowest doses, but that it was not associated with extensive COD solubilization. For validation, the model was used to simulate the temporal dynamics of the pilot-scale operational data. Increasing the description accuracy of the inactivation process improved the precision of the model in predicting the operational data. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. The influence of active region information on the prediction of solar flares: an empirical model using data mining

    Directory of Open Access Journals (Sweden)

    M. Núñez

    2005-11-01

    Full Text Available Predicting the occurrence of solar flares is a challenge of great importance for many space weather scientists and users. We introduce a data mining approach, called Behavior Pattern Learning (BPL, for automatically discovering correlations between solar flares and active region data, in order to predict the former. The goal of BPL is to predict the interval of time to the next solar flare and provide a confidence value for the associated prediction. The discovered correlations are described in terms of easy-to-read rules. The results indicate that active region dynamics is essential for predicting solar flares.

  9. Factors predicting changes in physical activity through adolescence: the Young-HUNT Study, Norway.

    Science.gov (United States)

    Rangul, Vegar; Holmen, Turid Lingaas; Bauman, Adrian; Bratberg, Grete H; Kurtze, Nanna; Midthjell, Kristian

    2011-06-01

    The purpose of this prospective population-based study was to analyze predictors of changes in physical activity (PA) levels from early to late adolescence. Data presented are from 2,348 adolescents and their parents who participated in the Nord-Trøndelag Health study (HUNT 2, 1995-1997) and at follow-up in Young-HUNT 2, 2000-2001 Participants completed a self-reported questionnaire and participated in a clinical examination that included measurements of height and weight. Four patterns of PA emerged in the study: active or inactive at both time points (active maintainers, 13%; inactive maintainers, 59%), inactive and became active (adopters, 12%), active and became inactive (relapsers, 16%). Being overweight, dissatisfied with life, and not actively participating in sports at baseline were significant predictors of change regarding PA among boys at follow-up. For girls, smoking, drinking, low maternal education, and physical inactivity predicted relapsers and inactive maintainers. Higher levels of education and more physically active parents at baseline seemed to protect against decreased PA during follow-up for both genders. Predictors of change in, or maintaining PA status during adolescence differed by gender. These results suggest that PA-promoting interventions should be tailored by gender and focus on encouraging activity for inactive adolescents and maintenance of PA in those already active. Copyright © 2011 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  10. Urinary aminopeptidase activities as early and predictive biomarkers of renal dysfunction in cisplatin-treated rats.

    Directory of Open Access Journals (Sweden)

    Andrés Quesada

    Full Text Available This study analyzes the fluorimetric determination of alanyl- (Ala, glutamyl- (Glu, leucyl-cystinyl- (Cys and aspartyl-aminopeptidase (AspAp urinary enzymatic activities as early and predictive biomarkers of renal dysfunction in cisplatin-treated rats. Male Wistar rats (n = 8 each group received a single subcutaneous injection of either saline or cisplatin 3.5 or 7 mg/kg, and urine samples were taken at 0, 1, 2, 3 and 14 days after treatment. In urine samples we determined Ala, Glu, Cys and AspAp activities, proteinuria, N-acetyl-β-D-glucosaminidase (NAG, albumin, and neutrophil gelatinase-associated lipocalin (NGAL. Plasma creatinine, creatinine clearance and renal morphological variables were measured at the end of the experiment. CysAp, NAG and albumin were increased 48 hours after treatment in the cisplatin 3.5 mg/kg treated group. At 24 hours, all urinary aminopeptidase activities and albuminuria were significantly increased in the cisplatin 7 mg/kg treated group. Aminopeptidase urinary activities correlated (p0.259 with plasma creatinine, creatinine clearance and/or kidney weight/body weight ratio at the end of the experiment and they could be considered as predictive biomarkers of renal injury severity. ROC-AUC analysis was made to study their sensitivity and specificity to distinguish between treated and untreated rats at day 1. All aminopeptidase activities showed an AUC>0.633. We conclude that Ala, Cys, Glu and AspAp enzymatic activities are early and predictive urinary biomarkers of the renal dysfunction induced by cisplatin. These determinations can be very useful in the prognostic and diagnostic of renal dysfunction in preclinical research and clinical practice.

  11. Development of Predictive QSAR Models of 4-Thiazolidinones Antitrypanosomal Activity using Modern Machine Learning Algorithms.

    Science.gov (United States)

    Kryshchyshyn, Anna; Devinyak, Oleg; Kaminskyy, Danylo; Grellier, Philippe; Lesyk, Roman

    2017-11-14

    This paper presents novel QSAR models for the prediction of antitrypanosomal activity among thiazolidines and related heterocycles. The performance of four machine learning algorithms: Random Forest regression, Stochastic gradient boosting, Multivariate adaptive regression splines and Gaussian processes regression have been studied in order to reach better levels of predictivity. The results for Random Forest and Gaussian processes regression are comparable and outperform other studied methods. The preliminary descriptor selection with Boruta method improved the outcome of machine learning methods. The two novel QSAR-models developed with Random Forest and Gaussian processes regression algorithms have good predictive ability, which was proved by the external evaluation of the test set with corresponding Q 2 ext =0.812 and Q 2 ext =0.830. The obtained models can be used further for in silico screening of virtual libraries in the same chemical domain in order to find new antitrypanosomal agents. Thorough analysis of descriptors influence in the QSAR models and interpretation of their chemical meaning allows to highlight a number of structure-activity relationships. The presence of phenyl rings with electron-withdrawing atoms or groups in para-position, increased number of aromatic rings, high branching but short chains, high HOMO energy, and the introduction of 1-substituted 2-indolyl fragment into the molecular structure have been recognized as trypanocidal activity prerequisites. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Adsorption of selected pharmaceuticals and an endocrine disrupting compound by granular activated carbon. 2. Model prediction

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Z.; Peldszus, S.; Huck, P.M. [University of Waterloo, Waterloo, ON (Canada). NSERC Chair in Water Treatment

    2009-03-01

    The adsorption of two representative pharmaceutically active compounds (PhACs) naproxen and carbamazepine and one endocrine disrupting compound (EDC) nonylphenol was studied in pilot-scale granular activated carbon (GAC) adsorbers using post-sedimentation (PS) water from a full-scale drinking water treatment plant. The GAC adsorbents were coal-based Calgon Filtrasorb 400 and coconut shell-based PICA CTIF TE. Acidic naproxen broke through fastest while nonylphenol was removed best, which was consistent with the degree to which fouling affected compound removals. Model predictions and experimental data were generally in good agreement for all three compounds, which demonstrated the effectiveness and robustness of the pore and surface diffusion model (PSDM) used in combination with the time-variable parameter approach for predicting removals at environmentally relevant concentrations (i.e., ng/L range). Sensitivity analyses suggested that accurate determination of film diffusion coefficients was critical for predicting breakthrough for naproxen and carbamazepine, in particular when high removals are targeted. Model simulations demonstrated that GAC carbon usage rates (CURs) for naproxen were substantially influenced by the empty bed contact time (EBCT) at the investigated conditions. Model-based comparisons between GAC CURs and minimum CURs for powdered activated carbon (PAC) applications suggested that PAC would be most appropriate for achieving 90% removal of naproxen, whereas GAC would be more suitable for nonylphenol. 25 refs., 4 figs., 1 tab.

  13. Situational Motivation and Perceived Intensity: Their Interaction in Predicting Changes in Positive Affect from Physical Activity

    Directory of Open Access Journals (Sweden)

    Eva Guérin

    2012-01-01

    Full Text Available There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE] in predicting changes in positive affect following an acute bout of preferred physical activity, namely, running. Fourty-one female runners engaged in a 30-minute self-paced treadmill run in a laboratory context. Situational motivation for running, pre- and post-running positive affect, and RPE were assessed via validated self-report questionnaires. Hierarchical regression analyses revealed a significant interaction effect between RPE and introjection (P<.05 but not between RPE and identified regulation or intrinsic motivation. At low levels of introjection, the influence of RPE on the change in positive affect was considerable, with higher RPE ratings being associated with greater increases in positive affect. The implications of the findings in light of SDT principles as well as the potential contingencies between the regulations and RPE in predicting positive affect among women are discussed.

  14. A balance of activity in brain control and reward systems predicts self-regulatory outcomes.

    Science.gov (United States)

    Lopez, Richard B; Chen, Pin-Hao A; Huckins, Jeremy F; Hofmann, Wilhelm; Kelley, William M; Heatherton, Todd F

    2017-05-01

    Previous neuroimaging work has shown that increased reward-related activity following exposure to food cues is predictive of self-control failure. The balance model suggests that self-regulation failures result from an imbalance in reward and executive control mechanisms. However, an open question is whether the relative balance of activity in brain systems associated with executive control (vs reward) supports self-regulatory outcomes when people encounter tempting cues in daily life. Sixty-nine chronic dieters, a population known for frequent lapses in self-control, completed a food cue-reactivity task during an fMRI scanning session, followed by a weeklong sampling of daily eating behaviors via ecological momentary assessment. We related participants' food cue activity in brain systems associated with executive control and reward to real-world eating patterns. Specifically, a balance score representing the amount of activity in brain regions associated with self-regulatory control, relative to automatic reward-related activity, predicted dieters' control over their eating behavior during the following week. This balance measure may reflect individual self-control capacity and be useful for examining self-regulation success in other domains and populations. © The Author (2017). Published by Oxford University Press.

  15. Situational motivation and perceived intensity: their interaction in predicting changes in positive affect from physical activity.

    Science.gov (United States)

    Guérin, Eva; Fortier, Michelle S

    2012-01-01

    There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE)] in predicting changes in positive affect following an acute bout of preferred physical activity, namely, running. Fourty-one female runners engaged in a 30-minute self-paced treadmill run in a laboratory context. Situational motivation for running, pre- and post-running positive affect, and RPE were assessed via validated self-report questionnaires. Hierarchical regression analyses revealed a significant interaction effect between RPE and introjection (P positive affect was considerable, with higher RPE ratings being associated with greater increases in positive affect. The implications of the findings in light of SDT principles as well as the potential contingencies between the regulations and RPE in predicting positive affect among women are discussed.

  16. A cluster expansion model for predicting activation barrier of atomic processes

    International Nuclear Information System (INIS)

    Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit

    2013-01-01

    We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEB results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog

  17. Motorized Activity on Legacy Seismic Lines: A Predictive Modeling Approach to Prioritize Restoration Efforts.

    Science.gov (United States)

    Hornseth, M L; Pigeon, K E; MacNearney, D; Larsen, T A; Stenhouse, G; Cranston, J; Finnegan, L

    2018-05-11

    Natural regeneration of seismic lines, cleared for hydrocarbon exploration, is slow and often hindered by vegetation damage, soil compaction, and motorized human activity. There is an extensive network of seismic lines in western Canada which is known to impact forest ecosystems, and seismic lines have been linked to declines in woodland caribou (Rangifer tarandus caribou). Seismic line restoration is costly, but necessary for caribou conservation to reduce cumulative disturbance. Understanding where motorized activity may be impeding regeneration of seismic lines will aid in prioritizing restoration. Our study area in west-central Alberta, encompassed five caribou ranges where restoration is required under federal species at risk recovery strategies, hence prioritizing seismic lines for restoration is of immediate conservation value. To understand patterns of motorized activity on seismic lines, we evaluated five a priori hypotheses using a predictive modeling framework and Geographic Information System variables across three landscapes in the foothills and northern boreal regions of Alberta. In the northern boreal landscape, motorized activity was most common in dry areas with a large industrial footprint. In highly disturbed areas of the foothills, motorized activity on seismic lines increased with low vegetation heights, relatively dry soils, and further from forest cutblocks, while in less disturbed areas of the foothills, motorized activity on seismic lines decreased proportional to seismic line density, slope steepness, and white-tailed deer abundance, and increased proportional with distance to roads. We generated predictive maps of high motorized activity, identifying 21,777 km of seismic lines where active restoration could expedite forest regeneration.

  18. Error-related anterior cingulate cortex activity and the prediction of conscious error awareness

    Directory of Open Access Journals (Sweden)

    Catherine eOrr

    2012-06-01

    Full Text Available Research examining the neural mechanisms associated with error awareness has consistently identified dorsal anterior cingulate activity (ACC as necessary but not predictive of conscious error detection. Two recent studies (Steinhauser and Yeung, 2010; Wessel et al. 2011 have found a contrary pattern of greater dorsal ACC activity (in the form of the error-related negativity during detected errors, but suggested that the greater activity may instead reflect task influences (e.g., response conflict, error probability and or individual variability (e.g., statistical power. We re-analyzed fMRI BOLD data from 56 healthy participants who had previously been administered the Error Awareness Task, a motor Go/No-go response inhibition task in which subjects make errors of commission of which they are aware (Aware errors, or unaware (Unaware errors. Consistent with previous data, the activity in a number of cortical regions was predictive of error awareness, including bilateral inferior parietal and insula cortices, however in contrast to previous studies, including our own smaller sample studies using the same task, error-related dorsal ACC activity was significantly greater during aware errors when compared to unaware errors. While the significantly faster RT for aware errors (compared to unaware was consistent with the hypothesis of higher response conflict increasing ACC activity, we could find no relationship between dorsal ACC activity and the error RT difference. The data suggests that individual variability in error awareness is associated with error-related dorsal ACC activity, and therefore this region may be important to conscious error detection, but it remains unclear what task and individual factors influence error awareness.

  19. Objectively Quantified Physical Activity and Sedentary Behavior in Predicting Visceral Adiposity and Liver Fat

    Directory of Open Access Journals (Sweden)

    Shelley E. Keating

    2016-01-01

    Full Text Available Objective. Epidemiologic studies suggest an inverse relationship between nonalcoholic fatty liver disease (NAFLD, visceral adipose tissue (VAT, and self-reported physical activity levels. However, subjective measurements can be inaccurate and prone to reporter bias. We investigated whether objectively quantified physical activity levels predicted liver fat and VAT in overweight/obese adults. Methods. Habitual physical activity was measured by triaxial accelerometry for four days (n=82. Time spent in sedentary behavior (MET < 1.6 and light (MET 1.6 < 3, moderate (MET 3 < 6, and vigorous (MET 6 < 9 physical activity was quantified. Magnetic resonance imaging and spectroscopy were used to quantify visceral and liver fat. Bivariate correlations and hierarchical multiple regression analyses were performed. Results. There were no associations between physical activity or sedentary behavior and liver lipid. Sedentary behavior and moderate and vigorous physical activity accounted for just 3% of variance for VAT (p=0.14 and 0.003% for liver fat (p=0.96. Higher levels of VAT were associated with time spent in moderate activity (r=0.294, p=0.007, but there was no association with sedentary behavior. Known risk factors for obesity-related NAFLD accounted for 62% and 40% of variance in VAT and liver fat, respectively (p<0.01. Conclusion. Objectively measured levels of habitual physical activity and sedentary behavior did not influence VAT or liver fat.

  20. How many days of accelerometer monitoring predict weekly physical activity behaviour in obese youth?

    Science.gov (United States)

    Vanhelst, Jérémy; Fardy, Paul S; Duhamel, Alain; Béghin, Laurent

    2014-09-01

    The aim of this study was to determine the type and the number of accelerometer monitoring days needed to predict weekly sedentary behaviour and physical activity in obese youth. Fifty-three obese youth wore a triaxial accelerometer for 7 days to measure physical activity in free-living conditions. Analyses of variance for repeated measures, Intraclass coefficient (ICC) and regression linear analyses were used. Obese youth spent significantly less time in physical activity on weekends or free days compared with school days. ICC analyses indicated a minimum of 2 days is needed to estimate physical activity behaviour. ICC were 0·80 between weekly physical activity and weekdays and 0·92 between physical activity and weekend days. The model has to include a weekday and a weekend day. Using any combination of one weekday and one weekend day, the percentage of variance explained is >90%. Results indicate that 2 days of monitoring are needed to estimate the weekly physical activity behaviour in obese youth with an accelerometer. Our results also showed the importance of taking into consideration school day versus free day and weekday versus weekend day in assessing physical activity in obese youth. © 2013 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

  1. Activity limitations predict health care expenditures in the general population in Belgium.

    Science.gov (United States)

    Van der Heyden, Johan; Van Oyen, Herman; Berger, Nicolas; De Bacquer, Dirk; Van Herck, Koen

    2015-03-19

    Disability and chronic conditions both have an impact on health expenditures and although they are conceptually related, they present different dimensions of ill-health. Recent concepts of disability combine a biological understanding of impairment with the social dimension of activity limitation and resulted in the development of the Global Activity Limitation Indicator (GALI). This paper reports on the predictive value of the GALI on health care expenditures in relation to the presence of chronic conditions. Data from the Belgian Health Interview Survey 2008 were linked with data from the compulsory national health insurance (n = 7,286). The effect of activity limitation on health care expenditures was assessed via cost ratios from multivariate linear regression models. To study the factors contributing to the difference in health expenditure between persons with and without activity limitations, the Blinder-Oaxaca decomposition method was used. Activity limitations are a strong determinant of health care expenditures. People with severe activity limitations (5.1%) accounted for 16.9% of the total health expenditure, whereas those without activity limitations (79.0%), were responsible for 51.5% of the total health expenditure. These observed differences in health care expenditures can to some extent be explained by chronic conditions, but activity limitations also contribute substantially to higher health care expenditures in the absence of chronic conditions (cost ratio 2.46; 95% CI 1.74-3.48 for moderate and 4.45; 95% CI 2.47-8.02 for severe activity limitations). The association between activity limitation and health care expenditures is stronger for reimbursed health care costs than for out-of-pocket payments. In the absence of chronic conditions, activity limitations appear to be an important determinant of health care expenditures. To make projections on health care expenditures, routine data on activity limitations are essential and complementary to data

  2. Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons.

    Directory of Open Access Journals (Sweden)

    Kyriaki Sidiropoulou

    stimulus that code for its ability to induce persistent activity and predict differential roles of RS and IB neurons in persistent activity expression.

  3. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

    Science.gov (United States)

    Bertolino, Alessandro; Taurisano, Paolo; Pisciotta, Nicola Marco; Blasi, Giuseppe; Fazio, Leonardo; Romano, Raffaella; Gelao, Barbara; Lo Bianco, Luciana; Lozupone, Madia; Di Giorgio, Annabella; Caforio, Grazia; Sambataro, Fabio; Niccoli-Asabella, Artor; Papp, Audrey; Ursini, Gianluca; Sinibaldi, Lorenzo; Popolizio, Teresa; Sadee, Wolfgang; Rubini, Giuseppe

    2010-02-22

    Variation of the gene coding for D2 receptors (DRD2) has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560) predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic) and D2L (mainly post-synaptic). However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known. Thirty-seven healthy subjects were genotyped for rs1076560 (G>T) and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors) and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors), as well as BOLD fMRI during N-Back working memory. Subjects carrying the T allele (previously associated with reduced D2S expression) had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers) and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT. Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway.

  4. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

    Directory of Open Access Journals (Sweden)

    Alessandro Bertolino

    2010-02-01

    Full Text Available Variation of the gene coding for D2 receptors (DRD2 has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560 predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic and D2L (mainly post-synaptic. However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known.Thirty-seven healthy subjects were genotyped for rs1076560 (G>T and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors, as well as BOLD fMRI during N-Back working memory.Subjects carrying the T allele (previously associated with reduced D2S expression had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT.Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway.

  5. Docosahexaenoic Acid Inhibits Tumor Promoter-Induced Urokinase-Type Plasminogen Activator Receptor by Suppressing PKCδ- and MAPKs-Mediated Pathways in ECV304 Human Endothelial Cells.

    Directory of Open Access Journals (Sweden)

    Sen Lian

    Full Text Available The overexpression of urokinase-type plasminogen activator receptor (uPAR is associated with inflammation and virtually all human cancers. Despite the fact that docosahexaenoic acid (DHA has been reported to possess anti-inflammatory and anti-tumor properties, the negative regulation of uPAR by DHA is still undefined. Here, we investigated the effect of DHA on 12-O-tetradecanoylphorbol-13-acetate (TPA-induced uPAR expression and the underlying molecular mechanisms in ECV304 human endothelial cells. DHA concentration-dependently inhibited TPA-induced uPAR. Specific inhibitors and mutagenesis studies showed that PKCδ, JNK1/2, Erk1/2, NF-κB, and AP-1 were critical for TPA-induced uPAR expression. Application of DHA suppressed TPA-induced translocation of PKCδ, activation of the JNK1/2 and Erk1/2 signaling pathways, and subsequent AP-1 and NF-κB transactivation. In conclusion, these observations suggest a novel role for DHA in reducing uPAR expression and cell invasion by inhibition of PKCδ, JNK1/2, and Erk1/2, and the reduction of AP-1 and NF-κB activation in ECV304 human endothelial cells.

  6. Antithrombotic and cytotoxic activities of four Bangladeshi plants and PASS prediction of their isolated compounds.

    Science.gov (United States)

    Kabir, Mohammad Shah Hafez; Mahamoud, Md Sofi; Chakrabarty, Nishan; Ahmad, Shabbir; Masum, Md Abdullah Al; Hoque, Md Akramul; Hossain, Mohammed Munawar; Rahman, Md Mominur; Uddin, Mir Muhammad Nasir

    2016-11-01

    This study aims to investigate whether tested organic extracts possess antithrombotic properties with minimal or no toxicity and to predict the activity of some of their isolated compounds. An in vitro thrombolytic model was used to check the clot lysis effect of four Bangladeshi herbal extracts viz., roots of Curculigo recurvata W.T. Aiton (Satipata), leaf of Amorphophallus bulbifer Roxb. (Olkachu), leaf of Phyllanthus sikkimensis Muell. Arg., and whole plant of Thunbergia grandiflora Roxb. (Nillata) using streptokinase as a positive control and water as a negative control. Cytotoxicity was screened by brine shrimp lethality bioassay using vincristine sulfate as positive control. In silico prediction of activity spectra for substances (PASS) prediction was applied for phytoconstituents, namely, nyasicoside, glucomannan, grandifloric acid, serine, and alanine. Using an in vitro thrombolytic model, C. recurvata, A. bulbifer, P. sikkimensis, and T. grandiflora showed 28.10±1.64%, 42.47±1.96%, 32.86±1.92%, and 25.51±1.67% of clot lysis, respectively. Reference drug streptokinase exhibited 75.00±3.04% clot lysis. Examined herbs showed significant (p<0.001) percentage (%) of clot lysis compared to negative control. In brine shrimp cytotoxic assay, C. recurvata, A. bulbifer, P. sikkimensis, and T. grandiflora showed LC50 values 210.64±3.44, 98.51±1.47, 187.29±2.01, and 386.43±3.02 μg/mL, respectively, with reference to vincristine sulfate (LC50 0.76±0.04). PASS predicted that examined phytoconstituents have a wide range of biological activity. Through our study it was found that A. bulbifer and P. sikkimensis could be considered as very promising and beneficial thrombolytic agents.

  7. Horticultural activity predicts later localized limb status in a contemporary pre-industrial population.

    Science.gov (United States)

    Stieglitz, Jonathan; Trumble, Benjamin C; Kaplan, Hillard; Gurven, Michael

    2017-07-01

    Modern humans may have gracile skeletons due to low physical activity levels and mechanical loading. Tests using pre-historic skeletons are limited by the inability to assess behavior directly, while modern industrialized societies possess few socio-ecological features typical of human evolutionary history. Among Tsimane forager-horticulturalists, we test whether greater activity levels and, thus, increased loading earlier in life are associated with greater later-life bone status and diminished age-related bone loss. We used quantitative ultrasonography to assess radial and tibial status among adults aged 20+ years (mean ± SD age = 49 ± 15; 52% female). We conducted systematic behavioral observations to assess earlier-life activity patterns (mean time lag between behavioural observation and ultrasound = 12 years). For a subset of participants, physical activity was again measured later in life, via accelerometry, to determine whether earlier-life time use is associated with later-life activity levels. Anthropometric and demographic data were collected during medical exams. Structural decline with age is reduced for the tibia (female: -0.25 SDs/decade; male: 0.05 SDs/decade) versus radius (female: -0.56 SDs/decade; male: -0.20 SDs/decade), which is expected if greater loading mitigates bone loss. Time allocation to horticulture, but not hunting, positively predicts later-life radial status (β Horticulture  = 0.48, p = 0.01), whereas tibial status is not significantly predicted by subsistence or sedentary leisure participation. Patterns of activity- and age-related change in bone status indicate localized osteogenic responses to loading, and are generally consistent with the logic of bone functional adaptation. Nonmechanical factors related to subsistence lifestyle moderate the association between activity patterns and bone structure. © 2017 Wiley Periodicals, Inc.

  8. D2 receptor genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans.

    Science.gov (United States)

    Fazio, Leonardo; Blasi, Giuseppe; Taurisano, Paolo; Papazacharias, Apostolos; Romano, Raffaella; Gelao, Barbara; Ursini, Gianluca; Quarto, Tiziana; Lo Bianco, Luciana; Di Giorgio, Annabella; Mancini, Marina; Popolizio, Teresa; Rubini, Giuseppe; Bertolino, Alessandro

    2011-02-14

    Pre-synaptic D2 receptors regulate striatal dopamine release and DAT activity, key factors for modulation of motor pathways. A functional SNP of DRD2 (rs1076560 G>T) is associated with alternative splicing such that the relative expression of D2S (mainly pre-synaptic) vs. D2L (mainly post-synaptic) receptor isoforms is decreased in subjects with the T allele with a putative increase of striatal dopamine levels. To evaluate how DRD2 genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans, we have investigated the association of rs1076560 with BOLD fMRI activity during a motor task. To further evaluate the relationship of this circuitry with dopamine signaling, we also explored the correlation between genotype based differences in motor brain activity and pre-synaptic striatal DAT binding measured with [(123)I] FP-CIT SPECT. Fifty healthy subjects, genotyped for DRD2 rs1076560 were studied with BOLD-fMRI at 3T while performing a visually paced motor task with their right hand; eleven of these subjects also underwent [(123)I]FP-CIT SPECT. SPM5 random-effects models were used for statistical analyses. Subjects carrying the T allele had greater BOLD responses in left basal ganglia, thalamus, supplementary motor area, and primary motor cortex, whose activity was also negatively correlated with reaction time at the task. Moreover, left striatal DAT binding and activity of left supplementary motor area were negatively correlated. The present results suggest that DRD2 genetic variation was associated with focusing of responses in the whole motor network, in which activity of predictable nodes was correlated with reaction time and with striatal pre-synaptic dopamine signaling. Our results in humans may help shed light on genetic risk for neurobiological mechanisms involved in the pathophysiology of disorders with dysregulation of striatal dopamine like Parkinson's disease. Copyright © 2010 Elsevier Inc. All rights reserved.

  9. Neural network versus activity-specific prediction equations for energy expenditure estimation in children.

    Science.gov (United States)

    Ruch, Nicole; Joss, Franziska; Jimmy, Gerda; Melzer, Katarina; Hänggi, Johanna; Mäder, Urs

    2013-11-01

    The aim of this study was to compare the energy expenditure (EE) estimations of activity-specific prediction equations (ASPE) and of an artificial neural network (ANNEE) based on accelerometry with measured EE. Forty-three children (age: 9.8 ± 2.4 yr) performed eight different activities. They were equipped with one tri-axial accelerometer that collected data in 1-s epochs and a portable gas analyzer. The ASPE and the ANNEE were trained to estimate the EE by including accelerometry, age, gender, and weight of the participants. To provide the activity-specific information, a decision tree was trained to recognize the type of activity through accelerometer data. The ASPE were applied to the activity-type-specific data recognized by the tree (Tree-ASPE). The Tree-ASPE precisely estimated the EE of all activities except cycling [bias: -1.13 ± 1.33 metabolic equivalent (MET)] and walking (bias: 0.29 ± 0.64 MET; P MET) and walking (bias: 0.61 ± 0.72 MET) and underestimated the EE of cycling (bias: -0.90 ± 1.18 MET; P MET, Tree-ASPE: 0.08 ± 0.21 MET) and walking (ANNEE 0.61 ± 0.72 MET, Tree-ASPE: 0.29 ± 0.64 MET) were significantly smaller in the Tree-ASPE than in the ANNEE (P < 0.05). The Tree-ASPE was more precise in estimating the EE than the ANNEE. The use of activity-type-specific information for subsequent EE prediction equations might be a promising approach for future studies.

  10. Structure prediction and activity analysis of human heme oxygenase-1 and its mutant.

    Science.gov (United States)

    Xia, Zhen-Wei; Zhou, Wen-Pu; Cui, Wen-Jun; Zhang, Xue-Hong; Shen, Qing-Xiang; Li, Yun-Zhu; Yu, Shan-Chang

    2004-08-15

    To predict wild human heme oxygenase-1 (whHO-1) and hHO-1 His25Ala mutant (delta hHO-1) structures, to clone and express them and analyze their activities. Swiss-PdbViewer and Antheprot 5.0 were used for the prediction of structure diversity and physical-chemical changes between wild and mutant hHO-1. hHO-1 His25Ala mutant cDNA was constructed by site-directed mutagenesis in two plasmids of E. coli DH5alpha. Expression products were purified by ammonium sulphate precipitation and Q-Sepharose Fast Flow column chromatography, and their activities were measured. rHO-1 had the structure of a helical fold with the heme sandwiched between heme-heme oxygenase-1 helices. Bond angle, dihedral angle and chemical bond in the active pocket changed after Ala25 was replaced by His25, but Ala25 was still contacting the surface and the electrostatic potential of the active pocket was negative. The mutated enzyme kept binding activity to heme. Two vectors pBHO-1 and pBHO-1(M) were constructed and expressed. Ammonium sulphate precipitation and column chromatography yielded 3.6-fold and 30-fold higher purities of whHO-1, respectively. The activity of delta hHO-1 was reduced 91.21% after mutation compared with whHO-1. Proximal His25 ligand is crucial for normal hHO-1 catalytic activity. delta hHO-1 is deactivated by mutation but keeps the same binding site as whHO-1. delta hHO-1 might be a potential inhibitor of whHO-1 for preventing neonatal hyperbilirubinemia.

  11. Neural activity in the hippocampus predicts individual visual short-term memory capacity.

    Science.gov (United States)

    von Allmen, David Yoh; Wurmitzer, Karoline; Martin, Ernst; Klaver, Peter

    2013-07-01

    Although the hippocampus had been traditionally thought to be exclusively involved in long-term memory, recent studies raised controversial explanations why hippocampal activity emerged during short-term memory tasks. For example, it has been argued that long-term memory processes might contribute to performance within a short-term memory paradigm when memory capacity has been exceeded. It is still unclear, though, whether neural activity in the hippocampus predicts visual short-term memory (VSTM) performance. To investigate this question, we measured BOLD activity in 21 healthy adults (age range 19-27 yr, nine males) while they performed a match-to-sample task requiring processing of object-location associations (delay period  =  900 ms; set size conditions 1, 2, 4, and 6). Based on individual memory capacity (estimated by Cowan's K-formula), two performance groups were formed (high and low performers). Within whole brain analyses, we found a robust main effect of "set size" in the posterior parietal cortex (PPC). In line with a "set size × group" interaction in the hippocampus, a subsequent Finite Impulse Response (FIR) analysis revealed divergent hippocampal activation patterns between performance groups: Low performers (mean capacity  =  3.63) elicited increased neural activity at set size two, followed by a drop in activity at set sizes four and six, whereas high performers (mean capacity  =  5.19) showed an incremental activity increase with larger set size (maximal activation at set size six). Our data demonstrated that performance-related neural activity in the hippocampus emerged below capacity limit. In conclusion, we suggest that hippocampal activity reflected successful processing of object-location associations in VSTM. Neural activity in the PPC might have been involved in attentional updating. Copyright © 2013 Wiley Periodicals, Inc.

  12. Physical activity predicts quality of life and happiness in children and adolescents with cerebral palsy.

    Science.gov (United States)

    Maher, Carol Ann; Toohey, Monica; Ferguson, Monika

    2016-01-01

    To examine the associations between physical activity, health-related quality of life and happiness in young people with cerebral palsy. A total of 70 young people with cerebral palsy (45 males, 25 females; mean age 13 years 11 months, SD 2 years 0 month) took part in a cross-sectional, descriptive postal survey assessing physical activity (Physical Activity Questionnaire for Adolescents), functional ability (Gross Motor Function Classification System), quality of life (Pediatric Quality of Life Inventory 4.0) and happiness (single Likert-scale item). Relationships between physical activity, quality of life and happiness were examined using backward stepwise linear regression. Physical activity significantly predicted physical quality of life (R(2 )= 0.64, β = 6.12, p = 0.02), social quality of life (R(2 )= 0.28, β = 9.27, p happiness (R(2 )= 0.08, β = 0.9, p = 0.04). Physical activity was not associated with emotional or school quality of life. This study found a positive association between physical activity, social and physical quality of life, and happiness in young people with cerebral palsy. Findings underscore the potential benefits of physical activity for the wellbeing of young people with cerebral palsy, in addition to its well-recognised physical and health benefits. Physical activity is a key predictor of quality of life and happiness in young people with cerebral palsy. Physical activity is widely recognised as having physical health benefits for young people with cerebral palsy; however, this study also highlights that it may have important benefits for wellbeing, quality of life and happiness. This emphasises the need for clinical services and intervention studies aimed specifically at increasing physical activity amongst children and adolescents with cerebral palsy.

  13. Psychological, interpersonal, and clinical factors predicting time spent on physical activity among Mexican patients with hypertension.

    Science.gov (United States)

    Ybarra Sagarduy, José Luis; Camacho Mata, Dacia Yurima; Moral de la Rubia, José; Piña López, Julio Alfonso; Yunes Zárraga, José Luis Masud

    2018-01-01

    It is widely known that physical activity is the key to the optimal management and clinical control of hypertension. This research was conducted to identify factors that can predict the time spent on physical activity among Mexican adults with hypertension. This cross-sectional study was conducted among 182 Mexican patients with hypertension, who completed a set of self-administered questionnaires related to personality, social support, and medical adherence and health care behaviors, body mass index, and time since the disease diagnosis. Several path analyses were performed in order to test the predictors of the study behavior. Lower tolerance to frustration, more tolerance to ambiguity, more effective social support, and less time since the disease diagnosis predicted more time spent on physical activity, accounting for 13.3% of the total variance. The final model shows a good fit to the sample data ( p BS =0.235, χ 2 / gl =1.519, Jöreskog and Sörbom's Goodness of Fit Index =0.987, adjusted modality =0.962, Bollen's Incremental Fit Index =0.981, Bentler-Bonett Normed Fit Index =0.946, standardized root mean square residual =0.053). The performance of physical activity in patients with hypertension depends on a complex set of interactions between personal, interpersonal, and clinical variables. Understanding how these factors interact might enhance the design of interdisciplinary intervention programs so that quality of life of patients with hypertension improves and they might be able to manage and control their disease well.

  14. Prediction-error in the context of real social relationships modulates reward system activity.

    Science.gov (United States)

    Poore, Joshua C; Pfeifer, Jennifer H; Berkman, Elliot T; Inagaki, Tristen K; Welborn, Benjamin L; Lieberman, Matthew D

    2012-01-01

    The human reward system is sensitive to both social (e.g., validation) and non-social rewards (e.g., money) and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward-social validation-and this activity's relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants' expectations for their romantic partners' positive regard of them were confirmed (validated) or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust.

  15. Predicting risk-taking behavior from prefrontal resting-state activity and personality.

    Directory of Open Access Journals (Sweden)

    Bettina Studer

    Full Text Available Risk-taking is subject to considerable individual differences. In the current study, we tested whether resting-state activity in the prefrontal cortex and trait sensitivity to reward and punishment can help predict risk-taking behavior. Prefrontal activity at rest was assessed in seventy healthy volunteers using electroencephalography, and compared to their choice behavior on an economic risk-taking task. The Behavioral Inhibition System/Behavioral Activation System scale was used to measure participants' trait sensitivity to reward and punishment. Our results confirmed both prefrontal resting-state activity and personality traits as sources of individual differences in risk-taking behavior. Right-left asymmetry in prefrontal activity and scores on the Behavioral Inhibition System scale, reflecting trait sensitivity to punishment, were correlated with the level of risk-taking on the task. We further discovered that scores on the Behavioral Inhibition System scale modulated the relationship between asymmetry in prefrontal resting-state activity and risk-taking. The results of this study demonstrate that heterogeneity in risk-taking behavior can be traced back to differences in the basic physiology of decision-makers' brains, and suggest that baseline prefrontal activity and personality traits might interplay in guiding risk-taking behavior.

  16. Predicting Risk-Taking Behavior from Prefrontal Resting-State Activity and Personality

    Science.gov (United States)

    Studer, Bettina; Pedroni, Andreas; Rieskamp, Jörg

    2013-01-01

    Risk-taking is subject to considerable individual differences. In the current study, we tested whether resting-state activity in the prefrontal cortex and trait sensitivity to reward and punishment can help predict risk-taking behavior. Prefrontal activity at rest was assessed in seventy healthy volunteers using electroencephalography, and compared to their choice behavior on an economic risk-taking task. The Behavioral Inhibition System/Behavioral Activation System scale was used to measure participants’ trait sensitivity to reward and punishment. Our results confirmed both prefrontal resting-state activity and personality traits as sources of individual differences in risk-taking behavior. Right-left asymmetry in prefrontal activity and scores on the Behavioral Inhibition System scale, reflecting trait sensitivity to punishment, were correlated with the level of risk-taking on the task. We further discovered that scores on the Behavioral Inhibition System scale modulated the relationship between asymmetry in prefrontal resting-state activity and risk-taking. The results of this study demonstrate that heterogeneity in risk-taking behavior can be traced back to differences in the basic physiology of decision-makers’ brains, and suggest that baseline prefrontal activity and personality traits might interplay in guiding risk-taking behavior. PMID:24116176

  17. Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

    Science.gov (United States)

    Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

    2018-05-17

    In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. New mechanistically based model for predicting reduction of biosolids waste by ozonation of return activated sludge

    International Nuclear Information System (INIS)

    Isazadeh, Siavash; Feng, Min; Urbina Rivas, Luis Enrique; Frigon, Dominic

    2014-01-01

    Highlights: • Biomass inactivation followed an exponential decay with increasing ozone doses. • From pure cultures, inactivation did not result in significant COD solubilization. • Ozone dose inactivation thresholds resulted from floc structure modifications. • Modeling description of biomass inactivation during RAS-ozonation was improved. • Model best describing inactivation resulted in best performance predictions. - Abstract: Two pilot-scale activated sludge reactors were operated for 98 days to provide the necessary data to develop and validate a new mathematical model predicting the reduction of biosolids production by ozonation of the return activated sludge (RAS). Three ozone doses were tested during the study. In addition to the pilot-scale study, laboratory-scale experiments were conducted with mixed liquor suspended solids and with pure cultures to parameterize the biomass inactivation process during exposure to ozone. The experiments revealed that biomass inactivation occurred even at the lowest doses, but that it was not associated with extensive COD solubilization. For validation, the model was used to simulate the temporal dynamics of the pilot-scale operational data. Increasing the description accuracy of the inactivation process improved the precision of the model in predicting the operational data

  19. New mechanistically based model for predicting reduction of biosolids waste by ozonation of return activated sludge

    Energy Technology Data Exchange (ETDEWEB)

    Isazadeh, Siavash; Feng, Min; Urbina Rivas, Luis Enrique; Frigon, Dominic, E-mail: dominic.frigon@mcgill.ca

    2014-04-01

    Highlights: • Biomass inactivation followed an exponential decay with increasing ozone doses. • From pure cultures, inactivation did not result in significant COD solubilization. • Ozone dose inactivation thresholds resulted from floc structure modifications. • Modeling description of biomass inactivation during RAS-ozonation was improved. • Model best describing inactivation resulted in best performance predictions. - Abstract: Two pilot-scale activated sludge reactors were operated for 98 days to provide the necessary data to develop and validate a new mathematical model predicting the reduction of biosolids production by ozonation of the return activated sludge (RAS). Three ozone doses were tested during the study. In addition to the pilot-scale study, laboratory-scale experiments were conducted with mixed liquor suspended solids and with pure cultures to parameterize the biomass inactivation process during exposure to ozone. The experiments revealed that biomass inactivation occurred even at the lowest doses, but that it was not associated with extensive COD solubilization. For validation, the model was used to simulate the temporal dynamics of the pilot-scale operational data. Increasing the description accuracy of the inactivation process improved the precision of the model in predicting the operational data.

  20. Predicting physical activity energy expenditure in wheelchair users with a multisensor device.

    Science.gov (United States)

    Nightingale, T E; Walhin, J P; Thompson, D; Bilzon, J L J

    2015-01-01

    To assess the error in predicting physical activity energy expenditure (PAEE), using a multisensor device in wheelchair users, and to examine the efficacy of using an individual heart rate calibration (IC) method. 15 manual wheelchair users (36±10 years, 72±11 kg) completed 10 activities: resting, folding clothes, wheelchair propulsion on a 1% gradient (3456 and 7 km/h) and propulsion at 4 km/h (with an additional 8% of body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. Criterion PAEE was measured using a computerised indirect calorimetry system. Participants wore a combined accelerometer and heart rate monitor (Actiheart). They also performed an incremental arm crank ergometry test to exhaustion which permitted retrospective individual calibration of the Actiheart for the activity protocol. Linear regression analysis was conducted between criterion (indirect calorimetry) and estimated PAEE from the Actiheart using the manufacturer's proprietary algorithms (group calibration, GC) or IC. Bland-Altman plots were used and mean absolute error was calculated to assess the agreement between criterion values and estimated PAEE. Predicted PAEE was significantly (p<0.01) correlated with criterion PAEE (GC, r=0.76 and IC, r=0.95). The absolute bias ±95% limits of agreement were 0.51±3.75 and -0.22±0.96 kcal/min for GC and IC, respectively. Mean absolute errors across the activity protocol were 51.4±38.9% using GC and 16.8±15.8% using IC. PAEE can be accurately and precisely estimated using a combined accelerometer and heart rate monitor device, with integration of an IC. Interindividual variance in cardiovascular function and response to exercise is high in this population. Therefore, in manual wheelchair users, we advocate the use of an IC when using the Actiheart to predict PAEE.

  1. Attitudes toward physical activity and exercise: comparison of memory clinic patients and their caregivers and prediction of activity levels.

    Science.gov (United States)

    O'Connell, Megan E; Dal Bello-Haas, Vanina; Crossley, Margaret; Morgan, Debra G

    2015-01-01

    Regular physical activity and exercise (PA&E) reduces cognitive aging, may delay dementia onset, and for persons with dementia, may slow progression and improve quality of life. Memory clinic patients and caregivers described their PA&E and completed the Older Persons' Attitudes Toward Physical Activity and Exercise Questionnaire (OPAPAEQ). Caregivers and patients differed in their PA&E attitudes: patients were less likely to believe in the importance of PA&E for health promotion. PA&E attitudes were explored as predictors of self-reported exercise habits. Belief in the importance of high intensity exercise for health maintenance was the only variable that significantly predicted engagement in regular PA&E. Moreover, caregivers' attitudes toward high intensity exercise predicted memory patients' participation in PA&E. These findings may aid in development of exercise interventions for people with memory problems, and suggest that modification of specific attitudes toward exercise is an important component to ensure maximum participation and engagement in PA&E.

  2. Perceived competence and enjoyment in predicting students' physical activity and cardiorespiratory fitness.

    Science.gov (United States)

    Gao, Zan

    2008-10-01

    This study investigated the predictive strength of perceived competence and enjoyment on students' physical activity and cardiorespiratory fitness in physical education classes. Participants (N = 307; 101 in Grade 6, 96 in Grade 7, 110 in Grade 8; 149 boys, 158 girls) responded to questionnaires assessing perceived competence and enjoyment of physical education, then their cardiorespiratory fitness was assessed on the Progressive Aerobic Cardiovascular Endurance Run (PACER) test. Physical activity in one class was estimated via pedometers. Regression analyses showed enjoyment (R2 = 16.5) and perceived competence (R2 = 4.2) accounted for significant variance of only 20.7% of physical activity and, perceived competence was the only significant contributor to cardiorespiratory fitness performance (R2 = 19.3%). Only a small amount of variance here leaves 80% unaccounted for. Some educational implications and areas for research are mentioned.

  3. Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

    2017-01-01

    This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....

  4. Ventral striatum activation to prosocial rewards predicts longitudinal declines in adolescent risk taking.

    Science.gov (United States)

    Telzer, Eva H; Fuligni, Andrew J; Lieberman, Matthew D; Galván, Adriana

    2013-01-01

    Adolescence is a period of intensified emotions and an increase in motivated behaviors and passions. Evidence from developmental neuroscience suggests that this heightened emotionality occurs, in part, due to a peak in functional reactivity to rewarding stimuli, which renders adolescents more oriented toward reward-seeking behaviors. Most prior work has focused on how reward sensitivity may create vulnerabilities, leading to increases in risk taking. Here, we test whether heightened reward sensitivity may potentially be an asset for adolescents when engaged in prosocial activities. Thirty-two adolescents were followed over a one-year period to examine whether ventral striatum activation to prosocial rewards predicts decreases in risk taking over a year. Results show that heightened ventral striatum activation to prosocial stimuli relates to longitudinal declines in risk taking. Therefore, the very same neural region that has conferred vulnerability for adolescent risk taking may also be protective against risk taking. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. Antecedent occipital alpha band activity predicts the impact of oculomotor events in perceptual switching

    Directory of Open Access Journals (Sweden)

    Hironori eNakatani

    2013-05-01

    Full Text Available Oculomotor events such as blinks and saccades transiently interrupt the visual input and, even though this mostly goes undetected, these brief interruptions could still influence the percept. In particular, both blinking and saccades facilitate switching in ambiguous figures such as the Necker cube. To investigate the neural state antecedent to these oculomotor events during the perception of an ambiguous figure, we measured the human scalp electroencephalogram (EEG. When blinking led to perceptual switching, antecedent occipital alpha band activity exhibited a transient increase in amplitude. When a saccade led to switching, a series of transient increases and decreases in amplitude was observed in the antecedent occipital alpha band activity. Our results suggest that the state of occipital alpha band activity predicts the impact of oculomotor events on the percept.

  6. Higher frequency network activity flow predicts lower frequency node activity in intrinsic low-frequency BOLD fluctuations.

    Science.gov (United States)

    Bajaj, Sahil; Adhikari, Bhim Mani; Dhamala, Mukesh

    2013-01-01

    The brain remains electrically and metabolically active during resting conditions. The low-frequency oscillations (LFO) of the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI) coherent across distributed brain regions are known to exhibit features of this activity. However, these intrinsic oscillations may undergo dynamic changes in time scales of seconds to minutes during resting conditions. Here, using wavelet-transform based time-frequency analysis techniques, we investigated the dynamic nature of default-mode networks from intrinsic BOLD signals recorded from participants maintaining visual fixation during resting conditions. We focused on the default-mode network consisting of the posterior cingulate cortex (PCC), the medial prefrontal cortex (mPFC), left middle temporal cortex (LMTC) and left angular gyrus (LAG). The analysis of the spectral power and causal flow patterns revealed that the intrinsic LFO undergo significant dynamic changes over time. Dividing the frequency interval 0 to 0.25 Hz of LFO into four intervals slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz), we further observed significant positive linear relationships of slow-4 in-out flow of network activity with slow-5 node activity, and slow-3 in-out flow of network activity with slow-4 node activity. The network activity associated with respiratory related frequency (slow-2) was found to have no relationship with the node activity in any of the frequency intervals. We found that the net causal flow towards a node in slow-3 band was correlated with the number of fibers, obtained from diffusion tensor imaging (DTI) data, from the other nodes connecting to that node. These findings imply that so-called resting state is not 'entirely' at rest, the higher frequency network activity flow can predict the lower frequency node activity, and the network activity flow can reflect underlying structural

  7. Predicting the activity coefficients of free-solvent for concentrated globular protein solutions using independently determined physical parameters.

    Directory of Open Access Journals (Sweden)

    Devin W McBride

    Full Text Available The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations.

  8. Reading a suspenseful literary text activates brain areas related to social cognition and predictive inference.

    Directory of Open Access Journals (Sweden)

    Moritz Lehne

    Full Text Available Stories can elicit powerful emotions. A key emotional response to narrative plots (e.g., novels, movies, etc. is suspense. Suspense appears to build on basic aspects of human cognition such as processes of expectation, anticipation, and prediction. However, the neural processes underlying emotional experiences of suspense have not been previously investigated. We acquired functional magnetic resonance imaging (fMRI data while participants read a suspenseful literary text (E.T.A. Hoffmann's "The Sandman" subdivided into short text passages. Individual ratings of experienced suspense obtained after each text passage were found to be related to activation in the medial frontal cortex, bilateral frontal regions (along the inferior frontal sulcus, lateral premotor cortex, as well as posterior temporal and temporo-parietal areas. The results indicate that the emotional experience of suspense depends on brain areas associated with social cognition and predictive inference.

  9. Design and analysis of a model predictive controller for active queue management.

    Science.gov (United States)

    Wang, Ping; Chen, Hong; Yang, Xiaoping; Ma, Yan

    2012-01-01

    Model predictive (MP) control as a novel active queue management (AQM) algorithm in dynamic computer networks is proposed. According to the predicted future queue length in the data buffer, early packets at the router are dropped reasonably by the MPAQM controller so that the queue length reaches the desired value with minimal tracking error. The drop probability is obtained by optimizing the network performance. Further, randomized algorithms are applied to analyze the robustness of MPAQM successfully, and also to provide the stability domain of systems with uncertain network parameters. The performances of MPAQM are evaluated through a series of simulations in NS2. The simulation results show that the MPAQM algorithm outperforms RED, PI, and REM algorithms in terms of stability, disturbance rejection, and robustness. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  10. Analysis Of The Method Of Predictive Control Applicable To Active Magnetic Suspension Systems Of Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Kurnyta-Mazurek Paulina

    2015-12-01

    Full Text Available Conventional controllers are usually synthesized on the basis of already known parameters associated with the model developed for the object to be controlled. However, sometimes it proves extremely difficult or even infeasible to find out these parameters, in particular when they subject to changes during the exploitation lifetime. If so, much more sophisticated control methods have to be applied, e.g. the method of predictive control. Thus, the paper deals with application of the predictive control approach to follow-up tracking of an active magnetic suspension where the mathematical and simulation models for such a control system are disclosed with preliminary results from simulation investigations of the control system in question.

  11. Predicting the activity of drugs for a group of imidazopyridine anticoccidial compounds.

    Science.gov (United States)

    Si, Hongzong; Lian, Ning; Yuan, Shuping; Fu, Aiping; Duan, Yun-Bo; Zhang, Kejun; Yao, Xiaojun

    2009-10-01

    Gene expression programming (GEP) is a novel machine learning technique. The GEP is used to build nonlinear quantitative structure-activity relationship model for the prediction of the IC(50) for the imidazopyridine anticoccidial compounds. This model is based on descriptors which are calculated from the molecular structure. Four descriptors are selected from the descriptors' pool by heuristic method (HM) to build multivariable linear model. The GEP method produced a nonlinear quantitative model with a correlation coefficient and a mean error of 0.96 and 0.24 for the training set, 0.91 and 0.52 for the test set, respectively. It is shown that the GEP predicted results are in good agreement with experimental ones.

  12. Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of Amaryllidaceae

    DEFF Research Database (Denmark)

    Rønsted, Nina; Symonds, Matthew R. E.; Birkholm, Trine

    2012-01-01

    a predictive approach enabling more efficient selection of plants for the development of traditional medicine and lead discovery. However, this relationship has rarely been rigorously tested and the potential predictive power is consequently unknown. Results: We produced a phylogenetic hypothesis......Background: During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer...... for the medicinally important plant subfamily Amaryllidoideae (Amaryllidaceae) based on parsimony and Bayesian analysis of nuclear, plastid, and mitochondrial DNA sequences of over 100 species. We tested if alkaloid diversity and activity in bioassays related to the central nervous system are significantly correlated...

  13. Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness.

    Science.gov (United States)

    Verikas, Antanas; Vaiciukynas, Evaldas; Gelzinis, Adas; Parker, James; Olsson, M Charlotte

    2016-04-23

    This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features

  14. Predictive value of European Scleroderma Group Activity Index in an early scleroderma cohort.

    Science.gov (United States)

    Nevskaya, Tatiana; Baron, Murray; Pope, Janet E

    2017-07-01

    To estimate the effect of disease activity, as measured by the European Scleroderma Research Group Activity Index (EScSG-AI), on the risk of subsequent organ damage in a large systemic sclerosis (SSc) cohort. Of 421 SSc patients from the Canadian Scleroderma Research Group database with disease duration of ⩽ 3 years, 197 who had no evidence of end-stage organ damage initially and available 3 year follow-up were included. Disease activity was assessed by the EScSG-AI with two variability measures: the adjusted mean EScSG-AI (the area under the curve of the EScSG-AI over the observation period) and persistently active disease/flare. Outcomes were based on the Medsger severity scale and included accrual of a new severity score (Δ ⩾ 1) overall and within organ systems or reaching a significant level of deterioration in health status. After adjustment for covariates, the adjusted mean EScSG-AI was the most consistent predictor of risk across the study outcomes over 3 years in dcSSc: disease progression defined as Δ ⩾ 1 in any major internal organ, significant decline in forced vital capacity and diffusing capacity of carbon monoxide, severity of visceral disease and HAQ Disability Index worsening. In multivariate analysis, progression of lung disease was predicted solely by adjusted mean EScSG-AI, while the severity of lung disease was predicted the adjusted mean EScSG-AI, older age, modified Rodnan skin score (mRSS) and initial severity. The EScSG-AI was associated with patient- and physician-assessed measures of health status and overpowered the mRSS in predicting disease outcomes. Disease activity burden quantified with the adjusted mean EScSG-AI predicted the risk of deterioration in health status and severe organ involvement in dcSSc. The EScSG-AI is more responsive when done repeatedly and averaged. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email

  15. Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness

    Directory of Open Access Journals (Sweden)

    Antanas Verikas

    2016-04-01

    Full Text Available This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each. The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG

  16. Seasonal prediction of lightning activity in North Western Venezuela: Large-scale versus local drivers

    Science.gov (United States)

    Muñoz, Á. G.; Díaz-Lobatón, J.; Chourio, X.; Stock, M. J.

    2016-05-01

    The Lake Maracaibo Basin in North Western Venezuela has the highest annual lightning rate of any place in the world (~ 200 fl km- 2 yr- 1), whose electrical discharges occasionally impact human and animal lives (e.g., cattle) and frequently affect economic activities like oil and natural gas exploitation. Lightning activity is so common in this region that it has a proper name: Catatumbo Lightning (plural). Although short-term lightning forecasts are now common in different parts of the world, to the best of the authors' knowledge, seasonal prediction of lightning activity is still non-existent. This research discusses the relative role of both large-scale and local climate drivers as modulators of lightning activity in the region, and presents a formal predictability study at seasonal scale. Analysis of the Catatumbo Lightning Regional Mode, defined in terms of the second Empirical Orthogonal Function of monthly Lightning Imaging Sensor (LIS-TRMM) and Optical Transient Detector (OTD) satellite data for North Western South America, permits the identification of potential predictors at seasonal scale via a Canonical Correlation Analysis. Lightning activity in North Western Venezuela responds to well defined sea-surface temperature patterns (e.g., El Niño-Southern Oscillation, Atlantic Meridional Mode) and changes in the low-level meridional wind field that are associated with the Inter-Tropical Convergence Zone migrations, the Caribbean Low Level Jet and tropical cyclone activity, but it is also linked to local drivers like convection triggered by the topographic configuration and the effect of the Maracaibo Basin Nocturnal Low Level Jet. The analysis indicates that at seasonal scale the relative contribution of the large-scale drivers is more important than the local (basin-wide) ones, due to the synoptic control imposed by the former. Furthermore, meridional CAPE transport at 925 mb is identified as the best potential predictor for lightning activity in the Lake

  17. Active Mirror Predictive and Requirements Verification Software (AMP-ReVS)

    Science.gov (United States)

    Basinger, Scott A.

    2012-01-01

    This software is designed to predict large active mirror performance at various stages in the fabrication lifecycle of the mirror. It was developed for 1-meter class powered mirrors for astronomical purposes, but is extensible to other geometries. The package accepts finite element model (FEM) inputs and laboratory measured data for large optical-quality mirrors with active figure control. It computes phenomenological contributions to the surface figure error using several built-in optimization techniques. These phenomena include stresses induced in the mirror by the manufacturing process and the support structure, the test procedure, high spatial frequency errors introduced by the polishing process, and other process-dependent deleterious effects due to light-weighting of the mirror. Then, depending on the maturity of the mirror, it either predicts the best surface figure error that the mirror will attain, or it verifies that the requirements for the error sources have been met once the best surface figure error has been measured. The unique feature of this software is that it ties together physical phenomenology with wavefront sensing and control techniques and various optimization methods including convex optimization, Kalman filtering, and quadratic programming to both generate predictive models and to do requirements verification. This software combines three distinct disciplines: wavefront control, predictive models based on FEM, and requirements verification using measured data in a robust, reusable code that is applicable to any large optics for ground and space telescopes. The software also includes state-of-the-art wavefront control algorithms that allow closed-loop performance to be computed. It allows for quantitative trade studies to be performed for optical systems engineering, including computing the best surface figure error under various testing and operating conditions. After the mirror manufacturing process and testing have been completed, the

  18. Lupus anticoagulant, disease activity and low complement in the first trimester are predictive of pregnancy loss.

    Science.gov (United States)

    Mankee, Anil; Petri, Michelle; Magder, Laurence S

    2015-01-01

    Multiple factors, including proteinuria, antiphospholipid syndrome, thrombocytopenia and hypertension, are predictive of pregnancy loss in systemic lupus erythematosus (SLE). In the PROMISSE study of predictors of pregnancy loss, only a battery of lupus anticoagulant tests was predictive of a composite of adverse pregnancy outcomes. We examined the predictive value of one baseline lupus anticoagulant test (dilute Russell viper venom time) with pregnancy loss in women with SLE. From the Hopkins Lupus Cohort, there were 202 pregnancies from 175 different women after excluding twin pregnancies and pregnancies for which we did not have a first trimester assessment of lupus anticoagulant. We determined the percentage of women who had a pregnancy loss in groups defined by potential risk factors. The lupus anticoagulant was determined by dilute Russell viper venom time with appropriate mixing and confirmatory testing. Generalised estimating equations were used to calculate p values, accounting for repeated pregnancies in the same woman. The age at pregnancy was 40 (3%). 55% were Caucasian and 34% African-American. Among those with lupus anticoagulant during the first trimester, 6/16 (38%) experienced a pregnancy loss compared with only 16/186 (9%) of other pregnancies (p=0.003). In addition, those with low complement or higher disease activity had a higher rate of pregnancy loss than those without (p=0.049 and 0.005, respectively). In contrast, there was no association between elevated anticardiolipin in the first trimester and pregnancy loss. The strongest predictor of pregnancy loss in SLE in the first trimester is the lupus anticoagulant. In addition, moderate disease activity by the physician global assessment and low complement measured in the first trimester were predictive of pregnancy loss. These data suggest that treatment of the lupus anticoagulant could be considered, even in the absence of history of pregnancy loss.

  19. Quantitative structure activity relationship for the computational prediction of nitrocompounds carcinogenicity

    International Nuclear Information System (INIS)

    Morales, Aliuska Helguera; Perez, Miguel Angel Cabrera; Combes, Robert D.; Gonzalez, Maykel Perez

    2006-01-01

    Several nitrocompounds have been screened for carcinogenicity in rodents, but this is a lengthy and expensive process, taking two years and typically costing 2.5 million dollars, and uses large numbers of animals. There is, therefore, much impetus to develop suitable alternative methods. One possible way of predicting carcinogenicity is to use quantitative structure-activity relationships (QSARs). QSARs have been widely utilized for toxicity testing, thereby contributing to a reduction in the need for experimental animals. This paper describes the results of applying a TOPological substructural molecular design (TOPS-MODE) approach for predicting the rodent carcinogenicity of nitrocompounds. The model described 79.10% of the experimental variance, with a standard deviation of 0.424. The predictive power of the model was validated by leave-one-out validation, with a determination coefficient of 0.666. In addition, this approach enabled the contribution of different fragments to carcinogenic potency to be assessed, thereby making the relationships between structure and carcinogenicity to be transparent. It was found that the carcinogenic activity of the chemicals analysed was increased by the presence of a primary amine group bonded to the aromatic ring, a manner that was proportional to the ring aromaticity. The nitro group bonded to an aromatic carbon atom is a more important determinant of carcinogenicity than the nitro group bonded to an aliphatic carbon. Finally, the TOPS-MODE approach was compared with four other predictive models, but none of these could explain more than 66% of the variance in the carcinogenic potency with the same number of variables

  20. Decreased activation and subsyndromal manic symptoms predict lower remission rates in bipolar depression.

    Science.gov (United States)

    Caldieraro, Marco Antonio; Walsh, Samantha; Deckersbach, Thilo; Bobo, William V; Gao, Keming; Ketter, Terence A; Shelton, Richard C; Reilly-Harrington, Noreen A; Tohen, Mauricio; Calabrese, Joseph R; Thase, Michael E; Kocsis, James H; Sylvia, Louisa G; Nierenberg, Andrew A

    2017-11-01

    Activation encompasses energy and activity and is a central feature of bipolar disorder. However, the impact of activation on treatment response of bipolar depression requires further exploration. The aims of this study were to assess the association of decreased activation and sustained remission in bipolar depression and test for factors that could affect this association. We assessed participants with Diagnostic and Statistical Manual of Mental Disorders (4th ed) bipolar depression ( n = 303) included in a comparative effectiveness study of lithium- and quetiapine-based treatments (the Bipolar CHOICE study). Activation was evaluated using items from the Bipolar Inventory of Symptoms Scale. The selection of these items was based on a dimension of energy and interest symptoms associated with poorer treatment response in major depression. Decreased activation was associated with lower remission rates in the raw analyses and in a logistic regression model adjusted for baseline severity and subsyndromal manic symptoms (odds ratio = 0.899; p = 0.015). The manic features also predicted lower remission (odds ratio = 0.934; p bipolar depression. Patients with these features may require specific treatment approaches, but new studies are necessary to identify treatments that could improve outcomes in this population.

  1. Modeling and Predicting the Daily Equatorial Plasma Bubble Activity Using the Tiegcm

    Science.gov (United States)

    Carter, B. A.; Retterer, J. M.; Yizengaw, E.; Wiens, K. C.; Wing, S.; Groves, K. M.; Caton, R. G.; Bridgwood, C.; Francis, M. J.; Terkildsen, M. B.; Norman, R.; Zhang, K.

    2014-12-01

    Describing and understanding the daily variability of Equatorial Plasma Bubble (EPB) occurrence has remained a significant challenge over recent decades. In this study we use the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM), which is driven by solar (F10.7) and geomagnetic (Kp) activity indices, to study daily variations of the linear Rayleigh-Taylor (R-T) instability growth rate in relation to the measured scintillation strength at five longitudinally distributed stations. For locations characterized by generally favorable conditions for EPB growth (i.e., within the scintillation season for that location) we find that the TIEGCM is capable of identifying days when EPB development, determined from the calculated R-T growth rate, is suppressed as a result of geomagnetic activity. Both observed and modeled upward plasma drift indicate that the pre-reversal enhancement scales linearly with Kp from several hours prior, from which it is concluded that even small Kp changes cause significant variations in daily EPB growth. This control of Kp variations on EPB growth prompted an investigation into the use of predicted Kp values from the Wing Kp model over a 2-month equinoctial campaign in 2014. It is found that both the 1-hr and 4-hr predicted Kp values can be reliably used as inputs into the TIEGCM to forecast the EPB growth conditions during scintillation season, when daily EPB variability is governed by the suppression of EPBs on days with increased, but not necessarily high, geomagnetic activity.

  2. vmPFC activation during a stressor predicts positive emotions during stress recovery

    Science.gov (United States)

    Yang, Xi; Garcia, Katelyn M; Jung, Youngkyoo; Whitlow, Christopher T; McRae, Kateri; Waugh, Christian E

    2018-01-01

    Abstract Despite accruing evidence showing that positive emotions facilitate stress recovery, the neural basis for this effect remains unclear. To identify the underlying mechanism, we compared stress recovery for people reflecting on a stressor while in a positive emotional context with that for people in a neutral context. While blood–oxygen-level dependent data were being collected, participants (N = 43) performed a stressful anagram task, which was followed by a recovery period during which they reflected on the stressor while watching a positive or neutral video. Participants also reported positive and negative emotions throughout the task as well as retrospective thoughts about the task. Although there was no effect of experimental context on emotional recovery, we found that ventromedial prefrontal cortex (vmPFC) activation during the stressor predicted more positive emotions during recovery, which in turn predicted less negative emotions during recovery. In addition, the relationship between vmPFC activation and positive emotions during recovery was mediated by decentering—the meta-cognitive detachment of oneself from one’s feelings. In sum, successful recovery from a stressor seems to be due to activation of positive emotion-related regions during the stressor itself as well as to their downstream effects on certain cognitive forms of emotion regulation. PMID:29462404

  3. ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

    Energy Technology Data Exchange (ETDEWEB)

    Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

    2009-02-01

    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

  4. Prediction-error in the context of real social relationships modulates reward system activity

    Directory of Open Access Journals (Sweden)

    Joshua ePoore

    2012-08-01

    Full Text Available The human reward system is sensitive to both social (e.g., validation and non-social rewards (e.g., money and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward—social validation—and this activity’s relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants’ expectations for their romantic partners’ positive regard of them were confirmed (validated or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust.

  5. Cortical ensemble activity increasingly predicts behaviour outcomes during learning of a motor task

    Science.gov (United States)

    Laubach, Mark; Wessberg, Johan; Nicolelis, Miguel A. L.

    2000-06-01

    When an animal learns to make movements in response to different stimuli, changes in activity in the motor cortex seem to accompany and underlie this learning. The precise nature of modifications in cortical motor areas during the initial stages of motor learning, however, is largely unknown. Here we address this issue by chronically recording from neuronal ensembles located in the rat motor cortex, throughout the period required for rats to learn a reaction-time task. Motor learning was demonstrated by a decrease in the variance of the rats' reaction times and an increase in the time the animals were able to wait for a trigger stimulus. These behavioural changes were correlated with a significant increase in our ability to predict the correct or incorrect outcome of single trials based on three measures of neuronal ensemble activity: average firing rate, temporal patterns of firing, and correlated firing. This increase in prediction indicates that an association between sensory cues and movement emerged in the motor cortex as the task was learned. Such modifications in cortical ensemble activity may be critical for the initial learning of motor tasks.

  6. High-Throughput Gene Expression Profiles to Define Drug Similarity and Predict Compound Activity.

    Science.gov (United States)

    De Wolf, Hans; Cougnaud, Laure; Van Hoorde, Kirsten; De Bondt, An; Wegner, Joerg K; Ceulemans, Hugo; Göhlmann, Hinrich

    2018-04-01

    By adding biological information, beyond the chemical properties and desired effect of a compound, uncharted compound areas and connections can be explored. In this study, we add transcriptional information for 31K compounds of Janssen's primary screening deck, using the HT L1000 platform and assess (a) the transcriptional connection score for generating compound similarities, (b) machine learning algorithms for generating target activity predictions, and (c) the scaffold hopping potential of the resulting hits. We demonstrate that the transcriptional connection score is best computed from the significant genes only and should be interpreted within its confidence interval for which we provide the stats. These guidelines help to reduce noise, increase reproducibility, and enable the separation of specific and promiscuous compounds. The added value of machine learning is demonstrated for the NR3C1 and HSP90 targets. Support Vector Machine models yielded balanced accuracy values ≥80% when the expression values from DDIT4 & SERPINE1 and TMEM97 & SPR were used to predict the NR3C1 and HSP90 activity, respectively. Combining both models resulted in 22 new and confirmed HSP90-independent NR3C1 inhibitors, providing two scaffolds (i.e., pyrimidine and pyrazolo-pyrimidine), which could potentially be of interest in the treatment of depression (i.e., inhibiting the glucocorticoid receptor (i.e., NR3C1), while leaving its chaperone, HSP90, unaffected). As such, the initial hit rate increased by a factor 300, as less, but more specific chemistry could be screened, based on the upfront computed activity predictions.

  7. Successful emotion regulation is predicted by amygdala activity and aspects of personality: A latent variable approach.

    Science.gov (United States)

    Morawetz, Carmen; Alexandrowicz, Rainer W; Heekeren, Hauke R

    2017-04-01

    The experience of emotions and their cognitive control are based upon neural responses in prefrontal and subcortical regions and could be affected by personality and temperamental traits. Previous studies established an association between activity in reappraisal-related brain regions (e.g., inferior frontal gyrus and amygdala) and emotion regulation success. Given these relationships, we aimed to further elucidate how individual differences in emotion regulation skills relate to brain activity within the emotion regulation network on the one hand, and personality/temperamental traits on the other. We directly examined the relationship between personality and temperamental traits, emotion regulation success and its underlying neuronal network in a large sample (N = 82) using an explicit emotion regulation task and functional MRI (fMRI). We applied a multimethodological analysis approach, combing standard activation-based analyses with structural equation modeling. First, we found that successful downregulation is predicted by activity in key regions related to emotion processing. Second, the individual ability to successfully upregulate emotions is strongly associated with the ability to identify feelings, conscientiousness, and neuroticism. Third, the successful downregulation of emotion is modulated by openness to experience and habitual use of reappraisal. Fourth, the ability to regulate emotions is best predicted by a combination of brain activity and personality as well temperamental traits. Using a multimethodological analysis approach, we provide a first step toward a causal model of individual differences in emotion regulation ability by linking biological systems underlying emotion regulation with descriptive constructs. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  8. Distributed Model Predictive Control for Active Power Control of Wind Farm

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

    2014-01-01

    This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

  9. Predicting above normal wildfire activity in southern Europe as a function of meteorological drought

    International Nuclear Information System (INIS)

    Gudmundsson, L; Seneviratne, S I; Rego, F C; Rocha, M

    2014-01-01

    Wildfires are a recurrent feature of ecosystems in southern Europe, regularly causing large ecological and socio-economic damages. For efficient management of this hazard, long lead time forecasts could be valuable tools. Using logistic regression, we show that the probability of above normal summer wildfire activity in the 1985–2010 time period can be forecasted as a function of meteorological drought with significant predictability (p <0.05) several months in advance. The results show that long lead time forecasts of this natural hazard are feasible in southern Europe, which could potentially aid decision-makers in the design of strategies for forest management. (letter)

  10. Active load management in an intelligent building using model predictive control strategy

    DEFF Research Database (Denmark)

    Zong, Yi; Kullmann, Daniel; Thavlov, Anders

    2011-01-01

    This paper introduces PowerFlexHouse, a research facility for exploring the technical potential of active load management in a distributed power system (SYSLAB) with a high penetration of renewable energy and presents in detail on how to implement a thermal model predictive controller for load...... shifting in PowerFlexHouse heaters' power consumption scheme. With this demand side control study, it is expected that this method of demand response can dramatically raise energy efficiencies and improve grid reliability, when there is a high penetration of intermittent energy resources in the power...

  11. Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

    Science.gov (United States)

    Kim, Hui Kwon; Min, Seonwoo; Song, Myungjae; Jung, Soobin; Choi, Jae Woo; Kim, Younggwang; Lee, Sangeun; Yoon, Sungroh; Kim, Hyongbum Henry

    2018-03-01

    We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

  12. Motor Skill Competence and Perceived Motor Competence: Which Best Predicts Physical Activity among Girls?

    OpenAIRE

    Khodaverdi, Zeinab; Bahram, Abbas; Khalaji, Hassan; Kazemnejad, Anoshirvan

    2013-01-01

    Abstract Background The main purpose of this study was to determine which correlate, perceived motor competence or motor skill competence, best predicts girls? physical activity behavior. Methods A sample of 352 girls (mean age=8.7, SD=0.3 yr) participated in this study. To assess motor skill competence and perceived motor competence, each child completed the Test of Gross Motor Development-2 and Physical Ability sub-scale of Marsh?s Self-Description Questionnaire. Children?s physical activit...

  13. Prediction of Optimal Daily Step Count Achievement from Segmented School Physical Activity

    Directory of Open Access Journals (Sweden)

    Ryan D. Burns

    2015-01-01

    Full Text Available Optimizing physical activity in childhood is needed for prevention of disease and for healthy social and psychological development. There is limited research examining how segmented school physical activity patterns relate to a child achieving optimal physical activity levels. The purpose of this study was to examine the predictive relationship between step counts during specific school segments and achieving optimal school (6,000 steps/day and daily (12,000 steps/day step counts in children. Participants included 1,714 school-aged children (mean age = 9.7±1.0 years recruited across six elementary schools. Physical activity was monitored for one week using pedometers. Generalized linear mixed effects models were used to determine the adjusted odds ratios (ORs of achieving both school and daily step count standards for every 1,000 steps taken during each school segment. The school segment that related in strongest way to a student achieving 6,000 steps during school hours was afternoon recess (OR = 40.03; P<0.001 and for achieving 12,000 steps for the entire day was lunch recess (OR = 5.03; P<0.001. School segments including lunch and afternoon recess play an important role for optimizing daily physical activity in children.

  14. Predicting mountain lion activity using radiocollars equipped with mercury tip-sensors

    Science.gov (United States)

    Janis, Michael W.; Clark, Joseph D.; Johnson, Craig

    1999-01-01

    Radiotelemetry collars with tip-sensors have long been used to monitor wildlife activity. However, comparatively few researchers have tested the reliability of the technique on the species being studied. To evaluate the efficacy of using tip-sensors to assess mountain lion (Puma concolor) activity, we radiocollared 2 hand-reared mountain lions and simultaneously recorded their behavior and the associated telemetry signal characteristics. We noted both the number of pulse-rate changes and the percentage of time the transmitter emitted a fast pulse rate (i.e., head up) within sampling intervals ranging from 1-5 minutes. Based on 27 hours of observations, we were able to correctly distinguish between active and inactive behaviors >93% of the time using a logistic regression model. We present several models to predict activity of mountain lions; the selection of which to us would depend on study objectives and logistics. Our results indicate that field protocols that use only pulse-rate changes to indicate activity can lead to significant classification errors.

  15. Antioxidant defense parameters as predictive biomarkers for fermentative capacity of active dried wine yeast.

    Science.gov (United States)

    Gamero-Sandemetrio, Esther; Gómez-Pastor, Rocío; Matallana, Emilia

    2014-08-01

    The production of active dried yeast (ADY) is a common practice in industry for the maintenance of yeast starters and as a means of long term storage. The process, however, causes multiple cell injuries, with oxidative damage being one of the most important stresses. Consequentially, dehydration tolerance is a highly appreciated property in yeast for ADY production. In this study we analyzed the cellular redox environment in three Saccharomyces cerevisiae wine strains, which show markedly different fermentative capacities after dehydration. To measure/quantify the effect of dehydration on the S. cerevisiae strains, we used: (i) fluorescent probes; (ii) antioxidant enzyme activities; (ii) intracellular damage; (iii) antioxidant metabolites; and (iv) gene expression, to select a minimal set of biochemical parameters capable of predicting desiccation tolerance in wine yeasts. Our results show that naturally enhanced antioxidant defenses prevent oxidative damage after wine yeast biomass dehydration and improve fermentative capacity. Based on these results we chose four easily assayable parameters/biomarkers for the selection of industrial yeast strains of interest for ADY production: trehalose and glutathione levels, and glutathione reductase and catalase enzymatic activities. Yeast strains selected in accordance with this process display high levels of trehalose, low levels of oxidized glutathione, a high induction of glutathione reductase activity, as well as a high basal level and sufficient induction of catalase activity, which are properties inherent in superior ADY strains. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers

    International Nuclear Information System (INIS)

    Ellis, Katherine; Lanckriet, Gert; Kerr, Jacqueline; Godbole, Suneeta; Wing, David; Marshall, Simon

    2014-01-01

    Wrist accelerometers are being used in population level surveillance of physical activity (PA) but more research is needed to evaluate their validity for correctly classifying types of PA behavior and predicting energy expenditure (EE). In this study we compare accelerometers worn on the wrist and hip, and the added value of heart rate (HR) data, for predicting PA type and EE using machine learning. Forty adults performed locomotion and household activities in a lab setting while wearing three ActiGraph GT3X+ accelerometers (left hip, right hip, non-dominant wrist) and a HR monitor (Polar RS400). Participants also wore a portable indirect calorimeter (COSMED K4b2), from which EE and metabolic equivalents (METs) were computed for each minute. We developed two predictive models: a random forest classifier to predict activity type and a random forest of regression trees to estimate METs. Predictions were evaluated using leave-one-user-out cross-validation. The hip accelerometer obtained an average accuracy of 92.3% in predicting four activity types (household, stairs, walking, running), while the wrist accelerometer obtained an average accuracy of 87.5%. Across all 8 activities combined (laundry, window washing, dusting, dishes, sweeping, stairs, walking, running), the hip and wrist accelerometers obtained average accuracies of 70.2% and 80.2% respectively. Predicting METs using the hip or wrist devices alone obtained root mean square errors (rMSE) of 1.09 and 1.00 METs per 6 min bout, respectively. Including HR data improved MET estimation, but did not significantly improve activity type classification. These results demonstrate the validity of random forest classification and regression forests for PA type and MET prediction using accelerometers. The wrist accelerometer proved more useful in predicting activities with significant arm movement, while the hip accelerometer was superior for predicting locomotion and estimating EE. (paper)

  17. A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers.

    Science.gov (United States)

    Ellis, Katherine; Kerr, Jacqueline; Godbole, Suneeta; Lanckriet, Gert; Wing, David; Marshall, Simon

    2014-11-01

    Wrist accelerometers are being used in population level surveillance of physical activity (PA) but more research is needed to evaluate their validity for correctly classifying types of PA behavior and predicting energy expenditure (EE). In this study we compare accelerometers worn on the wrist and hip, and the added value of heart rate (HR) data, for predicting PA type and EE using machine learning. Forty adults performed locomotion and household activities in a lab setting while wearing three ActiGraph GT3X+ accelerometers (left hip, right hip, non-dominant wrist) and a HR monitor (Polar RS400). Participants also wore a portable indirect calorimeter (COSMED K4b2), from which EE and metabolic equivalents (METs) were computed for each minute. We developed two predictive models: a random forest classifier to predict activity type and a random forest of regression trees to estimate METs. Predictions were evaluated using leave-one-user-out cross-validation. The hip accelerometer obtained an average accuracy of 92.3% in predicting four activity types (household, stairs, walking, running), while the wrist accelerometer obtained an average accuracy of 87.5%. Across all 8 activities combined (laundry, window washing, dusting, dishes, sweeping, stairs, walking, running), the hip and wrist accelerometers obtained average accuracies of 70.2% and 80.2% respectively. Predicting METs using the hip or wrist devices alone obtained root mean square errors (rMSE) of 1.09 and 1.00 METs per 6 min bout, respectively. Including HR data improved MET estimation, but did not significantly improve activity type classification. These results demonstrate the validity of random forest classification and regression forests for PA type and MET prediction using accelerometers. The wrist accelerometer proved more useful in predicting activities with significant arm movement, while the hip accelerometer was superior for predicting locomotion and estimating EE.

  18. Similar patterns of neural activity predict memory function during encoding and retrieval.

    Science.gov (United States)

    Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

    2017-07-15

    Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Intrinsic predictive factors for ankle sprain in active university students: a prospective study.

    Science.gov (United States)

    de Noronha, M; França, L C; Haupenthal, A; Nunes, G S

    2013-10-01

    The ankle is the joint most affected among the sports-related injuries. The current study investigated whether certain intrinsic factors could predict ankle sprains in active students. The 125 participants were submitted to a baseline assessment in a single session were then followed-up for 52 weeks regarding the occurrence of sprain. The baseline assessment were performed in both ankles and included the questionnaire Cumberland ankle instability tool - Portuguese, the foot lift test, dorsiflexion range of motion, Star Excursion Balance Test (SEBT), the side recognition task, body mass index, and history of previous sprain. Two groups were used for analysis: one with those who suffered an ankle sprain and the other with those who did not suffer an ankle sprain. After Cox regression analysis, participants with history of previous sprain were twice as likely to suffer subsequent sprains [hazard ratio (HR) 2.21 and 95% confidence interval (CI) 1.07-4.57] and people with better performance on the SEBT in the postero-lateral (PL) direction were less likely to suffer a sprain (HR 0.96 and 95% CI 0.92-0.99). History of previous sprain was the strongest predictive factor and a weak performance on SEBT PL was also considered a predictive factor for ankle sprains. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  20. Predicting personal exposure to airborne carbonyls using residential measurements and time/activity data

    Science.gov (United States)

    Liu, Weili; Zhang, Junfeng (Jim); Korn, Leo R.; Zhang, Lin; Weisel, Clifford P.; Turpin, Barbara; Morandi, Maria; Stock, Tom; Colome, Steve

    As a part of the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study, 48 h integrated residential indoor, outdoor, and personal exposure concentrations of 10 carbonyls were simultaneously measured in 234 homes selected from three US cities using the Passive Aldehydes and Ketones Samplers (PAKS). In this paper, we examine the feasibility of using residential indoor concentrations to predict personal exposures to carbonyls. Based on paired t-tests, the means of indoor concentrations were not different from those of personal exposure concentrations for eight out of the 10 measured carbonyls, indicating indoor carbonyls concentrations, in general, well predicted the central tendency of personal exposure concentrations. In a linear regression model, indoor concentrations explained 47%, 55%, and 65% of personal exposure variance for formaldehyde, acetaldehyde, and hexaldehyde, respectively. The predictability of indoor concentrations on cross-individual variability in personal exposure for the other carbonyls was poorer, explainingexposure concentrations. It was found that activities related to driving a vehicle and performing yard work had significant impacts on personal exposures to a few carbonyls.

  1. Diabetes that impacts on routine activities predicts slower recovery after total knee arthroplasty: an observational study

    Directory of Open Access Journals (Sweden)

    Nurudeen Amusat

    2014-12-01

    . Physiotherapists could institute closer monitoring within the hospital and community settings for people undergoing TKA who perceive that diabetes impacts on their routine activities. [Amusat N, Beaupre L, Jhangri GS, Pohar SL, Simpson S, Warren S, Jones CA (2014 Diabetes that impacts on routine activities predicts slower recovery after total knee arthroplasty: an observational study. Journal of Physiotherapy 60: 217–223

  2. Fluorinated Cannabidiol Derivatives: Enhancement of Activity in Mice Models Predictive of Anxiolytic, Antidepressant and Antipsychotic Effects.

    Directory of Open Access Journals (Sweden)

    Aviva Breuer

    Full Text Available Cannabidiol (CBD is a major Cannabis sativa constituent, which does not cause the typical marijuana psychoactivity. However, it has been shown to be active in a numerous pharmacological assays, including mice tests for anxiety, obsessive-compulsive disorder, depression and schizophrenia. In human trials the doses of CBD needed to achieve effects in anxiety and schizophrenia are high. We report now the synthesis of 3 fluorinated CBD derivatives, one of which, 4'-F-CBD (HUF-101 (1, is considerably more potent than CBD in behavioral assays in mice predictive of anxiolytic, antidepressant, antipsychotic and anti-compulsive activity. Similar to CBD, the anti-compulsive effects of HUF-101 depend on cannabinoid receptors.

  3. The Functional Movement Screen and Injury Risk: Association and Predictive Value in Active Men.

    Science.gov (United States)

    Bushman, Timothy T; Grier, Tyson L; Canham-Chervak, Michelle; Anderson, Morgan K; North, William J; Jones, Bruce H

    2016-02-01

    The Functional Movement Screen (FMS) is a series of 7 tests used to assess the injury risk in active populations. To determine the association of the FMS with the injury risk, assess predictive values, and identify optimal cut points using 3 injury types. Cohort study; Level of evidence, 2. Physically active male soldiers aged 18 to 57 years (N = 2476) completed the FMS. Demographic and fitness data were collected by survey. Medical record data for overuse injuries, traumatic injuries, and any injury 6 months after the FMS assessment were obtained. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated along with the receiver operating characteristic (ROC) to determine the area under the curve (AUC) and identify optimal cut points for the risk assessment. Risks, risk ratios (RRs), odds ratios (ORs), and 95% CIs were calculated to assess injury risks. Soldiers who scored ≤14 were at a greater risk for injuries compared with those who scored >14 using the composite score for overuse injuries (RR, 1.84; 95% CI, 1.63-2.09), traumatic injuries (RR, 1.26; 95% CI, 1.03-1.54), and any injury (RR, 1.60; 95% CI, 1.45-1.77). When controlling for other known injury risk factors, multivariate logistic regression analysis identified poor FMS performance (OR [score ≤14/19-21], 2.00; 95% CI, 1.42-2.81) as an independent risk factor for injuries. A cut point of ≤14 registered low measures of predictive value for all 3 injury types (sensitivity, 28%-37%; PPV, 19%-52%; AUC, 54%-61%). Shifting the injury risk cut point of ≤14 to the optimal cut points indicated by the ROC did not appreciably improve sensitivity or the PPV. Although poor FMS performance was associated with a higher risk of injuries, it displayed low sensitivity, PPV, and AUC. On the basis of these findings, the use of the FMS to screen for the injury risk is not recommended in this population because of the low predictive value and misclassification of the

  4. Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle.

    Science.gov (United States)

    Borchers, M R; Chang, Y M; Proudfoot, K L; Wadsworth, B A; Stone, A E; Bewley, J M

    2017-07-01

    The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (lying bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine-learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sensitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was

  5. Inhibition of Cartilage Acidic Protein 1 Reduces Ultraviolet B Irradiation Induced-Apoptosis through P38 Mitogen-Activated Protein Kinase and Jun Amino-Terminal Kinase Pathways

    Directory of Open Access Journals (Sweden)

    Yinghong Ji

    2016-11-01

    Full Text Available Background/Aims: Ultraviolet B (UVB irradiation can easily induce apoptosis in human lens epithelial cells (HLECs and further lead to various eye diseases including cataract. Here for the first time, we investigated the role of cartilage acidic protein 1 (CRTAC1 gene in UVB irradiation induced-apoptosis in HLECs. Methods: Three groups of HLECs were employed including model group, empty vector group, and CRTAC1 interference group. Results: After UVB irradiation, the percentage of primary apoptotic cells was obviously fewer in CRTAC1 interference group. Meanwhile, inhibition of CRTAC1 also reduced both reactive oxygen species (ROS production and intracellular Ca2+ concentration, but the level of mitochondrial membrane potential (Δψm was increased in HLECs. Further studies indicated that superoxide dismutase (SOD activity and total antioxidative (T-AOC level were significantly increased in CRTAC1-inhibited cells, while the levels of malondialdehyde (MDA and lactate dehydrogenase (LDH were significantly decreased. ELISA analysis of CRTAC1-inhibited cells showed that the concentrations of tumor necrosis factor-α (TNF-α and interleukin-6 (IL-6 were significantly decreased, but the concentration of interleukin-10 (IL-10 was significantly increased. Western blot analyses of eight apoptosis-associated proteins including Bax, Bcl-2, p38, phospho-p38 (p-p38, Jun amino-terminal kinases (JNK1/2, phospho-JNK1/2 (p-JNK1/2, calcium-sensing receptor (CasR, and Ca2+/calmodulin-dependent protein kinase II (CaMKII indicated that the inhibition of CRTAC1 alleviated oxidative stress and inflammation response, inactivated calcium-signaling pathway, p38 and JNK1/2 signal pathways, and eventually reduced UVB irradiation induced-apoptosis in HLECs. Conclusion: These results provided new insights into the mechanism of cataract development, and demonstrated that CRTAC1 could be a potentially novel target for cataract treatment.

  6. Inhibition of Cartilage Acidic Protein 1 Reduces Ultraviolet B Irradiation Induced-Apoptosis through P38 Mitogen-Activated Protein Kinase and Jun Amino-Terminal Kinase Pathways.

    Science.gov (United States)

    Ji, Yinghong; Rong, Xianfang; Li, Dan; Cai, Lei; Rao, Jun; Lu, Yi

    2016-01-01

    Ultraviolet B (UVB) irradiation can easily induce apoptosis in human lens epithelial cells (HLECs) and further lead to various eye diseases including cataract. Here for the first time, we investigated the role of cartilage acidic protein 1 (CRTAC1) gene in UVB irradiation induced-apoptosis in HLECs. Three groups of HLECs were employed including model group, empty vector group, and CRTAC1 interference group. After UVB irradiation, the percentage of primary apoptotic cells was obviously fewer in CRTAC1 interference group. Meanwhile, inhibition of CRTAC1 also reduced both reactive oxygen species (ROS) production and intracellular Ca2+ concentration, but the level of mitochondrial membrane potential (Δψm) was increased in HLECs. Further studies indicated that superoxide dismutase (SOD) activity and total antioxidative (T-AOC) level were significantly increased in CRTAC1-inhibited cells, while the levels of malondialdehyde (MDA) and lactate dehydrogenase (LDH) were significantly decreased. ELISA analysis of CRTAC1-inhibited cells showed that the concentrations of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were significantly decreased, but the concentration of interleukin-10 (IL-10) was significantly increased. Western blot analyses of eight apoptosis-associated proteins including Bax, Bcl-2, p38, phospho-p38 (p-p38), Jun amino-terminal kinases (JNK1/2), phospho-JNK1/2 (p-JNK1/2), calcium-sensing receptor (CasR), and Ca2+/calmodulin-dependent protein kinase II (CaMKII) indicated that the inhibition of CRTAC1 alleviated oxidative stress and inflammation response, inactivated calcium-signaling pathway, p38 and JNK1/2 signal pathways, and eventually reduced UVB irradiation induced-apoptosis in HLECs. These results provided new insights into the mechanism of cataract development, and demonstrated that CRTAC1 could be a potentially novel target for cataract treatment. © 2016 The Author(s) Published by S. Karger AG, Basel.

  7. Implicit theories about willpower predict the activation of a rest goal following self-control exertion.

    Science.gov (United States)

    Job, Veronika; Bernecker, Katharina; Miketta, Stefanie; Friese, Malte

    2015-10-01

    Past research indicates that peoples' implicit theories about the nature of willpower moderate the ego-depletion effect. Only people who believe or were led to believe that willpower is a limited resource (limited-resource theory) showed lower self-control performance after an initial demanding task. As of yet, the underlying processes explaining this moderating effect by theories about willpower remain unknown. Here, we propose that the exertion of self-control activates the goal to preserve and replenish mental resources (rest goal) in people with a limited-resource theory. Five studies tested this hypothesis. In Study 1, individual differences in implicit theories about willpower predicted increased accessibility of a rest goal after self-control exertion. Furthermore, measured (Study 2) and manipulated (Study 3) willpower theories predicted an increased preference for rest-conducive objects. Finally, Studies 4 and 5 provide evidence that theories about willpower predict actual resting behavior: In Study 4, participants who held a limited-resource theory took a longer break following self-control exertion than participants with a nonlimited-resource theory. Longer resting time predicted decreased rest goal accessibility afterward. In Study 5, participants with an induced limited-resource theory sat longer on chairs in an ostensible product-testing task when they had engaged in a task requiring self-control beforehand. This research provides consistent support for a motivational shift toward rest after self-control exertion in people holding a limited-resource theory about willpower. (c) 2015 APA, all rights reserved).

  8. Toxicity of ionic liquids: Database and prediction via quantitative structure–activity relationship method

    International Nuclear Information System (INIS)

    Zhao, Yongsheng; Zhao, Jihong; Huang, Ying; Zhou, Qing; Zhang, Xiangping; Zhang, Suojiang

    2014-01-01

    Highlights: • A comprehensive database on toxicity of ionic liquids (ILs) was established. • Relationship between structure and toxicity of IL has been analyzed qualitatively. • Two new QSAR models were developed for predicting toxicity of ILs to IPC-81. • Accuracy of proposed nonlinear SVM model is much higher than the linear MLR model. • The established models can be explored in designing novel green agents. - Abstract: A comprehensive database on toxicity of ionic liquids (ILs) is established. The database includes over 4000 pieces of data. Based on the database, the relationship between IL's structure and its toxicity has been analyzed qualitatively. Furthermore, Quantitative Structure–Activity relationships (QSAR) model is conducted to predict the toxicities (EC 50 values) of various ILs toward the Leukemia rat cell line IPC-81. Four parameters selected by the heuristic method (HM) are used to perform the studies of multiple linear regression (MLR) and support vector machine (SVM). The squared correlation coefficient (R 2 ) and the root mean square error (RMSE) of training sets by two QSAR models are 0.918 and 0.959, 0.258 and 0.179, respectively. The prediction R 2 and RMSE of QSAR test sets by MLR model are 0.892 and 0.329, by SVM model are 0.958 and 0.234, respectively. The nonlinear model developed by SVM algorithm is much outperformed MLR, which indicates that SVM model is more reliable in the prediction of toxicity of ILs. This study shows that increasing the relative number of O atoms of molecules leads to decrease in the toxicity of ILs

  9. Prediction of solar activity from solar background magnetic field variations in cycles 21-23

    International Nuclear Information System (INIS)

    Shepherd, Simon J.; Zharkov, Sergei I.; Zharkova, Valentina V.

    2014-01-01

    A comprehensive spectral analysis of both the solar background magnetic field (SBMF) in cycles 21-23 and the sunspot magnetic field in cycle 23 reported in our recent paper showed the presence of two principal components (PCs) of SBMF having opposite polarity, e.g., originating in the northern and southern hemispheres, respectively. Over a duration of one solar cycle, both waves are found to travel with an increasing phase shift toward the northern hemisphere in odd cycles 21 and 23 and to the southern hemisphere in even cycle 22. These waves were linked to solar dynamo waves assumed to form in different layers of the solar interior. In this paper, for the first time, the PCs of SBMF in cycles 21-23 are analyzed with the symbolic regression technique using Hamiltonian principles, allowing us to uncover the underlying mathematical laws governing these complex waves in the SBMF presented by PCs and to extrapolate these PCs to cycles 24-26. The PCs predicted for cycle 24 very closely fit (with an accuracy better than 98%) the PCs derived from the SBMF observations in this cycle. This approach also predicts a strong reduction of the SBMF in cycles 25 and 26 and, thus, a reduction of the resulting solar activity. This decrease is accompanied by an increasing phase shift between the two predicted PCs (magnetic waves) in cycle 25 leading to their full separation into the opposite hemispheres in cycle 26. The variations of the modulus summary of the two PCs in SBMF reveals a remarkable resemblance to the average number of sunspots in cycles 21-24 and to predictions of reduced sunspot numbers compared to cycle 24: 80% in cycle 25 and 40% in cycle 26.

  10. Integrating circadian activity and gene expression profiles to predict chronotoxicity of Drosophila suzukii response to insecticides.

    Science.gov (United States)

    Hamby, Kelly A; Kwok, Rosanna S; Zalom, Frank G; Chiu, Joanna C

    2013-01-01

    Native to Southeast Asia, Drosophila suzukii (Matsumura) is a recent invader that infests intact ripe and ripening fruit, leading to significant crop losses in the U.S., Canada, and Europe. Since current D. suzukii management strategies rely heavily on insecticide usage and insecticide detoxification gene expression is under circadian regulation in the closely related Drosophila melanogaster, we set out to determine if integrative analysis of daily activity patterns and detoxification gene expression can predict chronotoxicity of D. suzukii to insecticides. Locomotor assays were performed under conditions that approximate a typical summer or winter day in Watsonville, California, where D. suzukii was first detected in North America. As expected, daily activity patterns of D. suzukii appeared quite different between 'summer' and 'winter' conditions due to differences in photoperiod and temperature. In the 'summer', D. suzukii assumed a more bimodal activity pattern, with maximum activity occurring at dawn and dusk. In the 'winter', activity was unimodal and restricted to the warmest part of the circadian cycle. Expression analysis of six detoxification genes and acute contact bioassays were performed at multiple circadian times, but only in conditions approximating Watsonville summer, the cropping season, when most insecticide applications occur. Five of the genes tested exhibited rhythmic expression, with the majority showing peak expression at dawn (ZT0, 6am). We observed significant differences in the chronotoxicity of D. suzukii towards malathion, with highest susceptibility at ZT0 (6am), corresponding to peak expression of cytochrome P450s that may be involved in bioactivation of malathion. High activity levels were not found to correlate with high insecticide susceptibility as initially hypothesized. Chronobiology and chronotoxicity of D. suzukii provide valuable insights for monitoring and control efforts, because insect activity as well as insecticide timing

  11. Alcohol-Related Facebook Activity Predicts Alcohol Use Patterns in College Students

    Science.gov (United States)

    Marczinski, Cecile A.; Hertzenberg, Heather; Goddard, Perilou; Maloney, Sarah F.; Stamates, Amy L.; O’Connor, Kathleen

    2016-01-01

    The purpose of this study was to determine if a brief 10-item alcohol-related Facebook® activity (ARFA) questionnaire would predict alcohol use patterns in college students (N = 146). During a single laboratory session, participants first privately logged on to their Facebook® profiles while they completed the ARFA measure, which queries past 30 day postings related to alcohol use and intoxication. Participants were then asked to complete five additional questionnaires: three measures of alcohol use (the Alcohol Use Disorders Identification Test [AUDIT], the Timeline Follow-Back [TLFB], and the Personal Drinking Habits Questionnaire [PDHQ]), the Barratt Impulsiveness Scale (BIS-11), and the Marlowe-Crowne Social Desirability Scale (MC-SDS). Regression analyses revealed that total ARFA scores were significant predictors of recent drinking behaviors, as assessed by the AUDIT, TLFB, and PDHQ measures. Moreover, impulsivity (BIS-11) and social desirability (MC-SDS) did not predict recent drinking behaviors when ARFA total scores were included in the regressions. The findings suggest that social media activity measured via the ARFA scale may be useful as a research tool for identifying risky alcohol use. PMID:28138317

  12. Assessing the reliability of predictive activity coefficient models for molecules consisting of several functional groups

    Directory of Open Access Journals (Sweden)

    R. P. Gerber

    2013-03-01

    Full Text Available Currently, the most successful predictive models for activity coefficients are those based on functional groups such as UNIFAC. In contrast, these models require a large amount of experimental data for the determination of their parameter matrix. A more recent alternative is the models based on COSMO, for which only a small set of universal parameters must be calibrated. In this work, a recalibrated COSMO-SAC model was compared with the UNIFAC (Do model employing experimental infinite dilution activity coefficient data for 2236 non-hydrogen-bonding binary mixtures at different temperatures. As expected, UNIFAC (Do presented better overall performance, with a mean absolute error of 0.12 ln-units against 0.22 for our COSMO-SAC implementation. However, in cases involving molecules with several functional groups or when functional groups appear in an unusual way, the deviation for UNIFAC was 0.44 as opposed to 0.20 for COSMO-SAC. These results show that COSMO-SAC provides more reliable predictions for multi-functional or more complex molecules, reaffirming its future prospects.

  13. Structural insights into Cydia pomonella pheromone binding protein 2 mediated prediction of potentially active semiochemicals

    Science.gov (United States)

    Tian, Zhen; Liu, Jiyuan; Zhang, Yalin

    2016-03-01

    Given the advantages of behavioral disruption application in pest control and the damage of Cydia pomonella, due progresses have not been made in searching active semiochemicals for codling moth. In this research, 31 candidate semiochemicals were ranked for their binding potential to Cydia pomonella pheromone binding protein 2 (CpomPBP2) by simulated docking, and this sorted result was confirmed by competitive binding assay. This high predicting accuracy of virtual screening led to the construction of a rapid and viable method for semiochemicals searching. By reference to binding mode analyses, hydrogen bond and hydrophobic interaction were suggested to be two key factors in determining ligand affinity, so is the length of molecule chain. So it is concluded that semiochemicals of appropriate chain length with hydroxyl group or carbonyl group at one head tended to be favored by CpomPBP2. Residues involved in binding with each ligand were pointed out as well, which were verified by computational alanine scanning mutagenesis. Progress made in the present study helps establish an efficient method for predicting potentially active compounds and prepares for the application of high-throughput virtual screening in searching semiochemicals by taking insights into binding mode analyses.

  14. Predict-share-observe-explain learning activity for the Torricelli's tank experiment

    Science.gov (United States)

    Panich, Charunya; Puttharugsa, Chokchai; Khemmani, Supitch

    2018-01-01

    The purpose of this research was to study the students' scientific concept and achievement on fluid mechanics before and after the predict-share-observe-explain (PSOE) learning activity for the Torricelli's tank experiment. The 24 participants, who were selected by purposive sampling, were students at grade 12 at Nannakorn School, Nan province. A one group pre-test/post-test design was employed in the study. The research instruments were 1) the lesson plans using the PSOE learning activity and 2) two-tier multiple choice question and subjective tests. The results indicated that students had better scientific concept about Torricelli's tank experiment and the post-test mean score was significantly higher than the pre-test mean score at a 0.05 level of significance. Moreover, the students had retention of knowledge after the PSOE learning activity for 4 weeks at a 0.05 level of significance. The study showed that the PSOE learning activity is suitable for developing students' scientific concept and achievement.

  15. Theories of Person Perception Predict Patterns of Neural Activity During Mentalizing.

    Science.gov (United States)

    Thornton, Mark A; Mitchell, Jason P

    2017-08-22

    Social life requires making inferences about other people. What information do perceivers spontaneously draw upon to make such inferences? Here, we test 4 major theories of person perception, and 1 synthetic theory that combines their features, to determine whether the dimensions of such theories can serve as bases for describing patterns of neural activity during mentalizing. While undergoing functional magnetic resonance imaging, participants made social judgments about well-known public figures. Patterns of brain activity were then predicted using feature encoding models that represented target people's positions on theoretical dimensions such as warmth and competence. All 5 theories of person perception proved highly accurate at reconstructing activity patterns, indicating that each could describe the informational basis of mentalizing. Cross-validation indicated that the theories robustly generalized across both targets and participants. The synthetic theory consistently attained the best performance-approximately two-thirds of noise ceiling accuracy--indicating that, in combination, the theories considered here can account for much of the neural representation of other people. Moreover, encoding models trained on the present data could reconstruct patterns of activity associated with mental state representations in independent data, suggesting the use of a common neural code to represent others' traits and states. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  16. Exercise training raises daily activity stronger than predicted from exercise capacity in patients with COPD.

    Science.gov (United States)

    Behnke, Michaela; Wewel, Alexandra R; Kirsten, Detlef; Jörres, Rudolf A; Magnussen, Helgo

    2005-06-01

    The 6-min walking (6MWD) and 6-min treadmill distance (6MTD) are often used as measures of exercise performance in patients with COPD. The aim of our study was to assess their relationship to daily activity in the course of an exercise training program. Eighty-eight patients with stable COPD (71m/17f; mean +/- SD age, 60 +/-8 year; FEV1, 43+/-14% pred) were recruited, 66 of whom performed a hospital-based 10-day walking training, whereas 22 were treated as control. On day 16MTD, and on days 8 and 10, 6MTD and 6MWD were determined. In addition, patients used an accelerometer (TriTrac-R3D) to record 24 h-activity, whereby training sessions were excluded. In both groups there was a linear relationship (r > or = 0.84 and P daily activity did not markedly vary with exercise capacity under baseline conditions. Participation in a training program increased activity significantly stronger than predicted from the gain in exercise capacity. This underlines the importance of non-physiological, patient-centered factors associated with training in COPD.

  17. Brain Activity in Valuation Regions while Thinking about the Future Predicts Individual Discount Rates

    Science.gov (United States)

    Cooper, Nicole; Kim, B. Kyu; Zauberman, Gal

    2013-01-01

    People vary widely in how much they discount delayed rewards, yet little is known about the sources of these differences. Here we demonstrate that neural activity in ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) when human subjects are asked to merely think about the future—specifically, to judge the subjective length of future time intervals—predicts delay discounting. High discounters showed lower activity for longer time delays, while low discounters showed the opposite pattern. Our results demonstrate that the correlation between VMPFC and VS activity and discounting occurs even in the absence of choices about future rewards, and does not depend on a person explicitly evaluating future outcomes or judging their self-relevance. This suggests a link between discounting and basic processes involved in thinking about the future, such as temporal perception. Our results also suggest that reducing impatience requires not suppression of VMPFC and VS activity altogether, but rather modulation of how these regions respond to the present versus the future. PMID:23926268

  18. Evaluation of anthelmintic activity and in silico PASS assisted prediction of Cordia dichotoma (Forst.) root extract.

    Science.gov (United States)

    Jamkhande, Prasad G; Barde, Sonal R

    2014-01-01

    Worm infection and associated complications are severe problems that afflict a large population worldwide. Failure of synthetic drugs in worm infections because of drug resistance has made alternative drug therapy desirable. Cordia dichotoma (Forst.) is an ethnomedicinal plant which is rich in several secondary metabolites. Traditionally, the plant has been claimed to have high medicinal properties including antimicrobial activity and cytotoxicity. The study begun with an aim to explore plant-based natural anthelmintic agents against Pheretima posthuma, an Indian earthworm. Methanol extract of the drug was obtained by successive soxhlet extraction. The extract was tested for different phytochemicals. Worms were exposed to 10 mg/ml, 25 mg/ml, 50 mg/ml, and 75 mg/ml concentrations of extract and standard drug, albendazole. A software-based tool, prediction of activity spectra for substances was used to estimate anthelmintic efficacy of plant metabolites. The phytochemical analysis revealed presence of alkaloids, tannins, glycosides, saponins, flavonoids, and phenols. The extract showed dose-dependent effects, affecting worm motility, viability, and mortality. It was also found that the biological activity spectrum of the plant phytoconstituents such as octacosanol, lupeol, caffeic acid, and hentricontanol were >0.5 (probable activity > 0.5). The findings of the present work suggest that the extract of C. dichotoma significantly interferes with motility pattern of P. posthuma. The paralysis and mortality of P. posthuma might be due to the combined effects different phytoconstituents. The extract of C. dichotoma promises natural sources to control worm infection.

  19. Frontal responses during learning predict vulnerability to the psychotogenic effects of ketamine : Linking cognition, brain activity, and psychosis

    NARCIS (Netherlands)

    Corlett, Philip R.; Honey, Garry D.; Aitken, Michael R. F.; Dickinson, Anthony; Shanks, David R.; Absalom, Anthony R.; Lee, Michael; Pomarol-Clotet, Edith; Murray, Graham K.; McKenna, Peter J.; Robbins, Trevor W.; Bullmore, Edward T.; Fletcher, Paul C.

    Context: Establishing a neurobiological account of delusion formation that links cognitive processes, brain activity, and symptoms is important to furthering our understanding of psychosis. Objective: To explore a theoretical model of delusion formation that implicates prediction error - dependent

  20. Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

    Science.gov (United States)

    Nightingale, Tom Edward; Walhin, Jean-Philippe; Thompson, Dylan; Bilzon, James Lee John

    2015-01-01

    To assess the validity of two accelerometer devices, at two different anatomical locations, for the prediction of physical activity energy expenditure (PAEE) in manual wheelchair users (MWUs). Seventeen MWUs (36 ± 10 yrs, 72 ± 11 kg) completed ten activities; resting, folding clothes, propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1) and propulsion at 4km·hr-1 (with an additional 8% body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. GT3X+ and GENEActiv accelerometers were worn on the right wrist (W) and upper arm (UA). Linear regression analysis was conducted between outputs from each accelerometer and criterion PAEE, measured using indirect calorimetry. Subsequent error statistics were calculated for the derived regression equations for all four device/location combinations, using a leave-one-out cross-validation analysis. Accelerometer outputs at each anatomical location were significantly (p < .01) associated with PAEE (GT3X+-UA; r = 0.68 and GT3X+-W; r = 0.82. GENEActiv-UA; r = 0.87 and GENEActiv-W; r = 0.88). Mean ± SD PAEE estimation errors for all activities combined were 15 ± 45%, 14 ± 50%, 3 ± 25% and 4 ± 26% for GT3X+-UA, GT3X+-W, GENEActiv-UA and GENEActiv-W, respectively. Absolute PAEE estimation errors for devices varied, 19 to 66% for GT3X+-UA, 17 to 122% for GT3X+-W, 15 to 26% for GENEActiv-UA and from 17.0 to 32% for the GENEActiv-W. The results indicate that the GENEActiv device worn on either the upper arm or wrist provides the most valid prediction of PAEE in MWUs. Variation in error statistics between the two devices is a result of inherent differences in internal components, on-board filtering processes and outputs of each device.

  1. A Prediction on the Unit Cost Estimation for Decommissioning Activities Using the Experienced Data from DECOMMIS

    Energy Technology Data Exchange (ETDEWEB)

    Park, Seung Kook; Park, Hee Seong; Choi, Yoon Dong; Song, Chan Ho; Moon, Jei Kwon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2014-05-15

    The KAERI (Korea Atomic Energy Research Institute) has developed the DECOMMIS (Decommissioning Information Management System) and have been applied for the decommissioning project of the KRR (Korea Research Reactor)-1 and 2 and UCP (Uranium Conversion Plant), as the meaning of the first decommissioning project in Korea. All information and data which are from the decommissioning activities are input, saved, output and managed in the DECOMMIS. This system was consists of the web server and the database server. The users could be access through a web page, depending on the input, processing and output, and be modified the permissions to do such activities can after the decommissioning activities have created the initial system-wide data is stored. When it could be used the experienced data from DECOMMIS, the cost estimation on the new facilities for the decommissioning planning will be established with the basic frame of the WBS structures and its codes. In this paper, the prediction on the cost estimation through using the experienced data which were store in DECOMMIS was studied. For the new decommissioning project on the nuclear facilities in the future, through this paper, the cost estimation for the decommissioning using the experienced data which were WBS codes, unit-work productivity factors and annual governmental unit labor cost is proposed. These data were from the KRR and UCP decommissioning project. The differences on the WBS code sectors and facility characterization between new objected components and experienced dismantled components was reduces as scaling factors. The study on the establishment the scaling factors and cost prediction for the cost estimation is developing with the algorithms from the productivity data, now.

  2. Elevated left mid-frontal cortical activity prospectively predicts conversion to bipolar I disorder

    Science.gov (United States)

    Nusslock, Robin; Harmon-Jones, Eddie; Alloy, Lauren B.; Urosevic, Snezana; Goldstein, Kim; Abramson, Lyn Y.

    2013-01-01

    Bipolar disorder is characterized by a hypersensitivity to reward-relevant cues and a propensity to experience an excessive increase in approach-related affect, which may be reflected in hypo/manic symptoms. The present study examined the relationship between relative left-frontal electroencephalographic (EEG) activity, a proposed neurophysiological index of approach-system sensitivity and approach/reward-related affect, and bipolar course and state-related variables. Fifty-eight individuals with cyclothymia or bipolar II disorder and 59 healthy control participants with no affective psychopathology completed resting EEG recordings. Alpha power was obtained and asymmetry indices computed for homologous electrodes. Bipolar spectrum participants were classified as being in a major/minor depressive episode, a hypomanic episode, or a euthymic/remitted state at EEG recording. Participants were then followed prospectively for an average 4.7 year follow-up period with diagnostic interview assessments every four-months. Sixteen bipolar spectrum participants converted to bipolar I disorder during follow-up. Consistent with hypotheses, elevated relative left-frontal EEG activity at baseline 1) prospectively predicted a greater likelihood of converting from cyclothymia or bipolar II disorder to bipolar I disorder over the 4.7 year follow-up period, 2) was associated with an earlier age-of-onset of first bipolar spectrum episode, and 3) was significantly elevated in bipolar spectrum individuals in a hypomanic episode at EEG recording. This is the first study to identify a neurophysiological marker that prospectively predicts conversion to bipolar I disorder. The fact that unipolar depression is characterized by decreased relative left-frontal EEG activity suggests that unipolar depression and vulnerability to hypo/mania may be characterized by different profiles of frontal EEG asymmetry. PMID:22775582

  3. Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

    Directory of Open Access Journals (Sweden)

    Peek Andrew S

    2007-06-01

    Full Text Available Abstract Background RNA interference (RNAi is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM approach was used to quantitatively model RNA interference activities. Results Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative. Conclusion The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid

  4. Using bench press load to predict upper body exercise loads in physically active individuals.

    Science.gov (United States)

    Wong, Del P; Ngo, Kwan-Lung; Tse, Michael A; Smith, Andrew W

    2013-01-01

    This study investigated whether loads for assistance exercises of the upper body can be predicted from the loads of the bench press exercise. Twenty-nine physically active collegiate students (age: 22.6 ± 2.5; weight training experience: 2.9 ± 2.1 years; estimated 1RM bench press: 54.31 ± 14.60 kg; 1RM: body weight ratio: 0.80 ± 0.22; BMI: 22.7 ± 2.1 kg·m(-2)) were recruited. The 6RM loads for bench press, barbell bicep curl, overhead dumbbell triceps extension, hammer curl and dumbbell shoulder press were measured. Test-retest reliability for the 5 exercises as determined by Pearson product moment correlation coefficient was very high to nearly perfect (0.82-0.98, p bench press load was significantly correlated with the loads of the 4 assistance exercises (r ranged from 0.80 to 0.93, p bench press load was a significant (R(2) range from 0.64 to 0.86, p Bench press load (0.28) + 6.30 kg, (b) Barbell biceps curl = Bench press load (0.33) + 6.20 kg, (c) Overhead triceps extension = Bench press load (0.33) - 0.60 kg, and (d) Dumbbell shoulder press = Bench press load (0.42) + 5.84 kg. The difference between the actual load and the predicted load using the four equations ranged between 6.52% and 8.54%, such difference was not significant. Fitness professionals can use the 6RM bench press load as a time effective and accurate method to predict training loads for upper body assistance exercises. Key pointsThe bench press load was significantly correlated with the loads of the 4 assistance exercises.No significant differences were found between the actual load and the predicted load in the four equations.6RM bench press load can be a time effective and accurate method to predict training loads for upper body assistance exercises.

  5. Predicting the minimum liquid surface tension activity of pseudomonads expressing biosurfactants.

    Science.gov (United States)

    Mohammed, I U; Deeni, Y; Hapca, S M; McLaughlin, K; Spiers, A J

    2015-01-01

    Bacteria produce a variety of biosurfactants capable of significantly reducing liquid (aqueous) surface tension (γ) with a range of biological roles and biotechnological uses. To determine the lowest achievable surface tension (γMin ), we tested a diverse collection of Pseudomonas-like isolates from contaminated soil and activated sludge and identified those expressing biosurfactants by drop-collapse assay. Liquid surface tension-reducing ability was quantitatively determined by tensiometry, with 57 isolates found to significantly lower culture supernatant surface tensions to 24·5-49·1 mN m(-1) . Differences in biosurfactant behaviour determined by foaming, emulsion and oil-displacement assays were also observed amongst isolates producing surface tensions of 25-27 mN m(-1) , suggesting that a range of structurally diverse biosurfactants were being expressed. Individual distribution identification (IDI) analysis was used to identify the theoretical probability distribution that best fitted the surface tension data, which predicted a γMin of 24·24 mN m(-1) . This was in agreement with predictions based on earlier work of published mixed bacterial spp. data, suggesting a fundamental limit to the ability of bacterial biosurfactants to reduce surface tensions in aqueous systems. This implies a biological restriction on the synthesis and export of these agents or a physical-chemical restriction on their functioning once produced. Numerous surveys of biosurfactant-producing bacteria have been conducted, but only recently has an attempt been made to predict the minimum liquid surface tension these surface-active agents can achieve. Here, we determine a theoretical minimum of 24 mN m(-1) by statistical analysis of tensiometry data, suggesting a fundamental limit for biosurfactant activity in bacterial cultures incubated under standard growth conditions. This raises a challenge to our understanding of biosurfactant expression, secretion and function, as well as

  6. Psychological, interpersonal, and clinical factors predicting time spent on physical activity among Mexican patients with hypertension

    Directory of Open Access Journals (Sweden)

    Ybarra Sagarduy JL

    2018-01-01

    Full Text Available José Luis Ybarra Sagarduy,1 Dacia Yurima Camacho Mata,1 José Moral de la Rubia,2 Julio Alfonso Piña López,3 José Luis Masud Yunes Zárraga4 1Unit of Social Work and Human Development, Autonomous University of Tamaulipas, Ciudad Victoria, 2School of Psychology, Autonomous University of Nuevo Leon, Monterrey, 3Independent Researcher, Hermosillo, 4Institute of Health and Safety Services for State Workers, Clinic for the Study and Prevention of the Chilhood Obesity, Ciudad Victoria, Mexico Background: It is widely known that physical activity is the key to the optimal management and clinical control of hypertension.Purpose: This research was conducted to identify factors that can predict the time spent on physical activity among Mexican adults with hypertension.Methods: This cross-sectional study was conducted among 182 Mexican patients with hypertension, who completed a set of self-administered questionnaires related to personality, social support, and medical adherence and health care behaviors, body mass index, and time since the disease diagnosis. Several path analyses were performed in order to test the predictors of the study behavior.Results: Lower tolerance to frustration, more tolerance to ambiguity, more effective social support, and less time since the disease diagnosis predicted more time spent on physical activity, accounting for 13.3% of the total variance. The final model shows a good fit to the sample data (pBS =0.235, χ2/gl =1.519, Jöreskog and Sörbom’s Goodness of Fit Index =0.987, adjusted modality =0.962, Bollen’s Incremental Fit Index =0.981, Bentler-Bonett Normed Fit Index =0.946, standardized root mean square residual =0.053.Conclusion: The performance of physical activity in patients with hypertension depends on a complex set of interactions between personal, interpersonal, and clinical variables. Understanding how these factors interact might enhance the design of interdisciplinary intervention programs so

  7. Application of Molecular Topology for the Prediction of Reaction Yields and Anti-Inflammatory Activity of Heterocyclic Amidine Derivatives

    Directory of Open Access Journals (Sweden)

    Ramón García-Domenech

    2011-02-01

    Full Text Available Topological-mathematical models based on multiple linear regression analyses have been built to predict the reaction yields and the anti-inflammatory activity of a set of heterocylic amidine derivatives, synthesized under environmental friendly conditions, using microwave irradiation. Two models with three variables each were selected. The models were validated by cross-validation and randomization tests. The final outcome demonstrates a good agreement between the predicted and experimental results, confirming the robustness of the method. These models also enabled the screening of virtual libraries for new amidine derivatives predicted to show higher values of reaction yields and anti-inflammatory activity.

  8. PTSD Psychotherapy Outcome Predicted by Brain Activation During Emotional Reactivity and Regulation.

    Science.gov (United States)

    Fonzo, Gregory A; Goodkind, Madeleine S; Oathes, Desmond J; Zaiko, Yevgeniya V; Harvey, Meredith; Peng, Kathy K; Weiss, M Elizabeth; Thompson, Allison L; Zack, Sanno E; Lindley, Steven E; Arnow, Bruce A; Jo, Booil; Gross, James J; Rothbaum, Barbara O; Etkin, Amit

    2017-12-01

    Exposure therapy is an effective treatment for posttraumatic stress disorder (PTSD), but many patients do not respond. Brain functions governing treatment outcome are not well characterized. The authors examined brain systems relevant to emotional reactivity and regulation, constructs that are thought to be central to PTSD and exposure therapy effects, to identify the functional traits of individuals most likely to benefit from treatment. Individuals with PTSD underwent functional MRI (fMRI) while completing three tasks assessing emotional reactivity and regulation. Participants were then randomly assigned to immediate prolonged exposure treatment (N=36) or a waiting list condition (N=30). A random subset of the prolonged exposure group (N=17) underwent single-pulse transcranial magnetic stimulation (TMS) concurrent with fMRI to examine whether predictive activation patterns reflect causal influence within circuits. Linear mixed-effects modeling in line with the intent-to-treat principle was used to examine how baseline brain function moderated the effect of treatment on PTSD symptoms. At baseline, individuals with larger treatment-related symptom reductions (compared with the waiting list condition) demonstrated 1) greater dorsal prefrontal activation and 2) less left amygdala activation, both during emotion reactivity; 3) better inhibition of the left amygdala induced by single TMS pulses to the right dorsolateral prefrontal cortex; and 4) greater ventromedial prefrontal/ventral striatal activation during emotional conflict regulation. Reappraisal-related activation was not a significant moderator of the treatment effect. Capacity to benefit from prolonged exposure in PTSD is gated by the degree to which prefrontal resources are spontaneously engaged when superficially processing threat and adaptively mitigating emotional interference, but not when deliberately reducing negative emotionality.

  9. Predicting energy expenditure of physical activity using hip- and wrist-worn accelerometers.

    Science.gov (United States)

    Chen, Kong Y; Acra, Sari A; Majchrzak, Karen; Donahue, Candice L; Baker, Lemont; Clemens, Linda; Sun, Ming; Buchowski, Maciej S

    2003-01-01

    To investigate the association between physical activity and health, we need accurate and detailed free-living physical activity measurements. The determination of energy expenditure of activity (EEACT) may also be useful in the treatment and maintenance of nutritional diseases such as diabetes mellitus. Minute-to-minute energy expenditure during a 24-h period was measured in 60 sedentary normal female volunteers (35.4 +/- 9.0 years, body mass index 30.0 +/- 5.9 kg/m2), using a state-of-the-art whole-room indirect calorimeter. The activities ranged from sedentary deskwork to walking and stepping at different intensities. Body movements were simultaneously measured using a hip-worn triaxial accelerometer (Tritrac-R3D, Hemokentics, Inc., Madison, Wisconsin) and a wrist-worn uniaxial accelerometer (ActiWatch AW64, MiniMitter Co., Sunriver, Oregon) on the dominant arm. Movement data from the accelerometers were used to develop nonlinear prediction models (separately and combined) to estimate EEACT and compared for accuracy. In a subgroup (n=12), a second 24-h study period was repeated for cross-validation of the combined model. The combined model, using Tritrac-R3D and ActiWatch, accurately estimated total EEACT (97.7 +/- 3.2% of the measured values, p=0.781), as compared with using ActiWatch (86.0 +/- 4.7%, ptypes and intensity of activities. This concept can be extended to develop valid models for the accurate measurement of free-living energy metabolism in clinical populations.

  10. The embodiment of emotion: language use during the feeling of social emotions predicts cortical somatosensory activity.

    Science.gov (United States)

    Saxbe, Darby E; Yang, Xiao-Fei; Borofsky, Larissa A; Immordino-Yang, Mary Helen

    2013-10-01

    Complex social emotions involve both abstract cognitions and bodily sensations, and individuals may differ on their relative reliance on these. We hypothesized that individuals' descriptions of their feelings during a semi-structured emotion induction interview would reveal two distinct psychological styles-a more abstract, cognitive style and a more body-based, affective style-and that these would be associated with somatosensory neural activity. We examined 28 participants' open-ended verbal responses to admiration- and compassion-provoking narratives in an interview and BOLD activity to the same narratives during subsequent functional magnetic resonance imaging scanning. Consistent with hypotheses, individuals' affective and cognitive word use were stable across emotion conditions, negatively correlated and unrelated to reported emotion strength in the scanner. Greater use of affective relative to cognitive words predicted more activation in SI, SII, middle anterior cingulate cortex and insula during emotion trials. The results suggest that individuals' verbal descriptions of their feelings reflect differential recruitment of neural regions supporting physical body awareness. Although somatosensation has long been recognized as an important component of emotion processing, these results offer 'proof of concept' that individual differences in open-ended speech reflect different processing styles at the neurobiological level. This study also demonstrates SI involvement during social emotional experience.

  11. Perceived Stress Predicts Lower Physical Activity in African-American Boys, but not Girls.

    Science.gov (United States)

    McGlumphy, Kellye C; Shaver, Erika R; Ajibewa, Tiwaloluwa A; Hasson, Rebecca E

    2018-03-01

    The purpose of this study was to examine cross-sectional relationships of psychological stress, stress coping, and minutes of moderate-to-vigorous physical activity (MVPA) in Amer- ican-American (AA) boys and girls. A community-based sample of 139 AA adolescents (mean age 14.7 years; SD = 1.8 years; 64.7% girls; 30% obese) from Washtenaw County, Michigan was included in this analysis. Psychological stress was assessed using the Daily Stress Inventory and the Perceived Stress Scale. Coping strategies were evaluated using the Schoolager's Coping Strategies questionnaire. Physical activity was measured objectively via accelerometry. Compared to boys, girls participated in approximately 13 fewer minutes of MVPA (p girls reported using a greater number of coping strategies (p = .01) at a greater frequency (p = .04) compared to boys. However, perceived stress significantly predicted lower levels of MVPA (p = .03) in boys only. There are important gender differences in how AA girls perceive, experience, and cope with stress compared to AA boys. Although AA girls reported higher levels of stress and employed more coping strategies, perceived stress was associated with physical inactivity in AA boys, but not girls. Additional research is warranted to better understand the influence of stress on the choice to be physically active in AA youth.

  12. V4 activity predicts the strength of visual short-term memory representations.

    Science.gov (United States)

    Sligte, Ilja G; Scholte, H Steven; Lamme, Victor A F

    2009-06-10

    Recent studies have shown the existence of a form of visual memory that lies intermediate of iconic memory and visual short-term memory (VSTM), in terms of both capacity (up to 15 items) and the duration of the memory trace (up to 4 s). Because new visual objects readily overwrite this intermediate visual store, we believe that it reflects a weak form of VSTM with high capacity that exists alongside a strong but capacity-limited form of VSTM. In the present study, we isolated brain activity related to weak and strong VSTM representations using functional magnetic resonance imaging. We found that activity in visual cortical area V4 predicted the strength of VSTM representations; activity was low when there was no VSTM, medium when there was a weak VSTM representation regardless of whether this weak representation was available for report or not, and high when there was a strong VSTM representation. Altogether, this study suggests that the high capacity yet weak VSTM store is represented in visual parts of the brain. Allegedly, only some of these VSTM traces are amplified by parietal and frontal regions and as a consequence reside in traditional or strong VSTM. The additional weak VSTM representations remain available for conscious access and report when attention is redirected to them yet are overwritten as soon as new visual stimuli hit the eyes.

  13. Habit strength is predicted by activity dynamics in goal-directed brain systems during training.

    Science.gov (United States)

    Zwosta, Katharina; Ruge, Hannes; Goschke, Thomas; Wolfensteller, Uta

    2018-01-15

    Previous neuroscientific research revealed insights into the brain networks supporting goal-directed and habitual behavior, respectively. However, it remains unclear how these contribute to inter-individual differences in habit strength which is relevant for understanding not only normal behavior but also more severe dysregulations between these types of action control, such as in addiction. In the present fMRI study, we trained subjects on approach and avoidance behavior for an extended period of time before testing the habit strength of the acquired stimulus-response associations. We found that stronger habits were associated with a stronger decrease in inferior parietal lobule activity for approach and avoidance behavior and weaker vmPFC activity at the end of training for avoidance behavior, areas associated with the anticipation of outcome identity and value. VmPFC in particular showed markedly different activity dynamics during the training of approach and avoidance behavior. Furthermore, while ongoing training was accompanied by increasing functional connectivity between posterior putamen and premotor cortex, consistent with previous assumptions about the neural basis of increasing habitualization, this was not predictive of later habit strength. Together, our findings suggest that inter-individual differences in habitual behavior are driven by differences in the persistent involvement of brain areas supporting goal-directed behavior during training. Copyright © 2017. Published by Elsevier Inc.

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

    Science.gov (United States)

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

    2012-09-01

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

  15. Error-related brain activity predicts cocaine use after treatment at 3-month follow-up.

    Science.gov (United States)

    Marhe, Reshmi; van de Wetering, Ben J M; Franken, Ingmar H A

    2013-04-15

    Relapse after treatment is one of the most important problems in drug dependency. Several studies suggest that lack of cognitive control is one of the causes of relapse. In this study, a relative new electrophysiologic index of cognitive control, the error-related negativity, is investigated to examine its suitability as a predictor of relapse. The error-related negativity was measured in 57 cocaine-dependent patients during their first week in detoxification treatment. Data from 49 participants were used to predict cocaine use at 3-month follow-up. Cocaine use at follow-up was measured by means of self-reported days of cocaine use in the last month verified by urine screening. A multiple hierarchical regression model was used to examine the predictive value of the error-related negativity while controlling for addiction severity and self-reported craving in the week before treatment. The error-related negativity was the only significant predictor in the model and added 7.4% of explained variance to the control variables, resulting in a total of 33.4% explained variance in the prediction of days of cocaine use at follow-up. A reduced error-related negativity measured during the first week of treatment was associated with more days of cocaine use at 3-month follow-up. Moreover, the error-related negativity was a stronger predictor of recent cocaine use than addiction severity and craving. These results suggest that underactive error-related brain activity might help to identify patients who are at risk of relapse as early as in the first week of detoxification treatment. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  16. Understanding the origin of the solar cyclic activity for an improved earth climate prediction

    Science.gov (United States)

    Turck-Chièze, Sylvaine; Lambert, Pascal

    This review is dedicated to the processes which could explain the origin of the great extrema of the solar activity. We would like to reach a more suitable estimate and prediction of the temporal solar variability and its real impact on the Earth climatic models. The development of this new field is stimulated by the SoHO helioseismic measurements and by some recent solar modelling improvement which aims to describe the dynamical processes from the core to the surface. We first recall assumptions on the potential different solar variabilities. Then, we introduce stellar seismology and summarize the main SOHO results which are relevant for this field. Finally we mention the dynamical processes which are presently introduced in new solar models. We believe that the knowledge of two important elements: (1) the magnetic field interplay between the radiative zone and the convective zone and (2) the role of the gravity waves, would allow to understand the origin of the grand minima and maxima observed during the last millennium. Complementary observables like acoustic and gravity modes, radius and spectral irradiance from far UV to visible in parallel to the development of 1D-2D-3D simulations will improve this field. PICARD, SDO, DynaMICCS are key projects for a prediction of the next century variability. Some helioseismic indicators constitute the first necessary information to properly describe the Sun-Earth climatic connection.

  17. Predicting Hydride Donor Strength via Quantum Chemical Calculations of Hydride Transfer Activation Free Energy.

    Science.gov (United States)

    Alherz, Abdulaziz; Lim, Chern-Hooi; Hynes, James T; Musgrave, Charles B

    2018-01-25

    We propose a method to approximate the kinetic properties of hydride donor species by relating the nucleophilicity (N) of a hydride to the activation free energy ΔG ⧧ of its corresponding hydride transfer reaction. N is a kinetic parameter related to the hydride transfer rate constant that quantifies a nucleophilic hydridic species' tendency to donate. Our method estimates N using quantum chemical calculations to compute ΔG ⧧ for hydride transfers from hydride donors to CO 2 in solution. A linear correlation for each class of hydrides is then established between experimentally determined N values and the computationally predicted ΔG ⧧ ; this relationship can then be used to predict nucleophilicity for different hydride donors within each class. This approach is employed to determine N for four different classes of hydride donors: two organic (carbon-based and benzimidazole-based) and two inorganic (boron and silicon) hydride classes. We argue that silicon and boron hydrides are driven by the formation of the more stable Si-O or B-O bond. In contrast, the carbon-based hydrides considered herein are driven by the stability acquired upon rearomatization, a feature making these species of particular interest, because they both exhibit catalytic behavior and can be recycled.

  18. Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of amaryllidaceae

    Directory of Open Access Journals (Sweden)

    Rønsted Nina

    2012-09-01

    Full Text Available Abstract Background During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer a predictive approach enabling more efficient selection of plants for the development of traditional medicine and lead discovery. However, this relationship has rarely been rigorously tested and the potential predictive power is consequently unknown. Results We produced a phylogenetic hypothesis for the medicinally important plant subfamily Amaryllidoideae (Amaryllidaceae based on parsimony and Bayesian analysis of nuclear, plastid, and mitochondrial DNA sequences of over 100 species. We tested if alkaloid diversity and activity in bioassays related to the central nervous system are significantly correlated with phylogeny and found evidence for a significant phylogenetic signal in these traits, although the effect is not strong. Conclusions Several genera are non-monophyletic emphasizing the importance of using phylogeny for interpretation of character distribution. Alkaloid diversity and in vitro inhibition of acetylcholinesterase (AChE and binding to the serotonin reuptake transporter (SERT are significantly correlated with phylogeny. This has implications for the use of phylogenies to interpret chemical evolution and biosynthetic pathways, to select candidate taxa for lead discovery, and to make recommendations for policies regarding traditional use and conservation priorities.

  19. Musical Preferences Predict Personality: Evidence From Active Listening and Facebook Likes.

    Science.gov (United States)

    Nave, Gideon; Minxha, Juri; Greenberg, David M; Kosinski, Michal; Stillwell, David; Rentfrow, Jason

    2018-03-01

    Research over the past decade has shown that various personality traits are communicated through musical preferences. One limitation of that research is external validity, as most studies have assessed individual differences in musical preferences using self-reports of music-genre preferences. Are personality traits communicated through behavioral manifestations of musical preferences? We addressed this question in two large-scale online studies with demographically diverse populations. Study 1 ( N = 22,252) shows that reactions to unfamiliar musical excerpts predicted individual differences in personality-most notably, openness and extraversion-above and beyond demographic characteristics. Moreover, these personality traits were differentially associated with particular music-preference dimensions. The results from Study 2 ( N = 21,929) replicated and extended these findings by showing that an active measure of naturally occurring behavior, Facebook Likes for musical artists, also predicted individual differences in personality. In general, our findings establish the robustness and external validity of the links between musical preferences and personality.

  20. Impact of microbial activity on the radioactive waste disposal: long term prediction of biocorrosion processes.

    Science.gov (United States)

    Libert, Marie; Schütz, Marta Kerber; Esnault, Loïc; Féron, Damien; Bildstein, Olivier

    2014-06-01

    This study emphasizes different experimental approaches and provides perspectives to apprehend biocorrosion phenomena in the specific disposal environment by investigating microbial activity with regard to the modification of corrosion rate, which in turn can have an impact on the safety of radioactive waste geological disposal. It is found that iron-reducing bacteria are able to use corrosion products such as iron oxides and "dihydrogen" as new energy sources, especially in the disposal environment which contains low amounts of organic matter. Moreover, in the case of sulphate-reducing bacteria, the results show that mixed aerobic and anaerobic conditions are the most hazardous for stainless steel materials, a situation which is likely to occur in the early stage of a geological disposal. Finally, an integrated methodological approach is applied to validate the understanding of the complex processes and to design experiments aiming at the acquisition of kinetic data used in long term predictive modelling of biocorrosion processes. © 2013.

  1. Excelling at selling: The charming personality style predicts occupational activities, sales performance, and persuasive competence.

    Science.gov (United States)

    Kazén, Miguel; Kuhl, Julius; Boermans, Sylvie; Koole, Sander L

    2013-08-01

    The present research investigates how individual differences in charming personality are related to occupational activities, sales performance, and persuasive competence. Study 1 showed that sales representatives had higher scores on the charming personality style than executive managers. Study 2 showed that the charming personality style predicted actual sales performance among branch managers of a large German insurance company over a period of 2 years; the explicit power motivation served as a mediator in this relation. Finally, Study 3, carried out in a laboratory setting, confirmed the hypothesis that a charming personality is associated with persuasive competence, which suggests that this style is more relevant for sales representatives than for executive managers. The authors conclude that the charming personality style represents an important psychological resource for organizations. © 2013 The Institute of Psychology, Chinese Academy of Sciences and Wiley Publishing Asia Pty Ltd.

  2. Back to the Roots: Prediction of Biologically Active Natural Products from Ayurveda Traditional Medicine

    DEFF Research Database (Denmark)

    Polur, Honey; Joshi, Tejal; Workman, Christopher

    2011-01-01

    Ayurveda, the traditional Indian medicine is one of the most ancient, yet living medicinal traditions. In the present work, we developed an in silico library of natural products from Ayurveda medicine, coupled with structural information, plant origin and traditional therapeutic use. Following this....... We hereby present a number of examples where the traditional medicinal use of the plant matches with the medicinal use of the drug that is structurally similar to a plant component. With this approach, we have brought to light a number of obscure compounds of natural origin (e.g. kanugin......, we compared their structures with those of drugs from DrugBank and we constructed a structural similarity network. Information on the traditional therapeutic use of the plants was integrated in the network in order to provide further evidence for the predicted biologically active natural compounds...

  3. Brain activity elicited by viewing pictures of the own virtually amputated body predicts xenomelia.

    Science.gov (United States)

    Oddo-Sommerfeld, Silvia; Hänggi, Jürgen; Coletta, Ludovico; Skoruppa, Silke; Thiel, Aylin; Stirn, Aglaja V

    2018-01-08

    Xenomelia is a rare condition characterized by the persistent desire for the amputation of physically healthy limbs. Prior studies highlighted the importance of superior and inferior parietal lobuli (SPL/IPL) and other sensorimotor regions as key brain structures associated with xenomelia. We expected activity differences in these areas in response to pictures showing the desired body state, i.e. that of an amputee in xenomelia. Functional magnetic resonance images were acquired in 12 xenomelia individuals and 11 controls while they viewed pictures of their own real and virtually amputated body. Pictures were rated on several dimensions. Multivariate statistics using machine learning was performed on imaging data. Brain activity when viewing pictures of one's own virtually amputated body predicted group membership accurately with a balanced accuracy of 82.58% (p = 0.002), sensitivity of 83.33% (p = 0.018), specificity of 81.82% (p = 0.015) and an area under the ROC curve of 0.77. Among the highest predictive brain regions were bilateral SPL, IPL, and caudate nucleus, other limb representing areas, but also occipital regions. Pleasantness and attractiveness ratings were higher for amputated bodies in xenomelia. Findings show that neuronal processing in response to pictures of one's own desired body state is different in xenomelia compared with controls and might represent a neuronal substrate of the xenomelia complaints that become behaviourally relevant, at least when rating the pleasantness and attractiveness of one's own body. Our findings converge with structural peculiarities reported in xenomelia and partially overlap in task and results with that of anorexia and transgender research. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Predicting trace organic compound breakthrough in granular activated carbon using fluorescence and UV absorbance as surrogates.

    Science.gov (United States)

    Anumol, Tarun; Sgroi, Massimiliano; Park, Minkyu; Roccaro, Paolo; Snyder, Shane A

    2015-06-01

    This study investigated the applicability of bulk organic parameters like dissolved organic carbon (DOC), UV absorbance at 254 nm (UV254), and total fluorescence (TF) to act as surrogates in predicting trace organic compound (TOrC) removal by granular activated carbon in water reuse applications. Using rapid small-scale column testing, empirical linear correlations for thirteen TOrCs were determined with DOC, UV254, and TF in four wastewater effluents. Linear correlations (R(2) > 0.7) were obtained for eight TOrCs in each water quality in the UV254 model, while ten TOrCs had R(2) > 0.7 in the TF model. Conversely, DOC was shown to be a poor surrogate for TOrC breakthrough prediction. When the data from all four water qualities was combined, good linear correlations were still obtained with TF having higher R(2) than UV254 especially for TOrCs with log Dow>1. Excellent linear relationship (R(2) > 0.9) between log Dow and the removal of TOrC at 0% surrogate removal (y-intercept) were obtained for the five neutral TOrCs tested in this study. Positively charged TOrCs had enhanced removals due to electrostatic interactions with negatively charged GAC that caused them to deviate from removals that would be expected with their log Dow. Application of the empirical linear correlation models to full-scale samples provided good results for six of seven TOrCs (except meprobamate) tested when comparing predicted TOrC removal by UV254 and TF with actual removals for GAC in all the five samples tested. Surrogate predictions using UV254 and TF provide valuable tools for rapid or on-line monitoring of GAC performance and can result in cost savings by extended GAC run times as compared to using DOC breakthrough to trigger regeneration or replacement. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Graph-based representation of behavior in detection and prediction of daily living activities.

    Science.gov (United States)

    Augustyniak, Piotr; Ślusarczyk, Grażyna

    2018-04-01

    Various surveillance systems capture signs of human activities of daily living (ADLs) and store multimodal information as time line behavioral records. In this paper, we present a novel approach to the analysis of a behavioral record used in a surveillance system designed for use in elderly smart homes. The description of a subject's activity is first decomposed into elementary poses - easily detectable by dedicated intelligent sensors - and represented by the share coefficients. Then, the activity is represented in the form of an attributed graph, where nodes correspond to elementary poses. As share coefficients of poses are expressed as attributes assigned to graph nodes, their change corresponding to a subject's action is represented by flow in graph edges. The behavioral record is thus a time series of graphs, which tiny size facilitates storage and management of long-term monitoring results. At the system learning stage, the contribution of elementary poses is accumulated, discretized and probability-ordered leading to a finite list representing the possible transitions between states. Such a list is independently built for each room in the supervised residence, and employed for assessment of the current action in the context of subject's habits and a room purpose. The proposed format of a behavioral record, applied to an adaptive surveillance system, is particularly advantageous for representing new activities not known at the setup stage, for providing a quantitative measure of transitions between poses and for expressing the difference between a predicted and actual action in a numerical way. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  6. Evaluation of anthelmintic activity and in silico PASS assisted prediction of Cordia dichotoma (Forst.) root extract

    Science.gov (United States)

    Jamkhande, Prasad G.; Barde, Sonal R.

    2014-01-01

    Background: Worm infection and associated complications are severe problems that afflict a large population worldwide. Failure of synthetic drugs in worm infections because of drug resistance has made alternative drug therapy desirable. Cordia dichotoma (Forst.) is an ethnomedicinal plant which is rich in several secondary metabolites. Traditionally, the plant has been claimed to have high medicinal properties including antimicrobial activity and cytotoxicity. Materials and Methods: The study begun with an aim to explore plant-based natural anthelmintic agents against Pheretima posthuma, an Indian earthworm. Methanol extract of the drug was obtained by successive soxhlet extraction. The extract was tested for different phytochemicals. Worms were exposed to 10 mg/ml, 25 mg/ml, 50 mg/ml, and 75 mg/ml concentrations of extract and standard drug, albendazole. A software-based tool, prediction of activity spectra for substances was used to estimate anthelmintic efficacy of plant metabolites. Result: The phytochemical analysis revealed presence of alkaloids, tannins, glycosides, saponins, flavonoids, and phenols. The extract showed dose-dependent effects, affecting worm motility, viability, and mortality. It was also found that the biological activity spectrum of the plant phytoconstituents such as octacosanol, lupeol, caffeic acid, and hentricontanol were >0.5 (probable activity > 0.5). Conclusion: The findings of the present work suggest that the extract of C. dichotoma significantly interferes with motility pattern of P. posthuma. The paralysis and mortality of P. posthuma might be due to the combined effects different phytoconstituents. The extract of C. dichotoma promises natural sources to control worm infection. PMID:25737609

  7. A quantitative structure-activity relationship to predict efficacy of granular activated carbon adsorption to control emerging contaminants.

    Science.gov (United States)

    Kennicutt, A R; Morkowchuk, L; Krein, M; Breneman, C M; Kilduff, J E

    2016-08-01

    A quantitative structure-activity relationship was developed to predict the efficacy of carbon adsorption as a control technology for endocrine-disrupting compounds, pharmaceuticals, and components of personal care products, as a tool for water quality professionals to protect public health. Here, we expand previous work to investigate a broad spectrum of molecular descriptors including subdivided surface areas, adjacency and distance matrix descriptors, electrostatic partial charges, potential energy descriptors, conformation-dependent charge descriptors, and Transferable Atom Equivalent (TAE) descriptors that characterize the regional electronic properties of molecules. We compare the efficacy of linear (Partial Least Squares) and non-linear (Support Vector Machine) machine learning methods to describe a broad chemical space and produce a user-friendly model. We employ cross-validation, y-scrambling, and external validation for quality control. The recommended Support Vector Machine model trained on 95 compounds having 23 descriptors offered a good balance between good performance statistics, low error, and low probability of over-fitting while describing a wide range of chemical features. The cross-validated model using a log-uptake (qe) response calculated at an aqueous equilibrium concentration (Ce) of 1 μM described the training dataset with an r(2) of 0.932, had a cross-validated r(2) of 0.833, and an average residual of 0.14 log units.

  8. Comparison of semantic and episodic memory BOLD fMRI activation in predicting cognitive decline in older adults.

    Science.gov (United States)

    Hantke, Nathan; Nielson, Kristy A; Woodard, John L; Breting, Leslie M Guidotti; Butts, Alissa; Seidenberg, Michael; Carson Smith, J; Durgerian, Sally; Lancaster, Melissa; Matthews, Monica; Sugarman, Michael A; Rao, Stephen M

    2013-01-01

    Previous studies suggest that task-activated functional magnetic resonance imaging (fMRI) can predict future cognitive decline among healthy older adults. The present fMRI study examined the relative sensitivity of semantic memory (SM) versus episodic memory (EM) activation tasks for predicting cognitive decline. Seventy-eight cognitively intact elders underwent neuropsychological testing at entry and after an 18-month interval, with participants classified as cognitively "Stable" or "Declining" based on ≥ 1.0 SD decline in performance. Baseline fMRI scanning involved SM (famous name discrimination) and EM (name recognition) tasks. SM and EM fMRI activation, along with Apolipoprotein E (APOE) ε4 status, served as predictors of cognitive outcome using a logistic regression analysis. Twenty-seven (34.6%) participants were classified as Declining and 51 (65.4%) as Stable. APOE ε4 status alone significantly predicted cognitive decline (R(2) = .106; C index = .642). Addition of SM activation significantly improved prediction accuracy (R(2) = .285; C index = .787), whereas the addition of EM did not (R(2) = .212; C index = .711). In combination with APOE status, SM task activation predicts future cognitive decline better than EM activation. These results have implications for use of fMRI in prevention clinical trials involving the identification of persons at-risk for age-associated memory loss and Alzheimer's disease.

  9. The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Morowatisharifabad

    2018-03-01

    CONCLUSION: Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour.

  10. Predicting novel substrates for enzymes with minimal experimental effort with active learning.

    Science.gov (United States)

    Pertusi, Dante A; Moura, Matthew E; Jeffryes, James G; Prabhu, Siddhant; Walters Biggs, Bradley; Tyo, Keith E J

    2017-11-01

    Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of enzyme promiscuity. Enzyme promiscuity is currently characterized with a limited number of human-selected compounds that may not be representative of the enzyme's versatility. While testing large numbers of compounds may be impractical, computational approaches can exploit existing data to determine the most informative substrates to test next, thereby more thoroughly exploring an enzyme's versatility. To demonstrate this, we used existing studies and tested compounds for four different enzymes, developed support vector machine (SVM) models using these datasets, and selected additional compounds for experiments using an active learning approach. SVMs trained on a chemically diverse set of compounds were discovered to achieve maximum accuracies of ~80% using ~33% fewer compounds than datasets based on all compounds tested in existing studies. Active learning-selected compounds for testing resolved apparent conflicts in the existing training data, while adding diversity to the dataset. The application of these algorithms to wide arrays of metabolic enzymes would result in a library of SVMs that can predict high-probability promiscuous enzymatic reactions and could prove a valuable resource for the design of novel metabolic pathways. Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  11. Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules

    Science.gov (United States)

    Ranganathan, Rajiv; Krishnan, Chandramouli; Dhaher, Yasin Y.; Rymer, William Z.

    2018-01-01

    The motor module hypothesis in motor control proposes that the nervous system can simplify the problem of controlling a large number of muscles in human movement by grouping muscles into a smaller number of modules. Here, we tested one prediction of the modular organization hypothesis by examining whether there is preferential exploration along these motor modules during the learning of a new gait pattern. Healthy college-aged participants learned a new gait pattern which required increased hip and knee flexion during the swing phase while walking in a lower-extremity robot (Lokomat). The new gait pattern was displayed as a foot trajectory in the sagittal plane and participants attempted to match their foot trajectory to this template. We recorded EMG from 8 lower-extremity muscles and we extracted motor modules during both baseline walking and target-tracking using non-negative matrix factorization (NMF). Results showed increased trajectory variability in the first block of learning, indicating that participants were engaged in exploratory behavior. Critically, when we examined the muscle activity during this exploratory phase, we found that the composition of motor modules changed significantly within the first few strides of attempting the new gait pattern. The lack of persistence of the motor modules under even short time scales suggests that motor modules extracted during locomotion may be more indicative of correlated muscle activity induced by the task constraints of walking, rather than reflecting a modular control strategy. PMID:26916510

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

    Directory of Open Access Journals (Sweden)

    John eBest

    2014-05-01

    Full Text Available 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 to 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 = -.36, p .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.

  13. Cross-Layer Active Predictive Congestion Control Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yinfeng Wu

    2009-10-01

    Full Text Available In wireless sensor networks (WSNs, there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node‟s neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.

  14. Is this car looking at you? How anthropomorphism predicts fusiform face area activation when seeing cars.

    Science.gov (United States)

    Kühn, Simone; Brick, Timothy R; Müller, Barbara C N; Gallinat, Jürgen

    2014-01-01

    Anthropomorphism encompasses the attribution of human characteristics to non-living objects. In particular the human tendency to see faces in cars has long been noticed, yet its neural correlates are unknown. We set out to investigate whether the fusiform face area (FFA) is associated with seeing human features in car fronts, or whether, the higher-level theory of mind network (ToM), namely temporoparietal junction (TPJ) and medial prefrontal cortex (MPFC) show a link to anthropomorphism. Twenty participants underwent fMRI scanning during a passive car-front viewing task. We extracted brain activity from FFA, TPJ and MPFC. After the fMRI session participants were asked to spontaneously list adjectives that characterize each car front. Five raters judged the degree to which each adjective can be applied as a characteristic of human beings. By means of linear mixed models we found that the implicit tendency to anthropomorphize individual car fronts predicts FFA, but not TPJ or MPFC activity. The results point to an important role of FFA in the phenomenon of ascribing human attributes to non-living objects. Interestingly, brain regions that have been associated with thinking about beliefs and mental states of others (TPJ, MPFC) do not seem to be related to anthropomorphism of car fronts.

  15. Predicting the effects of microbial activity on the corrosion of copper nuclear fuel waste disposal containers

    International Nuclear Information System (INIS)

    King, F.; Stroes-Gascoyne, S.

    1996-08-01

    Microbially influenced corrosion (MIC) of copper nuclear fuel waste containers may occur in a disposal vault located 500-1000 m underground in the granitic rock of the Canadian Shield. The extent and diversity of microbial activity in the vault is expected to be limited initially because of the aggressive conditions produced by γ-radiation, elevated temperatures and desiccation of the clay-based buffer in which the containers will be embedded. Experimental results on the heat- and radiation-sensitivity of the natural microbiota in buffer material are presented. The data suggest that the low water activity in the buffer material will severely limit the growth of microbes near the container. The most likely form of MIC involves sulphate-reducing bacteria (SRB). Electrochemical experiments using a clay-covered copper electrode have shown that sulphide ions produced by SRB could diffuse through buffer material and induce corrosion of the container. A method to predict the long-term corrosion behaviour is presented. (author)

  16. Uncovering Camouflage: Amygdala Activation Predicts Long-Term Memory of Induced Perceptual Insight

    Science.gov (United States)

    Ludmer, Rachel; Dudai, Yadin; Rubin, Nava

    2012-01-01

    What brain mechanisms underlie learning of new knowledge from single events? We studied encoding in long-term memory of a unique type of one-shot experience, induced perceptual insight. While undergoing an fMRI brain scan, participants viewed degraded images of real-world pictures where the underlying objects were hard to recognize (‘camouflage’), followed by brief exposures to the original images (‘solution’), which led to induced insight (“Aha!”). A week later, participants’ memory was tested; a solution image was classified as ‘remembered’ if detailed perceptual knowledge was elicited from the camouflage image alone. During encoding, subsequently remembered images enjoyed higher activity in mid-level visual cortex and medial frontal cortex, but most pronouncedly in the amygdala, whose activity could be used to predict which solutions will remain in long-term memory. Our findings extend the known roles of amygdala in memory to include promoting of long-term memory of the sudden reorganization of internal representations. PMID:21382558

  17. Cross-layer active predictive congestion control protocol for wireless sensor networks.

    Science.gov (United States)

    Wan, Jiangwen; Xu, Xiaofeng; Feng, Renjian; Wu, Yinfeng

    2009-01-01

    In wireless sensor networks (WSNs), there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC) for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node's neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.

  18. Predicting novel substrates for enzymes with minimal experimental effort with active learning

    Energy Technology Data Exchange (ETDEWEB)

    Pertusi, Dante A.; Moura, Matthew E.; Jeffryes, James G.; Prabhu, Siddhant; Walters Biggs, Bradley; Tyo, Keith E. J.

    2017-11-01

    Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of enzyme promiscuity. Enzyme promiscuity is currently characterized with a limited number of human-selected compounds that may not be representative of the enzyme's versatility. While testing large numbers of compounds may be impractical, computational approaches can exploit existing data to determine the most informative substrates to test next, thereby more thoroughly exploring an enzyme's versatility. To demonstrate this, we used existing studies and tested compounds for four different enzymes, developed support vector machine (SVM) models using these datasets, and selected additional compounds for experiments using an active learning approach. SVMs trained on a chemically diverse set of compounds were discovered to achieve maximum accuracies of similar to 80% using similar to 33% fewer compounds than datasets based on all compounds tested in existing studies. Active learning-selected compounds for testing resolved apparent conflicts in the existing training data, while adding diversity to the dataset. The application of these algorithms to wide arrays of metabolic enzymes would result in a library of SVMs that can predict high-probability promiscuous enzymatic reactions and could prove a valuable resource for the design of novel metabolic pathways.

  19. Circulating Biologically Active Adrenomedullin (bio-ADM) Predicts Hemodynamic Support Requirement and Mortality During Sepsis.

    Science.gov (United States)

    Caironi, Pietro; Latini, Roberto; Struck, Joachim; Hartmann, Oliver; Bergmann, Andreas; Maggio, Giuseppe; Cavana, Marco; Tognoni, Gianni; Pesenti, Antonio; Gattinoni, Luciano; Masson, Serge

    2017-08-01

    The biological role of adrenomedullin (ADM), a hormone involved in hemodynamic homeostasis, is controversial in sepsis because administration of either the peptide or an antibody against it may be beneficial. Plasma biologically active ADM (bio-ADM) was assessed on days 1, 2, and 7 after randomization of 956 patients with sepsis or septic shock to albumin or crystalloids for fluid resuscitation in the multicenter Albumin Italian Outcome Sepsis trial. We tested the association of bio-ADM and its time-dependent variation with fluid therapy, vasopressor administration, organ failures, and mortality. Plasma bio-ADM on day 1 (median [Q1-Q3], 110 [59-198] pg/mL) was higher in patients with septic shock, associated with 90-day mortality, multiple organ failures and the average extent of hemodynamic support therapy (fluids and vasopressors), and serum lactate time course over the first week. Moreover, it predicted incident cardiovascular dysfunction in patients without shock at enrollment (OR [95% CI], 1.9 [1.4-2.5]; P sepsis, the circulating, biologically active form of ADM may help individualizing hemodynamic support therapy, while avoiding harmful effects. Its possible pathophysiologic role makes bio-ADM a potential candidate for future targeted therapies. ClinicalTrials.gov; No.: NCT00707122. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

  20. Life Prediction of Large Lithium-Ion Battery Packs with Active and Passive Balancing

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Ying [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Smith, Kandler A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zane, Regan [Utah State University; Anderson, Dyche [Ford Motor Company

    2017-07-03

    Lithium-ion battery packs take a major part of large-scale stationary energy storage systems. One challenge in reducing battery pack cost is to reduce pack size without compromising pack service performance and lifespan. Prognostic life model can be a powerful tool to handle the state of health (SOH) estimate and enable active life balancing strategy to reduce cell imbalance and extend pack life. This work proposed a life model using both empirical and physical-based approaches. The life model described the compounding effect of different degradations on the entire cell with an empirical model. Then its lower-level submodels considered the complex physical links between testing statistics (state of charge level, C-rate level, duty cycles, etc.) and the degradation reaction rates with respect to specific aging mechanisms. The hybrid approach made the life model generic, robust and stable regardless of battery chemistry and application usage. The model was validated with a custom pack with both passive and active balancing systems implemented, which created four different aging paths in the pack. The life model successfully captured the aging trajectories of all four paths. The life model prediction errors on capacity fade and resistance growth were within +/-3% and +/-5% of the experiment measurements.

  1. Body-Related Shame and Guilt Predict Physical Activity in Breast Cancer Survivors Over Time.

    Science.gov (United States)

    Castonguay, Andrée L; Wrosch, Carsten; Pila, Eva; Sabiston, Catherine M

    2017-07-01

    To test body-related shame and guilt as predictors of breast cancer survivors' (BCS') moderate to vigorous intensity physical activity (MVPA) during six months and to examine motivational regulations as mediators of this association.
. Prospective study.
. Survivors were recruited through advertisements and oncologist referrals from medical clinics and hospitals in Montreal, Quebec, Canada.
. 149 female BCS.
. Self-reports of body-related shame and guilt, motivational regulations, and MVPA were measured among BCS at baseline. MVPA was assessed a second time six months later. Residual change scores were used.
. Body-related shame and guilt; external, introjected, and autonomous (identified and intrinsic) motivational regulations; MVPA.
. In the multiple mediation models, body-related shame was associated with low levels of MVPA, as well as external, introjected, and autonomous motivational regulations. Guilt was related to high levels of MVPA and introjected and autonomous motivational regulations. Indirect effects linked shame, guilt, and MVPA via autonomous motivation. Only body-related shame was a significant predictor of six-month changes in MVPA.
. Based on these results, the specific emotions of shame and guilt contextualized to the body differentially predict BCS' health motivations and behavior over time.
. Survivorship programs may benefit from integrating intervention strategies aimed at reducing body-related shame and helping women manage feelings of guilt to improve physical activity.

  2. Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

    Directory of Open Access Journals (Sweden)

    Tom Edward Nightingale

    Full Text Available To assess the validity of two accelerometer devices, at two different anatomical locations, for the prediction of physical activity energy expenditure (PAEE in manual wheelchair users (MWUs.Seventeen MWUs (36 ± 10 yrs, 72 ± 11 kg completed ten activities; resting, folding clothes, propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1 and propulsion at 4km·hr-1 (with an additional 8% body mass, 2% and 3% gradient on a motorised wheelchair treadmill. GT3X+ and GENEActiv accelerometers were worn on the right wrist (W and upper arm (UA. Linear regression analysis was conducted between outputs from each accelerometer and criterion PAEE, measured using indirect calorimetry. Subsequent error statistics were calculated for the derived regression equations for all four device/location combinations, using a leave-one-out cross-validation analysis.Accelerometer outputs at each anatomical location were significantly (p < .01 associated with PAEE (GT3X+-UA; r = 0.68 and GT3X+-W; r = 0.82. GENEActiv-UA; r = 0.87 and GENEActiv-W; r = 0.88. Mean ± SD PAEE estimation errors for all activities combined were 15 ± 45%, 14 ± 50%, 3 ± 25% and 4 ± 26% for GT3X+-UA, GT3X+-W, GENEActiv-UA and GENEActiv-W, respectively. Absolute PAEE estimation errors for devices varied, 19 to 66% for GT3X+-UA, 17 to 122% for GT3X+-W, 15 to 26% for GENEActiv-UA and from 17.0 to 32% for the GENEActiv-W.The results indicate that the GENEActiv device worn on either the upper arm or wrist provides the most valid prediction of PAEE in MWUs. Variation in error statistics between the two devices is a result of inherent differences in internal components, on-board filtering processes and outputs of each device.

  3. A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance

    Science.gov (United States)

    Astrand, Elaine

    2018-06-01

    Objective. Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Approach. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, n\\in [1,2] . Main results. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  <  0.05). It is furthermore shown that this measure allows to predict task performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. Significance. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain–machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or

  4. The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes

    Science.gov (United States)

    Ali Morowatisharifabad, Mohammad; Abdolkarimi, Mahdi; Asadpour, Mohammad; Fathollahi, Mahmood Sheikh; Balaee, Parisa

    2018-01-01

    INTRODUCTION: Theory-based education tailored to target behaviour and group can be effective in promoting physical activity. AIM: The purpose of this study was to examine the predictive power of Protection Motivation Theory on intent and behaviour of Physical Activity in Patients with Type 2 Diabetes. METHODS: This descriptive study was conducted on 250 patients in Rafsanjan, Iran. To examine the scores of protection motivation theory structures, a researcher-made questionnaire was used. Its validity and reliability were confirmed. The level of physical activity was also measured by the International Short - form Physical Activity Inventory. Its validity and reliability were also approved. Data were analysed by statistical tests including correlation coefficient, chi-square, logistic regression and linear regression. RESULTS: The results revealed that there was a significant correlation between all the protection motivation theory constructs and the intention to do physical activity. The results showed that the Theory structures were able to predict 60% of the variance of physical activity intention. The results of logistic regression demonstrated that increase in the score of physical activity intent and self - efficacy increased the chance of higher level of physical activity by 3.4 and 1.5 times, respectively OR = (3.39, 1.54). CONCLUSION: Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour. PMID:29731945

  5. The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes.

    Science.gov (United States)

    Ali Morowatisharifabad, Mohammad; Abdolkarimi, Mahdi; Asadpour, Mohammad; Fathollahi, Mahmood Sheikh; Balaee, Parisa

    2018-04-15

    Theory-based education tailored to target behaviour and group can be effective in promoting physical activity. The purpose of this study was to examine the predictive power of Protection Motivation Theory on intent and behaviour of Physical Activity in Patients with Type 2 Diabetes. This descriptive study was conducted on 250 patients in Rafsanjan, Iran. To examine the scores of protection motivation theory structures, a researcher-made questionnaire was used. Its validity and reliability were confirmed. The level of physical activity was also measured by the International Short - form Physical Activity Inventory. Its validity and reliability were also approved. Data were analysed by statistical tests including correlation coefficient, chi-square, logistic regression and linear regression. The results revealed that there was a significant correlation between all the protection motivation theory constructs and the intention to do physical activity. The results showed that the Theory structures were able to predict 60% of the variance of physical activity intention. The results of logistic regression demonstrated that increase in the score of physical activity intent and self - efficacy increased the chance of higher level of physical activity by 3.4 and 1.5 times, respectively OR = (3.39, 1.54). Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour.

  6. CT angiography spot sign in intracerebral hemorrhage predicts active bleeding during surgery.

    Science.gov (United States)

    Brouwers, H Bart; Raffeld, Miriam R; van Nieuwenhuizen, Koen M; Falcone, Guido J; Ayres, Alison M; McNamara, Kristen A; Schwab, Kristin; Romero, Javier M; Velthuis, Birgitta K; Viswanathan, Anand; Greenberg, Steven M; Ogilvy, Christopher S; van der Zwan, Albert; Rinkel, Gabriel J E; Goldstein, Joshua N; Klijn, Catharina J M; Rosand, Jonathan

    2014-09-02

    To determine whether the CT angiography (CTA) spot sign marks bleeding complications during and after surgery for spontaneous intracerebral hemorrhage (ICH). In a 2-center study of consecutive spontaneous ICH patients who underwent CTA followed by surgical hematoma evacuation, 2 experienced readers (blinded to clinical and surgical data) reviewed CTAs for spot sign presence. Blinded raters assessed active intraoperative and postoperative bleeding. The association between spot sign and active intraoperative bleeding, postoperative rebleeding, and residual ICH volumes was evaluated using univariable and multivariable logistic regression. A total of 95 patients met inclusion criteria: 44 lobar, 17 deep, 33 cerebellar, and 1 brainstem ICH; ≥1 spot sign was identified in 32 patients (34%). The spot sign was the only independent marker of active bleeding during surgery (odds ratio [OR] 3.4; 95% confidence interval [CI] 1.3-9.0). Spot sign (OR 4.1; 95% CI 1.1-17), female sex (OR 6.9; 95% CI 1.7-37), and antiplatelet use (OR 4.6; 95% CI 1.2-21) were predictive of postoperative rebleeding. Larger residual hematomas and postoperative rebleeding were associated with higher discharge case fatality (OR 3.4; 95% CI 1.1-11) and a trend toward increased case fatality at 3 months (OR 2.9; 95% CI 0.9-8.8). The CTA spot sign is associated with more intraoperative bleeding, more postoperative rebleeding, and larger residual ICH volumes in patients undergoing hematoma evacuation for spontaneous ICH. The spot sign may therefore be useful to select patients for future surgical trials. © 2014 American Academy of Neurology.

  7. Color vision predicts processing modes of goal activation during action cascading.

    Science.gov (United States)

    Jongkees, Bryant J; Steenbergen, Laura; Colzato, Lorenza S

    2017-09-01

    One of the most important functions of cognitive control is action cascading: the ability to cope with multiple response options when confronted with various task goals. A recent study implicates a key role for dopamine (DA) in this process, suggesting higher D1 efficiency shifts the action cascading strategy toward a more serial processing mode, whereas higher D2 efficiency promotes a shift in the opposite direction by inducing a more parallel processing mode (Stock, Arning, Epplen, & Beste, 2014). Given that DA is found in high concentration in the retina and modulation of retinal DA release displays characteristics of D2-receptors (Peters, Schweibold, Przuntek, & Müller, 2000), color vision discrimination might serve as an index of D2 efficiency. We used color discrimination, assessed with the Lanthony Desaturated Panel D-15 test, to predict individual differences (N = 85) in a stop-change paradigm that provides a well-established measure of action cascading. In this task it is possible to calculate an individual slope value for each participant that estimates the degree of overlap in task goal activation. When the stopping process of a previous task goal has not finished at the time the change process toward a new task goal is initiated (parallel processing), the slope value becomes steeper. In case of less overlap (more serial processing), the slope value becomes flatter. As expected, participants showing better color vision were more prone to activate goals in a parallel manner as indicated by a steeper slope. Our findings suggest that color vision might represent a predictor of D2 efficiency and the predisposed processing mode of goal activation during action cascading. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance.

    Science.gov (United States)

    Astrand, Elaine

    2018-06-01

    Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, [Formula: see text]. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain-machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for

  9. The Na+/H+ exchanger, NHE1, differentially regulates mitogen-activated protein kinase subfamilies after osmotic shrinkage in Ehrlich Lettre Ascites cells

    DEFF Research Database (Denmark)

    Petersen, Stine Helene Falsig; Rasmussen, Maria; Darborg, Barbara Vasek

    2007-01-01

    Osmotic stress modulates mitogen activated protein kinase (MAPK) activities, leading to altered gene transcription and cell death/survival balance, however, the mechanisms involved are incompletely elucidated. Here, we show, using a combination of biochemical and molecular biology approaches...... by human (h) NHE1 expression in cells lacking endogenous NHE1 activity. The effect of NHE1 on ERK1/2 was pH(i)-independent and upstream of MEK1/2. Shrinkage-activation of JNK1/2 was attenuated by EIPA, augmented by hNHE1 expression, and abolished in the presence of HCO(3)(-). Basal JNK activity...

  10. Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology.

    Science.gov (United States)

    Min, Hua; Mobahi, Hedyeh; Irvin, Katherine; Avramovic, Sanja; Wojtusiak, Janusz

    2017-09-16

    Bio-ontologies are becoming increasingly important in knowledge representation and in the machine learning (ML) fields. This paper presents a ML approach that incorporates bio-ontologies and its application to the SEER-MHOS dataset to discover patterns of patient characteristics that impact the ability to perform activities of daily living (ADLs). Bio-ontologies are used to provide computable knowledge for ML methods to "understand" biomedical data. This retrospective study included 723 cancer patients from the SEER-MHOS dataset. Two ML methods were applied to create predictive models for ADL disabilities for the first year after a patient's cancer diagnosis. The first method is a standard rule learning algorithm; the second is that same algorithm additionally equipped with methods for reasoning with ontologies. The models showed that a patient's race, ethnicity, smoking preference, treatment plan and tumor characteristics including histology, staging, cancer site, and morphology were predictors for ADL performance levels one year after cancer diagnosis. The ontology-guided ML method was more accurate at predicting ADL performance levels (P ontologies. This study demonstrated that bio-ontologies can be harnessed to provide medical knowledge for ML algorithms. The presented method demonstrates that encoding specific types of hierarchical relationships to guide rule learning is possible, and can be extended to other types of semantic relationships present in biomedical ontologies. The ontology-guided ML method achieved better performance than the method without ontologies. The presented method can also be used to promote the effectiveness and efficiency of ML in healthcare, in which use of background knowledge and consistency with existing clinical expertise is critical.

  11. Predicting mixed-gas adsorption equilibria on activated carbon for precombustion CO2 capture.

    Science.gov (United States)

    García, S; Pis, J J; Rubiera, F; Pevida, C

    2013-05-21

    We present experimentally measured adsorption isotherms of CO2, H2, and N2 on a phenol-formaldehyde resin-based activated carbon, which had been previously synthesized for the separation of CO2 in a precombustion capture process. The single component adsorption isotherms were measured in a magnetic suspension balance at three different temperatures (298, 318, and 338 K) and over a large range of pressures (from 0 to 3000-4000 kPa). These values cover the temperature and pressure conditions likely to be found in a precombustion capture scenario, where CO2 needs to be separated from a CO2/H2/N2 gas stream at high pressure (~1000-1500 kPa) and with a high CO2 concentration (~20-40 vol %). Data on the pure component isotherms were correlated using the Langmuir, Sips, and dual-site Langmuir (DSL) models, i.e., a two-, three-, and four-parameter model, respectively. By using the pure component isotherm fitting parameters, adsorption equilibrium was then predicted for multicomponent gas mixtures by the extended models. The DSL model was formulated considering the energetic site-matching concept, recently addressed in the literature. Experimental gas-mixture adsorption equilibrium data were calculated from breakthrough experiments conducted in a lab-scale fixed-bed reactor and compared with the predictions from the models. Breakthrough experiments were carried out at a temperature of 318 K and five different pressures (300, 500, 1000, 1500, and 2000 kPa) where two different CO2/H2/N2 gas mixtures were used as the feed gas in the adsorption step. The DSL model was found to be the one that most accurately predicted the CO2 adsorption equilibrium in the multicomponent mixture. The results presented in this work highlight the importance of performing experimental measurements of mixture adsorption equilibria, as they are of utmost importance to discriminate between models and to correctly select the one that most closely reflects the actual process.

  12. Human V4 Activity Patterns Predict Behavioral Performance in Imagery of Object Color.

    Science.gov (United States)

    Bannert, Michael M; Bartels, Andreas

    2018-04-11

    Color is special among basic visual features in that it can form a defining part of objects that are engrained in our memory. Whereas most neuroimaging research on human color vision has focused on responses related to external stimulation, the present study investigated how sensory-driven color vision is linked to subjective color perception induced by object imagery. We recorded fMRI activity in male and female volunteers during viewing of abstract color stimuli that were red, green, or yellow in half of the runs. In the other half we asked them to produce mental images of colored, meaningful objects (such as tomato, grapes, banana) corresponding to the same three color categories. Although physically presented color could be decoded from all retinotopically mapped visual areas, only hV4 allowed predicting colors of imagined objects when classifiers were trained on responses to physical colors. Importantly, only neural signal in hV4 was predictive of behavioral performance in the color judgment task on a trial-by-trial basis. The commonality between neural representations of sensory-driven and imagined object color and the behavioral link to neural representations in hV4 identifies area hV4 as a perceptual hub linking externally triggered color vision with color in self-generated object imagery. SIGNIFICANCE STATEMENT Humans experience color not only when visually exploring the outside world, but also in the absence of visual input, for example when remembering, dreaming, and during imagery. It is not known where neural codes for sensory-driven and internally generated hue converge. In the current study we evoked matching subjective color percepts, one driven by physically presented color stimuli, the other by internally generated color imagery. This allowed us to identify area hV4 as the only site where neural codes of corresponding subjective color perception converged regardless of its origin. Color codes in hV4 also predicted behavioral performance in an

  13. Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory

    Energy Technology Data Exchange (ETDEWEB)

    Gregor P. Henze; Moncef Krarti

    2005-09-30

    Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very

  14. Flux balance modeling to predict bacterial survival during pulsed-activity events

    Science.gov (United States)

    Jose, Nicholas A.; Lau, Rebecca; Swenson, Tami L.; Klitgord, Niels; Garcia-Pichel, Ferran; Bowen, Benjamin P.; Baran, Richard; Northen, Trent R.

    2018-04-01

    Desert biological soil crusts (BSCs) are cyanobacteria-dominated surface soil microbial communities common to plant interspaces in arid environments. The capability to significantly dampen their metabolism allows them to exist for extended periods in a desiccated dormant state that is highly robust to environmental stresses. However, within minutes of wetting, metabolic functions reboot, maximizing activity during infrequent permissive periods. Microcoleus vaginatus, a primary producer within the crust ecosystem and an early colonizer, initiates crust formation by binding particles in the upper layer of soil via exopolysaccharides, making microbial dominated biological soil crusts highly dependent on the viability of this organism. Previous studies have suggested that biopolymers play a central role in the survival of this organism by powering resuscitation, rapidly forming compatible solutes, and fueling metabolic activity in dark, hydrated conditions. To elucidate the mechanism of this phenomenon and provide a basis for future modeling of BSCs, we developed a manually curated, genome-scale metabolic model of Microcoleus vaginatus (iNJ1153). To validate this model, gas chromatography-mass spectroscopy (GC-MS) and liquid chromatography-mass spectroscopy (LC-MS) were used to characterize the rate of biopolymer accumulation and depletion in in hydrated Microcoleus vaginatus under light and dark conditions. Constraint-based flux balance analysis showed agreement between model predictions and experimental reaction fluxes. A significant amount of consumed carbon and light energy is invested into storage molecules glycogen and polyphosphate, while β-polyhydroxybutyrate may function as a secondary resource. Pseudo-steady-state modeling suggests that glycogen, the primary carbon source with the fastest depletion rate, will be exhausted if M. vaginatus experiences dark wetting events 4 times longer than light wetting events.

  15. Activities-specific balance confidence scale for predicting future falls in Indian older adults

    Directory of Open Access Journals (Sweden)

    Moiz JA

    2017-04-01

    Full Text Available Jamal Ali Moiz,1 Vishal Bansal,2 Majumi M Noohu,1 Shailendra Nath Gaur,3 Mohammad Ejaz Hussain,1 Shahnawaz Anwer,4,5 Ahmad Alghadir4 1Centre for Physiotherapy and Rehabilitation Sciences, Jamia Millia Islamia, New Delhi, India; 2Department of Physiology, 3Department of Respiratory Medicine, Vallabhbhai Patel Chest Institute, University of Delhi, Delhi, India; 4Rehabilitation Research Chair, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia; 5Department of Musculoskeletal Science, Dr D.Y. Patil College of Physiotherapy, Dr D.Y. Patil Vidyapeeth, Pune, India Background: Activities-specific balance confidence (ABC scale is a subjective measure of confidence in performing various ambulatory activities without falling or experiencing a sense of unsteadiness. Objective: This study aimed to examine the ability of the Hindi version of the ABC scale (ABC-H scale to discriminate between fallers and non-fallers and to examine its predictive validity for prospective falls. Design: This was a prospective cohort study. Materials and methods: A total of 125 community-dwelling older adults (88 were men completed the ABC-H scale. The occurrence of falls over the follow-up period of 12 months was recorded. Discriminative validity was analyzed by comparing the total ABC-H scale scores between the faller and non-faller groups. A receiver operating characteristic curve analysis and a logistic regression analysis were used to examine the predictive accuracy of the ABC-H scale. Results: The mean ABC-H scale score of the faller group was significantly lower than that of the non-faller group (52.6±8.1 vs 73.1±12.2; P<0.001. The optimal cutoff value for distinguishing faller and non-faller adults was ≤58.13. The sensitivity, specificity, area under the curve, and positive and negative likelihood ratios of the cutoff score were 86.3%, 87.3%, 0.91 (P<0.001, 6.84, and 0.16, respectively. The percentage test accuracy and false-positive and

  16. Measurement of exercise habits and prediction of leisure-time activity in established exercise.

    Science.gov (United States)

    Tappe, Karyn A; Glanz, Karen

    2013-01-01

    Habit formation may be important to maintaining repetitive healthy behaviors like exercise. Existing habit questionnaires only measure part of the definition of habit (automaticity; frequency). A novel habit questionnaire was evaluated that measured contextual cueing. We designed a two-stage observational cohort study of regular exercisers. For stage 1, we conducted an in-person interview on a university campus. For stage 2, we conducted an internet-based survey. Participants were 156 adults exercising at least once per week. A novel measure, The Exercise Habit Survey (EHS) assessed contextual cueing through 13 questions on constancy of place, time, people, and exercise behaviors. A subset of the Self-Report Habit Index (SRHI), measuring automaticity, was also collected along with measures of intention and self-efficacy, and the International Physical Activity Questionnaire (IPAQ), leisure-time section. The EHS was evaluated using factor analysis and test-retest reliability. Its correlation to other exercise predictors and exercise behavior was evaluated using Pearson's r and hierarchical regression. Results suggested that the EHS comprised four subscales (People, Place, Time, Exercise Constancy). Only Exercise Constancy correlated significantly with SRHI. Only the People subscale predicted IPAQ exercise metabolic equivalents. The SRHI was a strong predictor. Contextual cueing is an important aspect of habit but measurement methodologies warrant refinement and comparison by different methods.

  17. The negativity bias predicts response rate to Behavioral Activation for depression.

    Science.gov (United States)

    Gollan, Jackie K; Hoxha, Denada; Hunnicutt-Ferguson, Kallio; Norris, Catherine J; Rosebrock, Laina; Sankin, Lindsey; Cacioppo, John

    2016-09-01

    This treatment study investigated the extent to which asymmetric dimensions of affective responding, specifically the positivity offset and the negativity bias, at pretreatment altered the rate of response to Behavioral Activation treatment for depression. Forty-one depressed participants were enrolled into 16 weekly sessions of BA. An additional 36 lifetime healthy participants were evaluated prospectively for 16 weeks to compare affective responding between healthy and remitted patients at post-treatment. All participants were assessed at Weeks 0, 8 and 16 using repeated measures, involving a structured clinical interview for DSM-IV Axis I disorders, questionnaires, and a computerized task designed to measure affective responses to unpleasant, neutral, and pleasant images. The negativity bias at pre-treatment predicted the rate of response to BA, while the positivity offset did not. Only one treatment condition was used in this study and untreated depressed participants were not enrolled, limiting our ability to compare the effect of BA. Baseline negativity bias may serve as a signal for patients to engage in and benefit from the goal-directed BA strategies, thereby accelerating rate of response. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Intrinsic spontaneous brain activity predicts individual variability in associative memory in older adults.

    Science.gov (United States)

    Zheng, Zhiwei; Li, Rui; Xiao, Fengqiu; He, Rongqiao; Zhang, Shouzi; Li, Juan

    2018-04-19

    Older adults demonstrate notable individual differences in associative memory. Here, resting-state functional magnetic resonance imaging (rsfMRI) was used to investigate whether intrinsic brain activity at rest could predict individual differences in associative memory among cognitively healthy older adults. Regional amplitude of low-frequency fluctuations (ALFF) analysis and a correlation-based resting-state functional connectivity (RSFC) approach were used to analyze data acquired from 102 cognitively normal elderly who completed the paired-associative learning test (PALT) and underwent fMRI scans. Participants were divided into two groups based on the retrospective self-reports on whether or not they utilized encoding strategies during the PALT. The behavioral results revealed better associative memory performance in the participants who reported utilizing memory strategies compared with participants who reported not doing so. The fMRI results showed that higher associative memory performance was associated with greater functional connectivity between the right superior frontal gyrus and the right posterior cerebellum lobe in the strategy group. The regional ALFF values in the right superior frontal gyrus were linked to associative memory performance in the no-strategy group. These findings suggest that the regional spontaneous fluctuations and functional connectivity during rest may subserve the individual differences in the associative memory in older adults, and that this is modulated by self-initiated memory strategy use. © 2018 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

  19. Scaling model for prediction of radionuclide activity in cooling water using a regression triplet technique

    International Nuclear Information System (INIS)

    Silvia Dulanska; Lubomir Matel; Milan Meloun

    2010-01-01

    The decommissioning of the nuclear power plant (NPP) A1 Jaslovske Bohunice (Slovakia) is a complicated set of problems that is highly demanding both technically and financially. The basic goal of the decommissioning process is the total elimination of radioactive materials from the nuclear power plant area, and radwaste treatment to a form suitable for its safe disposal. The initial conditions of decommissioning also include elimination of the operational events, preparation and transport of the fuel from the plant territory, radiochemical and physical-chemical characterization of the radioactive wastes. One of the problems was and still is the processing of the liquid radioactive wastes. Such media is also the cooling water of the long-term storage of spent fuel. A suitable scaling model for predicting the activity of hard-to-detect radionuclides 239,240 Pu, 90 Sr and summary beta in cooling water using a regression triplet technique has been built using the regression triplet analysis and regression diagnostics. (author)

  20. Predictive functional control for active queue management in congested TCP/IP networks.

    Science.gov (United States)

    Bigdeli, N; Haeri, M

    2009-01-01

    Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.

  1. Methods for the prediction and achievement of a low circuit activity

    International Nuclear Information System (INIS)

    Faircloth, R.; Knowles, A.N.

    1975-10-01

    While there are about 60,000 fuel pins in the core of an LWR power station, in a comparable HTR there would be over 10 10 coated particles. This five orders of magnitude disparity in the number of basic fission product retaining units has led to important differences in the approach to the prediction and achievement of a low circuit activity. With the HTR, the very large number of units requires statistical treatment of the failure mechanisms involved in the escape of key fission products from the particles and in the assessment of the distribution in the core of burnup, dose and temperature. The methods created to deal with these factors have proved to be very powerful, leading to a situation in which the distribution of fission products within the core and the probability of experiencing a given release are better known for the HTR than for the metal clad fuel of other thermal systems. This advantage has been exploited and reinforced in the UK studies, first by the development of the technology of particle design (a combination of irradiation testing and theoretical analysis) and second by refining the study of fission product movement. This is a continuing process, but already it has usefully illuminated several aspects of design and operation, ranging from the specification and quality control of the fuel itself to the philosophy of outer containments. This paper is intended to summarise this progress, the account being mainly concerned with normal operation. (author)

  2. Emotionally laden impulsivity interacts with affect in predicting addictive use of online sexual activity in men.

    Science.gov (United States)

    Wéry, Aline; Deleuze, Jory; Canale, Natale; Billieux, Joël

    2018-01-01

    The interest in studying addictive use of online sexual activities (OSA) has grown sharply over the last decade. Despite the burgeoning number of studies conceptualizing the excessive use of OSA as an addictive disorder, few have tested its relations to impulsivity, which is known to constitute a hallmark of addictive behaviors. To address this missing gap in the literature, we tested the relationships between addictive OSA use, impulsivity traits, and affect among a convenience sample of men (N=182; age, M=29.17, SD = 9.34), building upon a theoretically driven model that distinguishes the various facets of impulsivity. Results showed that negative urgency (an impulsivity trait reflecting the tendency to act rashly in negative emotional states) and negative affect interact in predicting addictive OSA use. These results highlight the pivotal role played by negative urgency and negative affect in addictive OSA use, supporting the relevance of psychological interventions that focus on improving emotional regulation (e.g., to reduce negative affect and learn healthier coping strategies) to mitigate excessive use of OSA. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Decreases in daily physical activity predict acute decline in attention and executive function in heart failure.

    Science.gov (United States)

    Alosco, Michael L; Spitznagel, Mary Beth; Cohen, Ronald; Sweet, Lawrence H; Hayes, Scott M; Josephson, Richard; Hughes, Joel; Gunstad, John

    2015-04-01

    Reduced physical activity (PA) may be one factor that contributes to cognitive decline and dementia in heart failure (HF). Yet, the longitudinal relationship between PA and cognition in HF is poorly understood owing to limitations of past work, including single-time assessments of PA. This is the first study to examine changes in objectively measured PA and cognition over time in HF. At baseline and 12 weeks, 57 HF patients completed psychosocial self-report measures and a neuropsychological battery and wore an accelerometer for 7 days. At baseline, HF patients spent an average of 597.83 (SD 75.91) minutes per day sedentary. Steps per day declined from baseline to the 12-week follow-up; there was also a trend for declines in moderate-vigorous PA. Regression analyses controlling for sex, HF severity, and depressive symptoms showed that decreases in light (P = .08) and moderate-vigorous (P = .04) daily PA emerged as strong predictors of declines in attention/executive function over the 12-week period, but not of memory or language. Reductions in daily PA predicted acute decline in attention/executive function in HF, but not of memory or language. Modifications to daily PA may attenuate cognitive decline, and prospective studies are needed to test this possibility. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. The Predictive Factors of the Promotion of Physical Activity by Air Force Squadron Commanders

    National Research Council Canada - National Science Library

    Whelan, Dana

    2001-01-01

    This research examined the relationship between beliefs about physical activity, physical activity levels, age and the promotional practices for physical activity employed by Air Force squadron commanders...

  5. Scale Development for Measuring and Predicting Adolescents’ Leisure Time Physical Activity Behavior

    Science.gov (United States)

    Ries, Francis; Romero Granados, Santiago; Arribas Galarraga, Silvia

    2009-01-01

    The aim of this study was to develop a scale for assessing and predicting adolescents’ physical activity behavior in Spain and Luxembourg using the Theory of Planned Behavior as a framework. The sample was comprised of 613 Spanish (boys = 309, girls = 304; M age =15.28, SD =1.127) and 752 Luxembourgish adolescents (boys = 343, girls = 409; M age = 14.92, SD = 1.198), selected from students of two secondary schools in both countries, with a similar socio-economic status. The initial 43-items were all scored on a 4-point response format using the structured alternative format and translated into Spanish, French and German. In order to ensure the accuracy of the translation, standardized parallel back-translation techniques were employed. Following two pilot tests and subsequent revisions, a second order exploratory factor analysis with oblimin direct rotation was used for factor extraction. Internal consistency and test-retest reliabilities were also tested. The 4-week test-retest correlations confirmed the items’ time stability. The same five factors were obtained, explaining 63.76% and 63.64% of the total variance in both samples. Internal consistency for the five factors ranged from α = 0.759 to α = 0. 949 in the Spanish sample and from α = 0.735 to α = 0.952 in the Luxembourgish sample. For both samples, inter-factor correlations were all reported significant and positive, except for Factor 5 where they were significant but negative. The high internal consistency of the subscales, the reported item test-retest reliabilities and the identical factor structure confirm the adequacy of the elaborated questionnaire for assessing the TPB-based constructs when used with a population of adolescents in Spain and Luxembourg. The results give some indication that they may have value in measuring the hypothesized TPB constructs for PA behavior in a cross-cultural context. Key points When using the structured alternative format, weak internal consistency was obtained

  6. Early lactate clearance for predicting active bleeding in critically ill patients with acute upper gastrointestinal bleeding: a retrospective study.

    Science.gov (United States)

    Wada, Tomoki; Hagiwara, Akiyoshi; Uemura, Tatsuki; Yahagi, Naoki; Kimura, Akio

    2016-08-01

    Not all patients with upper gastrointestinal bleeding (UGIB) require emergency endoscopy. Lactate clearance has been suggested as a parameter for predicting patient outcomes in various critical care settings. This study investigates whether lactate clearance can predict active bleeding in critically ill patients with UGIB. This single-center, retrospective, observational study included critically ill patients with UGIB who met all of the following criteria: admission to the emergency department (ED) from April 2011 to August 2014; had blood samples for lactate evaluation at least twice during the ED stay; and had emergency endoscopy within 6 h of ED presentation. The main outcome was active bleeding detected with emergency endoscopy. Classification and regression tree (CART) analyses were performed using variables associated with active bleeding to derive a prediction rule for active bleeding in critically ill UGIB patients. A total of 154 patients with UGIB were analyzed, and 31.2 % (48/154) had active bleeding. In the univariate analysis, lactate clearance was significantly lower in patients with active bleeding than in those without active bleeding (13 vs. 29 %, P bleeding is derived, and includes three variables: lactate clearance; platelet count; and systolic blood pressure at ED presentation. The rule has 97.9 % (95 % CI 90.2-99.6 %) sensitivity with 32.1 % (28.6-32.9 %) specificity. Lactate clearance may be associated with active bleeding in critically ill patients with UGIB, and may be clinically useful as a component of a prediction rule for active bleeding.

  7. Surface tensions of multi-component mixed inorganic/organic aqueous systems of atmospheric significance: measurements, model predictions and importance for cloud activation predictions

    Directory of Open Access Journals (Sweden)

    D. O. Topping

    2007-01-01

    , it would appear that in order to model multi-component surface tensions involving compounds used in this study one requires the use of appropriate binary data. However, results indicate that the use of theoretical frameworks which contain parameters derived from binary data may predict unphysical behaviour when taken beyond the concentration ranges used to fit such parameters. The effect of deviations between predicted and measured surface tensions on predicted critical saturation ratios was quantified, by incorporating the surface tension models into an existing thermodynamic framework whilst firstly neglecting bulk to surface partitioning. Critical saturation ratios as a function of dry size for all of the multi-component systems were computed and it was found that deviations between predictions increased with decreasing particle dry size. As expected, use of the surface tension of pure water, rather than calculate the influence of the solutes explicitly, led to a consistently higher value of the critical saturation ratio indicating that neglect of the compositional effects will lead to significant differences in predicted activation behaviour even at large particle dry sizes. Following this two case studies were used to study the possible effect of bulk to surface partitioning on critical saturation ratios. By employing various assumptions it was possible to perform calculations not only for a binary system but also for a mixed organic system. In both cases this effect lead to a significant increase in the predicted critical supersaturation ratio compared to the above treatment. Further analysis of this effect will form the focus of future work.

  8. Accuracy statistics in predicting Independent Activities of Daily Living (IADL) capacity with comprehensive and brief neuropsychological test batteries.

    Science.gov (United States)

    Karzmark, Peter; Deutsch, Gayle K

    2018-01-01

    This investigation was designed to determine the predictive accuracy of a comprehensive neuropsychological and brief neuropsychological test battery with regard to the capacity to perform instrumental activities of daily living (IADLs). Accuracy statistics that included measures of sensitivity, specificity, positive and negative predicted power and positive likelihood ratio were calculated for both types of batteries. The sample was drawn from a general neurological group of adults (n = 117) that included a number of older participants (age >55; n = 38). Standardized neuropsychological assessments were administered to all participants and were comprised of the Halstead Reitan Battery and portions of the Wechsler Adult Intelligence Scale-III. A comprehensive test battery yielded a moderate increase over base-rate in predictive accuracy that generalized to older individuals. There was only limited support for using a brief battery, for although sensitivity was high, specificity was low. We found that a comprehensive neuropsychological test battery provided good classification accuracy for predicting IADL capacity.

  9. Predicting clinical outcome using brain activation associated with set-shifting and central coherence skills in Anorexia Nervosa.

    Science.gov (United States)

    Garrett, Amy S; Lock, James; Datta, Nandini; Beenhaker, Judy; Kesler, Shelli R; Reiss, Allan L

    2014-10-01

    Patients with Anorexia Nervosa (AN) have neuropsychological deficits in Set-Shifting (SS) and central coherence (CC) consistent with an inflexible thinking style and overly detailed processing style, respectively. This study investigates brain activation during SS and CC tasks in patients with AN and tests whether this activation is a biomarker that predicts response to treatment. FMRI data were collected from 21 females with AN while performing an SS task (the Wisconsin Card Sort) and a CC task (embedded figures), and used to predict outcome following 16 weeks of treatment (either 16 weeks of cognitive behavioral therapy or 8 weeks cognitive remediation therapy followed by 8 weeks of cognitive behavioral therapy). Significant activation during the SS task included bilateral dorsolateral and ventrolateral prefrontal cortex and left anterior middle frontal gyrus. Higher scores on the neuropsychological test of SS (measured outside the scanner at baseline) were correlated with greater DLPFC and VLPFC/insula activation. Improvements in SS following treatment were significantly predicted by a combination of low VLPFC/insula and high anterior middle frontal activation (R squared = .68, p = .001). For the CC task, visual and parietal cortical areas were activated, but were not significantly correlated with neuropsychological measures of CC and did not predict outcome. Cognitive flexibility requires the support of several prefrontal cortex resources. As previous studies suggest that the VLPFC is important for selecting context-appropriate responses, patients who have difficulties with this skill may benefit the most from cognitive therapy with or without cognitive remediation therapy. The ability to sustain inhibition of an unwanted response, subserved by the anterior middle frontal gyrus, is a cognitive feature that predicts favorable outcome to cognitive treatment. CC deficits may not be an effective predictor of clinical outcome. Copyright © 2014 Elsevier Ltd. All

  10. Mathematical prediction of core body temperature from environment, activity, and clothing: The heat strain decision aid (HSDA).

    Science.gov (United States)

    Potter, Adam W; Blanchard, Laurie A; Friedl, Karl E; Cadarette, Bruce S; Hoyt, Reed W

    2017-02-01

    Physiological models provide useful summaries of complex interrelated regulatory functions. These can often be reduced to simple input requirements and simple predictions for pragmatic applications. This paper demonstrates this modeling efficiency by tracing the development of one such simple model, the Heat Strain Decision Aid (HSDA), originally developed to address Army needs. The HSDA, which derives from the Givoni-Goldman equilibrium body core temperature prediction model, uses 16 inputs from four elements: individual characteristics, physical activity, clothing biophysics, and environmental conditions. These inputs are used to mathematically predict core temperature (T c ) rise over time and can estimate water turnover from sweat loss. Based on a history of military applications such as derivation of training and mission planning tools, we conclude that the HSDA model is a robust integration of physiological rules that can guide a variety of useful predictions. The HSDA model is limited to generalized predictions of thermal strain and does not provide individualized predictions that could be obtained from physiological sensor data-driven predictive models. This fully transparent physiological model should be improved and extended with new findings and new challenging scenarios. Published by Elsevier Ltd.

  11. Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches.

    Science.gov (United States)

    Memarian, Negar; Torre, Jared B; Haltom, Kate E; Stanton, Annette L; Lieberman, Matthew D

    2017-09-01

    Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. © The Author (2017). Published by Oxford University Press.

  12. A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

    Science.gov (United States)

    Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

    2006-08-01

    A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

  13. Accurate cut-offs for predicting endoscopic activity and mucosal healing in Crohn's disease with fecal calprotectin

    Directory of Open Access Journals (Sweden)

    Juan María Vázquez-Morón

    Full Text Available Background: Fecal biomarkers, especially fecal calprotectin, are useful for predicting endoscopic activity in Crohn's disease; however, the cut-off point remains unclear. The aim of this paper was to analyze whether faecal calprotectin and M2 pyruvate kinase are good tools for generating highly accurate scores for the prediction of the state of endoscopic activity and mucosal healing. Methods: The simple endoscopic score for Crohn's disease and the Crohn's disease activity index was calculated for 71 patients diagnosed with Crohn's. Fecal calprotectin and M2-PK were measured by the enzyme-linked immunosorbent assay test. Results: A fecal calprotectin cut-off concentration of ≥ 170 µg/g (sensitivity 77.6%, specificity 95.5% and likelihood ratio +17.06 predicts a high probability of endoscopic activity, and a fecal calprotectin cut-off of ≤ 71 µg/g (sensitivity 95.9%, specificity 52.3% and likelihood ratio -0.08 predicts a high probability of mucosal healing. Three clinical groups were identified according to the data obtained: endoscopic activity (calprotectin ≥ 170, mucosal healing (calprotectin ≤ 71 and uncertainty (71 > calprotectin < 170, with significant differences in endoscopic values (F = 26.407, p < 0.01. Clinical activity or remission modified the probabilities of presenting endoscopic activity (100% vs 89% or mucosal healing (75% vs 87% in the diagnostic scores generated. M2-PK was insufficiently accurate to determine scores. Conclusions: The highly accurate scores for fecal calprotectin provide a useful tool for interpreting the probabilities of presenting endoscopic activity or mucosal healing, and are valuable in the specific clinical context.

  14. Towards an Online Seizure Advisory System—An Adaptive Seizure Prediction Framework Using Active Learning Heuristics

    NARCIS (Netherlands)

    Karuppiah Ramachandran, Vignesh Raja; Alblas, Huibert J.; Le Viet Duc, Duc Viet; Meratnia, Nirvana

    2018-01-01

    In the last decade, seizure prediction systems have gained a lot of attention because of their enormous potential to largely improve the quality-of-life of the epileptic patients. The accuracy of the prediction algorithms to detect seizure in real-world applications is largely limited because the

  15. Intraoperative Active Bleeding in Endoscopic Surgery for Spontaneous Intracerebral Hemorrhage is Predicted by the Spot Sign.

    Science.gov (United States)

    Miki, Koichi; Yagi, Kenji; Nonaka, Masani; Iwaasa, Mitsutoshi; Abe, Hiroshi; Morishita, Takashi; Arima, Hisatomi; Inoue, Tooru

    2018-05-30

    Endoscopic evacuation of hematoma (EEH) has recently been applied to treat patients with spontaneous intracerebral hemorrhage (sICH). Intraoperative active bleeding (IAB), which is occasionally observed in EEH, might lead to greater blood loss, further brain damage, and more postoperative recurrent hemorrhage. However, no definite predictor of IAB has been established. Because the spot sign is associated with other hemorrhagic complications, we aimed to evaluate whether it predicts IAB. We retrospectively assessed the incidence and risk factors of IAB, including the spot sign, in 127 sICH patients who underwent EEH within 6 hours after computed tomography angiography at our institution between June 2009 and December 2017. The study included 53 women and 74 men with an average age of 66.7 ± 11.8 years. IAB occurred in 40 (31.5%) of the 127 patients, and it was more frequent in patients with the spot sign than in patients without it (14/24 [58.3%] vs. 26/103 [25.2%]; P = 0.003). Multivariable regression analyses suggested that the spot sign was an independent predictor of IAB (odds ratio [OR], 3.02; 95% confidence interval [CI], 1.10-8.30; P = 0.03). In addition, earlier surgery gradually increased the risk of IAB, and surgery within 4 hours of onset was an independent risk factor (OR, 4.34; 95% CI, 1.12-16.9; P = 0.03, referring to postonset 8 hours or more). The spot sign and early surgery were independent predictors of IAB in EEH for sICH. In patients with sICH and spot sign, complete treatment of IAB by electrocoagulation might be important for minimizing surgical complications. Copyright © 2018 Elsevier Inc. All rights reserved.

  16. SCALE DEVELOPMENT FOR MEASURING AND PREDICTING ADOLESCENTS' LEISURE TIME PHYSICAL ACTIVITY BEHAVIOR

    Directory of Open Access Journals (Sweden)

    Silvia Arribas Galarraga

    2009-12-01

    Full Text Available The aim of this study was to develop a scale for assessing and predicting adolescents' physical activity behavior in Spain and Luxembourg using the Theory of Planned Behavior as a framework. The sample was comprised of 613 Spanish (boys = 309, girls = 304; M age =15.28, SD =1.127 and 752 Luxembourgish adolescents (boys = 343, girls = 409; M age = 14.92, SD = 1.198, selected from students of two secondary schools in both countries, with a similar socio-economic status. The initial 43-items were all scored on a 4-point response format using the structured alternative format and translated into Spanish, French and German. In order to ensure the accuracy of the translation, standardized parallel back-translation techniques were employed. Following two pilot tests and subsequent revisions, a second order exploratory factor analysis with oblimin direct rotation was used for factor extraction. Internal consistency and test-retest reliabilities were also tested. The 4-week test-retest correlations confirmed the items' time stability. The same five factors were obtained, explaining 63.76% and 63.64% of the total variance in both samples. Internal consistency for the five factors ranged from α = 0.759 to α = 0. 949 in the Spanish sample and from α = 0.735 to α = 0.952 in the Luxembourgish sample. For both samples, inter-factor correlations were all reported significant and positive, except for Factor 5 where they were significant but negative. The high internal consistency of the subscales, the reported item test-retest reliabilities and the identical factor structure confirm the adequacy of the elaborated questionnaire for assessing the TPB-based constructs when used with a population of adolescents in Spain and Luxembourg. The results give some indication that they may have value in measuring the hypothesized TPB constructs for PA behavior in a cross-cultural context

  17. A Model Predictive Algorithm for Active Control of Nonlinear Noise Processes

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    Qi-Zhi Zhang

    2005-01-01

    Full Text Available In this paper, an improved nonlinear Active Noise Control (ANC system is achieved by introducing an appropriate secondary source. For ANC system to be successfully implemented, the nonlinearity of the primary path and time delay of the secondary path must be overcome. A nonlinear Model Predictive Control (MPC strategy is introduced to deal with the time delay in the secondary path and the nonlinearity in the primary path of the ANC system. An overall online modeling technique is utilized for online secondary path and primary path estimation. The secondary path is estimated using an adaptive FIR filter, and the primary path is estimated using a Neural Network (NN. The two models are connected in parallel with the two paths. In this system, the mutual disturbances between the operation of the nonlinear ANC controller and modeling of the secondary can be greatly reduced. The coefficients of the adaptive FIR filter and weight vector of NN are adjusted online. Computer simulations are carried out to compare the proposed nonlinear MPC method with the nonlinear Filter-x Least Mean Square (FXLMS algorithm. The results showed that the convergence speed of the proposed nonlinear MPC algorithm is faster than that of nonlinear FXLMS algorithm. For testing the robust performance of the proposed nonlinear ANC system, the sudden changes in the secondary path and primary path of the ANC system are considered. Results indicated that the proposed nonlinear ANC system can rapidly track the sudden changes in the acoustic paths of the nonlinear ANC system, and ensure the adaptive algorithm stable when the nonlinear ANC system is time variable.

  18. Prediction of motor outcomes and activities of daily living function using diffusion tensor tractography in acute hemiparetic stroke patients.

    Science.gov (United States)

    Imura, Takeshi; Nagasawa, Yuki; Inagawa, Tetsuji; Imada, Naoki; Izumi, Hiroaki; Emoto, Katsuya; Tani, Itaru; Yamasaki, Hiroyuki; Ota, Yuichiro; Oki, Shuichi; Maeda, Tadanori; Araki, Osamu

    2015-05-01

    [Purpose] The efficacy of diffusion tensor imaging in the prediction of motor outcomes and activities of daily living function remains unclear. We evaluated the most appropriate diffusion tensor parameters and methodology to determine whether the region of interest- or tractography-based method was more useful for predicting motor outcomes and activities of daily living function in stroke patients. [Subjects and Methods] Diffusion tensor imaging data within 10 days after stroke onset were collected and analyzed for 25 patients. The corticospinal tract was analyzed. Fractional anisotropy, number of fibers, and apparent diffusion coefficient were used as diffusion tensor parameters. Motor outcomes and activities of daily living function were evaluated on the same day as diffusion tensor imaging and at 1 month post-onset. [Results] The fractional anisotropy value of the affected corticospinal tract significantly correlated with the motor outcome and activities of daily living function within 10 days post-onset and at 1 month post-onset. Tthere were no significant correlations between other diffusion tensor parameters and motor outcomes or activities of daily living function. [Conclusion] The fractional anisotropy value of the affected corticospinal tract obtained using the tractography-based method was useful for predicting motor outcomes and activities of daily living function in stroke patients.

  19. Theoretical prediction of thermodynamic activities of liquid Au-Sn-X (X=Bi, Sb, Zn) solder systems

    Energy Technology Data Exchange (ETDEWEB)

    Awe, O.E., E-mail: draweoe2004@yahoo.com [Department of Physics, University of Ibadan, Ibadan (Nigeria); Department of Physics and Engineering Physics, Obafemi Awolowo University, Ile-Ife (Nigeria); Oshakuade, O.M. [Department of Physics, University of Ibadan, Ibadan (Nigeria)

    2017-02-15

    Molecular interaction volume model has been theoretically used to predict the thermodynamic activities of tin in Au-Sn-Bi and Au-Sn-Sb and the thermodynamic activity of zinc in Au-Sn-Zn at experimental temperatures 800 K, 873 K and 973 K, respectively. On the premise of agreement between the predicted and experimental values, we predicted the activities of the remaining two components in each of the three systems. This prediction was extended from three cross-sections to five cross-sections, and to temperature range 400–600 K, relevant for applications. Iso-activities were plotted. Results show that addition of tin reduces the tendency for chemical short range order in both Au-Sb and Au-Zn systems, while addition of gold and bismuth, respectively, reduce the tendency for chemical short range order in Sn-Sb and Au-Sn systems. Also, we found that, in the desired high-temperature region for applications, while a combination of chemical order and miscibility of components exist in both Au-Sn-Bi and Au-Sn-Zn systems, only chemical order exist in the Au-Sn-Sb system. Results, further show that increase in temperature reduces the phase separation tendency in Au-Sn-Bi system.

  20. Absorbed in the task : Personality measures predict engagement during task performance as tracked by error negativity and asymmetrical frontal activity

    NARCIS (Netherlands)

    Tops, Mattie; Boksem, Maarten A. S.

    2010-01-01

    We hypothesized that interactions between traits and context predict task engagement, as measured by the amplitude of the error-related negativity (ERN), performance, and relative frontal activity asymmetry (RFA). In Study 1, we found that drive for reward, absorption, and constraint independently

  1. QUANTITATIVE STRUCTURE—PROPERTY RELATIONSHIPS FOR ENHANCING PREDICTIONS OF SYNTHETIC ORGANIC CHEMICAL REMOVAL FROM DRINKING WATER BY GRANULAR ACTIVATED CARBON

    Science.gov (United States)

    A number of mathematical models have been developed to predict activated carbon column performance using single-solute isotherm data as inputs. Many assumptions are built into these models to account for kinetics of adsorption and competition for adsorption sites. This work...

  2. Comparative Analysis of Predictive Models for Liver Toxicity Using ToxCast Assays and Quantitative Structure-Activity Relationships (MCBIOS)

    Science.gov (United States)

    Comparative Analysis of Predictive Models for Liver Toxicity Using ToxCast Assays and Quantitative Structure-Activity Relationships Jie Liu1,2, Richard Judson1, Matthew T. Martin1, Huixiao Hong3, Imran Shah1 1National Center for Computational Toxicology (NCCT), US EPA, RTP, NC...

  3. A novel method for predicting activity of cis-regulatory modules, based on a diverse training set.

    Science.gov (United States)

    Yang, Wei; Sinha, Saurabh

    2017-01-01

    With the rapid emergence of technologies for locating cis-regulatory modules (CRMs) genome-wide, the next pressing challenge is to assign precise functions to each CRM, i.e. to determine the spatiotemporal domains or cell-types where it drives expression. A popular approach to this task is to model the typical k-mer composition of a set of CRMs known to drive a common expression pattern, and assign that pattern to other CRMs exhibiting a similar k-mer composition. This approach does not rely on prior knowledge of transcription factors relevant to the CRM or their binding motifs, and is thus more widely applicable than motif-based methods for predicting CRM activity, but is also prone to false positive predictions. We present a novel strategy to improve the above-mentioned approach: to predict if a CRM drives a specific gene expression pattern, assess not only how similar the CRM is to other CRMs with similar activity but also to CRMs with distinct activities. We use a state-of-the-art statistical method to quantify a CRM's sequence similarity to many different training sets of CRMs, and employ a classification algorithm to integrate these similarity scores into a single prediction of the CRM's activity. This strategy is shown to significantly improve CRM activity prediction over current approaches. Our implementation of the new method, called IMMBoost, is freely available as source code, at https://github.com/weiyangedward/IMMBoost CONTACT: sinhas@illinois.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  4. The nematode Caenorhabditis elegans as a tool to predict chemical activity on mammalian development and identify mechanisms influencing toxicological outcome.

    Science.gov (United States)

    Harlow, Philippa H; Perry, Simon J; Widdison, Stephanie; Daniels, Shannon; Bondo, Eddie; Lamberth, Clemens; Currie, Richard A; Flemming, Anthony J

    2016-03-18

    To determine whether a C. elegans bioassay could predict mammalian developmental activity, we selected diverse compounds known and known not to elicit such activity and measured their effect on C. elegans egg viability. 89% of compounds that reduced C. elegans egg viability also had mammalian developmental activity. Conversely only 25% of compounds found not to reduce egg viability in C. elegans were also inactive in mammals. We conclude that the C. elegans egg viability assay is an accurate positive predictor, but an inaccurate negative predictor, of mammalian developmental activity. We then evaluated C. elegans as a tool to identify mechanisms affecting toxicological outcomes among related compounds. The difference in developmental activity of structurally related fungicides in C. elegans correlated with their rate of metabolism. Knockdown of the cytochrome P450s cyp-35A3 and cyp-35A4 increased the toxicity to C. elegans of the least developmentally active compounds to the level of the most developmentally active. This indicated that these P450s were involved in the greater rate of metabolism of the less toxic of these compounds. We conclude that C. elegans based approaches can predict mammalian developmental activity and can yield plausible hypotheses for factors affecting the biological potency of compounds in mammals.

  5. Matrix Metalloproteinase-9/Neutrophil Gelatinase-Associated Lipocalin Complex Activity in Human Glioma Samples Predicts Tumor Presence and Clinical Prognosis

    Directory of Open Access Journals (Sweden)

    Ming-Fa Liu

    2015-01-01

    Full Text Available Matrix metalloproteinase-9/neutrophil gelatinase-associated lipocalin (MMP-9/NGAL complex activity is elevated in brain tumors and may serve as a molecular marker for brain tumors. However, the relationship between MMP-9/NGAL activity in brain tumors and patient prognosis and treatment response remains unclear. Here, we compared the clinical characteristics of glioma patients with the MMP-9/NGAL activity measured in their respective tumor and urine samples. Using gelatin zymography assays, we found that MMP-9/NGAL activity was significantly increased in tumor tissues (TT and preoperative urine samples (Preop-1d urine. Activity was reduced by seven days after surgery (Postop-1w urine and elevated again in cases of tumor recurrence. The MMP-9/NGAL status correlated well with MRI-based tumor assessments. These findings suggest that MMP-9/NGAL activity could be a novel marker to detect gliomas and predict the clinical outcome of patients.

  6. Discovery and Characterization of Non-ATP Site Inhibitors of the Mitogen Activated Protein (MAP) Kinases

    Energy Technology Data Exchange (ETDEWEB)

    Comess, Kenneth M.; Sun, Chaohong; Abad-Zapatero, Cele; Goedken, Eric R.; Gum, Rebecca J.; Borhani, David W.; Argiriadi, Maria; Groebe, Duncan R.; Jia, Yong; Clampit, Jill E.; Haasch, Deanna L.; Smith, Harriet T.; Wang, Sanyi; Song, Danying; Coen, Michael L.; Cloutier, Timothy E.; Tang, Hua; Cheng, Xueheng; Quinn, Christopher; Liu, Bo; Xin, Zhili; Liu, Gang; Fry, Elizabeth H.; Stoll, Vincent; Ng, Teresa I.; Banach, David; Marcotte, Doug; Burns, David J.; Calderwood, David J.; Hajduk, Philip J. (Abbott)

    2012-03-02

    Inhibition of protein kinases has validated therapeutic utility for cancer, with at least seven kinase inhibitor drugs on the market. Protein kinase inhibition also has significant potential for a variety of other diseases, including diabetes, pain, cognition, and chronic inflammatory and immunologic diseases. However, as the vast majority of current approaches to kinase inhibition target the highly conserved ATP-binding site, the use of kinase inhibitors in treating nononcology diseases may require great selectivity for the target kinase. As protein kinases are signal transducers that are involved in binding to a variety of other proteins, targeting alternative, less conserved sites on the protein may provide an avenue for greater selectivity. Here we report an affinity-based, high-throughput screening technique that allows nonbiased interrogation of small molecule libraries for binding to all exposed sites on a protein surface. This approach was used to screen both the c-Jun N-terminal protein kinase Jnk-1 (involved in insulin signaling) and p38{alpha} (involved in the formation of TNF{alpha} and other cytokines). In addition to canonical ATP-site ligands, compounds were identified that bind to novel allosteric sites. The nature, biological relevance, and mode of binding of these ligands were extensively characterized using two-dimensional {sup 1}H/{sup 13}C NMR spectroscopy, protein X-ray crystallography, surface plasmon resonance, and direct enzymatic activity and activation cascade assays. Jnk-1 and p38{alpha} both belong to the MAP kinase family, and the allosteric ligands for both targets bind similarly on a ledge of the protein surface exposed by the MAP insertion present in the CMGC family of protein kinases and distant from the active site. Medicinal chemistry studies resulted in an improved Jnk-1 ligand able to increase adiponectin secretion in human adipocytes and increase insulin-induced protein kinase PKB phosphorylation in human hepatocytes, in

  7. Predicting physical activity in adolescents: the role of compensatory health beliefs within the Health Action Process Approach.

    Science.gov (United States)

    Berli, Corina; Loretini, Philipp; Radtke, Theda; Hornung, Rainer; Scholz, Urte

    2014-01-01

    Compensatory health beliefs (CHBs), defined as beliefs that healthy behaviours can compensate for unhealthy behaviours, may be one possible factor hindering people in adopting a healthier lifestyle. This study examined the contribution of CHBs to the prediction of adolescents' physical activity within the theoretical framework of the Health Action Process Approach (HAPA). The study followed a prospective survey design with assessments at baseline (T1) and two weeks later (T2). Questionnaire data on physical activity, HAPA variables and CHBs were obtained twice from 430 adolescents of four different Swiss schools. Multilevel modelling was applied. CHBs added significantly to the prediction of intentions and change in intentions, in that higher CHBs were associated with lower intentions to be physically active at T2 and a reduction in intentions from T1 to T2. No effect of CHBs emerged for the prediction of self-reported levels of physical activity at T2 and change in physical activity from T1 to T2. Findings emphasise the relevance of examining CHBs in the context of an established health behaviour change model and suggest that CHBs are of particular importance in the process of intention formation.

  8. Strength of figure-ground activity in monkey primary visual cortex predicts saccadic reaction time in a delayed detection task.

    Science.gov (United States)

    Supèr, Hans; Lamme, Victor A F

    2007-06-01

    When and where are decisions made? In the visual system a saccade, which is a fast shift of gaze toward a target in the visual scene, is the behavioral outcome of a decision. Current neurophysiological data and reaction time models show that saccadic reaction times are determined by a build-up of activity in motor-related structures, such as the frontal eye fields. These structures depend on the sensory evidence of the stimulus. Here we use a delayed figure-ground detection task to show that late modulated activity in the visual cortex (V1) predicts saccadic reaction time. This predictive activity is part of the process of figure-ground segregation and is specific for the saccade target location. These observations indicate that sensory signals are directly involved in the decision of when and where to look.

  9. Prediction of P53 mutants (multiple sites transcriptional activity based on structural (2D&3D properties.

    Directory of Open Access Journals (Sweden)

    R Geetha Ramani

    Full Text Available Prediction of secondary site mutations that reinstate mutated p53 to normalcy has been the focus of intense research in the recent past owing to the fact that p53 mutants have been implicated in more than half of all human cancers and restoration of p53 causes tumor regression. However laboratory investigations are more often laborious and resource intensive but computational techniques could well surmount these drawbacks. In view of this, we formulated a novel approach utilizing computational techniques to predict the transcriptional activity of multiple site (one-site to five-site p53 mutants. The optimal MCC obtained by the proposed approach on prediction of one-site, two-site, three-site, four-site and five-site mutants were 0.775,0.341,0.784,0.916 and 0.655 respectively, the highest reported thus far in literature. We have also demonstrated that 2D and 3D features generate higher prediction accuracy of p53 activity and our findings revealed the optimal results for prediction of p53 status, reported till date. We believe detection of the secondary site mutations that suppress tumor growth may facilitate better understanding of the relationship between p53 structure and function and further knowledge on the molecular mechanisms and biological activity of p53, a targeted source for cancer therapy. We expect that our prediction methods and reported results may provide useful insights on p53 functional mechanisms and generate more avenues for utilizing computational techniques in biological data analysis.

  10. Assessment of the possibility of using data mining methods to predict sorption isotherms of selected organic compounds on activated carbon

    Directory of Open Access Journals (Sweden)

    Dąbek Lidia

    2017-01-01

    Full Text Available The paper analyses the use of four data mining methods (Support Vector Machines. Cascade Neural Networks. Random Forests and Boosted Trees to predict sorption on activated carbons. The input data for statistical models included the activated carbon parameters, organic substances and equilibrium concentrations in the solution. The assessment of the predictive abilities of the developed models was made with the use of mean absolute error (MAE, mean absolute percentage error (MAPE, and root mean squared error (RMSE. The computations proved that methods of data mining considered in the study can be applied to predict sorption of selected organic compounds 011 activated carbon. The lowest values of sorption prediction errors were obtained with the Cascade Neural Networks method (MAE = 1.23 g/g; MAPE = 7.90% and RMSE = 1.81 g/g, while the highest error values were produced by the Boosted Trees method (MAE=14.31 g/g; MAPE = 39.43% and RMSE = 27.76 g/g.

  11. Ongoing activity in temporally coherent networks predicts intra-subject fluctuation of response time to sporadic executive control demands.

    Science.gov (United States)

    Nozawa, Takayuki; Sugiura, Motoaki; Yokoyama, Ryoichi; Ihara, Mizuki; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Kanno, Akitake; Kawashima, Ryuta

    2014-01-01

    Can ongoing fMRI BOLD signals predict fluctuations in swiftness of a person's response to sporadic cognitive demands? This is an important issue because it clarifies whether intrinsic brain dynamics, for which spatio-temporal patterns are expressed as temporally coherent networks (TCNs), have effects not only on sensory or motor processes, but also on cognitive processes. Predictivity has been affirmed, although to a limited extent. Expecting a predictive effect on executive performance for a wider range of TCNs constituting the cingulo-opercular, fronto-parietal, and default mode networks, we conducted an fMRI study using a version of the color-word Stroop task that was specifically designed to put a higher load on executive control, with the aim of making its fluctuations more detectable. We explored the relationships between the fluctuations in ongoing pre-trial activity in TCNs and the task response time (RT). The results revealed the existence of TCNs in which fluctuations in activity several seconds before the onset of the trial predicted RT fluctuations for the subsequent trial. These TCNs were distributed in the cingulo-opercular and fronto-parietal networks, as well as in perceptual and motor networks. Our results suggest that intrinsic brain dynamics in these networks constitute "cognitive readiness," which plays an active role especially in situations where information for anticipatory attention control is unavailable. Fluctuations in these networks lead to fluctuations in executive control performance.

  12. Does functional capacity, fall risk awareness and physical activity level predict falls in older adults in different age groups?

    Science.gov (United States)

    Moreira, Natália Boneti; Rodacki, Andre Luiz Felix; Pereira, Gléber; Bento, Paulo Cesar Barauce

    2018-04-11

    The aims of this study were to examine whether: i) functional capacity and physical activity level differ between fallers and non-fallers older adults, by controlling for fall risk awareness; ii) functional capacity, fall risk awareness and physical activity differ between fallers and non-fallers older adults, by controlling for age; iii) variables and which may predict falls in different age groups. 1826 older adults performed a series of functional tests and reported their fall episodes, fall risk awareness and physical activity level. The overall incidence of falls was high (40.2%), and falls risk awareness scores reduced with age. The older adults with greater falls risk awareness and non-fallers presented better scores in all functional tests and physical activity level (P age groups and differed between fallers and non-fallers, irrespective of age group (P age groups (odds ranging: 1.05-1.09). Handgrip strength and balance scores predicted falls until 79 years (OR = 1.04, 95%CI = 1.01-1.06). The physical activity level predicted falls up to 70 years (OR = 1.09, 95%CI = 1.06-1.12). Functional mobility was able to predict falls up to 80 years (OR = 1.06, 95%CI = 1.01-1.08). Therefore, according to age, functional capacity, physical activity level and falls risk awareness can be a predictor of falls in older adults. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. Differential Patterns of Amygdala and Ventral Striatum Activation Predict Gender-Specific Changes in Sexual Risk Behavior

    Science.gov (United States)

    Sansosti, Alexandra A.; Bowman, Hilary C.; Hariri, Ahmad R.

    2015-01-01

    Although the initiation of sexual behavior is common among adolescents and young adults, some individuals express this behavior in a manner that significantly increases their risk for negative outcomes including sexually transmitted infections. Based on accumulating evidence, we have hypothesized that increased sexual risk behavior reflects, in part, an imbalance between neural circuits mediating approach and avoidance in particular as manifest by relatively increased ventral striatum (VS) activity and relatively decreased amygdala activity. Here, we test our hypothesis using data from seventy 18- to 22-year-old university students participating in the Duke Neurogenetics Study. We found a significant three-way interaction between amygdala activation, VS activation, and gender predicting changes in the number of sexual partners over time. Although relatively increased VS activation predicted greater increases in sexual partners for both men and women, the effect in men was contingent on the presence of relatively decreased amygdala activation and the effect in women was contingent on the presence of relatively increased amygdala activation. These findings suggest unique gender differences in how complex interactions between neural circuit function contributing to approach and avoidance may be expressed as sexual risk behavior in young adults. As such, our findings have the potential to inform the development of novel, gender-specific strategies that may be more effective at curtailing sexual risk behavior. PMID:26063921

  14. Insulin resistance predicts early cardiovascular morbidity in men without diabetes mellitus, with effect modification by physical activity.

    Science.gov (United States)

    Hellgren, Margareta I; Daka, Bledar; Jansson, Per-Anders; Lindblad, Ulf; Larsson, Charlotte A

    2015-07-01

    to assess how well insulin resistance predicts cardiovascular disease (CVD) in non-diabetic men and women and to explore the influence of physical activity. in this prospective study 2563 men and women without diabetes were examined with an oral glucose tolerance test, anthropometric measurements and blood pressure assessment. Questionnaires about lifestyle and physical activity were completed. Insulin resistance was estimated by fasting concentrations of plasma insulin and by HOMA index for insulin resistance. Participants were followed up for cardiovascular morbidity and mortality during an 8-year period, using information from the National Swedish Inpatient and Mortality registers. at follow-up, HOMAir predicted CVD morbidity in males (50 events) and females (28 events) combined (HRage/sex-adj 1.4, 95% CI 1.1-1.7); however, when stratified by gender HOMAir was predictive solely in men (HRage-adj 1.8, 95% CI 1.3-2.4), whereas no association was found in women (HRage-adj 1.1, 95% CI 0.8-1.5). When stratifying the data for high and low physical activity, the predictive value of insulin resistance became stronger in sedentary men (HRage-adj 2.3, 95% CI 1.5-3.4) but was abolished in men performing moderate to vigorous physical activity (HRage-adj 1.0, 95% CI 0.6-1.6). The results remained when step-wise adjusted also for BMI, ApoB/ApoA1 and hypertension, as well as for smoking, alcohol consumption and education. Outcome for fasting plasma insulin was similar to HOMAir. insulin resistance predicts CVD in the general population; however, men may be more vulnerable to increased insulin resistance than women, and physically inactive men seem to be at high risk. © The European Society of Cardiology 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  15. PREVAIL: Predicting Recovery through Estimation and Visualization of Active and Incident Lesions.

    Science.gov (United States)

    Dworkin, Jordan D; Sweeney, Elizabeth M; Schindler, Matthew K; Chahin, Salim; Reich, Daniel S; Shinohara, Russell T

    2016-01-01

    The goal of this study was to develop a model that integrates imaging and clinical information observed at lesion incidence for predicting the recovery of white matter lesions in multiple sclerosis (MS) patients. Demographic, clinical, and magnetic resonance imaging (MRI) data were obtained from 60 subjects with MS as part of a natural history study at the National Institute of Neurological Disorders and Stroke. A total of 401 lesions met the inclusion criteria and were used in the study. Imaging features were extracted from the intensity-normalized T1-weighted (T1w) and T2-weighted sequences as well as magnetization transfer ratio (MTR) sequence acquired at lesion incidence. T1w and MTR signatures were also extracted from images acquired one-year post-incidence. Imaging features were integrated with clinical and demographic data observed at lesion incidence to create statistical prediction models for long-term damage within the lesion. The performance of the T1w and MTR predictions was assessed in two ways: first, the predictive accuracy was measured quantitatively using leave-one-lesion-out cross-validated (CV) mean-squared predictive error. Then, to assess the prediction performance from the perspective of expert clinicians, three board-certified MS clinicians were asked to individually score how similar the CV model-predicted one-year appearance was to the true one-year appearance for a random sample of 100 lesions. The cross-validated root-mean-square predictive error was 0.95 for normalized T1w and 0.064 for MTR, compared to the estimated measurement errors of 0.48 and 0.078 respectively. The three expert raters agreed that T1w and MTR predictions closely resembled the true one-year follow-up appearance of the lesions in both degree and pattern of recovery within lesions. This study demonstrates that by using only information from a single visit at incidence, we can predict how a new lesion will recover using relatively simple statistical techniques. The

  16. Predicting Wetland Distribution Changes under Climate Change and Human Activities in a Mid- and High-Latitude Region

    Directory of Open Access Journals (Sweden)

    Dandan Zhao

    2018-03-01

    Full Text Available Wetlands in the mid- and high-latitudes are particularly vulnerable to environmental changes and have declined dramatically in recent decades. Climate change and human activities are arguably the most important factors driving wetland distribution changes which will have important implications for wetland ecological functions and services. We analyzed the importance of driving variables for wetland distribution and investigated the relative importance of climatic factors and human activity factors in driving historical wetland distribution changes. We predicted wetland distribution changes under climate change and human activities over the 21st century using the Random Forest model in a mid- and high-latitude region of Northeast China. Climate change scenarios included three Representative Concentration Pathways (RCPs based on five general circulation models (GCMs downloaded from the Coupled Model Intercomparison Project, Phase 5 (CMIP5. The three scenarios (RCP 2.6, RCP 4.5, and RCP 8.5 predicted radiative forcing to peak at 2.6, 4.5, and 8.5 W/m2 by the 2100s, respectively. Our results showed that the variables with high importance scores were agricultural population proportion, warmness index, distance to water body, coldness index, and annual mean precipitation; climatic variables were given higher importance scores than human activity variables on average. Average predicted wetland area among three emission scenarios were 340,000 ha, 123,000 ha, and 113,000 ha for the 2040s, 2070s, and 2100s, respectively. Average change percent in predicted wetland area among three periods was greatest under the RCP 8.5 emission scenario followed by RCP 4.5 and RCP 2.6 emission scenarios, which were 78%, 64%, and 55%, respectively. Losses in predicted wetland distribution were generally around agricultural lands and expanded continually from the north to the whole region over time, while the gains were mostly associated with grasslands and water in the

  17. Prediction of radical scavenging activities of anthocyanins applying adaptive neuro-fuzzy inference system (ANFIS) with quantum chemical descriptors.

    Science.gov (United States)

    Jhin, Changho; Hwang, Keum Taek

    2014-08-22

    Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A) and electronegativity (χ) of flavylium cation, and ionization potential (I) of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively.

  18. Prediction of Radical Scavenging Activities of Anthocyanins Applying Adaptive Neuro-Fuzzy Inference System (ANFIS with Quantum Chemical Descriptors

    Directory of Open Access Journals (Sweden)

    Changho Jhin

    2014-08-01

    Full Text Available Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A and electronegativity (χ of flavylium cation, and ionization potential (I of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively.

  19. Sense of coherence predicts post-myocardial infarction trajectory of leisure time physical activity: a prospective cohort study

    Directory of Open Access Journals (Sweden)

    Gerber Yariv

    2011-09-01

    Full Text Available Abstract Background Physical activity confers a survival advantage after myocardial infarction (MI, yet the majority of post-MI patients are not regularly active. Since sense of coherence (SOC has been associated with health outcomes and some health behaviours, we investigated whether it plays a role in post-MI physical activity. We examined the predictive role of SOC in the long-term trajectory of leisure time physical activity (LTPA after MI using a prospective cohort design. Methods A cohort of 643 patients aged ≤ 65 years admitted to hospital in central Israel with incident MI between February 1992 and February 1993 were followed up for 13 years. Socioeconomic, clinical and psychological factors, including SOC, were assessed at baseline, and LTPA was self-reported on 5 separate occasions during follow-up. The predictive role of SOC in long-term trajectory of LTPA was assessed using generalized estimating equations. Results SOC was consistently associated with engagement in LTPA throughout follow-up. Patients in the lowest SOC tertile had almost twice the odds (odds ratio,1.99; 95% confidence interval,1.52-2.60 of decreasing their engagement in LTPA as those in the highest tertile. A strong association remained after controlling for disease severity, depression, sociodemographic and clinical factors. Conclusion Our evidence suggests that SOC predicts LTPA trajectory post-MI. Assessment of SOC can help identify high-risk MI survivors, who may require additional help in following secondary prevention recommendations which can dramatically improve prognosis.

  20. The Density Functional Theory of Flies: Predicting distributions of interacting active organisms

    Science.gov (United States)

    Kinkhabwala, Yunus; Valderrama, Juan; Cohen, Itai; Arias, Tomas

    On October 2nd, 2016, 52 people were crushed in a stampede when a crowd panicked at a religious gathering in Ethiopia. The ability to predict the state of a crowd and whether it is susceptible to such transitions could help prevent such catastrophes. While current techniques such as agent based models can predict transitions in emergent behaviors of crowds, the assumptions used to describe the agents are often ad hoc and the simulations are computationally expensive making their application to real-time crowd prediction challenging. Here, we pursue an orthogonal approach and ask whether a reduced set of variables, such as the local densities, are sufficient to describe the state of a crowd. Inspired by the theoretical framework of Density Functional Theory, we have developed a system that uses only measurements of local densities to extract two independent crowd behavior functions: (1) preferences for locations and (2) interactions between individuals. With these two functions, we have accurately predicted how a model system of walking Drosophila melanogaster distributes itself in an arbitrary 2D environment. In addition, this density-based approach measures properties of the crowd from only observations of the crowd itself without any knowledge of the detailed interactions and thus it can make predictions about the resulting distributions of these flies in arbitrary environments, in real-time. This research was supported in part by ARO W911NF-16-1-0433.

  1. In-Season Yield Prediction of Cabbage with a Hand-Held Active Canopy Sensor.

    Science.gov (United States)

    Ji, Rongting; Min, Ju; Wang, Yuan; Cheng, Hu; Zhang, Hailin; Shi, Weiming

    2017-10-08

    Efficient and precise yield prediction is critical to optimize cabbage yields and guide fertilizer application. A two-year field experiment was conducted to establish a yield prediction model for cabbage by using the Greenseeker hand-held optical sensor. Two cabbage cultivars (Jianbao and Pingbao) were used and Jianbao cultivar was grown for 2 consecutive seasons but Pingbao was only grown in the second season. Four chemical nitrogen application rates were implemented: 0, 80, 140, and 200 kg·N·ha -1 . Normalized difference vegetation index (NDVI) was collected 20, 50, 70, 80, 90, 100, 110, 120, 130, and 140 days after transplanting (DAT). Pearson correlation analysis and regression analysis were performed to identify the relationship between the NDVI measurements and harvested yields of cabbage. NDVI measurements obtained at 110 DAT were significantly correlated to yield and explained 87-89% and 75-82% of the cabbage yield variation of Jianbao cultivar over the two-year experiment and 77-81% of the yield variability of Pingbao cultivar. Adjusting the yield prediction models with CGDD (cumulative growing degree days) could make remarkable improvement to the accuracy of the prediction model and increase the determination coefficient to 0.82, while the modification with DFP (days from transplanting when GDD > 0) values did not. The integrated exponential yield prediction equation was better than linear or quadratic functions and could accurately make in-season estimation of cabbage yields with different cultivars between years.

  2. The contribution of former work-related activity levels to predict physical activity and sedentary time during early retirement: moderating role of educational level and physical functioning.

    Directory of Open Access Journals (Sweden)

    Delfien Van Dyck

    Full Text Available The transition to retirement introduces a decline in total physical activity and an increase in TV viewing time. Nonetheless, as more time becomes available, early retirement is an ideal stage to implement health interventions. Therefore, knowledge on specific determinants of physical activity and sedentary time is needed. Former work-related physical activity has been proposed as a potential determinant, but concrete evidence is lacking. The aim of this study was to examine if former work-related sitting, standing, walking or vigorous activities predict physical activity and sedentary time during early retirement. Additionally, moderating effects of educational level and physical functioning were examined.In total, 392 recently retired Belgian adults (>6 months, <5 years completed the International Physical Activity Questionnaire, the SF-36 Health Survey and a questionnaire on sociodemographics and former work-related activities. Generalized linear regression analyses were conducted in R. Moderating effects were examined by adding cross-products to the models.More former work-related sitting was predictive of more screen time during retirement. Lower levels of former work-related vigorous activities and higher levels of former work-related walking were associated with respectively more cycling for transport and more walking for transport during retirement. None of the predictors significantly explained passive transportation, cycling and walking for recreation, and leisure-time moderate-to-vigorous physical activity during retirement. Several moderating effects were found, but the direction of the interactions was not univocal.Former-work related behaviors are of limited importance to explain physical activity during early retirement, so future studies should focus on other individual, social and environmental determinants. Nonetheless, adults who previously had a sedentary job had higher levels of screen time during retirement, so this is an

  3. The contribution of former work-related activity levels to predict physical activity and sedentary time during early retirement: moderating role of educational level and physical functioning.

    Science.gov (United States)

    Van Dyck, Delfien; Cardon, Greet; Deforche, Benedicte; De Bourdeaudhuij, Ilse

    2015-01-01

    The transition to retirement introduces a decline in total physical activity and an increase in TV viewing time. Nonetheless, as more time becomes available, early retirement is an ideal stage to implement health interventions. Therefore, knowledge on specific determinants of physical activity and sedentary time is needed. Former work-related physical activity has been proposed as a potential determinant, but concrete evidence is lacking. The aim of this study was to examine if former work-related sitting, standing, walking or vigorous activities predict physical activity and sedentary time during early retirement. Additionally, moderating effects of educational level and physical functioning were examined. In total, 392 recently retired Belgian adults (>6 months, Physical Activity Questionnaire, the SF-36 Health Survey and a questionnaire on sociodemographics and former work-related activities. Generalized linear regression analyses were conducted in R. Moderating effects were examined by adding cross-products to the models. More former work-related sitting was predictive of more screen time during retirement. Lower levels of former work-related vigorous activities and higher levels of former work-related walking were associated with respectively more cycling for transport and more walking for transport during retirement. None of the predictors significantly explained passive transportation, cycling and walking for recreation, and leisure-time moderate-to-vigorous physical activity during retirement. Several moderating effects were found, but the direction of the interactions was not univocal. Former-work related behaviors are of limited importance to explain physical activity during early retirement, so future studies should focus on other individual, social and environmental determinants. Nonetheless, adults who previously had a sedentary job had higher levels of screen time during retirement, so this is an important subgroup to focus on during interventions

  4. Prediction based active ramp metering control strategy with mobility and safety assessment

    Science.gov (United States)

    Fang, Jie; Tu, Lili

    2018-04-01

    Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.

  5. Optimization of muscle activity for task-level goals predicts complex changes in limb forces across biomechanical contexts.

    Directory of Open Access Journals (Sweden)

    J Lucas McKay

    Full Text Available Optimality principles have been proposed as a general framework for understanding motor control in animals and humans largely based on their ability to predict general features movement in idealized motor tasks. However, generalizing these concepts past proof-of-principle to understand the neuromechanical transformation from task-level control to detailed execution-level muscle activity and forces during behaviorally-relevant motor tasks has proved difficult. In an unrestrained balance task in cats, we demonstrate that achieving task-level constraints center of mass forces and moments while minimizing control effort predicts detailed patterns of muscle activity and ground reaction forces in an anatomically-realistic musculoskeletal model. Whereas optimization is typically used to resolve redundancy at a single level of the motor hierarchy, we simultaneously resolved redundancy across both muscles and limbs and directly compared predictions to experimental measures across multiple perturbation directions that elicit different intra- and interlimb coordination patterns. Further, although some candidate task-level variables and cost functions generated indistinguishable predictions in a single biomechanical context, we identified a common optimization framework that could predict up to 48 experimental conditions per animal (n = 3 across both perturbation directions and different biomechanical contexts created by altering animals' postural configuration. Predictions were further improved by imposing experimentally-derived muscle synergy constraints, suggesting additional task variables or costs that may be relevant to the neural control of balance. These results suggested that reduced-dimension neural control mechanisms such as muscle synergies can achieve similar kinetics to the optimal solution, but with increased control effort (≈2× compared to individual muscle control. Our results are consistent with the idea that hierarchical, task

  6. Situational Motivation and Perceived Intensity: Their Interaction in Predicting Changes in Positive Affect from Physical Activity

    OpenAIRE

    Eva Guérin; Michelle S. Fortier

    2012-01-01

    There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE)] i...

  7. Prediction on sunspot activity based on fuzzy information granulation and support vector machine

    Science.gov (United States)

    Peng, Lingling; Yan, Haisheng; Yang, Zhigang

    2018-04-01

    In order to analyze the range of sunspots, a combined prediction method of forecasting the fluctuation range of sunspots based on fuzzy information granulation (FIG) and support vector machine (SVM) was put forward. Firstly, employing the FIG to granulate sample data and extract va)alid information of each window, namely the minimum value, the general average value and the maximum value of each window. Secondly, forecasting model is built respectively with SVM and then cross method is used to optimize these parameters. Finally, the fluctuation range of sunspots is forecasted with the optimized SVM model. Case study demonstrates that the model have high accuracy and can effectively predict the fluctuation of sunspots.

  8. Preliminary Evidence that Self-Efficacy Predicts Physical Activity in Multiple Sclerosis

    Science.gov (United States)

    Motl, Robert W.; McAuley, Edward; Doerksen, Shawna; Hu, Liang; Morris, Katherine S.

    2009-01-01

    Individuals with multiple sclerosis (MS) are less physically active than nondiseased people. One method for increasing physical activity levels involves the identification of factors that correlate with physical activity and that are modifiable by a well designed intervention. This study examined two types of self-efficacy as cross-sectional and…

  9. Processing of action- but not stimulus-related prediction errors differs between active and observational feedback learning.

    Science.gov (United States)

    Kobza, Stefan; Bellebaum, Christian

    2015-01-01

    Learning of stimulus-response-outcome associations is driven by outcome prediction errors (PEs). Previous studies have shown larger PE-dependent activity in the striatum for learning from own as compared to observed actions and the following outcomes despite comparable learning rates. We hypothesised that this finding relates primarily to a stronger integration of action and outcome information in active learners. Using functional magnetic resonance imaging, we investigated brain activations related to action-dependent PEs, reflecting the deviation between action values and obtained outcomes, and action-independent PEs, reflecting the deviation between subjective values of response-preceding cues and obtained outcomes. To this end, 16 active and 15 observational learners engaged in a probabilistic learning card-guessing paradigm. On each trial, active learners saw one out of five cues and pressed either a left or right response button to receive feedback (monetary win or loss). Each observational learner observed exactly those cues, responses and outcomes of one active learner. Learning performance was assessed in active test trials without feedback and did not differ between groups. For both types of PEs, activations were found in the globus pallidus, putamen, cerebellum, and insula in active learners. However, only for action-dependent PEs, activations in these structures and the anterior cingulate were increased in active relative to observational learners. Thus, PE-related activity in the reward system is not generally enhanced in active relative to observational learning but only for action-dependent PEs. For the cerebellum, additional activations were found across groups for cue-related uncertainty, thereby emphasising the cerebellum's role in stimulus-outcome learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

    Science.gov (United States)

    Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

    2017-10-12

    This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

  11. Predicting drunk driving: contribution of alcohol use and related problems, traffic behaviour, personality and platelet monoamine oxidase (MAO) activity.

    Science.gov (United States)

    Eensoo, Diva; Paaver, Marika; Harro, Maarike; Harro, Jaanus

    2005-01-01

    The aim of the study was to characterize the predictive value of socio-economic data, alcohol consumption measures, smoking, platelet monoamine oxidase (MAO) activity, traffic behaviour habits and impulsivity measures for actual drunk driving. Data were collected from 203 male drunk driving offenders and 211 control subjects using self-reported questionnaires, and blood samples were obtained from the two groups. We identified the combination of variables, which predicted correctly, approximately 80% of the subjects' belonging to the drunk driving and control groups. Significant independent discriminators in the final model were, among the health-behaviour measures, alcohol-related problems, frequency of using alcohol, the amount of alcohol consumed and smoking. Predictive traffic behaviour measures were seat belt use and paying for parking. Among the impulsivity measures, dysfunctional impulsivity was the best predictor; platelet MAO activity and age also had an independent predictive value. Our results support the notion that drunk driving is the result of a combination of various behavioural, biological and personality-related risk factors.

  12. Characterization of acute-on-chronic liver failure and prediction of mortality in Asian patients with active alcoholism.

    Science.gov (United States)

    Kim, Hwi Young; Chang, Young; Park, Jae Yong; Ahn, Hongkeun; Cho, Hyeki; Han, Seung Jun; Oh, Sohee; Kim, Donghee; Jung, Yong Jin; Kim, Byeong Gwan; Lee, Kook Lae; Kim, Won

    2016-02-01

    Alcoholic liver diseases often evolve to acute-on-chronic liver failure (ACLF), which increases the risk of (multi-)organ failure and death. We investigated the development and characteristics of alcohol-related ACLF and evaluated prognostic scores for prediction of mortality in Asian patients with active alcoholism. A total of 205 patients who were hospitalized with severe alcoholic liver disease were included in this retrospective cohort study, after excluding those with serious cardiovascular diseases, malignancy, or co-existing viral hepatitis. The Chronic Liver Failure (CLIF) Consortium Organ Failure score was used in the diagnosis and grading of ACLF, and the CLIF Consortium ACLF score (CLIF-C ACLFs) was used to predict mortality. Patients with ACLF had higher Maddrey discriminant function, model for end-stage liver disease (MELD), and MELD-sodium scores than those without ACLF. Infections were more frequently documented in patients with ACLF (33.3% vs 53.0%; P = 0.004). Predictive factors for ACLF development were systemic inflammatory response syndrome (odds ratio [OR], 2.239; P alcohol-related ACLF in Asian patients with active alcoholism. The CLIF-C ACLFs may be more useful for predicting mortality in ACLF cases than liver-specific scoring systems. © 2015 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  13. Physical Activity, Sleep and Nutrition Do Not Predict Cognitive Performance in Young and Middle-Aged Adults

    Directory of Open Access Journals (Sweden)

    Hieronymus eGijselaers

    2016-05-01

    Full Text Available Biological lifestyle factors such as physical activity, sleep and nutrition play a role in cognitive functioning. Research concerning the relation between biological lifestyle factors and cognitive performance is scarce however, especially in young and middle aged adults. Research has not yet focused on a multidisciplinary approach with respect to this relation in the abovementioned population, where lifestyle habits are more stable. The aim of this study was to examine the contribution of these biological lifestyle factors to cognitive performance. Path analysis was conducted in an observational study in which 1131 adults were analyzed using a cross-validation approach. Participants provided information on physical activity, sedentary behavior, chronotype, sleep duration, sleep quality, and the consumption of breakfast, fish, and caffeine via a survey. Their cognitive performance was measured using objective digital cognitive tests. Exploration yielded a predictive cohesive model that fitted the data properly, χ2/df=0.8, CFI=1.00, RMSEA<.001, SRMR=.016. Validation of the developed model indicated that the model fitted the data satisfactorily, χ2/df=2.75, CFI=0.95, RMSEA<.056, SRMR=.035. None of the variables within the BLFs were predictive for any of the cognitive performance measures, except for sedentary behavior. Although sedentary behavior was positively predictive for processing speed its contribution was small and unclear. The results indicate that the variables within the BLFs do not predict cognitive performance in young and middle aged adults.

  14. Excessive L-cysteine induces vacuole-like cell death by activating endoplasmic reticulum stress and mitogen-activated protein kinase signaling in intestinal porcine epithelial cells.

    Science.gov (United States)

    Ji, Yun; Wu, Zhenlong; Dai, Zhaolai; Sun, Kaiji; Zhang, Qing; Wu, Guoyao

    2016-01-01

    High intake of dietary cysteine is extremely toxic to animals and the underlying mechanism remains largely unknown. This study was conducted to test the hypothesis that excessive L-cysteine induces cell death by activating endoplasmic reticulum (ER) stress and mitogen-activated protein kinase (MAPK) signaling in intestinal porcine epithelial cells. Jejunal enterocytes were cultured in the presence of 0-10 mmol/L L-cysteine. Cell viability, morphologic alterations, mRNA levels for genes involved in ER stress, protein abundances for glucose-regulated protein 78, C/EBP homologous protein (CHOP), alpha subunit of eukaryotic initiation factor-2 (eIF2α), extracellular signal-regulated kinase (ERK1/2), p38 MAPK, and c-Jun N-terminal protein kinase (JNK1/2) were determined. The results showed that L-cysteine (5-10 mmol/L) reduced cell viability (P L-cysteine were not affected by the autophagy inhibitor 3-methyladenine. The protein abundances for CHOP, phosphorylated (p)-eIF2α, p-JNK1/2, p-p38 MAPK, and the spliced form of XBP-1 mRNA were enhanced (P L-cysteine induces vacuole-like cell death via the activation of ER stress and MAPK signaling in small intestinal epithelial cells. These signaling pathways may be potential targets for developing effective strategies to prevent the toxicity of dietary cysteine.

  15. A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals.

    Science.gov (United States)

    Hong, Huixiao; Shen, Jie; Ng, Hui Wen; Sakkiah, Sugunadevi; Ye, Hao; Ge, Weigong; Gong, Ping; Xiao, Wenming; Tong, Weida

    2016-03-25

    Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest) and the molecular descriptors calculated from two-dimensional structures by Mold² software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69%) and external validations using 22 chemicals (balanced accuracy of 71%). Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence) in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed.

  16. Percent voluntary inactivation and peak force predictions with the interpolated twitch technique in individuals with high ability of voluntary activation

    International Nuclear Information System (INIS)

    Herda, Trent J; Walter, Ashley A; Hoge, Katherine M; Stout, Jeffrey R; Costa, Pablo B; Ryan, Eric D; Cramer, Joel T

    2011-01-01

    The purpose of this study was to examine the sensitivity and peak force prediction capability of the interpolated twitch technique (ITT) performed during submaximal and maximal voluntary contractions (MVCs) in subjects with the ability to maximally activate their plantar flexors. Twelve subjects performed two MVCs and nine submaximal contractions with the ITT method to calculate percent voluntary inactivation (%VI). Additionally, two MVCs were performed without the ITT. Polynomial models (linear, quadratic and cubic) were applied to the 10–90% VI and 40–90% VI versus force relationships to predict force. Peak force from the ITT MVC was 6.7% less than peak force from the MVC without the ITT. Fifty-eight percent of the 10–90% VI versus force relationships were best fit with nonlinear models; however, all 40–90% VI versus force relationships were best fit with linear models. Regardless of the polynomial model or the contraction intensities used to predict force, all models underestimated the actual force from 22% to 28%. There was low sensitivity of the ITT method at high contraction intensities and the predicted force from polynomial models significantly underestimated the actual force. Caution is warranted when interpreting the % VI at high contraction intensities and predicted peak force from submaximal contractions

  17. Predicting competitive adsorption behavior of major toxic anionic elements onto activated alumina: A speciation-based approach

    International Nuclear Information System (INIS)

    Su Tingzhi; Guan Xiaohong; Tang Yulin; Gu Guowei; Wang Jianmin

    2010-01-01

    Toxic anionic elements such as arsenic, selenium, and vanadium often co-exist in groundwater. These elements may impact each other when adsorption methods are used to remove them. In this study, we investigated the competitive adsorption behavior of As(V), Se(IV), and V(V) onto activated alumina under different pH and surface loading conditions. Results indicated that these anionic elements interfered with each other during adsorption. A speciation-based model was developed to quantify the competitive adsorption behavior of these elements. This model could predict the adsorption data well over the pH range of 1.5-12 for various surface loading conditions, using the same set of adsorption constants obtained from single-sorbate systems. This model has great implications in accurately predicting the field capacity of activated alumina under various local water quality conditions when multiple competitive anionic elements are present.

  18. Prediction models discriminating between nonlocomotive and locomotive activities in children using a triaxial accelerometer with a gravity-removal physical activity classification algorithm.

    Science.gov (United States)

    Hikihara, Yuki; Tanaka, Chiaki; Oshima, Yoshitake; Ohkawara, Kazunori; Ishikawa-Takata, Kazuko; Tanaka, Shigeho

    2014-01-01

    The aims of our study were to examine whether a gravity-removal physical activity classification algorithm (GRPACA) is applicable for discrimination between nonlocomotive and locomotive activities for various physical activities (PAs) of children and to prove that this approach improves the estimation accuracy of a prediction model for children using an accelerometer. Japanese children (42 boys and 26 girls) attending primary school were invited to participate in this study. We used a triaxial accelerometer with a sampling interval of 32 Hz and within a measurement range of ±6 G. Participants were asked to perform 6 nonlocomotive and 5 locomotive activities. We measured raw synthetic acceleration with the triaxial accelerometer and monitored oxygen consumption and carbon dioxide production during each activity with the Douglas bag method. In addition, the resting metabolic rate (RMR) was measured with the subject sitting on a chair to calculate metabolic equivalents (METs). When the ratio of unfiltered synthetic acceleration (USA) and filtered synthetic acceleration (FSA) was 1.12, the rate of correct discrimination between nonlocomotive and locomotive activities was excellent, at 99.1% on average. As a result, a strong linear relationship was found for both nonlocomotive (METs = 0.013×synthetic acceleration +1.220, R2 = 0.772) and locomotive (METs = 0.005×synthetic acceleration +0.944, R2 = 0.880) activities, except for climbing down and up. The mean differences between the values predicted by our model and measured METs were -0.50 to 0.23 for moderate to vigorous intensity (>3.5 METs) PAs like running, ball throwing and washing the floor, which were regarded as unpredictable PAs. In addition, the difference was within 0.25 METs for sedentary to mild moderate PAs (model that discriminates between nonlocomotive and locomotive activities for children can be useful to evaluate the sedentary to vigorous PAs intensity of both nonlocomotive and

  19. GRIND2-based 3D-QSAR and prediction of activity spectra for symmetrical bis-pyridinium salts with promastigote antileishmanial activity.

    Science.gov (United States)

    Diniz, Evelyn Mirella Lopes Pina; Tomich de Paula da Silva, Carlos Henrique; Gómez-Perez, Verónica; Federico, Leonardo Bruno; Campos Rosa, Joaquín María

    2017-08-01

    Leishmaniasis is a major group of neglected tropical diseases caused by the protozoan parasite Leishmania. About 12 million people are affected in 98 countries and 350 million people worldwide are at risk of infection. Current leishmaniasis treatments rely on a relatively small arsenal of drugs, including amphotericin B, pentamidine and others, which in general have some type of inconvenience. Recently, we have synthesized antileishmanial bis-pyridinium derivatives and symmetrical bis-pyridinium cyclophanes. These compounds are considered structural analogues of pentamidine, where the amidino moiety, protonated at physiological pH, is replaced by a positively charged nitrogen atom as a pyridinium ring. In this work, a statistically significant GRIND2-based 3D-QSAR model was built and biological activity predictions were in silico carried out allowing rationalization of the different activities recently obtained against Leishmania donovani (in L. donovani promastigotes) for a data set of 19 bis-pyridinium compounds. We will emphasize the most important structural requirements to improve the biological activity and probable interactions with the biological receptor as a guide for lead and prototype optimization. In addition, since no information about the actual biological target for this series of active compounds is provided, we have used Prediction of Activity Spectra for Biologically Active Substances to propose our compounds as potential nicotinic α6β3β4α5 receptor antagonists. This proposal is reinforced by the high structural similarity observed between our compounds and several anthelmintic drugs in current clinical use, which have the same drug action mechanism here predicted. Such new findings would be confirmed with further and additional experimental assays.

  20. Fault-tolerant reference generation for model predictive control with active diagnosis of elevator jamming faults

    NARCIS (Netherlands)

    Ferranti, L.; Wan, Y.; Keviczky, T.

    2018-01-01

    This paper focuses on the longitudinal control of an Airbus passenger aircraft in the presence of elevator jamming faults. In particular, in this paper, we address permanent and temporary actuator jamming faults using a novel reconfigurable fault-tolerant predictive control design. Due to their

  1. Level of complement activity predicts cardiac dysfunction after acute myocardial infarction treated with primary percutaneous coronary intervention

    DEFF Research Database (Denmark)

    Haahr-Pedersen, Sune; Bjerre, Mette; Flyvbjerg, Allan

    2009-01-01

    BACKGROUND: The positive effect of reperfusion after ST-elevation myocardial infarction (STEMI) can be reduced by ischemic/reperfusion (I/R) injury.Mannose-binding-lectin (MBL) and soluble C5b-9 (membrane-attack-complex) are involved in complement-driven cell lysis and may play a role in human...... with increased risk of cardiac dysfunction in STEMI patients treated with pPCI, probably due to increased complement activity during the ischemic and reperfusion process. The predictive value of low peripheral plasma sC5b-9 may be explained by an accumulation and activation of sC5b-9 in the infarcted myocardium....

  2. Quantitative structure--property relationships for enhancing predictions of synthetic organic chemical removal from drinking water by granular activated carbon.

    Science.gov (United States)

    Magnuson, Matthew L; Speth, Thomas F

    2005-10-01

    Granular activated carbon is a frequently explored technology for removing synthetic organic contaminants from drinking water sources. The success of this technology relies on a number of factors based not only on the adsorptive properties of the contaminant but also on properties of the water itself, notably the presence of substances in the water which compete for adsorption sites. Because it is impractical to perform field-scale evaluations for all possible contaminants, the pore surface diffusion model (PSDM) has been developed and used to predict activated carbon column performance using single-solute isotherm data as inputs. Many assumptions are built into this model to account for kinetics of adsorption and competition for adsorption sites. This work further evaluates and expands this model, through the use of quantitative structure-property relationships (QSPRs) to predict the effect of natural organic matter fouling on activated carbon adsorption of specific contaminants. The QSPRs developed are based on a combination of calculated topographical indices and quantum chemical parameters. The QSPRs were evaluated in terms of their statistical predictive ability,the physical significance of the descriptors, and by comparison with field data. The QSPR-enhanced PSDM was judged to give results better than what could previously be obtained.

  3. Effects of the activation of self-esteem and perceived temporal distance on the preparation for an examination(2): Temporal changes in performance prediction

    OpenAIRE

    藤島, 喜嗣; Yoshitsugu, FUJISHIMA; 昭和女子大学大学院生活機構研究科

    2012-01-01

    Self-esteem is a global representation of the self that varies in its level of activation. Self-esteem should have an influence on future prediction depending on its activation level. According to the construal level theory, temporal distance moderates the influence of the activated self-esteem. Undergraduates (n=89) participated in a panel survey on predictions about their examination performance, in which their level of self-esteem activation was manipulated. Contrary to the hypothesis, the...

  4. Model evaluation for the prediction of solubility of active pharmaceutical ingredients (APIs to guide solid–liquid separator design

    Directory of Open Access Journals (Sweden)

    Kuveneshan Moodley

    2018-05-01

    Full Text Available The assumptions and models for solubility modelling or prediction in systems using non-polar solvents, or water and complex triterpene and other active pharmaceutical ingredients as solutes aren't well studied. Furthermore, the assumptions concerning heat capacity effects (negligibility, experimental values or approximations are explored, using non-polar solvents (benzene, or water as reference solvents, for systems with solute melting points in the range of 306–528 K and molecular weights in the range of 90–442 g/mol. New empirical estimation methods for the ΔfusCpi of APIs are presented which correlate the solute molecular masses and van der Waals surface areas with ΔfusCpi. Separate empirical parameters were required for oxygenated and non-oxygenated solutes. Subsequently, the predictive capabilities of the various approaches to solubility modelling for complex pharmaceuticals, for which data is limited, are analysed. The solute selection is based on a principal component analysis, considering molecular weights, fusion temperatures, and solubilities in a non-polar solvent, alcohol, and water, where data was available. New NRTL-SAC parameters were determined for selected steroids, by regression. The original UNIFAC, modified UNIFAC (Dortmund, COSMO-RS (OL, and COSMO-SAC activity coefficient predictions are then conducted, based on the availability of group constants and sigma profiles. These are undertaken to assess the predictive capabilities of these models when each assumption concerning heat capacity is employed. The predictive qualities of the models are assessed, based on the mean square deviation and provide guidelines for model selection, and assumptions concerning phase equilibrium, when designing solid–liquid separators for the pharmaceutical industry on process simulation software. The most suitable assumption regarding ΔfusCpi was found to be system specific, with modified UNIFAC (Dortmund performing well in benzene as

  5. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

    Science.gov (United States)

    Jhin, Changho; Hwang, Keum Taek

    2015-01-01

    One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS) applied quantitative structure-activity relationship models (QSAR) were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

  6. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

    Directory of Open Access Journals (Sweden)

    Changho Jhin

    Full Text Available One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS applied quantitative structure-activity relationship models (QSAR were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

  7. Emotional outlook on life predicts increases in physical activity among initially inactive men.

    Science.gov (United States)

    Baruth, Meghan; Lee, Duck-Chul; Sui, Xuemei; Church, Timothy S; Marcus, Bess H; Wilcox, Sara; Blair, Steven N

    2011-04-01

    This study examined the relationship between emotional outlook on life and change in physical activity among inactive adults in the Aerobics Center Longitudinal Study. A total of 2,132 sedentary adults completed a baseline medical examination and returned for a follow-up examination at least 6 months later. Participants self-reported physical activity level and emotional outlook on life. Emotional outlook on life was significantly and positively related to physical activity participation at the follow-up visit in men but not women. Men who were usually very happy and optimistic at baseline had significantly greater increases in physical activity compared to men who were not happy. Men with a more positive outlook on life (e.g., happier) may be more likely to increase physical activity levels. Physical activity interventions targeting men may be more successful if they first increase happiness.

  8. Identification of PPARgamma partial agonists of natural origin (II: in silico prediction in natural extracts with known antidiabetic activity.

    Directory of Open Access Journals (Sweden)

    Laura Guasch

    Full Text Available BACKGROUND: Natural extracts have played an important role in the prevention and treatment of diseases and are important sources for drug discovery. However, to be effectively used in these processes, natural extracts must be characterized through the identification of their active compounds and their modes of action. METHODOLOGY/PRINCIPAL FINDINGS: From an initial set of 29,779 natural products that are annotated with their natural source and using a previously developed virtual screening procedure (carefully validated experimentally, we have predicted as potential peroxisome proliferators-activated receptor gamma (PPARγ partial agonists 12 molecules from 11 extracts known to have antidiabetic activity. Six of these molecules are similar to molecules with described antidiabetic activity but whose mechanism of action is unknown. Therefore, it is plausible that these 12 molecules could be the bioactive molecules responsible, at least in part, for the antidiabetic activity of the extracts containing them. In addition, we have also identified as potential PPARγ partial agonists 10 molecules from 16 plants with undescribed antidiabetic activity but that are related (i.e., they are from the same genus to plants with known antidiabetic properties. None of the 22 molecules that we predict as PPARγ partial agonists show chemical similarity with a group of 211 known PPARγ partial agonists obtained from the literature. CONCLUSIONS/SIGNIFICANCE: Our results provide a new hypothesis about the active molecules of natural extracts with antidiabetic properties and their mode of action. We also suggest plants with undescribed antidiabetic activity that may contain PPARγ partial agonists. These plants represent a new source of potential antidiabetic extracts. Consequently, our work opens the door to the discovery of new antidiabetic extracts and molecules that can be of use, for instance, in the design of new antidiabetic drugs or functional foods focused

  9. Morning self-efficacy predicts physical activity throughout the day in knee osteoarthritis.

    Science.gov (United States)

    Zhaoyang, Ruixue; Martire, Lynn M; Sliwinski, Martin J

    2017-06-01

    The purpose of this study was to examine the within-day and cross-day prospective effects of knee osteoarthritis (OA) patients' self-efficacy to engage in physical activity despite the pain on their subsequent physical activity assessed objectively in their natural environment. Over 22 days, 135 older adults with knee OA reported their morning self-efficacy for being physically active throughout the day using a handheld computer and wore an accelerometer to measure moderate activity and steps. Morning self-efficacy had a significant positive effect on steps and moderate-intensity activity throughout that day, above and beyond the effects of demographic background and other psychosocial factors as well as spouses' support and social control. The lagged effect of morning self-efficacy on the next day's physical activity and the reciprocal lagged effect of physical activity on the next day's self-efficacy were not significant. Positive between-person effects of self-efficacy on physical activity were found. Future research should aim to better understand the mechanisms underlying fluctuations in patients' daily self-efficacy, and target patients' daily self-efficacy as a modifiable psychological mechanism for promoting physical activity. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  10. Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling.

    Science.gov (United States)

    Vlot, Anna H C; de Witte, Wilhelmus E A; Danhof, Meindert; van der Graaf, Piet H; van Westen, Gerard J P; de Lange, Elizabeth C M

    2017-12-04

    Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (K D ) and the target dissociation rate constant on target and tissue selectivity. The K D values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ 8 -tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the K D and k off for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal K D value is often not the lowest K D value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.

  11. A novel prediction approach for antimalarial activities of Trimethoprim, Pyrimethamine, and Cycloguanil analogues using extremely randomized trees.

    Science.gov (United States)

    Nattee, Cholwich; Khamsemanan, Nirattaya; Lawtrakul, Luckhana; Toochinda, Pisanu; Hannongbua, Supa

    2017-01-01

    Malaria is still one of the most serious diseases in tropical regions. This is due in part to the high resistance against available drugs for the inhibition of parasites, Plasmodium, the cause of the disease. New potent compounds with high clinical utility are urgently needed. In this work, we created a novel model using a regression tree to study structure-activity relationships and predict the inhibition constant, K i of three different antimalarial analogues (Trimethoprim, Pyrimethamine, and Cycloguanil) based on their molecular descriptors. To the best of our knowledge, this work is the first attempt to study the structure-activity relationships of all three analogues combined. The most relevant descriptors and appropriate parameters of the regression tree are harvested using extremely randomized trees. These descriptors are water accessible surface area, Log of the aqueous solubility, total hydrophobic van der Waals surface area, and molecular refractivity. Out of all possible combinations of these selected parameters and descriptors, the tree with the strongest coefficient of determination is selected to be our prediction model. Predicted K i values from the proposed model show a strong coefficient of determination, R 2 =0.996, to experimental K i values. From the structure of the regression tree, compounds with high accessible surface area of all hydrophobic atoms (ASA_H) and low aqueous solubility of inhibitors (Log S) generally possess low K i values. Our prediction model can also be utilized as a screening test for new antimalarial drug compounds which may reduce the time and expenses for new drug development. New compounds with high predicted K i should be excluded from further drug development. It is also our inference that a threshold of ASA_H greater than 575.80 and Log S less than or equal to -4.36 is a sufficient condition for a new compound to possess a low K i . Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Predicting for activity of second-line trastuzumab-based therapy in her2-positive advanced breast cancer

    Directory of Open Access Journals (Sweden)

    Rottenfusser Andrea

    2009-10-01

    Full Text Available Abstract Background In Her2-positive advanced breast cancer, the upfront use of trastuzumab is well established. Upon progression on first-line therapy, patients may be switched to lapatinib. Others however remain candidates for continued antibody treatment (treatment beyond progression. Here, we aimed to identify factors predicting for activity of second-line trastuzumab-based therapy. Methods Ninety-seven patients treated with > 1 line of trastuzumab-containing therapy were available for this analysis. Her2-status was determined by immunohistochemistry and re-analyzed by FISH if a score of 2+ was gained. Time to progression (TTP on second-line therapy was defined as primary study endpoint. TTP and overall survival (OS were estimated using the Kaplan-Meier product limit method. Multivariate analyses (Cox proportional hazards model, multinomial logistic regression were applied in order to identify factors associated with TTP, response, OS, and incidence of brain metastases. p values Results Median TTP on second-line trastuzumab-based therapy was 7 months (95% CI 5.74-8.26, and 8 months (95% CI 6.25-9.74 on first-line, respectively (n.s.. In the multivariate models, none of the clinical or histopthological features could reliably predict for activity of second-line trastuzumab-based treatment. OS was 43 months suggesting improved survival in patients treated with trastuzumab in multiple-lines. A significant deterioration of cardiac function was observed in three patients; 40.2% developed brain metastases while on second-line trastuzumab or thereafter. Conclusion Trastuzumab beyond progression showed considerable activity. None of the variables investigated correlated with activity of second-line therapy. In order to predict for activity of second-line trastuzumab, it appears necessary to evaluate factors known to confer trastuzumab-resistance.

  13. Ionosphere monitoring and forecast activities within the IAG working group "Ionosphere Prediction"

    Science.gov (United States)

    Hoque, Mainul; Garcia-Rigo, Alberto; Erdogan, Eren; Cueto Santamaría, Marta; Jakowski, Norbert; Berdermann, Jens; Hernandez-Pajares, Manuel; Schmidt, Michael; Wilken, Volker

    2017-04-01

    Ionospheric disturbances can affect technologies in space and on Earth disrupting satellite and airline operations, communications networks, navigation systems. As the world becomes ever more dependent on these technologies, ionospheric disturbances as part of space weather pose an increasing risk to the economic vitality and national security. Therefore, having the knowledge of ionospheric state in advance during space weather events is becoming more and more important. To promote scientific cooperation we recently formed a Working Group (WG) called "Ionosphere Predictions" within the International Association of Geodesy (IAG) under Sub-Commission 4.3 "Atmosphere Remote Sensing" of the Commission 4 "Positioning and Applications". The general objective of the WG is to promote the development of ionosphere prediction algorithm/models based on the dependence of ionospheric characteristics on solar and magnetic conditions combining data from different sensors to improve the spatial and temporal resolution and sensitivity taking advantage of different sounding geometries and latency. Our presented work enables the possibility to compare total electron content (TEC) prediction approaches/results from different centers contributing to this WG such as German Aerospace Center (DLR), Universitat Politècnica de Catalunya (UPC), Technische Universität München (TUM) and GMV. DLR developed a model-assisted TEC forecast algorithm taking benefit from actual trends of the TEC behavior at each grid point. Since during perturbations, characterized by large TEC fluctuations or ionization fronts, this approach may fail, the trend information is merged with the current background model which provides a stable climatological TEC behavior. The presented solution is a first step to regularly provide forecasted TEC services via SWACI/IMPC by DLR. UPC forecast model is based on applying linear regression to a temporal window of TEC maps in the Discrete Cosine Transform (DCT) domain

  14. Assessment of leisure-time physical activity for the prediction of inflammatory status and cardiometabolic profile.

    Science.gov (United States)

    Pires, Milena Monfort; Salvador, Emanuel P; Siqueira-Catania, Antonela; Folchetti, Luciana D; Cezaretto, Adriana; Ferreira, Sandra Roberta G

    2012-11-01

    Associations of leisure-time physical activity (LTPA), commuting and total physical activity with inflammatory markers, insulin resistance and metabolic profile in individuals at high cardiometabolic risk were investigated. This was a cross-sectional study. A total of 193 prediabetic adults were compared according to physical activity levels measured by the international physical activity questionnaire; p for trend and logistic regression was employed. The most active subset showed lower BMI and abdominal circumference, reaching significance only for LTPA (p for trend=0.02). Lipid profile improved with increased physical activity levels. Interleukin-6 decreased with increased total physical activity and LTPA (p for trend=0.02 and 0.03, respectively), while adiponectin increased in more active subsets for LTPA (p for trend=0.03). Elevation in adjusted OR for hypercholesterolemia was significant for lower LTPA durations (p for trend=0.04). High apolipoprotein B/apolipoprotein A ratio was inversely associated with LTPA, commuting and total physical activity. Increase in adjusted OR for insulin resistance was found from the highest to the lowest category of LTPA (p for trend=0.04) but significance disappeared after adjustments for BMI and energy intake. No association of increased C-reactive protein with physical activity domains was observed. In general, the associations of LTPA, but not commuting or total physical activity, with markers of cardiometabolic risk reinforces the importance of initiatives to increase this domain in programs for the prevention of lifestyle-related diseases. Copyright © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  15. Active Redesign of a Medicaid Care Management Strategy for Greater Return on Investment: Predicting Impactability.

    Science.gov (United States)

    DuBard, C Annette; Jackson, Carlos T

    2018-04-01

    Care management of high-cost/high-needs patients is an increasingly common strategy to reduce health care costs. A variety of targeting methodologies have emerged to identify patients with high historical or predicted health care utilization, but the more pertinent question for program planners is how to identify those who are most likely to benefit from care management intervention. This paper describes the evolution of complex care management targeting strategies in Community Care of North Carolina's (CCNC) work with the statewide non-dual Medicaid population, culminating in the development of an "Impactability Score" that uses administrative data to predict achievable savings. It describes CCNC's pragmatic approach for estimating intervention effects in a historical cohort of 23,455 individuals, using a control population of 14,839 to determine expected spending at an individual level, against which actual spending could be compared. The actual-to-expected spending difference was then used as the dependent variable in a multivariate model to determine the predictive contribution of a multitude of demographic, clinical, and utilization characteristics. The coefficients from this model yielded the information required to build predictive models for prospective use. Model variables related to medication adherence and historical utilization unexplained by disease burden proved to be more important predictors of impactability than any given diagnosis or event, disease profile, or overall costs of care. Comparison of this approach to alternative targeting strategies (emergency department super-utilizers, inpatient super-utilizers, or patients with highest Hierarchical Condition Category risk scores) suggests a 2- to 3-fold higher return on investment using impactability-based targeting.

  16. Anxiety Sensitivity Uniquely Predicts Exercise Behaviors in Young Adults Seeking to Increase Physical Activity.

    Science.gov (United States)

    Moshier, Samantha J; Szuhany, Kristin L; Hearon, Bridget A; Smits, Jasper A J; Otto, Michael W

    2016-01-01

    Individuals with elevated levels of anxiety sensitivity (AS) may be motivated to avoid aversive emotional or physical states, and therefore may have greater difficulty achieving healthy behavioral change. This may be particularly true for exercise, which produces many of the somatic sensations within the domain of AS concerns. Cross-sectional studies show a negative association between AS and exercise. However, little is known about how AS may prospectively affect attempts at behavior change in individuals who are motivated to increase their exercise. We recruited 145 young adults who self-identified as having a desire to increase their exercise behavior. Participants completed a web survey assessing AS and additional variables identified as important for behavior change-impulsivity, grit, perceived behavioral control, and action planning-and set a specific goal for exercising in the next week. One week later, a second survey assessed participants' success in meeting their exercise goals. We hypothesized that individuals with higher AS would choose lower exercise goals and would complete less exercise at the second survey. AS was not significantly associated with exercise goal level, but significantly and negatively predicted exercise at Time 2 and was the only variable to offer significant prediction beyond consideration of baseline exercise levels. These results underscore the importance of considering AS in relation to health behavior intentions. This is particularly apt given the absence of prediction offered by other traditional predictors of behavior change. © The Author(s) 2015.

  17. A model for signal processing and predictive control of semi-active ...

    Indian Academy of Sciences (India)

    Abstract. The theory for structural control has been well developed and applied to perform excellent energy dissipation using dampers. Both active and semi-active control systems may be used to decide on the optimal switch point of the damper based on the current and past structural responses to the excitation of external.

  18. Activity measurement and its use in predicting phase relationships in stainless steels

    International Nuclear Information System (INIS)

    Lee, M.C.Y.

    1989-01-01

    A combination Knudsen cell-mass spectrometer apparatus has been developed by the Bureau of Mines. This apparatus is accurate enough to permit the activity of many alloy components to be measured directly as the ratio of the ion currents of an appropriate isotope evaporated from the alloy and from the pure component. This apparatus has been used to determine the activity of each component as a function of temperature in 75Fe-10Cr-15Ni, 73Fe-6Cr-15Ni-6Al, and 75Fe-4Cr-15Ni-2Al-4Si (at%). The data indicate that additions of Ni, Cr, Al, and/or Si have practically no effect on the activity coefficient of Fe and that the partial substitution of Cr by Al and/or Si decreases the activity coefficient of Ni. In the case of Cr, temperature influences the activity coefficient more than does the content of Al and/or Si. The activity coefficient of Cr in each alloy increases with decreasing temperature, while the activity coefficients of Fe and Ni are temperature insensitive. The resistance of Fe-Ni-Cr base alloys to oxidation and sulfidation and the stability of the austentic phase in such alloys are discussed in light of these activity changes. (orig.)

  19. Online communication predicts Belgian adolescents’ initiation of romantic and sexual activity

    NARCIS (Netherlands)

    Vandenbosch, L.; Beyens, I.; Vangeel, L.; Eggermont, S.

    2016-01-01

    Online communication is associated with offline romantic and sexual activity among college students. Yet, it is unknown whether online communication is associated with the initiation of romantic and sexual activity among adolescents. This two-wave panel study investigated whether chatting, visiting

  20. {sup 13}C NMR spectral data and molecular descriptors to predict the antioxidant activity of flavonoids

    Energy Technology Data Exchange (ETDEWEB)

    Fernandes, Mariane Balerine; Muramatsu, Eric [Universidade de Sao Paulo (USP). Ribeirao Preto, SP (Brazil). Fac. de Ciencias Farmauceuticas; Emereciano, Vicente de Paula [Universidade de Sao Paulo (USP), SP (Brazil). Inst. de Quimica; Scotti, Marcus Tullius [Universidade Federal da Paraiba (UFPA), Joao Pessoa, PA (Brazil). Centro de Ciencias Aplicadas e Educacao; Scotti, Luciana; Tavares, Josean Fechine; Silva, Marcelo Sobral da [Universidade Federal da Paraiba (UFPA), Joao Pessoa, PA (Brazil). Lab. de Tecnologia Farmaceutica

    2011-04-15

    Tissue damage due to oxidative stress is directly linked to development of many, if not all, human morbidity factors and chronic diseases. In this context, the search for dietary natural occurring molecules with antioxidant activity, such as flavonoids, has become essential. In this study, we investigated a set of 41 flavonoids (23 flavones and 18 flavonols) analyzing their structures and biological antioxidant activity. The experimental data were submitted to a QSAR (quantitative structure-activity relationships) study. NMR {sup 13}C data were used to perform a Kohonen self-organizing map study, analyzing the weight that each carbon has in the activity. Additionally, we performed MLR (multilinear regression) using GA (genetic algorithms) and molecular descriptors to analyze the role that specific carbons and substitutions play in the activity. (author)

  1. Physical Activity Predicts Higher Physical Function in Older Adults: The Osteoarthritis Initiative.

    Science.gov (United States)

    Batsis, John A; Germain, Cassandra M; Vásquez, Elizabeth; Zbehlik, Alicia J; Bartels, Stephen J

    2016-01-01

    Physical activity reduces mobility impairments in elders. We examined the association of physical activity on risk of subjective and objective physical function in adults with and at risk for osteoarthritis (OA). Adults aged ≥ 60 years from the longitudinal Osteoarthritis Initiative, a prospective observational study of knee OA, were classified by sex-specific quartiles of Physical Activity Score for the Elderly scores. Using linear mixed models, we assessed 6-year data on self-reported health, gait speed, Late-Life Function and Disability Index (LLFDI) and chair stand. Of 2252 subjects, mean age ranged from 66 to 70 years. Within each quartile, physical component (PCS) of the Short Form-12 and gait speed decreased from baseline to follow-up in both sexes (all P physical activity is associated with maintained physical function and is mediated by muscle strength, highlighting the importance of encouraging physical activity in older adults with and at risk for OA.

  2. Preoperative Serum Thymidine Kinase Activity as Novel Monitoring, Prognostic, and Predictive Biomarker in Pancreatic Cancer.

    Science.gov (United States)

    Felix, Klaus; Hinz, Ulf; Dobiasch, Sophie; Hackert, Thilo; Bergmann, Frank; Neumüller, Magnus; Gronowitz, Simon; Bergqvist, Mattias; Strobel, Oliver

    2018-01-01

    The aim of the study was to investigate serum thymidine kinase 1 (S-TK) activity as a diagnostic and prognostic marker for patients with pancreatic ductal adenocarcinoma (PDAC). Using the sensitive TK activity assay DiviTum, preoperative serum samples from 404 PDAC, 28 chronic pancreatitis, and 25 autoimmune pancreatitis patients and 83 healthy volunteers were analyzed. The preoperative S-TK activities of 54 PDAC patients who received neoadjuvant therapy (nTx) were also compared with those of 258 PDAC patients who did not receive nTx. The preoperative S-TK activities of PDAC patients were significantly higher and discriminatory from autoimmune and chronic pancreatitis patients and control groups. The S-TK activity in PDAC patients was associated with overall survival. Patients with S-TK activity of less than 80 Du (DiviTum units)/L demonstrated median survival of 20.3 months with an estimated 18.0% 5-year survival rate; for S-TK activity of 80 Du/L or greater, median survival was 15.1 months with a 6.8% 5-year survival rate. For early-stage PDAC, these differences were even more pronounced. The S-TK activity in the nTx group was significantly higher than that in the group not receiving nTx. Pancreatic ductal adenocarcinomas reveal a significant increase in S-TK activity, which is associated with overall survival, especially in early tumor stages. Serum thymidine kinase 1 activity may be a useful parameter for monitoring nTx efficacy.

  3. Prediction of the effect on antihyperglycaemic action of sitagliptin by plasma active form glucagon-like peptide-1.

    Science.gov (United States)

    Kushiyama, Akifumi; Kikuchi, Takako; Tanaka, Kentaro; Tahara, Tazu; Takao, Toshiko; Onishi, Yukiko; Yoshida, Yoko; Kawazu, Shoji; Iwamoto, Yasuhiko

    2016-06-10

    To investigate whether active glucagon-like peptide-1 (GLP-1) is a prediction Factor of Effect of sitagliptin on patients with type 2 diabetes mellitus (GLP-1 FEST:UMIN000010645). Seventy-six patients with type 2 diabetes, who had insufficient glycemic control [Hemoglobin A1c (HbA1c) ≥ 7%] in spite of treatment with metformin and/or sulfonylurea, were included in the investigation. Patients were divided into three groups by tertiles of fasting plasma active GLP-1 level, before the administration of 50 mg sitagliptin. At baseline, body mass index, serum UA, insulin and HOMA-IR were higher in the high active GLP-1 group than in the other two groups. The high active GLP-1 group did not show any decline of HbA1c (7.6% ± 1.4% to 7.5% ± 1.5%), whereas the middle and low groups indicated significant decline of HbA1c (7.4 ± 0.7 to 6.8 ± 0.6 and 7.4 ± 1.2 to 6.9 ± 1.3, respectively) during six months. Only the low and middle groups showed a significant increment of active GLP-1, C-peptide level, a decreased log and proinsulin/insulin ratio after administration. In logistic analysis, the low or middle group is a significant explanatory variable for an HbA1c decrease of ≥ 0.5%, and its odds ratio is 4.5 (1.40-17.6) (P = 0.01) against the high active GLP-1 group. This remains independent when adjusted for HbA1c level before administration, patients' medical history, medications, insulin secretion and insulin resistance. Plasma fasting active GLP-1 is an independent predictive marker for the efficacy of dipeptidyl peptidase 4 inhibitor sitagliptin.

  4. Predicting Factors Associated with Regular Physical Activity among College Students: Applying BASNEF Model

    Directory of Open Access Journals (Sweden)

    B. Moeini

    2011-10-01

    Full Text Available Introduction & Objective: One of the important problems in modern society is people's sedentary life style. The aim of this study was to determine factors associated with regular physical activity among college students based on BASNEF model.Materials & Methods: This study was a cross-sectional study carried out on 400 students in Hamadan University of Medical Sciences. Based on the assignment among different schools, classified sampling method was chosen for data gathering using a questionnaire in three parts including: demographic information, constructs of BASNEF model, and standard international physical activity questionnaire (IPAQ. Data were analyzed by SPSS-13, and using appropriate statistical tests (Chi-square, T-test and regression. Results: Based on the results, 271 students(67.8 % had low, 124 (31% moderate ,and 5 (1.2% vigorous physical activity. There was a significant relationship (c2=6.739, df= 1, P= 0.034 between their residence and physical activity and students living in dormitory were reported to have higher level of physical activity. Behavioral intention and enabling factors from the constructs of BASNEF model were the best predictors for having physical activity in students (OR=1.215, P = 0.000 and (OR=1.119, P= 0.000 respectively.Conclusion: With regard to the fact that majority of the students did not engage in enough physical activity and enabling factors were the most effective predictors for having regular physical activity in them, it seems that providing sports facilities can promote physical activity among the students.(Sci J Hamadan Univ Med Sci 2011;18(3:70-76

  5. Prediction of Radix Astragali Immunomodulatory Effect of CD80 Expression from Chromatograms by Quantitative Pattern-Activity Relationship

    Directory of Open Access Journals (Sweden)

    Michelle Chun-har Ng

    2017-01-01

    Full Text Available The current use of a single chemical component as the representative quality control marker of herbal food supplement is inadequate. In this CD80-Quantitative-Pattern-Activity-Relationship (QPAR study, we built a bioactivity predictive model that can be applicable for complex mixtures. Through integrating the chemical fingerprinting profiles of the immunomodulating herb Radix Astragali (RA extracts, and their related biological data of immunological marker CD80 expression on dendritic cells, a chemometric model using the Elastic Net Partial Least Square (EN-PLS algorithm was established. The EN-PLS algorithm increased the biological predictive capability with lower value of RMSEP (11.66 and higher values of Rp2 (0.55 when compared to the standard PLS model. This CD80-QPAR platform provides a useful predictive model for unknown RA extract’s bioactivities using the chemical fingerprint inputs. Furthermore, this bioactivity prediction platform facilitates identification of key bioactivity-related chemical components within complex mixtures for future drug discovery and understanding of the batch-to-batch consistency for quality clinical trials.

  6. Predicting Treatment Outcomes from Prefrontal Cortex Activation for Self-Harming Patients with Borderline Personality Disorder: A Preliminary Study

    Science.gov (United States)

    Ruocco, Anthony C.; Rodrigo, Achala H.; McMain, Shelley F.; Page-Gould, Elizabeth; Ayaz, Hasan; Links, Paul S.

    2016-01-01

    Self-harm is a potentially lethal symptom of borderline personality disorder (BPD) that often improves with dialectical behavior therapy (DBT). While DBT is effective for reducing self-harm in many patients with BPD, a small but significant number of patients either does not improve in treatment or ends treatment prematurely. Accordingly, it is crucial to identify factors that may prospectively predict which patients are most likely to benefit from and remain in treatment. In the present preliminary study, 29 actively self-harming patients with BPD completed brain-imaging procedures probing activation of the prefrontal cortex (PFC) during impulse control prior to beginning DBT and after 7 months of treatment. Patients that reduced their frequency of self-harm the most over treatment displayed lower levels of neural activation in the bilateral dorsolateral prefrontal cortex (DLPFC) prior to beginning treatment, and they showed the greatest increases in activity within this region after 7 months of treatment. Prior to starting DBT, treatment non-completers demonstrated greater activation than treatment-completers in the medial PFC and right inferior frontal gyrus. Reductions in self-harm over the treatment period were associated with increases in activity in right DLPFC even after accounting for improvements in depression, mania, and BPD symptom severity. These findings suggest that pre-treatment patterns of activation in the PFC underlying impulse control may be prospectively associated with improvements in self-harm and treatment attrition for patients with BPD treated with DBT. PMID:27242484

  7. Predicting Treatment Outcomes from Prefrontal Cortex Activation for Self-Harming Patients with Borderline Personality Disorder: A Preliminary Study

    Directory of Open Access Journals (Sweden)

    Anthony Charles Ruocco

    2016-05-01

    Full Text Available Self-harm is a potentially lethal symptom of borderline personality disorder (BPD that often improves with dialectical behavior therapy (DBT. While DBT is effective for reducing self-harm in many patients with BPD, a small but significant number of patients either does not improve in treatment or ends treatment prematurely. Accordingly, it is crucial to identify factors that may prospectively predict which patients are most likely to benefit from and remain in treatment. In the present preliminary study, twenty-nine actively self-harming patients with BPD completed brain-imaging procedures probing activation of the prefrontal cortex during impulse control prior to beginning DBT and after seven months of treatment. Patients that reduced their frequency of self-harm the most over treatment displayed lower levels of neural activation in the bilateral dorsolateral prefrontal cortex prior to beginning treatment, and they showed the greatest increases in activity within this region after seven months of treatment. Prior to starting DBT, treatment non-completers demonstrated greater activation than treatment-completers in the medial prefrontal cortex and right inferior frontal gyrus. Reductions in self-harm over the treatment period were associated with increases in activity in right dorsolateral prefrontal cortex even after accounting for improvements in depression, mania, and BPD symptom severity. These findings suggest that pre-treatment patterns of activation in the prefrontal cortex underlying impulse control may be prospectively associated with improvements in self-harm and treatment attrition for patients with BPD treated with DBT.

  8. Predicting Treatment Outcomes from Prefrontal Cortex Activation for Self-Harming Patients with Borderline Personality Disorder: A Preliminary Study.

    Science.gov (United States)

    Ruocco, Anthony C; Rodrigo, Achala H; McMain, Shelley F; Page-Gould, Elizabeth; Ayaz, Hasan; Links, Paul S

    2016-01-01

    Self-harm is a potentially lethal symptom of borderline personality disorder (BPD) that often improves with dialectical behavior therapy (DBT). While DBT is effective for reducing self-harm in many patients with BPD, a small but significant number of patients either does not improve in treatment or ends treatment prematurely. Accordingly, it is crucial to identify factors that may prospectively predict which patients are most likely to benefit from and remain in treatment. In the present preliminary study, 29 actively self-harming patients with BPD completed brain-imaging procedures probing activation of the prefrontal cortex (PFC) during impulse control prior to beginning DBT and after 7 months of treatment. Patients that reduced their frequency of self-harm the most over treatment displayed lower levels of neural activation in the bilateral dorsolateral prefrontal cortex (DLPFC) prior to beginning treatment, and they showed the greatest increases in activity within this region after 7 months of treatment. Prior to starting DBT, treatment non-completers demonstrated greater activation than treatment-completers in the medial PFC and right inferior frontal gyrus. Reductions in self-harm over the treatment period were associated with increases in activity in right DLPFC even after accounting for improvements in depression, mania, and BPD symptom severity. These findings suggest that pre-treatment patterns of activation in the PFC underlying impulse control may be prospectively associated with improvements in self-harm and treatment attrition for patients with BPD treated with DBT.

  9. Prediction of activation energies for aromatic oxidation by cytochrome P450

    DEFF Research Database (Denmark)

    Rydberg, Patrik; Ryde, Ulf; Olsen, Lars

    2008-01-01

    We have estimated the activation energy for aromatic oxidation by compound I in cytochrome P450 for a diverse set of 17 substrates using state-of-the-art density functional theory (B3LYP) with large basis sets. The activation energies vary from 60 to 87 kJ/mol. We then test if these results can...... be reproduced by computationally less demanding methods. The best methods (a B3LYP calculation of the activation energy of a methoxy-radical model or a partial least-squares model of the semiempirical AM1 bond dissociation energies and spin densities of the tetrahedral intermediate for both a hydroxyl...

  10. Prediction of Physical Activity Level Using Processes of Change From the Transtheoretical Model: Experiential, Behavioral, or an Interaction Effect?

    Science.gov (United States)

    Romain, Ahmed Jérôme; Horwath, Caroline; Bernard, Paquito

    2018-01-01

    The purpose of the present study was to compare prediction of physical activity (PA) by experiential or behavioral processes of change (POCs) or an interaction between both types of processes. A cross-sectional study. This study was conducted using an online questionnaire. A total of 394 participants (244 women, 150 men), with a mean age of 35.12 ± 12.04 years and a mean body mass index of 22.97 ± 4.25 kg/m 2 were included. Participants completed the Processes of Change, Stages of Change questionnaires, and the International Physical Activity Questionnaire to evaluate self-reported PA level (total, vigorous, and moderate PA). Hierarchical multiple regression models were used to test the prediction of PA level. For both total PA (β = .261; P behavioral POCs were a significant predictor. Regarding moderate PA, only the interaction between experiential and behavioral POCs was a significant predictor (β = .123; P = .017). Our results provide confirmation that behavioral processes are most prominent in PA behavior. Nevertheless, it is of interest to note that the interaction between experiential and behavioral POCs was the only element predicting moderate PA level. Experiential processes were not associated with PA level.

  11. Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

    Science.gov (United States)

    Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

    2015-04-01

    The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Physical Activity, Sleep, and Nutrition Do Not Predict Cognitive Performance in Young and Middle-Aged Adults.

    Science.gov (United States)

    Gijselaers, Hieronymus J M; Elena, Barberà; Kirschner, Paul A; de Groot, Renate H M

    2016-01-01

    Biological lifestyle factors (BLFs) such as physical activity, sleep, and nutrition play a role in cognitive functioning. Research concerning the relation between BLFs and cognitive performance is scarce however, especially in young and middle-aged adults. Research has not yet focused on a multidisciplinary approach with respect to this relation in the abovementioned population, where lifestyle habits are more stable. The aim of this study was to examine the contribution of these BLFs to cognitive performance. Path analysis was conducted in an observational study in which 1131 adults were analyzed using a cross-validation approach. Participants provided information on physical activity, sedentary behavior, chronotype, sleep duration, sleep quality, and the consumption of breakfast, fish, and caffeine via a survey. Their cognitive performance was measured using objective digital cognitive tests. Exploration yielded a predictive cohesive model that fitted the data properly, χ(2) /df = 0.8, CFI = 1.00, RMSEA performance measures, except for sedentary behavior. Although sedentary behavior was positively predictive for processing speed its contribution was small and unclear. The results indicate that the variables within the BLFs do not predict cognitive performance in young and middle-aged adults.

  13. Detection of phosphorylated mitogen-activated protein kinase in the developing spinal cord of the mouse embryo

    International Nuclear Information System (INIS)

    Teraishi, Toshiya; Miura, Kenji

    2011-01-01

    Highlights: → We detected physiologically phosphorylated MAPKs in developing spinal cord. → We detected physiologically phosphorylated MAPKs by an improved method. → p-ERK1/2 and p-JNK1/2 were detected in the marginal layer and the dorsal horn. → p-ERK1/2 and p-JNK1/2 might play critical roles in the developing spinal cord. → Constructing phosphoprotein atlases will be possible if expanding this work. -- Abstract: Global understanding of the proteome is a major research topic. The comprehensive visualization of the distribution of proteins in vivo or the construction of in situ protein atlases may be a valuable strategy for proteomic researchers. Information about the distribution of various proteins under physiological and pathological conditions should be extremely valuable for the basic and clinical sciences. The mitogen-activated protein kinase (MAPK) cascade plays an essential role in intracellular signaling in organisms. This cascade also regulates biological processes involving development, differentiation, and proliferation. Phosphorylation and dephosphorylation are integral reactions in regulating the activity of MAPKs. Changes in the phosphorylation state of MAPKs are rapid and reversible; therefore, the localizations of physiologically phosphorylated MAPKs in vivo are difficult to accurately detect. Furthermore, phosphorylated MAPKs are likely to change phosphorylated states through commonly used experimental manipulations. In the present study, as a step toward the construction of in situ phosphoprotein atlases, we attempted to detect physiologically phosphorylated MAPKs in vivo in developing spinal cords of mice. We previously reported an improved immunohistochemical method for detecting unstable phosphorylated MAPKs. The distribution patterns of phosphorylated MAPKs in the spinal cords of embryonic mice from embryonic day 13 (E13) to E17 were observed with an improved immunohistochemical method. Phosphorylated extracellular signal

  14. Bactericidal activity does not predict sterilizing activity: the case of rifapentine in the murine model of Mycobacterium ulcerans disease.

    Directory of Open Access Journals (Sweden)

    Deepak V Almeida

    Full Text Available Since 2004, treatment of Mycobacterium ulcerans disease, or Buruli ulcer, has shifted from surgery to daily treatment with streptomycin (STR + rifampin (RIF for 8 weeks. For shortening treatment duration, we tested the potential of daily rifapentine (RPT, a long-acting rifamycin derivative, as a substitute for RIF.BALB/c mice were infected with M. ulcerans in the right hind footpad and treated either daily (7/7 with STR+RIF or five days/week (5/7 with STR+RIF or STR+RPT for 4 weeks, beginning 28 days after infection when CFU counts were 4.88±0.51. The relative efficacy of the drug treatments was compared by footpad CFU counts during treatment and median time to footpad swelling after treatment cessation as measure of sterilizing activity. All drug treatments were bactericidal. After 1 week of treatment, the decline in CFU counts was significantly greater in treated mice but not different between the three treated groups. After 2 weeks of treatment, the decline in CFU was greater in mice treated with STR+RPT 5/7 than in mice treated with STR+RIF 7/7 and STR+RIF 5/7. After 3 and 4 weeks of treatment, CFU counts were nil in mice treated with STR+RPT and reduced by more than 3 and 4 logs in mice treated with STR+RIF 5/7 and STR+RIF 7/7, respectively. In sharp contrast to the bactericidal activity, the sterilizing activity was not different between all drug regimens although it was in proportion to the treatment duration.The better bactericidal activity of daily STR+RIF and especially of STR+RPT did not translate into better prevention of relapse, possibly because relapse-freecure after treatment of Buruli ulcer is more related to the reversal of mycolactone-induced local immunodeficiency by drug treatment rather than to the bactericidal potency of drugs.

  15. Interleaved Buck Converter with Variable Number of Active Phases and a Predictive Current Sharing Scheme

    DEFF Research Database (Denmark)

    Jakobsen, Lars Tønnes; Garcia, O.; Oliver, J. A.

    2008-01-01

    The efficiency of an interleaved Buck converter is typically low at light load conditions because of the switching losses in each of the switching stages. Improvements in the converter efficiency can be achieved by dynamically changing the number of active phases depending on the load current....... This paper addresses the issues related to the transient response of the converter when the number of active phases is changed by a digital control scheme. The problem arises because the current in the individual phases of the interleaved Buck converter will not be equal immediately after the controller has...... changed the number of active phases. This paper proposes a current equalisation scheme that adjusts the duty cycle of each phase in a manner that ensures equal average inductor current in all active phases in one or two PWM periods. The current equalisation scheme relies on the measurement of the output...

  16. Direct electrical stimulation of human cortex evokes high gamma activity that predicts conscious somatosensory perception

    Science.gov (United States)

    Muller, Leah; Rolston, John D.; Fox, Neal P.; Knowlton, Robert; Rao, Vikram R.; Chang, Edward F.

    2018-04-01

    Objective. Direct electrical stimulation (DES) is a clinical gold standard for human brain mapping and readily evokes conscious percepts, yet the neurophysiological changes underlying these percepts are not well understood. Approach. To determine the neural correlates of DES, we stimulated the somatosensory cortex of ten human participants at frequency-amplitude combinations that both elicited and failed to elicit conscious percepts, meanwhile recording neural activity directly surrounding the stimulation site. We then compared the neural activity of perceived trials to that of non-perceived trials. Main results. We found that stimulation evokes distributed high gamma activity, which correlates with conscious perception better than stimulation parameters themselves. Significance. Our findings suggest that high gamma activity is a reliable biomarker for perception evoked by both natural and electrical stimuli.

  17. Airport Gate Activity Monitoring Tool Suite for Improved Turnaround Prediction, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this research is to create a suite of tools for monitoring airport gate activities with the objective of improving aircraft turnaround. Airport ramp...

  18. The Predictive Factors of the Promotion of Physical Activity by Air Force Squadron Commanders

    National Research Council Canada - National Science Library

    Whelan, Dana

    2001-01-01

    .... Web based surveys were completed by 178 commanders at bases world-wide. Positive correlations were observed between physical activity and both personal benefit beliefs and organizational benefit beliefs (.417 and .298, p < .001, respectively...

  19. Prediction of severe hypoglycaemia by angiotensin-converting enzyme activity and genotype in type 1 diabetes

    DEFF Research Database (Denmark)

    Pedersen-Bjerggaard, U.; Agerholm-Larsen, B.; Pramming, S.

    2003-01-01

    AIMS/HYPOTHESIS: We have previously shown a strong relationship between high angiotensin-converting enzyme (ACE) activity, presence of the deletion (D) allele of the ACEgene and recall of severe hypoglycaemic events in patients with Type 1 diabetes. This study was carried out to assess...... this relationship prospectively. METHODS: We followed 171 adult outpatients with Type 1 diabetes in a one-year observational study with the recording of severe hypoglycaemia. Participants were characterised by serum ACE activity and ACE genotype and not treated with ACE inhibitors or angiotensin II receptor...... antagonists. RESULTS: There was a positive relationship between serum ACE activity and rate of severe hypoglycaemia with a 2.7 times higher rate in the fourth quartile of ACE activity compared to the first quartile (p=0.0007). A similar relationship was observed for the subset of episodes with coma (2.9 times...

  20. Respiratory Sinus Arrhythmia Activity Predicts Internalizing and Externalizing Behaviors in Non-referred Boys

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2017-09-01

    Full Text Available Atypical respiratory sinus arrhythmia (RSA, a biomarker of emotion dysregulation, is associated with both externalizing and internalizing behaviors. In addition, social adversity and gender may moderate this association. In this study, we investigated if RSA (both resting RSA and RSA reactivity in an emotion regulation task predicts externalizing and/or internalizing behaviors and the extent to which social adversity moderates this relationship. Two hundred and fifty-three children (at Time 1, mean age = 9.05, SD = 0.60, 48% boys and their caregivers from the community participated in this study. Resting RSA and RSA reactivity were assessed, and caregivers reported children’s externalizing and internalizing behaviors at both Time 1 and Time 2 (1 year later. We found that lower resting RSA (but not RSA reactivity at Time 1 was associated with increased externalizing and internalizing behaviors at Time 2 in boys, even after controlling for the effects of Time 1 behavioral problems and Time 2 age. Moreover, there was a significant interaction effect between Time 1 resting RSA and social adversity such that lower resting RSA predicted higher externalizing and internalizing behaviors in boys only under conditions of high social adversity. Follow-up analyses revealed that these predictive effects were stronger for externalizing behavior than for internalizing behavior. No significant effects were found for girls. Our findings provide further evidence that low resting RSA may be a transdiagnostic biomarker of emotion dysregulation and a predisposing risk factor for both types of behavior problems, in particular for boys who grow up in adverse environments. We conclude that biosocial interaction effects and gender differences should be considered when examining the etiological mechanisms of child psychopathology.

  1. A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses

    Science.gov (United States)

    Montes, Jesus; Gomez, Elena; Merchán-Pérez, Angel; DeFelipe, Javier; Peña, Jose-Maria

    2013-01-01

    Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of synapses and it is

  2. A machine learning method for the prediction of receptor activation in the simulation of synapses.

    Directory of Open Access Journals (Sweden)

    Jesus Montes

    Full Text Available Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of

  3. Reward System Activation in Response to Alcohol Advertisements Predicts College Drinking.

    Science.gov (United States)

    Courtney, Andrea L; Rapuano, Kristina M; Sargent, James D; Heatherton, Todd F; Kelley, William M

    2018-01-01

    In this study, we assess whether activation of the brain's reward system in response to alcohol advertisements is associated with college drinking. Previous research has established a relationship between exposure to alcohol marketing and underage drinking. Within other appetitive domains, the relationship between cue exposure and behavioral enactment is known to rely on activation of the brain's reward system. However, the relationship between neural activation to alcohol advertisements and alcohol consumption has not been studied in a nondisordered population. In this cross-sectional study, 53 college students (32 women) completed a functional magnetic resonance imaging scan while viewing alcohol, food, and control (car and technology) advertisements. Afterward, they completed a survey about their alcohol consumption (including frequency of drinking, typical number of drinks consumed, and frequency of binge drinking) over the previous month. In 43 participants (24 women) meeting inclusion criteria, viewing alcohol advertisements elicited activation in the left orbitofrontal cortex and bilateral ventral striatum-regions of the reward system that typically activate to other appetitive rewards and relate to consumption behaviors. Moreover, the level of self-reported drinking correlated with the magnitude of activation in the left orbitofrontal cortex. Results suggest that alcohol cues are processed within the reward system in a way that may motivate drinking behavior.

  4. Different Predictive Control Strategies for Active Load Management in Distributed Power Systems with High Penetration of Renewable Energy Sources

    DEFF Research Database (Denmark)

    Zong, Yi; Bindner, Henrik W.; Gehrke, Oliver

    2013-01-01

    In order to achieve a Danish energy supply based on 100% renewable energy from combinations of wind, biomass, wave and solar power in 2050 and to cover 50% of the Danish electricity consumption by wind power in 2020, it requires more renewable energy in buildings and industries (e.g. cold stores......, greenhouses, etc.), and to coordinate the management of large numbers of distributed energy resources with the smart grid solution. This paper presents different predictive control (Genetic Algorithm-based and Model Predictive Control-based) strategies that schedule controlled loads in the industrial...... and residential sectors, based on dynamic power price and weather forecast, considering users’ comfort settings to meet an optimization objective, such as maximum profit or minimum energy consumption. Some field tests were carried out on a facility for intelligent, active and distributed power systems, which...

  5. Quantitative structure-activity relationships for predicting potential ecological hazard of organic chemicals for use in regulatory risk assessments.

    Science.gov (United States)

    Comber, Mike H I; Walker, John D; Watts, Chris; Hermens, Joop

    2003-08-01

    The use of quantitative structure-activity relationships (QSARs) for deriving the predicted no-effect concentration of discrete organic chemicals for the purposes of conducting a regulatory risk assessment in Europe and the United States is described. In the United States, under the Toxic Substances Control Act (TSCA), the TSCA Interagency Testing Committee and the U.S. Environmental Protection Agency (U.S. EPA) use SARs to estimate the hazards of existing and new chemicals. Within the Existing Substances Regulation in Europe, QSARs may be used for data evaluation, test strategy indications, and the identification and filling of data gaps. To illustrate where and when QSARs may be useful and when their use is more problematic, an example, methyl tertiary-butyl ether (MTBE), is given and the predicted and experimental data are compared. Improvements needed for new QSARs and tools for developing and using QSARs are discussed.

  6. Brain Activation during Associative Short-Term Memory Maintenance is Not Predictive for Subsequent Retrieval

    Directory of Open Access Journals (Sweden)

    Heiko eBergmann

    2015-09-01

    Full Text Available Performance on working memory (WM tasks may partially be supported by long-term memory (LTM processing. Hence, brain activation recently being implicated in WM may actually have been driven by (incidental LTM formation. We examined which brain regions actually support successful WM processing, rather than being confounded by LTM processes, during the maintenance and probe phase of a WM task. We administered a four-pair (faces and houses associative delayed-match-to-sample (WM task using event-related fMRI and a subsequent associative recognition LTM task, using the same stimuli. This enabled us to analyze subsequent memory effects for both the WM and the LTM test by contrasting correctly recognized pairs with incorrect pairs for either task. Critically, with respect to the subsequent WM effect, we computed this analysis exclusively for trials that were forgotten in the subsequent LTM recognition task. Hence, brain activity associated with successful WM processing was less likely to be confounded by incidental LTM formation. The subsequent LTM effect, in contrast, was analyzed exclusively for pairs that previously had been correctly recognized in the WM task, disclosing brain regions involved in successful LTM formation after successful WM processing. Results for the subsequent WM effect showed no significantly activated brain areas for WM maintenance, possibly due to an insensitivity of fMRI to mechanisms underlying active WM maintenance. In contrast, a correct decision at WM probe was linked to activation in the retrieval success network (anterior and posterior midline brain structures. The subsequent LTM analyses revealed greater activation in left dorsolateral prefrontal cortex and posterior parietal cortex in the early phase of the maintenance stage. No supra-threshold activation was found during the WM probe. Together, we obtained clearer insights in which brain regions support successful WM and LTM without the potential confound of the

  7. Physical activity assessed in routine care predicts mortality after a COPD hospitalisation

    Directory of Open Access Journals (Sweden)

    Marilyn L. Moy

    2016-03-01

    Full Text Available The independent relationship between physical inactivity and risk of death after an index chronic obstructive pulmonary disease (COPD hospitalisation is unknown. We conducted a retrospective cohort study in a large integrated healthcare system. Patients were included if they were hospitalised for COPD between January 1, 2011 and December 31, 2011. All-cause mortality in the 12 months after discharge was the primary outcome. Physical activity, expressed as self-reported minutes of moderate to vigorous physical activity (MVPA, was routinely assessed at outpatient visits prior to hospitalisation. 1727 (73% patients were inactive (0 min of MVPA per week, 412 (17% were insufficiently active (1–149 min of MVPA per week and 231 (10% were active (≥150 min of MVPA per week. Adjusted Cox regression models assessed risk of death across the MVPA categories. Among 2370 patients (55% females and mean age 73±11 years, there were 464 (20% deaths. Patients who were insufficiently active or active had a 28% (adjusted HR 0.72 (95% CI 0.54–0.97, p=0.03 and 47% (adjusted HR 0.53 (95% CI 0.34–0.84, p<0.01 lower risk of death, respectively, in the 12 months following an index COPD hospitalisation compared to inactive patients. Any level of MVPA is associated with lower risk of all-cause mortality after a COPD hospitalisation. Routine assessment of physical activity in clinical care would identify persons at high risk for dying after COPD hospitalisation.

  8. Brain activation during associative short-term memory maintenance is not predictive for subsequent retrieval.

    Science.gov (United States)

    Bergmann, Heiko C; Daselaar, Sander M; Beul, Sarah F; Rijpkema, Mark; Fernández, Guillén; Kessels, Roy P C

    2015-01-01

    Performance on working memory (WM) tasks may partially be supported by long-term memory (LTM) processing. Hence, brain activation recently being implicated in WM may actually have been driven by (incidental) LTM formation. We examined which brain regions actually support successful WM processing, rather than being confounded by LTM processes, during the maintenance and probe phase of a WM task. We administered a four-pair (faces and houses) associative delayed-match-to-sample (WM) task using event-related functional MRI (fMRI) and a subsequent associative recognition LTM task, using the same stimuli. This enabled us to analyze subsequent memory effects for both the WM and the LTM test by contrasting correctly recognized pairs with incorrect pairs for either task. Critically, with respect to the subsequent WM effect, we computed this analysis exclusively for trials that were forgotten in the subsequent LTM recognition task. Hence, brain activity associated with successful WM processing was less likely to be confounded by incidental LTM formation. The subsequent LTM effect, in contrast, was analyzed exclusively for pairs that previously had been correctly recognized in the WM task, disclosing brain regions involved in successful LTM formation after successful WM processing. Results for the subsequent WM effect showed no significantly activated brain areas for WM maintenance, possibly due to an insensitivity of fMRI to mechanisms underlying active WM maintenance. In contrast, a correct decision at WM probe was linked to activation in the "retrieval success network" (anterior and posterior midline brain structures). The subsequent LTM analyses revealed greater activation in left dorsolateral prefrontal cortex and posterior parietal cortex in the early phase of the maintenance stage. No supra-threshold activation was found during the WM probe. Together, we obtained clearer insights in which brain regions support successful WM and LTM without the potential confound of

  9. Personality traits predict brain activation and connectivity when witnessing a violent conflict.

    Science.gov (United States)

    Van den Stock, Jan; Hortensius, Ruud; Sinke, Charlotte; Goebel, Rainer; de Gelder, Beatrice

    2015-09-04

    As observers we excel in decoding the emotional signals telling us that a social interaction is turning violent. The neural substrate and its modulation by personality traits remain ill understood. We performed an fMRI experiment in which participants watched videos displaying a violent conflict between two people. Observers' attention was directed to either the aggressor or the victim. Focusing on the aggressor (vs. focusing on the victim) activated the superior temporal sulcus (STS), extra-striate body area (EBA), occipital poles and centro-medial amygdala (CMA). Stronger instantaneous connectivity occurred between these and the EBA, insula, and the red nucleus. When focusing on the victim, basolateral amygdala (BLA) activation was related to trait empathy and showed increased connectivity with the insula and red nucleus. STS activation was associated with trait aggression and increased connectivity with the hypothalamus. The findings reveal that focusing on the aggressor of a violent conflict triggers more activation in categorical (EBA) and emotion (CMA, STS) areas. This is associated with increased instantaneous connectivity among emotion areas (CMA-insula) and between categorical and emotion (EBA-STS) areas. When the focus is on the victim, personality traits (aggression/empathy) modulate activity in emotion areas (respectively STS and postcentral gyrus/ BLA), along with connectivity in the emotional diencephalon (hypothalamus) and early visual areas (occipital pole).

  10. [hHO-1 structure prediction and its mutant construct, expression, purification and activity analysis].

    Science.gov (United States)

    Xia, Zhen Wei; Cui, Wen Jun; Zhou, Wen Pu; Zhang, Xue Hong; Shen, Qing Xiang; Li, Yun Zhu; Yu, Shan Chang

    2004-10-01

    Human Heme Oxygenase-1 (hHO-1) is the rate-limiting enzyme in the catabolism reaction of heme, which directly regulates the concentration of bilirubin in human body. The mutant structure was simulated by Swiss-pdbviewer procedure, which showed that the structure of active pocket was changed distinctly after Ala25 substituted for His25 in active domain, but the mutated enzyme still binded with heme. On the basis of the results, the expression vectors, pBHO-1 and pBHO-1(M), were constructed, induced by IPTG and expressed in E. coli DH5alpha strain. The expression products were purified with 30%-60% saturation (NH4)2SO4 and Q-Sepharose Fast Flow column chromatography. The concentration of hHO-1 in 30%-60% saturation (NH4)2SO4 components and in fractions through twice column chromatography was 3.6-fold and 30-fold higher than that in initial product, respectively. The activity of wild hHO-1 (whHO-1) and mutant hHO-1 (deltahHO-1) showed that the activity of deltahHO-1 was reduced 91.21% compared with that of whHO-1. The study shows that His25 is of importance for the mechanism of hHO-1, and provides the possibility for effectively regulating the activity to exert biological function.

  11. Prediction of time-integrated activity coefficients in PRRT using simulated dynamic PET and a pharmacokinetic model.

    Science.gov (United States)

    Hardiansyah, Deni; Attarwala, Ali Asgar; Kletting, Peter; Mottaghy, Felix M; Glatting, Gerhard

    2017-10-01

    To investigate the accuracy of predicted time-integrated activity coefficients (TIACs) in peptide-receptor radionuclide therapy (PRRT) using simulated dynamic PET data and a physiologically based pharmacokinetic (PBPK) model. PBPK parameters were estimated using biokinetic data of 15 patients after injection of (152±15)MBq of 111 In-DTPAOC (total peptide amount (5.78±0.25)nmol). True mathematical phantoms of patients (MPPs) were the PBPK model with the estimated parameters. Dynamic PET measurements were simulated as being done after bolus injection of 150MBq 68 Ga-DOTATATE using the true MPPs. Dynamic PET scans around 35min p.i. (P 1 ), 4h p.i. (P 2 ) and the combination of P 1 and P 2 (P 3 ) were simulated. Each measurement was simulated with four frames of 5min each and 2 bed positions. PBPK parameters were fitted to the PET data to derive the PET-predicted MPPs. Therapy was simulated assuming an infusion of 5.1GBq of 90 Y-DOTATATE over 30min in both true and PET-predicted MPPs. TIACs of simulated therapy were calculated, true MPPs (true TIACs) and predicted MPPs (predicted TIACs) followed by the calculation of variabilities v. For P 1 and P 2 the population variabilities of kidneys, liver and spleen were acceptable (v10%). Treatment planning of PRRT based on dynamic PET data seems possible for the kidneys, liver and spleen using a PBPK model and patient specific information. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  12. Classifying organic materials by oxygen-to-carbon elemental ratio to predict the activation regime of Cloud Condensation Nuclei (CCN

    Directory of Open Access Journals (Sweden)

    M. Kuwata

    2013-05-01

    Full Text Available The governing highly soluble, slightly soluble, or insoluble activation regime of organic compounds as cloud condensation nuclei (CCN was examined as a function of oxygen-to-carbon elemental ratio (O : C. New data were collected for adipic, pimelic, suberic, azelaic, and pinonic acids. Secondary organic materials (SOMs produced by α-pinene ozonolysis and isoprene photo-oxidation were also included in the analysis. The saturation concentrations C of the organic compounds in aqueous solutions served as the key parameter for delineating regimes of CCN activation, and the values of C were tightly correlated to the O : C ratios. The highly soluble, slightly soluble, and insoluble regimes of CCN activation were found to correspond to ranges of [O : C] > 0.6, 0.2 < [O : C] < 0.6, and [O : C] < 0.2, respectively. These classifications were evaluated against CCN activation data of isoprene-derived SOM (O : C = 0.69–0.72 and α-pinene-derived SOM (O : C = 0.38–0.48. Isoprene-derived SOM had highly soluble activation behavior, consistent with its high O : C ratio. For α-pinene-derived SOM, although CCN activation can be modeled as a highly soluble mechanism, this behavior was not predicted by the O : C ratio, for which a slightly soluble mechanism was anticipated. Complexity in chemical composition, resulting in continuous water uptake and the absence of a deliquescence transition that can thermodynamically limit CCN activation, might explain the difference in the behavior of α-pinene-derived SOM compared to that of pure organic compounds. The present results suggest that atmospheric particles dominated by hydrocarbon-like organic components do not activate (i.e., insoluble regime whereas those dominated by oxygenated organic components activate (i.e., highly soluble regime for typical atmospheric cloud life cycles.

  13. Does Dog Walking Predict Physical Activity Participation: Results From a National Survey.

    Science.gov (United States)

    Richards, Elizabeth A

    2016-05-01

    The purpose of this study is to: (1) identify characteristics associated with dog owners who walk their dog, (2) describe the frequency and duration of walking the dog, and (3) determine whether dog owners who walk their dog participate in more physical activity than dog owners who do not walk their dog and non-dog owners. A cross-sectional study design was used. The study setting was nationwide. Adults (n = 4010) participating in the 2005 ConsumerStyles mail-panel survey were the study subjects. Measures used were demographic, physical activity, dog ownership, and dog walking questions from the 2005 ConsumerStyles mail-panel survey. Chi-square tests and analyses of variance were conducted to examine participant characteristics associated with dog walking and to describe the frequency and duration of dog walking. Analysis of covariance was used to determine whether dog owners who walk their dog participate in more physical activity than dog owners who do not walk their dog and non-dog owners. Among dog owners, 42% reported some dog walking in a typical week. Dog owners walked their dog an average 4.3 ± 0.1 times and 128.8 ± 5.6 minutes per week. There were no significant differences in weekly minutes of moderate or vigorous physical activity across the dog-ownership and dog walking groups. Most dog owners did not walk their dog. Dog owners were not more active than non-dog owners, except when considering the activity obtained via dog walking. © The Author(s) 2016.

  14. Computational Account of Spontaneous Activity as a Signature of Predictive Coding.

    Directory of Open Access Journals (Sweden)

    Veronika Koren

    2017-01-01

    Full Text Available Spontaneous activity is commonly observed in a variety of cortical states. Experimental evidence suggested that neural assemblies undergo slow oscillations with Up ad Down states even when the network is isolated from the rest of the brain. Here we show that these spontaneous events can be generated by the recurrent connections within the network and understood as signatures of neural circuits that are correcting their internal representation. A noiseless spiking neural network can represent its input signals most accurately when excitatory and inhibitory currents are as strong and as tightly balanced as possible. However, in the presence of realistic neural noise and synaptic delays, this may result in prohibitively large spike counts. An optimal working regime can be found by considering terms that control firing rates in the objective function from which the network is derived and then minimizing simultaneously the coding error and the cost of neural activity. In biological terms, this is equivalent to tuning neural thresholds and after-spike hyperpolarization. In suboptimal working regimes, we observe spontaneous activity even in the absence of feed-forward inputs. In an all-to-all randomly connected network, the entire population is involved in Up states. In spatially organized networks with local connectivity, Up states spread through local connections between neurons of similar selectivity and take the form of a traveling wave. Up states are observed for a wide range of parameters and have similar statistical properties in both active and quiescent state. In the optimal working regime, Up states are vanishing, leaving place to asynchronous activity, suggesting that this working regime is a signature of maximally efficient coding. Although they result in a massive increase in the firing activity, the read-out of spontaneous Up states is in fact orthogonal to the stimulus representation, therefore interfering minimally with the network

  15. Predicting objectively assessed physical activity from the content and regulation of exercise goals: evidence for a mediational model.

    Science.gov (United States)

    Sebire, Simon J; Standage, Martyn; Vansteenkiste, Maarten

    2011-04-01

    Grounded in self-determination theory (Deci & Ryan, 2000), the purpose of this work was to examine effects of the content and motivation of adults' exercise goals on objectively assessed moderate-to-vigorous physical activity (MVPA). After reporting the content and motivation of their exercise goals, 101 adult participants (Mage = 38.79 years; SD = 11.5) wore an ActiGraph (GT1M) accelerometer for seven days. Accelerometer data were analyzed to provide estimates of engagement in MVPA and bouts of physical activity. Goal content did not directly predict behavioral engagement; however, mediation analysis revealed that goal content predicted behavior via autonomous exercise motivation. Specifically, intrinsic versus extrinsic goals for exercise had a positive indirect effect on average daily MVPA, average daily MVPA accumulated in 10-min bouts and the number of days on which participants performed 30 or more minutes of MVPA through autonomous motivation. These results support a motivational sequence in which intrinsic versus extrinsic exercise goals influence physical activity behavior because such goals are associated with more autonomous forms of exercise motivation.

  16. Prediction of activity coefficients at infinite dilution for organic solutes in ionic liquids by artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Nami, Faezeh [Department of Chemistry, Shahid Beheshti University, G.C., Evin-Tehran 1983963113 (Iran, Islamic Republic of); Deyhimi, Farzad, E-mail: f-deyhimi@sbu.ac.i [Department of Chemistry, Shahid Beheshti University, G.C., Evin-Tehran 1983963113 (Iran, Islamic Republic of)

    2011-01-15

    To our knowledge, this work illustrates for the first time the ability of artificial neural network (ANN) to predict activity coefficients at infinite dilution for organic solutes in ionic liquids (ILs). Activity coefficient at infinite dilution ({gamma}{sup {infinity}}) is a useful parameter which can be used for the selection of effective solvent in the separation processes. Using a multi-layer feed-forward network with Levenberg-Marquardt optimization algorithm, the resulting ANN model generated activity coefficient at infinite dilution data over a temperature range of 298 to 363 K. The unavailable input data concerning softness (S) of organic compounds (solutes) and dipole moment ({mu}) of ionic liquids were calculated using GAMESS suites of quantum chemistry programs. The resulting ANN model and its validation are based on the investigation of up to 24 structurally different organic compounds (alkanes, alkenes, alkynes, cycloalkanes, aromatics, and alcohols) in 16 common imidazolium-based ionic liquids, at different temperatures within the range of 298 to 363 K (i.e. a total number of 914 {gamma}{sub Solute}{sup {infinity}}for each IL data point). The results show a satisfactory agreement between the predicted ANN and experimental data, where, the root mean square error (RMSE) and the determination coefficient (R{sup 2}) of the designed neural network were found to be 0.103, 0.996 for training data and 0.128, 0.994 for testing data, respectively.

  17. Macrophage activation markers predict mortality in patients with liver cirrhosis without or with acute-on-chronic liver failure (ACLF)

    DEFF Research Database (Denmark)

    Grønbæk, Henning; Rødgaard-Hansen, Sidsel; Aagaard, Niels Kristian

    2016-01-01

    BACKGROUND & AIMS: Activation of liver macrophages plays a key role in liver and systemic inflammation and may be involved in development and prognosis of acute-on-chronic liver failure (ACLF). We therefore measured the circulating macrophage activation markers soluble sCD163 and mannose receptor......-C ACLF and CLIF-C AD scores. Addition of the macrophage markers to the clinical scores improved the prognostic efficacy: In ACLF patients sCD163 improved prediction of short-term mortality (C-index: 0.74 (0.67-0.80)) and in patients without ACLF sMR improved prediction of long-term mortality (C-index: 0.......80 (0.76-0.85)). CONCLUSIONS: The severity related increase in sCD163 and sMR and close association with mortality suggest a primary importance of inflammatory activation of liver macrophages in the emergence and course of ACLF. Accordingly, supplementation of the macrophage biomarkers to the platform...

  18. Prediction of activity coefficients at infinite dilution for organic solutes in ionic liquids by artificial neural network

    International Nuclear Information System (INIS)

    Nami, Faezeh; Deyhimi, Farzad

    2011-01-01

    To our knowledge, this work illustrates for the first time the ability of artificial neural network (ANN) to predict activity coefficients at infinite dilution for organic solutes in ionic liquids (ILs). Activity coefficient at infinite dilution (γ ∞ ) is a useful parameter which can be used for the selection of effective solvent in the separation processes. Using a multi-layer feed-forward network with Levenberg-Marquardt optimization algorithm, the resulting ANN model generated activity coefficient at infinite dilution data over a temperature range of 298 to 363 K. The unavailable input data concerning softness (S) of organic compounds (solutes) and dipole moment (μ) of ionic liquids were calculated using GAMESS suites of quantum chemistry programs. The resulting ANN model and its validation are based on the investigation of up to 24 structurally different organic compounds (alkanes, alkenes, alkynes, cycloalkanes, aromatics, and alcohols) in 16 common imidazolium-based ionic liquids, at different temperatures within the range of 298 to 363 K (i.e. a total number of 914 γ Solute ∞ for each IL data point). The results show a satisfactory agreement between the predicted ANN and experimental data, where, the root mean square error (RMSE) and the determination coefficient (R 2 ) of the designed neural network were found to be 0.103, 0.996 for training data and 0.128, 0.994 for testing data, respectively.

  19. Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A

    Directory of Open Access Journals (Sweden)

    Huixiao Hong

    2016-07-01

    Full Text Available Bisphenol A (BPA is a ubiquitous compound used in polymer manufacturing for a wide array of applications; however, increasing evidence has shown that BPA causes significant endocrine disruption and this has raised public concerns over safety and exposure limits. The use of renewable materials as polymer feedstocks provides an opportunity to develop replacement compounds for BPA that are sustainable and exhibit unique properties due to their diverse structures. As new bio-based materials are developed and tested, it is important to consider the impacts of both monomers and polymers on human health. Molecular docking simulations using the Estrogenic Activity Database in conjunction with the decision forest were performed as part of a two-tier in silico model to predict the activity of 29 bio-based platform chemicals in the estrogen receptor-α (ERα. Fifteen of the candidates were predicted as ER binders and fifteen as non-binders. Gaining insight into the estrogenic activity of the bio-based BPA replacements aids in the sustainable development of new polymeric materials.

  20. Broca's region and Visual Word Form Area activation differ during a predictive Stroop task

    DEFF Research Database (Denmark)

    Wallentin, Mikkel; Gravholt, Claus Højbjerg; Skakkebæk, Anne

    2015-01-01

    displayed in green or red (incongruent vs congruent colors). One of the colors, however, was presented three times as often as the other, making it possible to study both congruency and frequency effects independently. Auditory stimuli saying “GREEN” or “RED” had the same distribution, making it possible...... to study frequency effects across modalities. We found significant behavioral effects of both incongruency and frequency. A significant effect (p effect of frequency was observed and no interaction. Conjoined effects of incongruency...... and frequency were found in parietal regions as well as in the Visual Word Form Area (VWFA). No interaction between perceptual modality and frequency was found in VWFA suggesting that the region is not strictly visual. These findings speak against a strong version of the prediction error processing hypothesis...

  1. Kinetic model for predicting the concentrations of active halogen species in chlorinated saline cooling waters

    International Nuclear Information System (INIS)

    Lietzke, M.H.; Haag, W.R.

    1979-01-01

    A kinetic model for predicting the composition of chlorinated water discharged from power plants using fresh water for cooling was previously reported. The model has now been extended to be applicable to power plants located on estuaries or on the seacoast where saline water is used for cooling purposes. When chloride is added to seawater to prevent biofouling in cooling systems, bromine is liberated. Since this reaction proceeds at a finite rate there is a competition between the bromine (i.e., hypobromous acid) and the added chlorine (i.e., hypochlorous acid) for halogenation of any amine species present in the water. Hence not only chloramines but also bromamines and bromochloramines will be formed, with the relative concentrations a function of the pH, temperature, and salinity of the water. The kinetic model takes into account the chemical reactions leading to the formation and disappearance of the more important halamines and hypohalous acids likely to be encountered in chlorinated saline water

  2. Development of quantitative structure-activity relationship (QSAR) models to predict the carcinogenic potency of chemicals

    International Nuclear Information System (INIS)

    Venkatapathy, Raghuraman; Wang Chingyi; Bruce, Robert Mark; Moudgal, Chandrika

    2009-01-01

    Determining the carcinogenicity and carcinogenic potency of new chemicals is both a labor-intensive and time-consuming process. In order to expedite the screening process, there is a need to identify alternative toxicity measures that may be used as surrogates for carcinogenic potency. Alternative toxicity measures for carcinogenic potency currently being used in the literature include lethal dose (dose that kills 50% of a study population [LD 50 ]), lowest-observed-adverse-effect-level (LOAEL) and maximum tolerated dose (MTD). The purpose of this study was to investigate the correlation between tumor dose (TD 50 ) and three alternative toxicity measures as an estimator of carcinogenic potency. A second aim of this study was to develop a Classification and Regression Tree (CART) between TD 50 and estimated/experimental predictor variables to predict the carcinogenic potency of new chemicals. Rat TD 50 s of 590 structurally diverse chemicals were obtained from the Cancer Potency Database, and the three alternative toxicity measures considered in this study were estimated using TOPKAT, a toxicity estimation software. Though poor correlations were obtained between carcinogenic potency and the three alternative toxicity (both experimental and TOPKAT) measures for the CPDB chemicals, a CART developed using experimental data with no missing values as predictor variables provided reasonable estimates of TD 50 for nine chemicals that were part of an external validation set. However, if experimental values for the three alternative measures, mutagenicity and logP are not available in the literature, then either the CART developed using missing experimental values or estimated values may be used for making a prediction

  3. Fuzzy-predictive direct power control implementation of a grid connected photovoltaic system, associated with an active power filter

    International Nuclear Information System (INIS)

    Ouchen, Sabir; Betka, Achour; Abdeddaim, Sabrina; Menadi, Abdelkrim

    2016-01-01

    Highlights: • An implementation on dSPACE 1104 of a double stage grid connected photovoltaic system, associated with an active power filter. • A fuzzy logic controller for maximum power point tracking of photovoltaic generator using a boost converter. • Predictive direct power control almost eliminates the effect of harmonics under a unite power factor. • The robustness of control strategies was examined in different irradiance level conditions. - Abstract: The present paper proposes a real time implementation of an optimal operation of a double stage grid connected photovoltaic system, associated with a shunt active power filter. On the photovoltaic side, a fuzzy logic based maximum power point taking control is proposed to track permanently the optimum point through an adequate tuning of a boost converter regardless the solar irradiance variations; whereas, on the grid side, a model predictive direct power control is applied, to ensure both supplying a part of the load demand with the extracted photovoltaic power, and a compensation of undesirable harmonic contents of the grid current, under a unity power factor operation. The implementation of the control strategies is conducted on a small scale photovoltaic system, controlled via a dSPACE 1104 single card. The obtained experimental results show on one hand, that the proposed Fuzzy logic based maximum power taking point technique provides fast and high performances under different irradiance levels while compared with a sliding mode control, and ensures 1.57% more in efficiency. On the other hand, the predictive power control ensures a flexible settlement of active power amounts exchanges with the grid, under a unity power functioning. Furthermore, the grid current presents a sinusoidal shape with a tolerable total harmonic distortion coefficient 4.71%.

  4. Quantitative analysis of contrast-enhanced ultrasonography of the bowel wall can predict disease activity in inflammatory bowel disease

    Energy Technology Data Exchange (ETDEWEB)

    Romanini, Laura, E-mail: laura.romanini@libero.it [Department of Radiology, Spedali Civili di Brescia, P.le Spedali Civili, 1, 25123 Brescia (Italy); Passamonti, Matteo, E-mail: matteopassamonti@gmail.com [Department of Radiology-AO Provincia di Lodi, Via Fissiraga, 15, 26900 Lodi (Italy); Navarria, Mario, E-mail: navarria.mario@tiscali.it [Department of Radiology-ASL Vallecamonica-Sebino, Via Manzoni 142, 25040 Esine, BS (Italy); Lanzarotto, Francesco, E-mail: francesco.lanzarotto@spedalicivili.brescia.it [Department of Gastroenterology, Spedali Civili di Brescia, P.le Spedali Civili, 1, 25123 Brescia (Italy); Villanacci, Vincenzo, E-mail: villanac@alice.it [Department of Pathology, Spedali Civili di Brescia, P.le Spedali Civili, 1, 25123 Brescia (Italy); Grazioli, Luigi, E-mail: radiologia1@spedalicivili.brescia.it [Department of Radiology, Spedali Civili di Brescia, P.le Spedali Civili, 1, 25123 Brescia (Italy); Calliada, Fabrizio, E-mail: fabrizio.calliada@gmail.com [Department of Radiology, University of Pavia, Viale Camillo Golgi 19, 27100 Pavia (Italy); Maroldi, Roberto, E-mail: rmaroldi@gmail.com [Department of Radiology, University of Brescia, P.le Spedali Civili, 1, 25123 Brescia (Italy)

    2014-08-15

    Purpose: To evaluate the accuracy of quantitative analysis of bowel wall enhancement in inflammatory bowel disease (IBD) with contrast enhanced ultrasound (CEUS) by comparing the results with vascular density in a biopsy sample from the same area of the intestinal tract, and to determine the usefulness of this analysis for the prediction of disease activity. Materials and methods: This prospective study was approved by our institute's ethics committee and all patients gave written informed consent. We enrolled 33 consecutive adult patients undergoing colonoscopy and biopsy for IBD. All patients underwent CEUS and the results were quantitatively analyzed. Vessel count per high-power field on biopsy specimens was compared with colonoscopy, baseline ultrasonography, and CEUS findings, and with analysis of peak intensity, time to peak, regional blood volume, mean transit time, and regional blood flow. Results in patients with high and low vascular density were compared using Fisher's test, t-test, Pearson's correlation test, and receiver operating characteristic curve (ROC) analysis. Cutoff values were determined using ROC analysis, and sensitivity and specificity were calculated. Results: High vascular density (>265 vessels per field) on histological examination was significantly correlated with active disease on colonoscopy, baseline ultrasonography, and CEUS (p < .0001). Quantitative analysis showed a higher enhancement peak, a shorter time to peak enhancement, a higher regional blood flow and regional blood volume in patients with high vascular density than in those with low vascular density. Cutoff values to distinguish between active and inactive disease were identified for peak enhancement (>40.5%), and regional blood flow (>54.8 ml/min). Conclusion: Quantitative analysis of CEUS data correlates with disease activity as determined by vascular density. Quantitative parameters of CEUS can be used to predict active disease with high sensitivity and

  5. Behavioral activation and inhibition system's role in predicting addictive behaviors of patients with bipolar disorder of Roozbeh Psychiatric Hospital

    Science.gov (United States)

    Abbasi, Moslem; Sadeghi, Hasan; Pirani, Zabih; Vatandoust, Leyla

    2016-01-01

    Background: Nowadays, prevalence of addictive behaviors among bipolar patients is considered to be a serious health threat by the World Health Organization. The aim of this study is to investigate the role of behavioral activation and inhibition systems in predicting addictive behaviors of male patients with bipolar disorder at the Roozbeh Psychiatric Hospital. Materials and Methods: The research method used in this study is correlation. The study population consisted of 80 male patients with bipolar disorder referring to the psychiatrics clinics of Tehran city in 2014 who were referred to the Roozbeh Psychiatric Hospital. To collect data, the international and comprehensive inventory diagnostic interview, behavioral activation and inhibition systems scale, and addictive behaviors scale were used. Results: The results showed that there is a positive and significant relationship between behavioral activation systems and addictive behaviors (addictive eating, alcohol addiction, television addiction, cigarette addiction, mobile addiction, etc.). In addition, correlation between behavioral inhibition systems and addictive behaviors (addictive eating, alcohol addiction, TV addiction, cigarette addiction, mobile addiction) is significantly negative. Finally, regression analysis showed that behavioral activation and inhibition systems could significantly predict 47% of addictive behaviors in patients with bipolar disorder. Conclusions: It can be said that the patients with bipolar disorder use substance and addictive behaviors for enjoyment and as pleasure stimulants; they also use substances to suppress unpleasant stimulants and negative emotions. These results indicate that behavioral activation and inhibition systems have an important role in the incidence and exacerbation of addictive behaviors. Therefore, preventive interventions in this direction seem to be necessary. PMID:28194203

  6. Quantitative analysis of contrast-enhanced ultrasonography of the bowel wall can predict disease activity in inflammatory bowel disease

    International Nuclear Information System (INIS)

    Romanini, Laura; Passamonti, Matteo; Navarria, Mario; Lanzarotto, Francesco; Villanacci, Vincenzo; Grazioli, Luigi; Calliada, Fabrizio; Maroldi, Roberto

    2014-01-01

    Purpose: To evaluate the accuracy of quantitative analysis of bowel wall enhancement in inflammatory bowel disease (IBD) with contrast enhanced ultrasound (CEUS) by comparing the results with vascular density in a biopsy sample from the same area of the intestinal tract, and to determine the usefulness of this analysis for the prediction of disease activity. Materials and methods: This prospective study was approved by our institute's ethics committee and all patients gave written informed consent. We enrolled 33 consecutive adult patients undergoing colonoscopy and biopsy for IBD. All patients underwent CEUS and the results were quantitatively analyzed. Vessel count per high-power field on biopsy specimens